Methods for evaluating tumor cell spheroids using 3D microfluidic cell culture device

Information

  • Patent Grant
  • 11098369
  • Patent Number
    11,098,369
  • Date Filed
    Friday, August 17, 2018
    6 years ago
  • Date Issued
    Tuesday, August 24, 2021
    3 years ago
Abstract
Provided herein are methods for evaluating tumor cell spheroids in a three-dimensional microfluidic device by determining changes in the relative levels of live cells and dead cells in aliquots cultured under different conditions. Methods described herein allow ex vivo recapitulation of the tumor microenvironment such that the in vivo effectiveness of a test compound in treating tumor tissue may be predicted.
Description
BACKGROUND

Existing patient-derived cancer models, including circulating tumor cells (CTCs), organoid cultures, and patient-derived xenografts (PDXs) can guide precision cancer therapy, but take weeks to months to generate and lack the native tumor immune microenvironment. Current approaches to study anti-tumor immune responses in patients are also limited by remote measurements in whole blood or plasma, or static assessment of biopsies.


Recently there has been developed a 3D microfluidic device for the short-term culture of murine- and patient-derived organotypic tumor spheroids. Cultured tumor spheroids are believed by some to more closely resemble the native immune microenvirolunent.


It would be desirable to be able to assess the effects of single drugs and combinations of drugs on tumor cells in the tumor micro-environment. It would be particularly helpful if there were a way to evaluate simultaneously the effects of a combination of immune blockade and anticancer compounds ex vivo. To date, efforts to evaluate tumor cells have been confounded by (i) the tumor cells changing when removed from the body, (ii) the absence of an intact immune system communicating with the tumor microenvironment when the tumor cells are removed from the body, (iii) the inability to distinguish the effects of tumor removal and culturing from the effects of a drug applied in vitro, and (iv) the complexity of measuring at a molecular level immune based markers and other markers which might predict whether a drug might work in vivo based on experiments conducted in vitro. To date, there is no simple assay for evaluating in in a high throughput manner the effects of drugs on human cancer cells in a native tumor microenvironment.


SUMMARY

It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid contains sufficient immune components to be predictive of a drug's activity when administered in vivo. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid contains sufficient immune components such that combinations of immune blockade compounds and anti-cancer drugs can be assessed, the results being predictive of administering the drugs in vivo. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid can be evaluated optically and reproducibly, to establish the effects of drugs on the tumor cells within the spheroids, while distinguishing the effects on tumor cells resulting from the act of culturing the tumor cells. It has been discovered, surprisingly, that such techniques for evaluating tumor spheroids can be utilized in a high throughput method for determining the relative amounts of live and dead cells in an environment mimicking that occurring in vivo.


In one aspect, the invention involves a novel approach for evaluating ex vivo response to Immune Checkpoint Blockade (ICB) using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS) cultured in a 3-dimensional microfluidic system. Spheroids isolated from fresh mouse and human tumor samples retain autologous lymphoid and myeloid cell populations, including antigen-experienced tumor infiltrating CD4 and CD8 T lymphocytes, and respond to ICB in short-term ex vivo culture. Tumor killing was recapitulated ex vivo using MDOTS derived from the anti-PD-1 sensitive MC38 syngeneic mouse cancer model, whereas relative resistance to anti-PD-1 therapy was preserved in the CT26 and B16F10 syngeneic models. Systematic cytokine/chemokine profiling following PD-1 blockade in PDOTS from patients with melanoma and other tumors identified significant induction of the immunoattractants CCL19 and CXCL13, which was confirmed in vivo and correlated with evidence of intratumoral immune cell infiltration. Resistance to anti-PD1 treatment in MDOTS and PDOTS also tracked with coinduction of immune suppressive chemokines. Ex vivo profiling revealed a combination therapy as a novel therapeutic strategy to enhance sensitivity to PD-1 blockade in this setting, which effectively predicted tumor response in vivo. These findings demonstrate feasibility of ex vivo profiling of PD-1 blockade, and offer a novel functional approach to facilitate precision immunooncology and develop novel therapeutic combinations.


According to one aspect of the invention, a method for evaluating tumor cell spheroids in a three-dimensional microfluidic device is provided. The method involves:


obtaining tumor spheroids from an enzyme treated tumor sample, suspending a first aliquot of the tumor spheroids in biocompatible gel; suspending a second aliquot of the tumor spheroids in biocompatible gel;


placing the first aliquot of the tumor spheroids in biocompatible gel in a first three-dimensional device,


contacting the first aliquot with a first fluorophore dye selective for dead cells, the first fluorophore dye emitting fluorescence at a first wavelength when bound to a dead cell,


contacting the first aliquot with a second fluorophore dye selective for live cells, the second fluorophore dye emitting fluorescence at a second wavelength different from the first wavelength when bound to a live cell,


measuring total fluorescence emitted by each of the first and second fluorophore dyes in the first aliquot,


culturing the second aliquot in a second three-dimensional device,


contacting the second aliquot with the first fluorophore dye,


contacting the second aliquot with the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye,


measuring total fluorescence emitted by each of the first and second fluorophore dyes in the second aliquot,


wherein an increase or decrease in the ratio of live cells to dead cells in each of the aliquots may be assessed.


In one embodiment, the total fluorescence emitted by each of the first and second fluorophore dyes is measured using a camera, preferably at a resolution of at least 2×, at least 3×, at least 4× or more, from directly above or below each three-dimensional device, and preferably wherein the three-dimensional devices are placed on a moveable stage permitting the camera to capture the total fluorescence in each aliquot.


In some embodiments, the dead cell fluorescence and the live cell fluorescence can be added together to yield a live and dead cell total. The amount of dead cells may be expressed as a percentage of the dead cell fluorescence to the total fluorescence. The amount of live cells can be expressed as a percentage of the live cell fluorescence to the total. In some embodiments, the dead cell fluorescence and the live cell fluorescence can be expressed as a ratio, that is, dead cells/live cells or live cells/dead cells. In this manner, changes to the number of dead cells to live cells can be tracked over time, wherein an initial ratio is established prior to culturing and changes to the ratio are determined over time.


In some embodiments, there are multiple aliquots of tumor spheroids, for example three, or four, or five, or six or more than six, and the contacting of the third, fourth, fifth, sixth or more than sixth such aliquots with the first fluorophore dye and second fluorophore dye is carried out, for example, two days, three days, four days, five days, and more than five days, respectively, after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye. The timing of testing aliquots may be separated by any time period, such as one day, less than a day, two days or three or more days. In one embodiment, an aliquot is tested six days after placing the spheroids in the gel.


In any of the embodiments, the second (or any subsequent) aliquot is contacted with at least one test compound during the culturing of the second aliquot and wherein said culturing of the second aliquot in the presence of the test compound occurs for at least 24 hours, at least two days, at least three days, at least four days, at least five days, or at least 6 days or more.


In any of the foregoing embodiments, the second aliquot can be contacted with at least two test compounds during the culturing of the second aliquot and wherein said culturing of the second aliquot in the presence of the test compounds occurs for at least 24 hours, at least two days, at least three days, at least four days, at least five days, or at least 6 days, and preferably wherein at least one of the test compounds is an immune checkpoint inhibitor.


The number of spheroids can be any number of spheroids convenient and available to the researcher, but in the system described below, the number of spheroids in the first and the second aliquots each contain between about 15 and 30 spheroids, preferably between about 20 and 25 spheroids.


In some embodiments, the first three-dimensional device can be a first three-dimensional microfluidic device and the second three-dimensional device can be a second three-dimensional microfluidic device. In some embodiments, the culturing of the first aliquot in the first three-dimensional microfluidic device, is for less than 6 hours, less than 3 hours, less than 2 hours and even less than 1 hour prior to contacting the first aliquot with the first and second fluorophore dyes. In particular, it may be desirable to contact the first aliquot with the dyes prior to culturing the spheroids at all, that is essentially upon introducing the spheroids into the three dimensional device.


In any of the foregoing embodiments, the enzyme can be collagenase.


In any of the foregoing embodiments, the first fluorophore dye can be propidium iodide, DRAQ7, 7-AAD, eBioscience Fixable Viability Dye EFLUOR® 455UV, eBioscience Fixable Viability Dye EFLUOR® 450, eBioscience Fixable Viability Dye EFLUOR® 506, eBioscience Fixable Viability Dye EFLUOR® 520, eBioscience Fixable Viability Dye EFLUOR® 660, eBioscience Fixable Viability Dye EFLUOR® 780, BioLegend Zombie AQUA™, BioLegend Zombie NIR™, BioLegend Zombie RED™ BioLegend Zombie VIOLET™, BioLegend Zombie UV™, or BioLegend Zombie YELLOW™, and/or the second fluorophore dye can be acridine orange, nuclear green LCS1 (ab138904), DRAQ5 (ab108410), CyTRAK Orange, NUCLEAR-ID Red DNA stain (ENZ-52406), SiR700-DNA, calcein AM, calcein violet AM, calcein blue AM, VYBRANT® DYECYCLE™ Violet, VYBRANT® DYECYCLE™ Green, VYBRANT® DYECYCLE™ Orange, or VYBRANT® DYECYCLE™ Ruby.


In any of the foregoing embodiments, the tumor spheroids can be obtained by mincing a primary tumor sample in a medium supplemented with serum; treating the minced primary tumor sample with an enzyme; and harvesting tumor spheroids from the enzyme treated sample. In some embodiments, the minced primary tumor sample is treated with the enzyme in an amount and/or for a time sufficient to yield a partial digestion of the minced primary tumor sample, and preferably wherein the treatment is for between 10 minutes and 60 minutes, and more preferably between 15 minutes and 45 minutes at a temperature of 25° C. to 39° C.


In any of the foregoing embodiments, the biocompatible gel can be collagen, BD Matrigel™ Matrix Basement Membrane, or fibrin hydrogel.


In any of the foregoing embodiments, the tumor sample can be derived from a murine model. In some embodiments, the murine model is a syngeneic model selected from the group consisting of Bladder MBT-2, Breast 4T1, EMT6, Colon, Colon26, CT-26, MC38, Fibrosarcoma WEHI-164, Kidney Renca, Leukemia C1498, L1210, Liver H22, KLN205, LL/2, LewisLung, Lymphoma A20 S, E.G7-OVA, EL4, Mastocytoma P815, Melanoma B16-BL6, B16-F10, S91, Myeloma MPC-11, Neuroblastoma Neuro-2a, Ovarian: ID8, Pancreatic Pan02, Plasmacytoma J558, and Prostate RM-1.


In any of the foregoing embodiments, the tumor sample can be a human tumor sample.


In any of the foregoing embodiments, the tumor sample can be a patient derived xenograft (PDX).


In any of the foregoing embodiments, the three-dimensional device can include one or more fluid channels flanked by one or more gel cage regions, wherein the one or more gel cage regions comprises the biocompatible gel in which the tumor spheroids are embedded, and wherein the device recapitulates in vivo tumor microenvironment. In any of the foregoing embodiments, the three-dimensional device can include: a substrate comprised of an optically transparent material and further comprising i) one or more fluid channels; ii) one or more fluid channel inlets; iii) one or more fluid channel outlets; iv) one or more gel cage regions; and v) a plurality of posts; wherein all or a portion of each gel cage region is flanked by all or a portion of one or more fluid channels, thereby creating one or more gel cage region-fluid channel interface regions; each gel cage region comprises at least one row of posts which forms the gel cage region; and the one or more gel cage region has a height of less than 500 μm.


In any of the foregoing embodiments, the test compound can be a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In any of the foregoing embodiments, the first test compound can be a chemotherapeutic compound, an immunomodulatory compound, or radiation. In any of the foregoing embodiments, the first test compound can be an alkylating compound, an antimetabolite, an anthracycline, a proteasome inhibitor, or an mTOR inhibitor. In any of the foregoing embodiments, the first test compound can be an immune modulator.


In some embodiments, the method further comprises isolating RNA from the first aliquot and second aliquot of tumor spheroids; and analyzing gene expression of the first aliquot and second aliquot of tumor spheroids based on the isolated RNA, wherein the gene expression is analyzed by performing RNA sequencing (RNA-seq) on the isolated RNA


In another aspect, provided herein is a method for detecting a change in tumor cell spheroids upon exposure to a test compound. The method comprises:


culturing a first aliquot of tumor cell spheroids in a first three-dimensional device;


culturing a second aliquot of tumor cell spheroids in the presence of a first test compound in a second three-dimensional device; and


detecting a change in the second aliquot as compared to the first aliquot, wherein the change is selected from:


a clustering of immune cells around one or more of the tumor cell spheroids of the first or second aliquot;


a decrease in size and/or number of the tumor cell spheroids of the first or second aliquot; or


a chemical change.


In some embodiments, the second aliquot is cultured in the presence of the first test compound and a second test compound. In some embodiments, the first aliquot is cultured in the presence of the first test compound.


In some embodiments, the method further comprises:


culturing a third aliquot of tumor cell spheroids in the presence of the first test compound and the second test compound in a third three-dimensional device; and


detecting a change in the third aliquot relative to the first and/or second aliquot.


In some embodiments, the first aliquot is cultured in the presence of the second and/or a third test compound. In some embodiments, the second aliquot is cultured in the presence of the third and/or a fourth test compound. In some embodiments, the third aliquot is cultured in the presence of the third and/or fourth test compound.


In some embodiments, detecting a chemical change comprises detecting a presence of a biological molecule secreted into tumor cell spheroid cell culture supernatant of the first, second, and/or third aliquots.


In some embodiments, the biological molecule is a protein, a carbohydrate, a lipid, a nucleic acid, a metabolite, or a combination thereof. In some embodiments, the biological molecule is a chemokine or a cytokine. In some embodiments, the biological molecule is known to be associated with activation of the immune system or otherwise an enhancement of the immune response.


In some embodiments, detecting a chemical change comprises detecting a change in nucleic acid content. In some embodiments, detecting the change in nucleic acid content comprises detecting a change in extracellular nucleic acids. In some embodiments, detecting the change in nucleic acid content comprises detecting a change in nucleic acids isolated from tumor cell spheroids from the first, second, and/or third aliquots.


In some embodiments, detecting the change in nucleic acid content comprises detecting a change in gene expression. In some embodiments, detecting a change in gene expression comprises detecting a change expression of genes associated with cytotoxicity. In some embodiments, genes associated with cytotoxicity comprise cytokines and cytokine receptors.


In some embodiments, detecting the change in nucleic acid content comprises analyzing DNA and/or RNA from the first, second, and/or third aliquots of tumor cell spheroids. In some embodiments, RNA from the first, second, and/or third aliquots of tumor cell spheroids is analyzed by RNA sequencing.


In some embodiments, the first, second, third, and/or fourth test compound is a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In some embodiments, the first, second, third, and/or fourth test compound is an immune modulator. In some embodiments, the immune modulator comprises immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of CTLA-4, PD-1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor inhibits PD1. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second test compound is a small molecule compound. In some embodiments, the small molecule compound is a TBK-1 inhibitor. In some embodiments, the first, second, third, and/or fourth test compound is a chemical from a test compound library. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second, third, and/or fourth test compound is a chemical from a test compound library.


In some embodiments, the first, second, and/or third aliquots are cultured in a biocompatible gel. In some embodiments, the first, second, and/or third aliquots are suspended in a biocompatible gel in a fluid channel of the three-dimensional microfluidic device before culturing.


In some embodiments, the first, second, and/or third aliquots are obtained from an enzyme treated tumor sample.


In another aspect, provided herein is a method for evaluating tumor cell spheroids in a three-dimensional microfluidic device. The method comprises:


culturing a first aliquot of tumor spheroids in a first three-dimensional device,


culturing the second aliquot of tumor spheroids in a second three-dimensional device in the presence of a first test compound;


isolating RNA from the first aliquot and second aliquot of tumor spheroids; and


analyzing gene expression of the first aliquot and second aliquot of tumor spheroids based on the isolated RNA.


In some embodiments, the second aliquot is cultured in the presence of a first test compound and a second test compound.


In some embodiments, the method further comprises:


culturing the third aliquot of tumor spheroids in a third three-dimensional device in the presence of the first test compound and a second test compound;


isolating RNA from the third aliquot of tumor spheroids; and


analyzing gene expression of the third aliquot of tumor spheroids based on the isolated RNA.


In some embodiments, the second aliquot is cultured in the presence of a third and/or fourth test compound. In some embodiments, the third aliquot is cultured in the presence of a third and/or fourth test compound.


In some embodiments, the RNA is isolated from the supernatant or from the cell culture of the first aliquot and second aliquot of tumor spheroids.


In some embodiments, the gene expression of the first aliquot and second aliquot of tumor spheroids is analyzed by performing RNA sequencing (RNA-seq) on the isolated RNA.


In some embodiments, the tumor cell spheroids are obtained from an enzyme treated tumor sample.


In some embodiments, the first, second, third, and/or fourth test compound is a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In some embodiments, the first test compound is an immune modulator. In some embodiments, the immune modulator comprises immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of CTLA-4, PD-1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor inhibits PD1. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second test compound is a small molecule compound. In some embodiments, the small molecule compound is a TBK-1 inhibitor. In some embodiments, the first, second, third, and/or fourth test compound is a chemical from a test compound library. In some embodiments, the first test compound is an immune checkpoint inhibitor and the second, third, and/or fourth test compound is a chemical from a test compound library.


In some embodiments, the first, second, and/or third aliquots are cultured in a biocompatible gel. In some embodiments, In some embodiments, the first, second, and/or third aliquots are suspended in a biocompatible gel in a fluid channel of the three-dimensional microfluidic device before culturing.





BRIEF DESCRIPTION OF THE DRAWINGS

The skilled artisan will understand that the figures, described herein, are for illustration purposes only. It is to be understood that, in some instances, various aspects of the invention may be shown exaggerated or enlarged to facilitate an understanding of the invention. In the drawings, like reference characters generally refer to like features, functionally similar and/or structurally similar elements throughout the various figures. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the teachings. The drawings are not intended to limit the scope of the present teachings in any way.


The features and advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings.


When describing embodiments in reference to the drawings, direction references (“above,” “below,” “top,” “bottom,” “left,” “right,” “horizontal,” “vertical,” etc.) may be used. Such references are intended merely as an aid to the reader viewing the drawings in a normal orientation. These directional references are not intended to describe a preferred or only orientation of an embodied device. A device may be embodied in other orientations.


As is apparent from the detailed description, the examples depicted in the figures and further described for the purpose of illustration throughout the application describe non-limiting embodiments, and in some cases may simplify certain processes or omit features or steps for the purpose of clearer illustration.



FIG. 1A is a schematic for preparation and analysis of MDOTS/PDOTS (S2 fraction) from murine or patient-derived tumor specimens.



FIG. 1B depicts MC38 allograft immune profiling by flow cytometry comparing bulk tumor (n=5) to S1, S2, S3 (n=6) spheroid fractions (Kruskal-Wallis with Dunn's multiple comparisons test, α=0.05; ns=not significant).



FIG. 1C depicts immune profiling of PDOTS (S2; n=40) (upper panel=% live cells, lower panel=% CD45+ cells) with indicated patient/tumor characteristics, grouped by tumor type and ranked by % CD8+ T cells.



FIG. 1D depicts immune cell correlation of S2/S3 fractions (CD45, n=14; CD3, n=15; CD4/CD8, n=13; CD4+CD45RO+, n=9; CD8+CD45RO+, n=8; activated=CD38+ and/or CD69+, n=6), R2 significant for all comparisons.



FIG. 1E depicts PD-1, CTLA-4, TIM-3 expression on CD4 and CD8 T cell populations in S2/S3 fractions (n=6), R2 significant for all comparisons.



FIG. 2A depicts phase-contrast imaging (4×) of MC38 MDOTS in 3D microfluidic culture.



FIG. 2B is a cytokine heatmap from cultured MC38 MDOTS expressed as log-2 fold change relative to Day 1.



FIG. 2C is a cytokine heatmap from cultured B16F10 MDOTS expressed as log-2 fold change relative to Day 1.



FIG. 2D illustrates MC38 allograft tumor volume following isotype control IgG (n=10) or rat-anti-mouse anti-PD-1 antibody (n=10) treatment.



FIG. 2E illustrates Day 22 MC38 tumor volumes (unpaired 2-sided t-test, p<0.05).



FIG. 2F is a schematic of MDOTS Live/Dead Imaging workflow.



FIG. 2G illustrates Live (AO=green)/dead (PI=red) quantification of MC38 MDOTS Day 0 (immediately after loading), Day 3, and Day 6 following IgG control or indicated anti-PD-1 antibody doses; n=4, biological replicates, **p<0.01, ****p<0.0001, Kruskal-Wallis Dunnett's with multiple comparisons test).



FIG. 2H illustrates Live/dead analysis of MC38 spheroids lacking immune cells±anti-PD 1 (n=4, biological replicates).



FIG. 2I illustrates Live/dead analysis of CT26 MDOTS±anti-PD1 (n=3, biological replicates, ****p<0.0001).



FIG. 2J illustrates Live/dead analysis of B16F10 MDOTS±anti-PD1 (n=3, biological replicates).



FIG. 2K depicts deconvolution fluorescence microscopy of MC38 and B16F10 MDOTS Day 6±anti-PD1 (representative images shown).



FIG. 3A is a cytokine heatmap that illustrates day 3±anti-PD-1 (n=28) expressed as log 2 fold-change (L2FC) relative to untreated control.



FIG. 3B is a cytokine heatmap that illustrates day 3±anti-CTLA-4 (n=24) expressed as log 2 fold-change (L2FC) relative to untreated control.



FIG. 3C is a cytokine heatmap that illustrates day 3±anti-PD-1±anti-CTLA-4 (n=24) expressed as log 2 fold-change (L2FC) relative to untreated control.



FIG. 3D depicts absolute CCL19/CXCL13 levels following single checkpoint blockade (2-sided, paired, t-test, α=0.05).



FIG. 3E depicts absolute CCL19/CXCL13 levels following single checkpoint blockade (2-sided, paired, t-test, α=0.05).



FIG. 3F depicts absolute CCL19/CXCL13 levels following dual checkpoint blockade (2-sided, paired, t-test, α=0.05).



FIG. 3G is a heatmap that illustrates CCL19/CXCL13 mRNA levels from melanoma biopsy samples on anti-PD1 treatment relative to pre-PD-1 (L2FC) by qRT-PCR (n=12).



FIG. 3H is a heatmap that illustrates CCL19/CXCL13 mRNA levels from melanoma biopsy samples on anti-PD1 treatment relative to pre-PD-1 (L2FC) by RNA-seq (n=17 from 10 patients).



FIG. 3I depicts absolute expression (RPKM) for CCL19 and CXCL13 in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB) or no clinical benefit (NCB) from checkpoint blockade.



FIG. 3J depicts absolute expression (RPKM) for CCR7 and CXCR5, the respective receptors for CCL19 and CXCL13, in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB) or no clinical benefit (NCB) from checkpoint blockade.



FIG. 3K is a heat map that illustrates immune signatures (GSEA) in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients).



FIG. 3L depicts a Kaplan-Meier survival curve by CCL19/CXCL13 expression (high vs. low).



FIG. 3M depicts a Kaplan-Meier survival curve by four-way sorting using cutaneous melanoma (SKCM) TCGA data20 (logrank Mantel-Cox test).



FIG. 3N illustrates immune signatures (GSEA) in melanoma biopsy specimens (pre- and on-treatment) in clusters of patients with varying expression of CCL19 and CXCL13 in cutaneous melanoma (SKCM) TCGA.



FIG. 3O is a heatmap that illustrates an unsupervised hierarchical clustering of Day 3 PDOTS anti-PD1 induced cytokines, expressed as row normalized (L2FC; n=14), annotated by response to anti-PD-1 therapy and timing of sample collection.



FIG. 4A depicts a scheme of impact of TBK1/IKKε inhibition on cytokine production from tumor cells and T cells.



FIG. 4B depicts the chemical structure of Compound 1 with IC50 towards TBK1/IKKE, and EC50 in HCT116 cells.



FIG. 4C depicts cytokine heatmaps for CT26 spheroids (lacking immune cells) on Day 1, 3, and 6±Compound 1 (n=3, biological replicates) expressed as log 2 fold-change (L2FC) relative to vehicle control.



FIG. 4D is a dose-response curve for Compound 1 on IL-2 in human CD4 (n=3) and CD8 (n=5) T cells.



FIG. 4E is a dose-response curve for Compound 1 on IFNγ in human CD4 (n=3) and CD8 (n=5) T cells.



FIG. 4F depicts cytokine heatmaps for CT26 MDOTS treated with IgG+Cmpd1 (1 μM), αPD-1 (10 μg/mL), or αPD-1+Cmpd1 (1 μM) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG with vehicle control. 2-sided Welch's 2-sample t-test with unequal variance (α=0.05).



FIG. 4G is a chart that depicts live (AO=green)/dead (PI=red) quantification of CT26 MDOTS after 6 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).



FIG. 4H depicts imaging results corresponding to live (AO=green)/dead (PI=red) quantification of CT26 MDOTS after 6 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).



FIG. 4I depicts CT26 allograft tumor volume over time following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 4J depicts CT26 allograft percent change in tumor volume following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 4K depicts CT26 allograft percent survival following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 5A depicts common gating for viable CD45+ cells in immune cell profiling by multi-color flow cytometry experiments.



FIG. 5B depicts gating hierarchy for T cell lineage and phenotypic marker in immune cell profiling by multi-color flow cytometry experiments.



FIG. 5C depicts myeloid cell gating hierarchy in immune cell profiling by multi-color flow cytometry experiments.



FIG. 5D depicts gating for NK lineage and Tregs in immune cell profiling by multi-color flow cytometry experiments.



FIG. 6A depicts immune cell sub-populations in MC38 tumors and/or spheroids from immune cell profiling of MDOTS. Immune cell sub-populations from MC38 (a) bulk tumor (n=5) to S1, S2, S3 (n=6) were evaluated by flow cytometry, as in FIG. 1b (Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; *p<0.05; ns=not significant).



FIG. 6B depicts a Pearson correlation matrix using composite of 21 cell surface markers in MC38 tumor, S1, S2, and S3 spheroids.



FIG. 6C depicts immune cell sub-populations in B16F10 tumors and/or spheroids from immune cell profiling of MDOTS. Immune cell sub-populations from B16F10 (a) bulk tumor (n=5) to S1 (n=4), S2 (n=5), and S3 (n=4) evaluated by flow cytometry (Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; *p<0.05; ns=not significant).



FIG. 6D depicts CD45+ cells (% live cells) in MC38 (n=6), B16F10 (n=5), and CT26 (n=5) MDOTS (S2). Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; *p<0.05.



FIG. 6E depicts immune sub-populations (% CD45+ cells) in MC38 (n=6), B16F10 (n=5), and CT26 (n=5) MDOTS (S2). 2-way ANOVA with Tukey's multiple comparisons test, (α=0.05; *p<0.05, ***p<0.001, ****p<0.0001).



FIG. 6F depicts surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD4 and CD8 populations in PDOTS (n=40) from immune cell profiling of PDOTS.



FIG. 6G depicts surface expression of PD-L1 and PD-L2 on myeloid sub-populations, including granulocytic myeloid-derived suppressor cells (gMDSCs), monocytes, tumor-associated macrophages (TAMs), monocytic myeloid-derived suppressor cells (mMDSCs), and plasmacytoid dendritic cells (pDCs).



FIG. 6H depicts immune cell sub-populations of PDOTS fractions (S1, S2, S3) evaluated by flow cytometry, for CD45+ (n=8), CD3+ (n=8), CD4+ (n=7), CD8+ (n=7), CD14+ (n=7), and CD15+ (n=6). Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; ns=not significant.



FIG. 6I depicts antigen-experienced sub-population (CD45RO+), effector memory (CD45RO+CCR7−) subtype, and surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD4 populations in PDOTS fractions (n≥3; Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; ns=not significant).



FIG. 6J depicts antigen-experienced sub-population (CD45RO+), effector memory (CD45RO+CCR7−) subtype, and surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD8 populations in PDOTS fractions (n≥3; Kruskal-Wallis test with Dunn's multiple comparisons test, α=0.05; ns=not significant).



FIG. 7A depicts immunofluorescence staining of MC38 MDOTS.



FIG. 7B depicts immunofluorescence staining of NSCLC PDOTS.



FIG. 7C depicts immunofluorescence staining of NSCLC PDOTS.



FIG. 7D depicts immunofluorescence staining for MC38 MDOTS stained for CD45+ immune cells (purple) and CD8+ T cells (yellow) with calcein (green) staining live cells and Hoechst (blue) staining all cell nuclei at Day 7 after treatment with IgG (10 μg/mL) or anti-PD-1 (10 μg/mL) (scale bar=20 μm).



FIG. 7E is a chart that depicts live/dead analysis of MC38 MDOTS±anti-PD-1 performed by independent lab (n=3, biological replicates).



FIG. 7F is a chart that depicts live/dead analysis of CT26 MDOTS performed on Day 6 following treatment with isotype IgG control (10 μg/mL) or anti-PD-1 (10 μg/mL)±anti-CD8 (10 μg/mL) (n=6, biological replicates; 2-way ANOVA with Tukey's multiple comparisons test; ****p<0.0001, ns=not significant).



FIG. 7G depicts a comparison of intratumoral and inter-tumoral heterogeneity evaluating CD8+ T cell counts (IF, performed on Day 4) and live/dead analysis (AO/PI staining) of CT26 MDOTS (Day 5).



FIG. 8A depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to αPD-1 grouped by Th1 and IFN-γ effector cytokines, (n=28; 2-sided, paired, t-test, α=0.05).



FIG. 8B depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to αPD-1 grouped by granulocyte chemoattractants, (n=28; 2-sided, paired, t-test, α=0.05).



FIG. 8C depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to αPD-1 grouped by IPRES immune suppressive cytokines, (n=28; 2-sided, paired, t-test, α=0.05).



FIG. 8D illustrates a comparison of PDOTS cytokine profiles after 3 days in standard growth conditions with and without isotype control IgG antibody (50 μg/mL) (n=2), performed using PDOTS derived from sample MGH-16 (melanoma).



FIG. 8E depicts CCL19 and CXCL13 levels (pg/mL) relative to the number of spheroids per device in control and treatment (αPD-1) conditions (R2=Pearson correlation coefficient).



FIG. 8F depicts results of biological replicates for MGH-16 PDOTS in response to PD-1 blockade (n=3, L2FC relative to untreated control on Day 3).



FIG. 8G depicts CCL19 and CXCL13 levels (pg/mL) from biological replicates for MGH-16 PDOTS in response to PD-1 blockade (n=3, L2FC relative to untreated control on Day 3).



FIG. 8H depicts the correlation between CCL19 and CXCL13 upregulation (log 2 fold-change relative to untreated control) in response to αPD-1, αCTLA-4, or αPD-1+αCTLA-4 (R2=Pearson correlation coefficient).



FIG. 8I illustrates the effect of culture in the microfluidic device on cytokine profile following αPD-1 treatment. Equal volumes of PDOTS from patient MGH-16 (in collagen hydrogels) were loaded for microfluidic device (or into a single well of a 96-well plate in equal volumes of culture media. Media was collected on Day 3 (control and αPD-1) for cytokine profiling. Induction of cytokines represented as fold-change relative to the untreated control.



FIG. 9A is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in DFCI-25 (melanoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.



FIG. 9B is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in MGH-12 (melanoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.



FIG. 9C is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in DFCI-16 (thyroid carcinoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.



FIG. 9D is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with αPD-1, αCTLA-4, or αPD-1+αCTLA-4 in DFCI-19 (pancreatic adenocarcinoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.



FIG. 10A depicts RNA-seq showing select cytokines, cytokine receptors, cytotoxic T cell (CTL) associated genes, and IPRES transcripts (L2FC relative to pre-treatment control in 10 sets of patient samples).



FIG. 10B depicts RNA-seq absolute expression (RPKM) for cytotoxic T cell effector associated genes (IFNG, IFNGR1, granzyme A, granzyme B) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients) from checkpoint blockade.



FIG. 10C depicts RNA-seq absolute expression (RPKM) for select IPRES genes in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients) from checkpoint blockade.



FIG. 10D depicts pre-treatment expression of CCL19 and CXCL13 in responders (n=15) and non-responders (n=13) to PD-1 blockade. Expression data is represented as transcripts per million (TPM) with error bars indicating standard deviation (ns=not significant; unpaired, 2-sided, Mann-Whitney test, α=0.05).



FIG. 10E depicts pre-treatment expression of CCL19 and CXCL13 in patients who experienced clinical benefit (CB, n=14), no clinical benefit (NCB, n=22), and no clinical benefit, but long-term survival (NCB+LTS, n=5) from ipilimumab (αCTLA-4). Expression data is represented as transcripts per million (TPM) with error bars indicating standard deviation (ns=not significant; Kruskal-Wallis with Dunn's multiple comparisons test, α=0.05).



FIG. 10F is a heatmap demonstrating log(2) fold change (on-αPD-1/pre-αPD-1) in expression of indicated cytokines.



FIG. 10G is a heatmap demonstrating log(2) fold change of plasma cytokines using matched plasma samples (on-treatment/pre-treatment) for responders (R; n=7) and non-responders (NR; n=4) to anti-PD-1 therapy.



FIG. 10H depicts four-way Kaplan-Meier survival curves by CCL19/CXCL13 expression (high-high, high-low, low-high, and low-low) using urothelial bladder carcinoma (BLCA), head & neck squamous cell carcinoma (HNSC), and breast carcinoma (BRCA) TCGA data (pairwise analysis using log-rank Mantel-Cox test, *p<0.05).



FIG. 11A depicts H&E imaging (10× objective) of tumor-associated tertiary lymphoid structure (TA-TLS), higher magnification (40× objective), and quantitation of TA-TLS identified in 52 H&E slides.



FIG. 11B depicts PDOTS divided into CCL19/CXCL13-high (n=14) and CCL19/CXCL13-low (n=14) by median L2FC (Mann-Whitney test, ****p<0.0001).



FIG. 11C depicts median immune cell composition (CD45+, CD4+, CD8+, CD14+, CD15+) between PDOTS with distinct ex vivo expression of CCL19/CXCL13 (high vs. low).



FIG. 11D depicts median immune cell composition (CD4+PD1+ and CD8+PD-1+) in CCL19/CXCL13 high vs. low PDOTS.



FIG. 11E depicts relative expression of CCL19 and CXCL13 by qRT-PCR in cancer-associated fibroblasts (CD45−CD90+), cancer-associated endothelial cells (CD31+CD144+), CD45− (cancer cells, etc.) and CD45+ immune cells following 4-way cell sorting (n=2, technical replicates from MGH-16).



FIG. 11F depicts immunohistochemical staining of CCL19, CXCL13, αSMA (cancer-associated fibroblasts), and CD31 (endothelial cells) in melanoma specimen (pt 422, on-treatment; 40× magnification, scale bar 400 μm).



FIG. 12A depicts mean cytokine changes from PDOTS following ex vivo PD-1 blockade in patients with clinical benefit (n=5; PR/SD) and without clinical benefit (n=9; MR/PD) from PD-1 blockade (*p<0.05).



FIG. 12B depicts four-way Kaplan-Meier survival curves by CX3CL1/CCL20 expression (high-high, high-low, low-high, and low-low) using melanoma TCGA data (pairwise analysis using log-rank Mantel-Cox test, α=0.05, ns=not significant).



FIG. 12C depicts composite IPRES6 score (sum of L2FC for CCL2, CCL7, CCL8, CCL13, IL-10) in response to ex vivo PD-1 blockade in PDOTS samples from patients with clinical benefit (PR/SD) and without clinical benefit (MR/PD) from PD-1 blockade.



FIG. 12D depicts heatmaps of Day 3 PDOTS anti-PD1 induced cytokines for samples DFCI-13, -16, -18, and -21 (serial sampling from same patient with metastatic papillary thyroid cancer), expressed as L2FC relative to untreated control.



FIG. 12E is a chart that depicts serial immune profiling of samples DFCI-13, -16, -18, -21, and -22 from the same patient undergoing indicated treatments.



FIG. 12F is a heatmap of relative anti-PD1 induced cytokine changes from MC38 and B16F10 MDOTS (L2FC relative to isotype control; n=3, biological replicates).



FIG. 12G is a chart that depicts absolute cytokine levels in CT26 MDOTS over time (n=3, biological replicates).



FIG. 12H depicts Live/Dead analysis at Day 6 in CT26 MDOTS treated with anti-CCL2±anti-PD-1 at Days 1, 3, and 6 (L2FC relative to isotype control; n=3, biological replicates).



FIG. 12I is a heatmap of relative cytokine changes in CT26 MDOTS treated with anti-CCL2±anti-PD-1 at Days 1, 3, and 6 (L2FC relative to isotype control; n=3, biological replicates).



FIG. 13A is a scheme that depicts chemical synthesis of Compound 1.



FIG. 13B is a chart that depicts IC50 values for indicated enzymes treated with Compound 1.



FIG. 13C depicts an IC50 curve for TBK1.



FIG. 13D depicts an IC50 curve for IKKε (IKBKE).



FIG. 13E is a chart that depicts effect of Compound 1 on viability of CT26 spheroids lacking immune cells (n=3, biological replicates).



FIG. 13F illustrates fold-change in IL-2 levels produced by Jurkat cells with increasing doses of Compound 1.



FIG. 13G depicts change in tumor volume following re-implantation of CT26 and EMT-6 cells into the flanks of mice previously treated with anti-PD-L1+Compound 1.



FIG. 14A is a cytokine heatmap for MC38 MDOTS treated with IgG+Cmpd1 (1 μM), αPD-1 (10 μg/mL), or αPD-1+Cmpd1 (1 μM) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG (10 μg/mL) with vehicle control (DMSO 0.1%). 2-sided Welch's 2-sample t-test with unequal variance (α=0.05).



FIG. 14B is a cytokine heatmap for B16F10 MDOTS treated with IgG+Cmpd1 (1 μM), αPD-1 (10 μg/mL), or αPD-1+Cmpd1 (1 μM) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG (10 μg/mL) with vehicle control (DMSO 0.1%). 2-sided Welch's 2-sample t-test with unequal variance (α=0.05).



FIG. 14C is a chart that depicts live (AO=green)/dead (PI=red) quantification of MC38 MDOTS after 5 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).



FIG. 14D depicts MC38 allograft tumor volume waterfall plot following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 14E depicts percent survival following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 14F is a chart that depicts live (AO=green)/dead (PI=red) quantification of B16F10 MDOTS after 6 days treated with IgG-DMSO, Cmpd1 (1 μM), αPD-1, and αPD-1+Cmpd1 (α=0.05, ns=not significant. Kruskal-Wallis ANOVA with multiple comparisons; n=3).



FIG. 14G depicts quantification of small lung metastases in B16F10 tail vein injection model following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, 1-way ANOVA with Tukey's multiple comparison's test, ns=not significant).



FIG. 14H depicts quantification of medium lung metastases in B16F10 tail vein injection model following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, 1-way ANOVA with Tukey's multiple comparison's test, ns=not significant).



FIG. 14I depicts MB49 allograft tumor volume waterfall plot following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 14J depicts MB49 allograft tumor volume waterfall plot as a bar chart following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 14K depicts percent survival following IgG+vehicle, IgG+Cmpd1, αPD-L1+vehicle, and αPD-L1+Cmpd1 (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).



FIG. 15 depicts a table summary of Pilot RNA Extraction, QC, and Quantitation (left), and a representation bioanalyzer trac showing fully intact total RNA from MDOTS (right).



FIG. 16A is a sample-sample correlation of RNA-seq data collected from a variety of MC38 MDOTS treatment types (αPD-1, αPD-1+CD8, IFNγ, IgG, PD-1) at two distinct timepoints (Day 3, Day 6).



FIG. 16B provides two depictions of a principal components (PC) analysis of RNA-seq data collected from a variety of MC38 MDOTS treatment types (αPD-1, αPD-1+CD8, IFNγ, IgG, PD-1) at two distinct timepoints (Day 3, Day 6).



FIG. 16C depicts RNA-seq data collected from MC38 MDOTS sample treated with IFNγ on Day 6. Of note, several IFNγ genes are induced, including CXCL10, CXCL11, PD-L1, IDO1, and IDO2.



FIG. 16D depicts RNA-seq data collected from MC38 MDOTS sample treated with αPD-1 on Day 6. Of note, several novel targets and biomarkers are induced, including SOCS3, Pde4b, Pde4d, and Adcy5.





DETAILED DESCRIPTION

Among other aspects, the disclosure provides methods for evaluating tumor cell spheroids in a three-dimensional microfluidic device by monitoring a ratio of live cells to dead cells. In some aspects, the methods include steps of exposing separate aliquots of a tumor spheroid sample to different conditions, such as the inclusion or exclusion of a test compound.


As such, in some embodiments, the effects of a test compound can be evaluated by monitoring its effects on the ratio of live cells to dead cells. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid can be evaluated optically and reproducibly, to establish the effects of drugs on the tumor cells within the spheroids, while distinguishing the effects on tumor cells resulting from the act of culturing the tumor cells. Also provided are other methods for evaluating tumor sphere spheroids, including monitoring a chemical change, e.g., such as a change in nucleic acid expression, when separate aliquots of a tumor spheroid sample are exposed to different conditions, such as the inclusion or exclusion of a test compound.


As used herein, the term “tumor” refers to a neoplasm, i.e., an abnormal growth of cells or tissue and is understood to include benign, i.e., non-cancerous growths, and malignant; i.e., cancerous growths including primary or metastatic cancerous growths.


Examples of neoplasms include, but are not limited to, mesothelioma, lung cancer (e.g., small-cell lung cancer, non-small cell lung cancer), skin cancer (e.g., melanoma), stomach cancer, liver cancer, colorectal cancer, breast cancer, pancreatic cancer, prostate cancer, blood cancer, bone cancer, bone marrow cancer, and other cancers.


The term “tumor spheroid,” or “tumor cell spheroid” as used herein, refers to an aggregation of tumor cells constituting a small mass, or lump of tumor cells. In some embodiments, tumor spheroids are less than about 3 cm, less than about 2 cm, less than about 1 cm, less than about 5 mm, less than about 2.5 mm, less than about 1 mm, less than about 100 μm, less than about 50 μm, less than about 25 μm, less than about 10 μm, or less than about 5 μm in diameter. In some embodiments, the tumor spheroids have a diameter of 10 μm to 500 μm. In some embodiments, the tumor spheroids have a diameter of 40 μm to 100 μm. In some embodiments, the tumor spheroids have a diameter of 40 μm to 70 μm.


The term “primary tumor sample” as used herein refers to a sample comprising tumor material obtained from a subject having cancer. The term encompasses tumor tissue samples, for example, tissue obtained by surgical resection and tissue obtained by biopsy, such as for example, a core biopsy or a fine needle biopsy. The term also encompasses patient derived xenograft (PDX). Patient derived xenografts are created when cancerous tissue from a patient's primary tumor is implanted directly into an immunodeficient mouse (see, for example, Morton C L, Houghton P J (2007). “Establishment of human tumor xenografts in immunodeficient mice”. Nature Protocols 2 (2): 247-50; Siolas D, Hannon G J (September 2013). “Patient-derived tumor xenografts: transforming clinical samples into mouse models”. Cancer Research 73 (17): 5315-9). PDX mirrors patients' histopathological and genetic profiles. It has improved predictive power as preclinical cancer models, and enables the true individualized therapy and discovery of predictive biomarkers.


In some embodiments, the subject is a human. In some embodiments, the subject is a non-human mammal or a non-human vertebrate. In some embodiments, the subject is laboratory animal, a mouse, a rat, a rodent, a farm animal, a pig, a cattle, a horse, a goat, a sheep, a companion animal, a dog a cat, or a guinea pig.


In some embodiments, a tumor sample as used herein is derived from a subject known to have resistance or sensitivity to a particular therapeutic treatment. For example, in some embodiments, methods provided herein can identify novel combination therapies and/or novel single therapies that overcome resistance to a specified treatment, e.g., PD-1 inhibition in the treatment of cancer. In some embodiments, where PD-1 combination therapies are to be evaluated, tumor samples may be derived from one or more subjects having the same or varied levels of sensitivity to PD-1 inhibition therapy. In some embodiments, the tumor sample is derived from a B16F10 murine model. B16F10 is a murine model that is minimally sensitive to PD-1 blockade. In some embodiments, the tumor sample is derived from an MC38 murine model. MC38 is a murine model that is highly sensitive to PD-1 blockade relative to B16F10. In some embodiments, the tumor sample is derived from a CT26 murine model. CT26 is a murine model that is of an intermediate sensitivity relative to B16F10 and MC38 models. In some embodiments, methods provided herein comprises steps of evaluating a combination of two or more of tumor samples derived from B16F10, MC38, or CT26 models.


Tumor cell spheroids can be prepared by any method known in the art. Exemplary methods for preparing tumor cell spheroids are described in WO 2016/112172, the disclosure of which is incorporated herein by reference.


In some embodiments, the primary tumor sample is collected in a serum-supplemented medium, for example but not limited to, RPMI medium supplemented with 10% fetal bovine serum. The sample is then minced, i.e., cut or chopped into tiny pieces. In some embodiments, the sample is minced on ice. In some embodiments, the minced primary tumor sample comprises tumor pieces in the size of about 3 mm, 2.5 mm, 2.0 mm, 1.5 mm, 1.0 mm, 0.5, or 0.25 mm.


In some embodiments, the primary tumor sample is not frozen and thawed.


In some embodiments, minced primary tumor sample is frozen in a medium supplemented with serum and thawed prior to treating with the composition comprising the enzyme. In some embodiments, the minced primary tumor sample is frozen for at least 6 hours 12 hours, 24 hours, 2 days, 1 week or one month. In some embodiments, the minced primary tumor sample is frozen at −80° C. In some embodiments, the minced primary tumor sample is frozen in liquid nitrogen. In some embodiments, the minced primary tumor sample is frozen in a medium supplemented with serum. In some embodiments, the minced primary tumor sample is frozen in a mixture containing serum and solvent such as Dimethyl sulfoxide (DMSO). In some embodiments, the minced primary tumor sample is frozen in a mixture containing fetal bovine serum and Dimethyl sulfoxide (DMSO).


In some embodiments, the frozen minced primary tumor sample is thawed, i.e., defrosted, before treating the sample with a composition comprising an enzyme. In some embodiments, the minced primary tumor sample is thawed in a water bath kept at about 37° C. (e.g., 35° C., 36° C., 37° C., 38° C., or 39° C.). In some embodiments, the minced primary tumor sample is thawed at room temperature.


The minced primary tumor sample is treated with an enzyme mix to digest the tumor samples. In some embodiments, the composition comprising an enzyme includes collagenase. In some embodiments, the composition comprising an enzyme includes a serum-supplemented culture medium, insulin, one or more corticosteroids, one or more antibiotics, collagenase and optionally one or more growth factors. Serum-supplemented culture media, corticosteroids, antibiotics, and growth factors are well-known in the art. In some embodiments, the composition comprising an enzyme comprises DMEM or RPMI, fetal bovine serum, insulin, epidermal growth factor, hydrocortisone, Penicillin and/or Streptomycin, and collagenase. In some embodiments, the composition comprising an enzyme comprises further comprises a buffering agent such as 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES).


“Treating the minced primary tumor sample with a composition comprising an enzyme” comprises incubating the minced tumor samples with the enzyme composition for at least 1 hour. In some embodiments, the minced tumor samples are incubated with the enzyme mix for at least 2 hours, at least 4 hours, at least 6 hours, at least 8 hours, at least 10 hours, at least 12 hours, at least 15 hours or at least 24 hours. In some embodiments, the minced primary tumor sample is incubated with the enzyme mix at 25° C., 26° C., 27° C., 28° C., 29° C., 30° C., 31° C., 32° C., 33° C., 34° C., 35° C., 36° C., 37° C., 38° C., or 39° C. In some embodiments, the minced primary tumor sample is incubated with the enzyme mix at 37° C.


In some embodiments, the minced primary tumor sample is treated with the composition comprising the enzyme in an amount or for a time sufficient yield a partial digestion of the minced primary tumor sample. In some embodiments, the minced primary tumor sample is treated with the composition comprising the enzyme for 30 minutes to 15 hours at a temperature of 25° C. to 39° C.


Collecting tumor spheroids from the enzyme mix treated sample comprises centrifuging and washing the sample at least twice followed by isolating the digested tumor spheroids of the desired size. In some embodiments, the enzyme mix treated sample is centrifuged and washed using phosphate buffered saline (PBS) at least twice. Tumor spheroids of the desired size are collected using sieves. In some embodiments, the tumor spheroids having a diameter of 10 μm, 50 μm, 100 μm, 200 μm, 300 μm, 400 μm, 450 μm, and 500 μm are collected from the enzyme mix treated sample with the use of a sieve. In some embodiments, the tumor spheroids having a diameter of 40 m to 100 μm are collected from the enzyme mix treated sample with the use of a sieve. In some embodiments, the tumor spheroids having a diameter of 40 μm, 50 μm, 60 μm and 70 μm are collected from the enzyme mix treated sample with the use of a sieve.


The tumor spheroids having a desired diameter are collected by sieving the enzyme mix treated sample through cell strainers. In some embodiments, the tumor spheroids having a diameter of 10 μm to 500 μm are collected by sieving the enzyme mix treated sample via 500 m and 10 μm cell strainers to yield tumor spheroids having a diameter of 10 μm to 500 μm. In some embodiments, the tumor spheroids having a diameter of 40 m to 100 μm are collected by sieving the enzyme mix treated sample via 100 μm and 40 μm cell strainers to yield tumor spheroids having a diameter of 10 μm to 500 μm. The tumor spheroids of the desired diameter are collected and suspended in a biocompatible gel. Examples of biocompatible gel include collagen, BD Matrigel™ Matrix Basement Membrane, or fibrin hydrogel (e.g., fibrin hydrogel generated from thrombin treatment of fibrinogen).


In some embodiments, the collected tumor spheroids are not frozen and then thawed before suspending in the biocompatible gel. In some embodiments, the collected tumor spheroids are introduced into the three-dimensional cell culture device within less than 2 hours, less than 1 hour, less than 30 minutes, less than 20 minutes, less than 10 minutes, or less after collection.


In some embodiments, the collected tumor spheroids are frozen in a freezing medium and then thawed before suspending in the biocompatible gel. In some embodiments, the collected tumor spheroids are frozen for at least 6 hours 12 hours, 24 hours, 2 days, 1 week or one month. In some embodiments, the collected tumor spheroids are frozen at −80° C. In some embodiments, the collected tumor spheroids are frozen in liquid nitrogen. In some embodiments, the collected tumor spheroids are frozen at −80° C. overnight, and then transferred to liquid nitrogen for storage. In some embodiments, the collected tumor spheroids are frozen in a medium supplemented with serum. In some embodiments, the collected tumor spheroids are frozen in a mixture containing culture medium such as DMEM or RPMI, fetal bovine serum and solvent such as Dimethyl sulfoxide (DMSO). The frozen spheroids are thawed, for example overnight at 4° C., and then suspended in the biocompatible gel.


The tumor spheroids are cultured, i.e., grown, in a three dimensional (3D) microfluidic device. In some embodiments, the tumor spheroids are cultured with endothelial cells, such as human umbilical vein endothelial cells (HUVECs). In some embodiments, the tumor spheroids are cultured without endothelial cells. In some embodiments, the tumor spheroids are cultured with or without endothelial cells for at least 1 day, at least 2 days, at least 4 days, at least 6 days, at least 1 week, or at least 2 weeks.


3D microfluidic devices are known in the art and include, for example, but not limited to, the devices described in US 2013/0143230, EP2741083, US 2014/0057311, U.S. Pat. No. 8,748,180, and WO 2016/112172, the disclosures of which are incorporated by reference herein.


In some embodiments, a 3D microfluidic device refers to a device that comprises one or more fluid channels flanked by one or more gel cage regions, wherein the one or more gel cage regions comprises the biocompatible gel in which the tumor spheroids are embedded, and wherein the device recapitulates, i.e., mimics, the in vivo tumor microenvironment. In order to facilitate visualization, the microfluidic device is typically comprised of a substrate that is transparent to light, referred to herein as “an optically transparent material”. As will be appreciated by those of skill in the art, suitable optically transparent materials include polymers, plastic, and glass. Examples of suitable polymers are polydimethylsiloxane (PDMS), poly(methyl methacrylate) (PMMA), polystyrene (PS), SU-8, and cyclic olefin copolymer (COC). In some embodiments, all or a portion of the device is made of a biocompatible material, e.g., the material is compatible with, or not toxic or injurious to, living material (e.g., cells, tissue).


The fluid channel can be used to contain a (one or more) fluid (e.g., cell culture media), cells such as endothelial cells, cellular material, tissue, fluorophore dyes, and/or compounds (e.g., drugs) to be assessed, while the gel cage regions may be used to contain a gel (e.g., biologically relevant gel, such as collagen, Matrigel™, or fibrin hydrogel (e.g., fibrin hydrogel generated from thrombin treatment of fibrinogen)). In some embodiments, the 3D microfluidic device comprises the device described in US 2014/0057311, the disclosure of which is incorporated by reference herein. In particular, paragraphs [0056] to [0107] which describe the regions, channels, chambers, posts, and arrangement of posts, and paragraphs [0127] to [0130] which describe the methods of making the device are incorporated by reference herein.


In some embodiments, the method for identifying a compound for treating cancer, comprises culturing a first and second aliquot of tumor cell spheroids in a three-dimensional microfluidic device as described herein in the presence and absence of one or more test compounds, detecting a change in the ratio of live cells to dead cells in the aliquots of tumor cell spheroids.


In some embodiments, the change in the ratio of live cells to dead cells in the aliquots of tumor cell spheroids is monitored by measuring the total fluorescence emitted by each of the first and second fluorophore dyes. Accordingly, in some embodiments, the dead cell fluorescence and the live cell fluorescence can be added together to yield a live and dead cell total. In some embodiments, the amount of dead cells may be expressed as a percentage of the dead cell fluorescence to the total fluorescence. In some embodiments, the amount of live cells can be expressed as a percentage of the live cell fluorescence to the total. In some embodiments, the dead cell fluorescence and the live cell fluorescence can be expressed as a ratio. For example, in some embodiments, the ratio is expressed as dead cells/live cells or live cells/dead cells. In this manner, expressing as a ratio provides a standardized method of evaluating tumor cell spheroids.


In some embodiments, proliferation and/or dispersion of the tumor cell spheroids are also assessed.


In some embodiments, the method for identifying a compound or combination of compounds for treating cancer, comprises obtaining tumor spheroids from an enzyme treated tumor sample, suspending a first aliquot of the tumor spheroids in biocompatible gel, and suspending a second aliquot of the tumor spheroids in biocompatible gel. In some embodiments, the method further comprises placing the first aliquot of the tumor spheroids in biocompatible gel in a first three-dimensional device, and contacting the first aliquot with a first fluorophore dye selective for dead cells and a second fluorophore dye selective for live cells, where the first fluorophore dye emits fluorescence at a first wavelength when bound to a dead cell and the second fluorophore dye emits fluorescence at a second wavelength different from the first wavelength when bound to a live cell. In some embodiments, the method further comprises measuring total fluorescence emitted by each of the first and second fluorophore dyes in the first aliquot. In some embodiments, the method further comprises culturing the second aliquot in a second three-dimensional device, contacting the second aliquot with the first fluorophore dye and the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye. In some embodiments, the method further comprises measuring total fluorescence emitted by each of the first and second fluorophore dyes in the second aliquot, wherein an increase or decrease in the ratio of live cells to dead cells in each of the aliquots may be assessed.


“Culturing patient-derived tumor cell spheroids in the presence of the test compound” comprises introducing the test compound into the one or more fluid channels of the device described herein, wherein the one or more gel cage regions of the device comprises a gel in which the tumor spheroids are embedded; and culturing the tumor spheroids under suitable culture conditions. Suitable conditions include growing the tumor cell spheroids under standard cell culture conditions (e.g. at 37° C. in a humidified atmosphere of >80% relative humidity air and 5 to 10% CO2).


In some embodiments, techniques provided herein relate to evaluating the effects of one or more therapeutic treatments in a tumor cell spheroid culture. In some embodiments, changes in the tumor cell spheroid culture are evaluated using one or more luminescent probes (e.g., one or more fluorescent dyes). For example, in some embodiments, methods described herein comprise steps of contacting a tumor cell spheroid culture with a first fluorophore dye and a second fluorophore dye that each selectively bind to a cell type that is different from the other, and where the fluorophore dyes emit fluorescence at different wavelengths when bound to the respective cell types. In some embodiments, the first fluorophore dye is selective for dead cells and the second fluorophore dye is selective for live cells. In some embodiments, the first fluorophore dye is selective for live cells and the second fluorophore dye is selective for dead cells.


In some embodiments, one or more fluorophore dye (e.g., one or more of a first fluorophore dye, one or more of a second fluorophore dye) is introduced into the one or more fluid channels of the cell culture device. The techniques provided in the present disclosure are envisioned to be compatible with any suitable fluorophore dye (e.g., fluorophore-containing dyes, stains, fluorescent labels, etc.). Suitable fluorophore dyes are known in the art and can be selected by a practitioner in view of a desired application of the techniques described herein. For example, in some embodiments, the one or more fluorophore dyes utilized in the techniques described herein can be compatible with staining under fixed or non-fixed conditions.


Fluorophore dyes that can be used for the detection of dead cells in non-fixed conditions include, by way of example and not limitation, DNA-dependent stains such as propidium iodide, DRAQ7, and 7-AAD. Fluorophore dyes that can be used for the detection of dead cells in either fixed or non-fixed conditions include, by way of example and not limitation, dyes listed in Table 1.









TABLE 1







Examples of dyes to stain for dead cells










Excitation
Emission


Dye
(max)
(max)





Propidium iodide
540 nm
620 nm


DRAQ7
600 nm
697 nm


7-AAD
550 nm
645 nm


eBioscience Fixable Viability Dye eFluor ® 455UV
350 nm
455 nm


eBioscience Fixable Viability Dye eFluor ® 450
405 nm
450 nm


eRinscience Fixable Viability Dye eFluor ® 506
405 nm
506 nm


eBioscience Fixable Viability Dye eFluor ® 520
488 nm
522 nm


eBioscience Fixable Viability Dye eFluor ® 660
633 nm
660 nm


eBioscience Fixable Viability Dye eFluor ® 780
633 nm
780 nm


BioLegend Zombie Aqua ™
382 nm
510 nm


BioLegend Zombie NIR ™
718 nm
746 nm


BioLegend Zombie Red ™
600 nm
624 nm


BioLegend Zombie Violet ™
400 nm
423 nm


BioLegend Zombie UV ™
362 nm
459 nm


BioLegend Zombie Yellow ™
396 nm
572 nm









The techniques provided in the present disclosure are envisioned to be compatible with any suitable fluorophore dye selective for live cells known in the art. Fluorophore dyes that can be used for the detection of live or fixed cells include, by way of example and not limitation, DNA-dependent stains such as acridine orange, nuclear green LCS1 (ab138904), DRAQ5 (ab108410), CyTRAK Orange, NUCLEAR-ID Red DNA stain (ENZ-52406), and SiR700-DNA. Examples of non-DNA-dependent fluorophore dyes that stain for live cells are known in the art and include, by way of example and not limitation, calcein AM, calcein violet AM, and calcein blue AM. Fluorophore dyes that can be used for the detection of live or fixed cells include, by way of example and not limitation, dyes shown in Table 2.









TABLE 2







Examples of dyes to stain for live cells









Dye
Excitation
Emission





Vybrant ® DyeCycle ™ Violet
UV, 405 nm
437


Vybrant ® DyeCycle ™ Green
488 nm
534


Vybrant ® DyeCycle ™ Orange
488, 532 nm
563


Vybrant ® DyeCycle ™ Ruby
188, 633/5 nm
686


acridine orange
500 nm
526 nm


nuclear green LCS1 (ab138904)
503 nm
526 nm


DRAQ5 (ab108410)
647 nm
681 nm


CyTRAK Orange
488-550 nm
610 nm


NUCLEAR-ID Red DNA stain
566 nm
650 nm


(ENZ-52406)




SiR700-DNA
689 nm
716 nm


calcein AM
495 nm
515 nm


calcein violet AM
408 nm
450 nm


calcein blue AM
360 nm
445 nm









Additionally, two-color cell viability assays are available and may be used with the techniques described herein. Examples of live/dead cytotoxicity kits include, by way of example and not limitation, kits shown in Table 3.









TABLE 3







Examples of kits containing dyes to stain for both live/dead cells











Kit Name
Platform
Fluorescent Dyes
Ex/Em (nm)
Em Colors





LIVE/DEAD
FC, FM, M
calcein AM
494/517
Green


Viability/Cytotoxicity Kit for

ethidium
517/617
(Live)


mammalian cells

homodimer-1

Red






(Dead)


LIVE/DEAD Cell-Mediated
FC, FM, M
DiOC18(3)
484/501
Green


Cytotoxicity Kit for animal

propidium
536/617
(Live)


cells, 2000 assays

iodide

Red






(Dead)


LIVE/DEAD Sperm Viability
FC, FM
SYBR ™ 14
485/517
Green


Kit 200-1,000 assays

dye propidium
536/617
(Live)




iodide

Red






(Dead)


LIVE/DEAD Cell Vitality
FC, FM, M
SYTOX ™
488/530
Green


Assay Kit C12-

Green dye
488/575
(Dead)


resazurin/SYTOX ™ Green

C12-resazurin

Red


1,000 assays



(Live)









Changes in the tumor cell spheroid culture which predict or demonstrate a reduction in proliferation and/or dispersion of the tumor cell spheroids in the presence or absence of the test compound can be detected using known methods in the art, such as, chemical or physical methods, or a combination thereof.


As described herein, a tumor cell spheroid sample is evaluated by analyzing the relative amounts of live cells and dead cells in separate aliquots of the sample. In some embodiments, the relative amounts of live cells and dead cells in an aliquot is determined by fluorescence measurement. For example, in some embodiments, fluorescence measurement comprises total fluorescence acquisition of the emissions detected from a first fluorophore dye that selectively binds dead cells and a second fluorophore dye that selectively binds live cells. Based on such measurements, the relative emission levels can be parsed out to provide the amount of live cells relative to the amount of dead cells in the aliquot.


In some embodiments, the relative amounts or ratio of live cells to dead cells in an aliquot can be expressed as a percentage of the total fluorescence, such that:

[(% live cells)+(% dead cells)=100%]

In some embodiments, the relative levels of live cells and dead cells in a first aliquot is compared to a similar measurement obtained for a second aliquot that has been treated with a test compound. An increase in (% dead cells) in the presence of the test compound compared to the first aliquot is indicative that the test compound is effective for inducing cell death. In some embodiments, the percentage of dead cells in the presence of an effective test compound is increased relative to the absence of the test compound by about 5%, by about 10%, by about 15%, by about 20%, by about 25%, by about 30%, by about 35%, by about 40%, by about 50%, by about 60%, by about 70%, by about 80%, by about 90%, or greater.


In some embodiments, a change in the tumor cell spheroid culture can further be detected visually, e.g., using confocal microscopy imaging. The images obtained can be analyzed as described in Aref et al. Integr Biol (Camb). 2013 February; 5(2):381-9, the disclosure of which is incorporated by reference in its entirety. In particular, the paragraphs on pages 387-388 relating to image acquisition and analysis (normalized dispersion, Δ/Δ0, and normalized cell number (N/N0)) are incorporated by reference in their entirety.


In some embodiments, the change in the tumor cell spheroid culture is a clustering of immune cells around one or more tumor cell spheroids in the culture. In some embodiments, the change in the tumor cell spheroid culture is a decrease in size and/or number of cells of one or more tumor cell spheroids in the culture.


In some embodiments, the change in the tumor cell culture is further detected chemically. For example, in some embodiments, the change in the tumor cell spheroid culture is determined by detection of the presence of a biological molecule secreted into the culture supernatant. In some embodiments, the biological molecule is a protein, carbohydrate, lipid, nucleic acid, metabolite, or a combination thereof. In some embodiments, the biological molecule is a chemokine or a cytokine. In some embodiments, the cytokine is a growth factor (see e.g., Example 2). In some embodiments, the biological molecule is known to be associated with activation of the immune system or otherwise an enhancement of the immune response.


In some embodiments, the detected biological molecule(s) involves single cell sequencing of T cell receptors on tumor spheroid associated CD4 and CD8 T cells that become activated in the device.


In some embodiments, a sample of tumor cell spheroid culture supernatant may be obtained from the 3D culture device. In some embodiments, a secreted biological molecule or a profile of secreted biological molecules, e.g., a cytokine profile or chemokine profile, may be detected in the tumor cell spheroid culture supernatant.


Methods for detecting secreted biological molecules are known in the art. Exemplary assays and cytokines are disclosed, for example, in WO 2016/112172, the disclosure of which is incorporated herein by reference.


In some embodiments, a sample of tumor cell spheroid is analyzed by nucleic acid content. For example, it is possible to analyze extracellular nucleic acids, e.g., nucleic acids present in a culture medium of a tumor cell spheroid sample using methods known in the art. Alternatively, nucleic acids can be isolated from cells in a cultured sample using methods known in the art. In some embodiments, such analysis can be used to assess gene expression, e.g., to evaluate the expression of genes associated with cytotoxicity, such as cytokines and cytokine receptors. In some embodiments, the cytokines are growth factors (see e.g., Example 2). In some embodiments, DNA and/or RNA (e.g., mRNA, rRNA, tRNA, etc.) from a sample may be analyzed.


In some embodiments, RNA content of a sample is analyzed using RNA sequencing (RNA-seq). RNA-seq is a reliable, scalable, and comprehensive method to evaluate transcriptomic changes in the tumor immune microenvironment. The use of RNA-seq enables a broad and comprehensive analysis of changes in the tumor immune microenvironment associated with response and resistance to immune checkpoint blockade and furthermore can readily be applied to molecular targeted therapies, combination therapies, engineered immune cells, and other related applications. In some embodiments, RNA content is analyzed using single-cell RNA-seq methodologies. In some embodiments, analysis by nucleic acid content will be utilized for medium- and high-throughput assay development.


In some embodiments, the test compound inhibits epithelial-mesenchymal transition (EMT). In some embodiments, the test compound is a small molecule compound. In some embodiments, the methods described herein are used to screen a library of test compounds, for example, a library of chemical compounds. In some embodiments, the test compound comprises a nucleic acid molecule, for example, a DNA molecule, an RNA molecule, or a DNA/RNA hybrid molecule, single-stranded, or double-stranded. In some embodiments, the test compound comprises an RNAi compound, for example, an antisense-RNA, an siRNA, an shRNA, a snoRNA, a microRNA (miRNA), or a small temporal RNA (stRNA). In some embodiments, the test compound comprises an aptamer. In some embodiments, the test compound comprises a protein or peptide. In some embodiments, the test compound comprises an antibody or an antigen-binding antibody fragment, e.g., a F(ab′)2 fragment, a Fab fragment, a Fab′ fragment, or an scFv fragment. In some embodiments, the antibody is a single domain antibody. In some embodiments, the compound comprises a ligand- or receptor-binding protein. In some embodiments, the compound comprises a gene therapy vector.


In some embodiments, more primary tumor cell spheroids are cultured in the presence of more than one compound, e.g., a first test compound and a second test compound, optionally a third test compound, fourth compound, etc.


In some embodiments, a test compound is an anti-cancer compound. In some embodiments a test compound is a chemotherapeutic compound, an immunomodulatory compound, or radiation.


Exemplary chemotherapeutic compounds include asparaginase, busulfan, carboplatin, cisplatin, daunorubicin, doxorubicin, fluorouracil, gemcitabine, hydroxyurea, methotrexate, paclitaxel, rituximab, vinblastine, vincristine, etc. In some embodiments, a test compound is a vinca alkaloid, e.g., vinblastine, vincristine, vindesine, vinorelbine. In some embodiments, a test compound is an alkylating compound, e.g., cyclophosphamide, decarbazine, melphalan, ifosfamide, temozolomide. In some embodiments, a test compound is an antimetabolite, e.g., folic acid antagonists, pyrimidine analogs, purine analogs or adenosine deaminase inhibitor, e.g., fludarabine. In some embodiments, a test compound is an mTOR inhibitor. In some embodiments, a test compound is a proteasome inhibitor, e.g., aclacinomycin A, gliotoxin or bortezomib.


In some embodiments, a test compound is a small molecule inhibitor, e.g., a TBK1 inhibitor, a MEK inhibitor, a FAK inhibitor, a BRD/BET inhibitor, a CDK 4/6 inhibitor, an HDAC inhibitor, a DNMT inhibitor (or hypomethylating compound), a MET inhibitor, an EGFR inhibitor, or a BRAF inhibitor. In some embodiments, a test compound is a kinase inhibitor, e.g., a TBK1 inhibitor, a MEK inhibitor, a FAK inhibitor, or a CDK 4/6 inhibitor. For example, TBK-1 inhibitors are known in the art, e.g., Yu, T., et al. “TBK1 inhibitors: a review of patent literature (2011-2014)” Exp. Opin. On Ther. Patents 25(12); Hasan, M., et al. J. Immunol. 195(10):4573-77; and US20150344473, the contents of each of which are incorporated herein by reference.


Exemplary immunomodulatory compounds include immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of: CTLA-4, PD-1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor is a peptide, antibody, interfering RNA, or small molecule. In some embodiments, the immune checkpoint inhibitor, e.g., inhibitor, is a monoclonal antibody, or an Ig fusion protein. In some embodiments, the immune checkpoint inhibitor is an antibody or an antigen binding fragment thereof. In some embodiments, the immune checkpoint inhibitor is an anti-PD-1 antibody.


In some embodiments, the immune checkpoint inhibitor inhibits PD1. In humans, programmed cell death protein 1 (PD-1) is encoded by the PDCD1 gene. PDCD1 has also been designated as CD279 (cluster of differentiation 279). This gene encodes a cell surface membrane protein of the immunoglobulin superfamily. PD-1 is a 288 amino acid cell surface protein molecule. PD-1 has two ligands, PDL1 and PD-L2, which are members of the B7 family. PD-1 is expressed on the surface of activated T cells, B cells, and macrophages. PD-1 is expressed in pro-B cells and is thought to play a role in their differentiation. See T. Shinohara 5 et al., Genomics 23 (3): 704-6 (1995). PD-1 is a member of the extended CD28/CTLA-4 family of T cell regulators. (Y. Ishida et al., “EMBO J. 11 (11): 3887-95, (1992)). PD-1 may negatively regulate immune responses. PD1 limits autoimmunity and the activity of T cells in peripheral tissues at the time of an inflammatory response to infection.


An immune checkpoint inhibitor that inhibits PD-1, or a PD-1 antagonist, as used herein is a molecule that binds to PD-1 and inhibits or prevents PD-1 activation. Without wishing to be bound by theory, it is believed that such molecules block the interaction of PD-1 with its ligand(s) PD-L1 and/or PD-L2.


PD-1 activity may be interfered with by antibodies that bind selectively to and block the activity of PD-1. The activity of PD-1 can also be inhibited or blocked by molecules other than antibodies that bind PD-1. Such molecules can be small molecules or can be peptide mimetics of PD-L1 and PD-L2 that bind PD-1 but do not activate PD-1. Molecules that antagonize PD-1 activity include those described in U.S. Publications 20130280265, 20130237580, 20130230514, 20130109843, 20130108651, 20130017199, and 20120251537, 2011/0271358, EP 217095911, the entire disclosures of which are incorporated herein by reference. See also M. A. Curran, et al., Proc. Natl. Acad. Sci. USA 107, 4275 (2010); S. L. Topalian, et al., New Engl. J. Med. 366, 2443 (2012); J. R. Brahmer, et al., New Engl. J. Med. 366, 2455 (2012); and D. E. Dolan et al., Cancer Control 21, 3 (2014). Herein, PD-1 antagonists include: nivolumab, also known as BMS-936558 (Bristol-Meyers Squibb, and also known as MDX-1106 or ONO-4538), a fully human IgG4 monoclonal antibody against PD-1; pidilizumab, also known as CT-011 (CureTech), a humanized IgG1 monoclonal antibody that binds PD-1; MK-3475 (Merck, and also known as SCH 900475), an anti-PD-1 antibody; and pembrolizumab (Merck, also known as MK-3475, lambrolizumab, or Keytruda), a humanized IgG4-kappa monoclonal antibody with activity against PD-1. Compounds that interfere bind to the DNA or mRNA encoding PD-1 also can act as PD-1 inhibitors. Examples include a small inhibitory anti-PD-1 RNAi, an anti-PD-1 antisense RNA, or a dominant negative protein. PD-L2 fusion protein AMP-224 (codeveloped by Glaxo Smith Kline and Amplimmune) is believed to bind to and block PD-1.


In some embodiments, the immune checkpoint inhibitor inhibits PD-L1. In humans, programmed death-ligand 1 (PD-L1), also known as B7 homolog 1 (B7-H1) or cluster of differentiation 274 (CD274), is a 40 kDa type 1 transmembrane protein that is encoded by the CD274 gene. Foreign antigens normally induce an immune response triggering proliferation of antigen-specific T cells, such as antigen-specific CD8+ T cells. PD-L1 is an immune checkpoint inhibitor that may block or lower such an immune response. PD-L1 may play a major role in suppressing the immune system during events such as pregnancy, tissue allografts, autoimmune disease, and other disease states, such as hepatitis and cancer. The PD-L1 ligand binds to its receptor, PD-1, found on activated T cells, B cells, and myeloid cells, thereby modulating activation or inhibition. In addition to PD-1, PD-L1 also has an affinity for the costimulatory molecule CD80 (B7-1). Upon IFN-γ stimulation, PDL1 is expressed on T cells, natural killer (NK) cells, macrophages, myeloid dendritic cells (DCs), B cells, epithelial cells, and vascular endothelial cells.


PD-L1 activity may be blocked by molecules that selectively bind to and block the activity of PD-L1. Anti-PD-L1 antibodies block interactions between PD-L1 and both PD-1 and B7-1 (also known as CD80). Block means inhibit or prevent the transmission of an inhibitory signal mediated via PD-L1. PD-L1 antagonists include, for example: BMS-30 936559, also known as MDX-1105 (Bristol-Meyers Squibb), a fully human, high affinity, immunoglobulin (Ig) G4 monoclonal antibody to PD-L1; MPDL3280A, also known as RG7446 or atezolizumab (Genentech/Roche), an engineered human monoclonal antibody targeting PDL1; MSB0010718C, also known as avelumab (Merck), a fully human IgG1 monoclonal antibody that binds to PD-L; and MED1473 (AstraZeneca/MedImmune), a human immunoglobulin (Ig) G1K monoclonal antibody that blocks PD-L1 binding to its 5 receptors. Compounds that bind to the DNA or mRNA encoding PD-L1 also can act as PD-L1 inhibitors, e.g., small inhibitory anti-PD-L1 RNAi, small inhibitory anti-PD-L1 RNA, anti-PD-L1 antisense RNA, or dominant negative PD-L1 protein. Antagonists of or compounds that antagonize PD-L1, e.g., anti-PD-L1 antibodies and PD-L1 antagonists, may include, but are not limited to those previously mentioned and any of those that are disclosed in Stewart et al., 2015, 3(9):1052-62; Herbst et al., 2014, Nature 515:563-567; Brahmer et al., N Engl J Med 2012; 366:2455-2465; U.S. Pat. No. 8,168,179; US20150320859; and/or US20130309250, all incorporated herein by reference.


In some embodiments, the immune checkpoint inhibitor inhibits CTLA-4. CTLA-4 (also known as CTLA-4 or cluster of differentiation 152 (CD152)), is a transmembrane glycoprotein that, in humans, is encoded by the CTLA-4 gene. CTLA-5 4 is a member of the immunoglobulin superfamily, which is expressed on the surface of helper T cells and is present in regulatory T cells, where it may be important for immune function. CTLA-4, like the homologous CD28, binds to B7 molecules, particularly CD80/B7-1 and CD86/B7-2 on antigen-presenting cells (APCs), thereby sending an inhibitory signal to T cells. CTLA-4 functions as an immune checkpoint that inhibits the immune system and is important for maintenance of immune tolerance.


CTLA-4 activity may be blocked by molecules that bind selectively to and block the activity of CTLA-4 or that bind selectively to its counter-receptors, e.g., CD80, CD86, etc. and block activity of CTLA-4. Blocking means inhibit or prevent the transmission of an inhibitory signal via CTLA-4. CTLA-4 antagonists include, for example, inhibitory antibodies directed to CD80, CD86, and/or CTLA-4; small molecule inhibitors of CD80, CD86, and CTLA-4; antisense molecules directed against CD80, CD86, and/or CTLA-4; adnectins directed against CD80, CD86, and/or CTLA-4; and RNAi inhibitors (both single and double stranded) of CD80, CD86, and/or CTLA-4.


Suitable CTLA-4 antagonists and/or anti-CTLA-4 antibodies include humanized anti-CTLA-4 antibodies, such as MDX-010/ipilimumab (Bristol-Meyers Squibb), tremelimumab/CP-675,206 (Pfizer; AstraZeneca), and antibodies that are disclosed in PCT Publication No. WO 2001/014424, PCT Publication No. WO 2004/035607, U.S. Publication No. 2005/0201994, European Patent No. EP 1212422 B1, U.S. Pat. Nos. 5,811,097, 5,855,887, 6,051,227, 6,984,720, 7,034,121, 8,475,790, U.S. Publication Nos. 2002/0039581 and/or 2002/086014, the entire disclosures of which are incorporated herein by reference. Other anti-CTLA-4 antibodies and/or CTLA-4 antagonists that can be used in a method of the present disclosure include, for example, those disclosed in Hurwitz et al., Proc. Natl. Acad. Sci. USA, 95(17):10067-10071 (1998); Camacho et al., J. Clin. Oncology, 22(145): Abstract No. 2505 (2004) (antibody CP9675206); Mokyr et al., Cancer Res., 58:5301-5304 (1998), and Lipson and Drake, Clin Cancer Res; 17(22) Nov. 15, 2011; U.S. Pat. No. 8,318,916; and/or EP1212422B1, all of which are herein incorporated by reference, in their entireties.


In some embodiments, the immune checkpoint inhibitor inhibits VISTA. V-domain Ig suppressor of T cell activation (VISTA), (also known as PD-II1, PD-1 homolog, or Diesl), is a negative regulator of T cell function. VISTA is a 309 aa type I transmembrane protein that is composed of seven exons, it has one Ig-V like domain, and its sequence is similar to the Ig-V domains of members of CD28 and B7 families. VISTA is highly expressed in the tumor microenvironment (TME) and on hematopoietic cells. It is also expressed on macrophages, dendritic cells, neutrophils, natural killer cells, and naive and activated T cells. Its expression is highly regulated on myeloid antigen-presenting cells (APCs) and T cells, while lower levels are found on CD4+ T cells, CD8+ T cells, and Treg cells. VISTA shows some sequence homology to the PD-1 ligand, PD-L1, however the two immune checkpoint inhibitors are structurally different and have different signaling pathways. VISTA blockade has been shown to enhance antitumor immune responses in mice, while in humans, blockade of the related PD-1 pathway has shown great potential in clinical immunotherapy trials. VISTA is a negative checkpoint regulator that suppresses T-cell activation and its blockade may be an efficacious immunotherapeutic strategy for human cancer. VISTA (Wang et al., 2011. JEM. 208(3):577-92; Lines et al., 2014. Cancer Res. 74(7):1924-32; Kondo et al. 2015. J. of Immuno. V194; WO2011120013; US20140105912; US20140220012; US20130177557, US20130177557, incorporated by reference herein, in their entireties).


VISTA activity may be blocked by molecules that selectively bind to and block the activity of VISTA. Molecules or compounds that are VISTA antagonists include peptides that bind VISTA, antisense molecules directed against VISTA, single- or doublestranded RNAi molecules targeted to degrade or inhibit VISTA, small molecule inhibitors of VISTA, anti-VISTA antibodies, inhibitory antibodies directed to VISTA, and humanized antibodies that selectively bind and inhibit VISTA. Antagonists of or compounds that antagonize VISTA, e.g., anti-VISTA antibodies and VISTA antagonists, are not limited to, but may include any of those that are disclosed in Liu et al. 2015. PNAS. 112(21):6682-6687; Wang et al., 2011. JEM. 208(3):577-92; Lines et al., 2014. Cancer Res. 74(7):1924-32; Kondo et al. 2015. J. of Immuno. V194; WO2015097536, EP2552947, WO2011120013, US20140056892, U.S. Pat. No. 8,236,304, WO2014039983, US20140105912, US20140220012, US20130177557; WO2015191881; US20140341920; CN105246507; and/or US20130177557, all of which are incorporated by reference herein, in their entireties.


In some embodiments, the immune checkpoint inhibitor inhibits TIM-3. In some embodiments, the immune checkpoint inhibitor inhibits LAG-3.


In some embodiments, a combination of test compounds are tested in the cell culture. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a CTLA-4 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a LAG-3 inhibitor.


In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a CTLA-4 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a TIM-3 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor, a CTLA-4 inhibitor, and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor, a CTLA-4 inhibitor, and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor, a TIM-3 inhibitor, and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor, a TIM-3 inhibitor, and a LAG-3 inhibitor.


In some embodiments, the combination of test compounds includes an immune checkpoint inhibitor and a small molecule compound. In some embodiments, the combination of test compounds includes an immune checkpoint inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a PD-1 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a PD-L1 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a CTLA-4 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a VISTA inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a TIM-3 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a LAG-3 inhibitor and a TBK-1 inhibitor.


In some embodiments, an immune activating compound is a CD28 antagonist, e.g., an anti-CD28 antibody. An antibody, or immunoglobulin, is a glycoprotein containing two identical light chains (L chains), each containing approximately 200 amino acids, and two identical heavy chains (H chains), which generally are at least twice as long as the L chains. The paratope of the antibody is specific for a particular epitope of an antigen, and their spacial complementarity (binding) “tags” the microbe for further action or neutralize its actions directly. The antibody communicates with other components of the immune response via its crystallizable fragment (Fc) region, which includes a conserved glycosylation site. There are five Fc regions, resulting in the five different antibody isotypes: IgA, IgD, IgE, IgG, and IgM. IgD functions as an antigen receptor on B cells that have not been exposed to antigens, and activates basophils and mast cells, resulting in the production of antimicrobial factors. IgG, expressed in four forms, provides the majority of antibody-based immunity against invading pathogens. IgM is expressed on the surface of B cells as a monomer, and in a secreted form as a pentamer. It eliminates pathogens during the early phases of humoral (B cell-mediated) immunity before there 5 are sufficient levels of IgG. IgG is often used in immunotherapy.


The term antibody is used in the broadest sense and specifically includes, for example, single monoclonal antibodies, antibody compositions with polyepitopic specificity, single chain antibodies, and antigen-binding fragments of antibodies. An antibody may include an immunoglobulin constant domain from any immunoglobulin, such as IgG1, IgG2, IgG3, or IgG4 subtypes, IgA (including IgA1 and IgA2), IgE, IgD or IgM.


A fluorescence light source provides an excitation wavelength to excite a fluorophore. A fluorescent light source can be used in connection with a photosensitive detector capable of detecting total fluorescence emitted by the excited fluorophore to generate an image. A fluorescence microscope can be configured to include a fluorescence light source and a photosensitive detector. Fluorescence microscopes are available in the art and are commercially available. A skilled artisan would be able to select a microscope with appropriate capabilities for the desired imaging and/or analysis.


Fluorescence microscopes are available in upright or inverted configurations, either of which are suitable for use with the provided methods. In an upright microscope configuration, the objective and photosensitive detector, e.g., camera, is disposed above the stage, pointing down. Exemplary upright fluorescent microscopes include, but are not limited to, Nikon Eclipse 80i Fluorescent Microscope. In an inverted microscope configuration, the light source is disposed above the stage pointing down, and the objective is disposed below the stage pointing up.


In some embodiments, a fluorescence microscope is an epifluorescence microscope, in which light of the appropriate excitation wavelength is passed through the objective lens onto the sample to be examined. In some such embodiments, fluorescence is emitted from the sample through the same objective lens through which the light initially passed, and is then detected via a photosensitive detector, e.g., a camera. In some instances, a dichroic beam splitter may be used to filter the emitted fluorescence by permitting fluorescence of a particular wavelength to pass through, while reflecting the remaining fluorescence, to increase the signal-to-noise ratio. In some embodiments, a fluorescence microscope is a confocal microscope. Confocal microscopes can be used, for example, to generate three dimensional structures from a series of optical section images. In some embodiments, a fluorescence microscope is a total internal reflection fluorescence microscope.


In some embodiments, the fluorescence microscope is configured to permit measurement of emission of fluorescence from two or more distinct fluorophore dyes at distinct wavelengths. For example, in some embodiments, the fluorescence microscope contains a filter arrangement that allows separation of the fluorescence emitted by the two or more distinct fluorophore dyes.


In some embodiments, the microscope is configured to permit measurement of multiple capture images of the same microfluidic device by moving the stage on which the microfluidic device is disposed. In some embodiments, the stage is a motorized stage. Motorized stages are known in the art and are commercially available. In some embodiments, the stage is configured to move one dimensionally, e.g., to move in the x-axis. In some embodiments, the stage is configured to move two dimensionally, e.g., to move in the x- and y-axes. In some embodiments, the stage is configured not to move in three dimensions, e.g., to not move in the z-axis. In some such embodiments, the focal plane of the tumor cell spheroids in the three-dimensional microfluidic device remains the same throughout the fluorescence detection.


In some embodiments, a three dimensional analysis of the tumor cell spheroids is performed. For example, in some embodiments, the stage is configured to move in three dimensions, e.g., moves in x-, y-, and z-axes. In such embodiments, images of multiple sections (e.g., focal planes) can be obtained to generate a Z stack using microscopes, photosensitive detectors, and software available in the art. For example, commercially available ProScan controller and TTL Breakout Box (Prior Scientific, Rockland, Mass.) can be used to control a CCD camera for Z-stack image acquisition.


The overall resolution of the fluorescence emission detection depends on the magnification of the objective lens through which the detectable signal passes, and/or the magnification of the photosensitive detection device, e.g., camera. In some embodiments, the magnification of the objective lens is at least 2×, at least 3×, at least 4×, at least 10×, at least 40×, at least 100×, or more. In some embodiments, the magnification of the photosensitive detection device, e.g., camera, is 0×. In some embodiments, the magnification of the photosensitive detection device, e.g., camera, is at least 2×, at least 3×, at least 4×, at least 100×, or more. In some embodiments, the overall resolution of the fluorescence detection is at least 2×, at least 3×, at least 4×, at least 10×, at least 40×, at least 100×, at least 400×, at least 1000×, or more. In some embodiments, the resolution at which the fluorescence is detected is such that the entire field of the three dimensional device containing the tumor cell spheroids can be imaged without adjusting the focal plane.


Images of the fluorescence emitted by the fluorophore dyes are detected and/or captured using a photosensitive detector. Photosensitive detectors capable of detecting total fluorescence are known in the art and commercially available. In some embodiments, a photosensitive detector is a camera or a photodiode. In some embodiments, the camera is a CCD camera. Exemplary cameras include, but are not limited to CoolSNAP CCD Camera (Roper Scientific). In some embodiments, the photodiode is an avalanche photodiode.


Images can be acquired by the photosensitive detector and analyzed, e.g., using commercially available software. Exemplary image capture and analysis software includes, but is not limited to NIS-Elements AR software package (Nikon). In some embodiments, multiple images of a microfluidic device are captured by the detector and stitched together. Images may be deconvoluted using available programs such as AutoQuant (Media Cybernetics).


The present invention is further illustrated by the following Examples, which in no way should be construed as further limiting. The entire contents of all of the references (including literature references, issued patents, published patent applications, and co pending patent applications) cited throughout this application are hereby expressly incorporated by reference.


EXAMPLES
Example 1. Materials and Methods for Ex Vivo Profiling

Patient Samples.


A cohort of patients (Tables S1-1 and S1-2) treated at Massachusetts General Hospital and Dana-Farber Cancer Institute was assembled for PDOTS profiling and culture between August 2015 and August 2016. Informed consent was obtained from all subjects. Tumor samples were collected and analyzed according to Dana-Farber/Harvard Cancer Center IRB-approved protocols. These studies were conducted according to the Declaration of Helsinki and approved by the MGH and DFCI IRBs. De-identified archival matched plasma and tissue samples from the MGH Melanoma Tissue Bank were obtained from patients pre- or on-treatment with anti-PD-1 therapy as indicated. Mutational analysis performed on clinically validated next-generation sequencing (NGS) platforms at MGH and DFCI. Clinical benefit (CB) to PD-1 was defined as absence of disease, decrease in tumor volume (radiographic or clinical), or stable disease, whereas patients with no clinical benefit (NCB) included patients with mixed response, progression on treatment, and primary non-responders.













TABLE S1-1





ID
Age/Sex
Diagnosis
Stage
Mutational Status







MGH-01
78/M
Melanoma
IV
BRAFWT,




(cutaneous)

NRASWT


MGH-02
69/M
Melanoma
IIIB
N/A




(cutaneous)




MGH-03
49/M
Melanoma
IV
N/A




(cutaneous)




MGH-04 (**)
28/M
Melanoma
IV
BRAFV600E




(cutaneous)




MGH-05
70/M
Melanoma
IV
BRAFWT,




(cutaneous)

NRASG13V


MGH-06
78/M
Melanoma
IV
BRAFWT,




(cutaneous)

NRASWT


MGH-07(**)
28/M
Melanoma
IV
BRAFV600E




(cutaneous)




MGH-08
80/M
Melanoma
IV
BRAFV600K




(cutaneous)




MGH-09
69/F
Melanoma
IV
BRAFV600E




(cutaneous)




MGH-10
74/F
Melanoma
IV
KITD816A




(mucosal)




MGH-11
63/F
Melanoma
IV
N/A




(cutaneous)




MGH-12 ( custom character  )
61/M
Melanoma
IV
TP53




(cutaneous)




MGH-13
65/F
Thyroid cancer
IV
BRAFV600E




(papillary)




MGH-14 ( custom character  )
61/M
Melanoma
IV
TP53




(cutaneous)




MGH-16
62/M
Melanoma (sino-
IV
NRASG12D




nasal)




MGH-18
68/M
Melanoma
IV
NRASQ61R




(cutaneous)




MGH-19
24/F
Adreno-cortical
II
N/A




carcinoma




DFCI-01
73/F
Melanoma
III
Not tested




(cutaneous)




DFCI-02 (#)
81/M
Melanoma
IV
CDKN2A (Q50*)




(cutaneous)




DFCI-04
72/F
Mesothelioma
IV
9p del,






polysomy 22


DFCI-06
42/F
Merkel cell
IV
BRCA2 (F439V)




carcinoma




DFCI-07
58/M
NSCLC/lung
IV
KRAS/ LKB1




adeno-carcinoma




DFCI-09
45/M
Pancreatic
IIB
KRASG12D, TP53




adenocarcinoma




DFCI-10 ({circumflex over ( )})
55/M
Thyroid cancer
IV
TP53, MSH2,




(Hurthle cell)

PTEN


DFCI-12
58/F
Head/neck
IV
Unknown




squamous cell






carcinoma




DFCI-13 (*)
76/M
Thyroid cancer
IV
Unknown




(papillary)




DFCI-15
75/F
Thyroid cancer
IV
BRAFV600E




(papillary)




DFCI-16 (*)
76/M
Thyroid cancer
IV
Unknown




(papillary)




DFCI-17 (#)
81/M
Melanoma
IV
CDKN2A (Q50*)




(cutaneous)




DFCI-18 (*)
76/M
Thyroid cancer
IV
Unknown




(papillary)




DFCI-19
67/M
Pancreatic
IIA
Unknown




adenocarcinoma




DFCI-20
51/M
Thyroid cancer
IV
None identified




(papillary)




DFCI-21 (*)
76/M
Thyroid cancer
IV
Unknown




(papillary)




DFCI-22 (*)
76/M
Thyroid cancer
IV
Unknown




(papillary)




DFCI-24
79/M
Small cell lung
IV
Unknown




cancer




DFCI-25
68/M
Melanoma
IV
NRASQ61K,




(cutaneous)

CDKN2A (Q50*)


DFCI-27
72/M
Melanoma
IV
BRAFWT




(cutaneous)




DFCI-29 ({circumflex over ( )})
55/M
Thyroid cancer
IV
TP53, MSH2,




(Hurthle cell)

PTEN


DFCI-30
52/M
Merkel cell
IV
Unknown




carcinoma




DFCI-31
67/M
Merkel cell
IV
Unknown




carcinoma




DFCI-32
89/M
Merkel cell
IIIb
Unknown




carcinoma




DFCI-33
49/M
Thyroid cancer
IV
Unknown




(differentiated)





(*) DFCI-13, 16, 18, 21, 22 represent serial pleural effusion samples from same patient.


(**) MGH-04 and MGH-07 are serial biopsies from the same patient.


(#) DFCI-02 and -17 are samples from same patient.


({circumflex over ( )}) DFCI-10 and DFCI-29 are samples from the same patient.


( custom character  ) MGH-12 and MGH-14 are serial samples from a patient with a brain metastasis requiring resection and subsequent re-resection.



















TABLE S1-2







Therapy








at







Prior
Time of

Subsequent




ID
Therapy
Biopsy
Site
Therapy
Response to
Status







MGH-01
None
None
subcutaneous
None
N/A
Deceased;








never








treated


MGH-02
None
None
lymph node
None
N/A
Alive; NED


MGH-03
None
None
lymph node
BRAFi +
N/A
Deceased;






MEKi →

progression






αPD-1 +








αCTLA-4




MGH-04
None
None
subcutaneous
αPD-1 +
N/A
Alive;


(**)



αCTLA-4→

ongoing






αPD-1

response






maintenance




MGH-05
αCTLA-4→
None
subcutaneous
None
Progression
Deceased;



αPD-1→




progression



clinical trial







MGH-06
αPD-1
αPD-1
lymph node
αPD-1
Mixed
Alive;






(irAE) →

ongoing






αCTLA-4

response


MGH-07
αPD-1 +
αPD-1 +
Subcutaneous
αPD-1
Response
Alive;


(**)
αCTLA-4
αCTLA-4



ongoing








response


MGH-08
αPD-1+
αPD-1
Subcutaneous
αCTLA-4→
Mixed
Alive;






BRAFi +
Response
ongoing






MEKi

response to








BRAFi +








MEKi


MGH-09
αPD-1 →
None
Subcutaneous
BRAFi +
Response
Alive;



irAE


MEKi
(SD x 4-5
ongoing







mo) PD off-
response to







therapy
BRAFi +








MEKi


MGH-10
Chemo-
None
Small bowel
None
Response
Alive;



therapy,



(partial)-
NED



radiation,



held for




surgery →



irAE




αCTLA-4→








αPD-1







MGH-11
BRAFi/
None
Lymph node
αPD-1
Response
Alive;



MEKi




ongoing








treatment


MGH-12
αCTLA-4
αPD-1
Brain
αPD-1
Mixed
Alive;


(□)
(PD) →

metastasis

Response
mixed



αPD-1 (MR)




response


MGH-13
Radioactive
None
Subcutaneous
Radiation
N/A
Alive;



iodine




awaiting








further








therapy


MGH-14
αPD-1
αPD-1
Brain
αPD-1 +
Mixed
Alive;


(□)


metastasis
radiation
Response
stable








disease


MGH-16
Anti-PD-L1 +
None
Subcutaneous
None
Progression
Deceased



MEKi (PD) →








high-dose








IL-2 (AE) →








αCTLA-4








(PD) →








αPD-1(MR→








PD) →








SIRT (liver








metastases) →








pan-RAFi








(PD)







MGH-18
Radiation →
αPD-1
Subcutaneous
αPD-1
Progression
Alive;



anti-PD-1 +



(slow)
slowly



anti-KIR




progressive



(irAE) →




disease



αCTLA-4








(PD) →pan-








RAFi (PD)→








αPD-1 +








radiation







MGH-19
None
None
Primary
None
N/A
Alive


DFCI-01
None
Unknown
Lymph node
N/A
Unknown
Unknown


DFCI-02
αCTLA-4,
αPD-1
Subcutaneous
αPD-1
Progression
Deceased


(#)
αPD-1







DFCI-04
None
Unknown
Primary
None
N/A
Deceased





(partial








pleurectomy)





DFCI-06
None
None
Subcutaneous
None
N/A
Deceased


DFCI-07
Chemotherapy
None
Peritoneal
None
Progression
Deceased



(PD) → αPD 1

fluid





DFCI-09
None
None
Pancreas
None
N/A
Alive;





(Whipple)


recurrent








disease


DFCI-10
None
None
Subcutaneous
lenvatinib
N/A
Alive


({circumflex over ( )})








DFCI-12
Cisplatin
None
Pleural biopsy
αPD-1
Progression
Deceased





(VATS)





DFCI-13
MLN-0128
MLN-0128
Pleural effusion
MLN-0128
Progression
Deceased


(*)








DFCI-15
MLN-0128
MLN-0128
Pleural effusion
None
N/A
Deceased


DFCI-16
MLN-0128
None
Pleural effusion
nivolumab
N/A
Deceased


(*)








DFCI-17
RTA 408 +
RTA 408 +
Subcutaneous
N/A
Progression
Alive;


(#)
αCTLA-4
αCTLA-4



Progressive








Disease


DFCI-18
MLN-0128
None
Pleural effusion
nivolumab
Progression
Deceased


(*)








DFCI-19
FOLFIRINO
None
Pancreas
5-FU
N/A
Alive



X →

(Whipple)


(NED)



capecitabine +








radiation







DFCI-20
lenvatinib
lenvatinib
Pleural effusion
MLN-0128
N/A
Progressive








Disease


DFCI-21
αPD-1
αPD-1
Pleural effusion
αPD-1
Progression
Deceased


(*)








DFCI-22
αPD-1
αPD-1
Pleural effusion
αPD-1
Progression
Deceased


(*)








DFCI-24
cisplatin-
αPD-1
Pleural effusion
None
Progression
Deceased



etoposide →








αPD-1







DFCI-25
αCTLA-
None
Lymph node
N/A
Response
Alive;



4 + αPD-1→



(held for irAE)
awaiting



αPD-1




further



maintenance →




therapy



irAE







DFCI-27
αPD-1
αPD-1
Subcutaneous
αPD-1
Mixed
Alive;







Response
on








treatment


DFCI-29
Lenvatinib →
everolimus
Subcutaneous
everolimus
N/A
Alive


({circumflex over ( )})
MLN-0128 →








everolimus







DFCI-30
carboplatin-
None
Lymph node
αPD-1
Response
Alive;



etoposide,




on



radiation




treatment



(recurrence)







DFCI-31
carboplatin-
None
Subcutaneous
αPD-1
Stable
Alive;



etoposide



Disease
on








treatment


DFCI-32
None
None
Primary
Radiation
N/A
Alive;








on








treatment


DFCI-33
Radioactive
None
Pleural effusion
lenvatinib
N/A
Alive;



iodine




on








treatment





(*)DFCI-13, 16, 18, 21, 22 represent serial pleural effusion samples from same patient.


(**) MGH-04 and MGH-07 are serial biopsies from the same patient.


(#) DFCI-02 and -17 are samples from same patient.


({circumflex over ( )}) DFCI-10 and DFCI-29 are samples from the same patient.


(□) MGH-12 and MGFI-14 are serial samples from a patient with a brain metastasis requiring resection and subsequent re-resection.


AE = adverse event.


irAE = immune-related adverse event.


MR = mixed response.


PD = progressive disease







Syngeneic Murine Models.


All animal experiments were performed in compliance with established ethical regulations and were approved by the Dana-Farber Animal Care and Use Committee. MC38 murine colon adenocarcinoma cells were generously provided by Dr. Gordon Freeman (DFCI) received under an MTA from Dr. Jeffrey Schlom of NCI (Bethesda, Md.). B16F10 melanoma cells, CT26 colon carcinoma cells, and EMT6 breast mammary carcinoma cells were obtained from ATCC. Cells were expanded, tested free for mycoplasma and mouse pathogens. Thawed cells were cultured for up to three passages in DMEM (MC38, B16F10) or RPMI 1640 (CT26) supplemented with 10% heat-inactivated FBS at 37° C. in a humidified incubator maintained at 5% CO2. Cell counts were performed prior to implantation by both hemocytometer & Invitrogen Countess Cell Counter. MC38 colon carcinoma cells, CT26 colon carcinoma cells, and B16F10 melanoma cells (5×105 cells/mouse in 100 μL), re-suspended in sterile PBS (Ca+, Mg+ free), were injected into 8 week old female C57BL/6 albino mice or Balb/c (Jackson) and tumors were collected 2-3 weeks post-implantation or on reaching 2000 mm3 in size (or if there were any humane reason, including decreased BW>15% for 1 week or moribund) and MDOTS were prepared as described below. Implantation of CT26 colon carcinoma cells was performed using BALB/c mice in identical fashion. For in vivo treatment studies, mice were randomized (using the deterministic method) and then injected with 10 mg/kg isotype control IgG (clone 2A3, BioXCell) or rat-anti-mouse PD-1 (clone RMP1-14, BioXCell) every 3 days×8 doses and tumor volume was measured as shown. Investigators were not blinded to treatment groups. Tumor volume (TV) was monitored on a weekly basis after the initial tumor volume is about 100 mm3. TV was measured twice weekly during the exponential tumor growth phase, and body weight was monitored on a weekly basis after implantation.


Spheroid Preparation and Microfluidic Culture.


Fresh tumor specimens (murine and human patients) were received in media (DMEM) on ice and minced in a 10 cm dish (on ice) using sterile forceps and scalpel. Minced tumor was resuspended in DMEM (4.5 mM glucose, 100 mM sodium pyruvate, 1:100 penicillin-streptomycin) (Corning CellGro, Manassas, Va.)+10% FBS (Gemini Bio-Products, West Sacramento, Calif.), 100 U/mL collagenase type IV (Life Technologies, Carlsbad, Calif.), and 15 mM HEPES (Life Technologies, Carlsbad, Calif.), except for CT26 tumors that were prepared in RPMI. Samples were pelleted and resuspended in 10-20 mL media. Red blood cells were removed from visibly bloody samples using RBC Lysis Buffer (Boston Bio-Products, Ashland, Mass.). Samples were pelleted and then resuspended in fresh DMEM+10% FBS and strained over 100 μm filter and 40 μm filters to generate S1 (>100 μm), S2 (40-100 μm), and S3 (<40 μm) spheroid fractions, which were subsequently maintained in ultra low-attachment tissue culture plates. S2 fractions were used for ex vivo culture. An aliquot of the S2 fraction was pelleted and resuspended in type I rat tail collagen (Corning, Corning, N.Y.) at a concentration of 2.5 mg/mL following addition of 10×PBS with phenol red with pH adjusted using NaOH (pH 7.0-7.5 confirmed using PANPEHA Whatman paper (Sigma-Aldrich, St. Louis, Mo.)). The spheroid-collagen mixture was then injected into the center gel region of the 3D microfluidic culture device. Collagen hydrogels containing PDOTS/MDOTS were hydrated with media with or without indicated therapeutic monoclonal antibodies after 30 minutes at 37° C. MDOTS were treated with isotype control IgG (10 μg/mL, clone 2A3) or anti-PD-1 (0.1, 1.0, 10 μg/mL, clone RMP1-14). Monoclonal rat-anti-mouse-CCL2 (5 μg/mL, clone 123616, R&D Systems) was used for CCL2 neutralization in MDOTS. PDOTS were treated with anti-PD-1 (pembrolizumab, 250 μg/mL), anti-CTLA-4 (ipilimumab, 50 μg/mL), or combination (250 μg/mL pembrolizumab+50 μg/mL ipilimumab). Doses were selected (1:100 dilutions of stock concentrations used clinically) to correspond to reported peak plasma concentrations of each drug following administration of 10 mg/kg (FDA CDER application). In select experiments, PDOTS were treated with InVivoMAb human IgG isotype control (BioXCell). For spheroid cultures lacking immune cells, MC38 or CT26 cells (1×106) were seeded in low attachment conditions for 24 hours and were filtered (as above). The S2 fraction was pelleted and resuspended in collagen (as above) prior to microfluidic culture.


Flow Cytometric Immune Profiling of Murine Tumors and MDOTS.


Tumors from MC38 and B16F10 syngeneic murine models were procured as described above. Cells were incubated for 20 minutes in the dark at room temperature using the Zombie NIR Fixable Viability Kit (Biolegend, 423105) at a dilution of 1:500 in PBS. FcR were blocked by incubation with the anti-mouse CD16/CD32 clone 2.4G2 blocking Ab (Fisher Scientific) for 15 minutes at 4° C. at a 1:100 dilution in flow cytometry staining buffer (PBS+5% FBS). Cell surface staining was performed by incubation for 20 minutes at 4° C. using the following Abs diluted in flow cytometry staining buffer (total staining volume of 100 uL): Lymphocyte Staining Panel—CD45 AF488 (BioLegend 103122), CD25 PE (BioLegend 101904), CD19 PE-Dazzle (115554), CD49b PE-Cy7 (BioLegend, 108922), CD3 BV421 (BioLegend, 100228), CD8 BV510 (BioLegend 100752), CD4 BV786 (Fisher Scientific #BDB563331); Myeloid Staining Panel—F4/80 AF488 (BioLegend #123120), MHCII PE (BioLegend #107608), CD11c BV421 (BioLegend #117330), Ly6G BV510 (BioLegend #127633), CD11b BV650 (BioLegend #101239), Ly6C BV711 (BioLegend #128037), CD45 BV786 (Fisher Scientific #BDB564225), CD19 APC-Cy7 (BioLegend #115530), and CD49b APC-Cy7 (BioLegend #108920) were included with the myeloid staining panel to be used as a dump channel along with the dead cells as determined by the Zombie NIR viability stain. After cell surface staining, cells were fixed by incubating in 200 μL IC Fixation Buffer (eBioscience #00-8222-49) for 10 minutes at room temperature. Cells were washed and resuspended in flow cytometry staining buffer and read the following day on a BD LSR Fortessa flow cytometer. Data were analyzed using FlowJo software version 10.0.8.


Flow Cytometric Immune Profiling of PDOTS and Human Tumor Samples.


Cells were incubated with Live/Dead Fixable Yellow Dead Cell Stain Kit (Life Technologies, Carlsbad, Calif.) for 8 minutes in the dark at room temperature or Live/Dead Fixable Zombie NIR™ (Biolegend, San Diego, Calif.) for 5 minutes in the dark at room temperature in FACS buffer (PBS+2% FBS) at a ratio of 250 μL L/D 1× dilution per 100 mg of original sample weight. Surface marker and intracellular staining were performed according to the manufacturer's protocol (eBioscience, San Diego, Calif.). FcR were blocked prior to surface antibody staining using Human FcR Blocking Reagent (Miltenyi, San Diego, Calif.). Cells were fixed in 1% PBS+2% FBS and washed prior to analysis on a BD LSRFortessa with FACSDiva software (BD Biosciences, San Jose, Calif.). Data were analyzed using FlowJo (Ashland, Oreg.) software version 10.0.8. Cell viability was determined by negative live/dead staining. Antibodies were specific for the following human markers: CD3 (HIT3a; UCHT1), CD8 (RPA-T8), CD14 (M5E2; MphiP9), CD45 (HI30), CD56 (B159), CCR7 (150503), EpCAM (EBA-1), HLA-DR (G46-6), PD-1 (EH12.1), and IgG1 isotype control (MOPC-21) from BD Biosciences (San Jose, Calif.); CD3 (UCHT1), CD4 (RPA-T4), CD14 (M5E2), CD15 (W6D3), CD16 (3G8), CD19 (HIB19), CD25 (BC96), CD33 (WM53), CD38 (HIT2), CD40L (24-31), CD45 (HI30), CD45RA (HI100), CD45RO (UCHL1), CD56 (HCD56; 5.1H11), CD66b (G10F5), CD69 (FN50), CD123 (6H6), CD163 (GHI/61), CTLA-4 (L3D10), CXCR5 (J252D4), EpCAM (9C4), Ki-67 (Ki-67), PD-1 (EH12.2H7), PD-L1 (29E.2A3), PD-L2 (24F.10C12), TIM-3 (F38-2E2), IgG2a isotype control (MOPC-173), IgG2b isotype control (MPC-11), and IgG1 isotype control (MOPC-21) from BioLegend (San Diego, Calif.); Pan-cytokeratin (C11) and PD-L1 (E1L3N) from Cell Signaling Technologies (Danvers, Mass.); CD45 (2D1), FOXP3 (236A/E7), and IL-10 (236A/E7) from Affymetrix/eBioscience (San Diego, Calif.). Four-way flow sorting of immune cells (CD45+), tumor cells (CD45−CD31−CD90−), cancer-associated fibroblasts (CD45−CD31−CD90+), and endothelial cells (CD45−CD31+CD144+) was conducted on a BD Aria II SORP with gates set using single stain controls and manual compensation using the following antibodies: CD31-APC (Biolegend, 303115), CD45-BV711 Biolegend, 304050), CD90-PE/Cy7 (Biolegend, 328123), and CD144-PE (Biolegend, 348505). Cells were sorted into cold PBS and stored on ice before mRNA extraction using established techniques.


Microfluidic Device Design and Fabrication.


Microfluidic device design and fabrication was performed according to methods known in the art (e.g., Aref, A. R. et al., Integr. Biol. (Camb.) (2013), the content of which is incorporated herein by reference in entirety), with modifications of device dimensions to accommodate larger volumes of media. MDOTS were also evaluated using DAX-1 3D cell culture chip (AIM Biotech, Singapore), for select studies.


Live/Dead Staining.


Dual labeling was performed by loading microfluidic device with Nexcelom ViaStain™ AO/PI Staining Solution (Nexcelom, CS2-0106). Following incubation with the dyes (20 minutes at room temperature in the dark), images were captured on a Nikon Eclipse 80i fluorescence microscope equipped with Z-stack (Prior) and CoolSNAP CCD camera (Roper Scientific). Image capture and analysis was performed using NIS-Elements AR software package. Image deconvolution was done using AutoQuant Module. Whole device images were achieved by stitching in multiple captures. Live and dead cell quantitation was performed by measuring total cell area of each dye. Three different laboratories verified immune-mediated cell death of MC38 MDOTS following PD-1 blockade. To inhibit CD8+ T cell cytotoxicity, CT26 MDOTS were treated with 10 μg/mL anti-CD8a Ab (clone 53-6.72, BioXCell). Intertumoral and intratumoral heterogeneity experiments were performed using CT26 allografts as described above. MDOTS were prepared using separate pieces of a larger tumor alongside MDOTS prepared from a smaller allograft. MDOTS were processed, treated, and profiled as described above. Immunofluorescence for CD8+ T cells was performed as described below.


Immunofluorescence and Time-Lapse Imaging.


For immunofluorescence studies, PDOTS and MDOTS were washed with PBS and blocked with FcR blocking reagent (PDOTS—Miltenyi, Cambridge, Mass., MDOTS—BioLegend, San Diego, Calif.) for 30 minutes at room temperature. Directly conjugated antibodies for PDOTS were CD326 EpCAM-PE (clone 9C4), CD45-AlexaFluor-488 (HI30), CD8a-AlexaFluor488 (RPA-T8); for MDOTS—CD45-AlexaFluor488 or 647 (30-F11), CD8a-PE (53-6.7) (BioLegend, San Diego, Calif.). Antibodies were diluted 1:50 in 10 ug/mL solution of Hoechst 33342 (Thermo Fisher Scientific, Waltham, Mass.) in PBS and loaded into microfluidic devices for 1-hour incubation at room temp in the dark. Spheroids were washed twice with PBS with 0.1% Tween20 followed by PBS. For viability assessment, microfluidic devices were loaded with 1:1000 solution of calcein AM (Thermo Fisher Scientific, Waltham, Mass.) in PBS. Images were captured on a Nikon Eclipse 80i fluorescence microscope equipped with Z-stack (Prior) and CoolSNAP CCD camera (Roper Scientific). Image capture and analysis was performed using NIS-Elements AR software package. Brightfield time-lapse images were captured with a 10×NA 0.3 objective and cooled CCD camera (Orca R2, Hamamatsu) in a humidified, temperature-controlled chamber. Illumination was with a CoolLED pe-100 white light LED. Time lapse imaging of several fields of view over time was controlled by NISElements software of a Prior motorized stage along with the LED and camera.


Cytokine Profiling.


Two multiplex assays were performed utilizing a bead-based immunoassay approach, the Bio-Plex Pro™ Human Cytokine 40-plex Assay (Cat #171AK99MR2) and Bio-Plex Pro™ Mouse Cytokine Panel 1, 23-plex (Cat #M60009RDPD) on a Bio-plex 200 system (Cat #171000201). MDOT/PDOT conditioned media concentration levels [pg/mL] of each protein were derived from 5-parameter curve fitting models. Fold changes relative to the MDOT/PDOT control were calculated and plotted as log 2FC. Lower and upper limits of quantitation (LLOQ/ULOQ) were imputed from standard curves for cytokines above or below detection. Conditioned media from PDOTS were assayed neat and plasma was diluted 1:4.


Tertiary Lymphoid Structure Evaluation.


Fifty-two sections stained with hematoxylin & eosin (H&E) of melanoma pre- and on-therapy with anti-PD-1 were evaluated independently by two dermatopathologists for the presence of tertiary lymphoid structures (TLS) at the periphery of these tumors. These are characterized by prominent lymphocytic infiltrate, sometimes with germinal center formation and with associated high endothelial venules, as shown in FIG. 10A.


RNA-seq.


Freshly isolated patient tumor samples (from patients consented to DF/HCC protocol 11-181) were snap frozen in liquid nitrogen and RNA was collected using the Qiagen RNeasy Mini kit. RNA libraries were prepared from 250 ng RNA per sample using standard Illumina protocols. RNA sequencing was performed at the Broad Institute (Illumina HiSeq2000) and the Wistar Institute (Illumina NextSeq 500). RNA samples were ribo-zero treated and then subjected to library prep using Epicentre's ScriptSeq Complete Gold kit. Quality check was done on the Bioanalyzer using the High Sensitivity DNA kit and quantification was carried out using KAPA Quantification kit. Raw RNA-Seq data (BAM files) read counts were summarized by featureCounts with parameters that only paired-ended, not chimeric and well mapped (mapping quality>/=20) reads are counted. Then normalization was applied to eliminate bias from sequencing depths and gene lengths by edgeR, thus RPKMs (Reads Per Kilobase of transcript per Million mapped reads).


Quantitative Real-Time PCR.


Analysis of expression levels of CCL19 and CXCL13 by quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed using tissue samples obtained from patients with metastatic melanoma. Samples were selected from patients treated with anti-PD-1 therapy with available tissue pre- and on-treatment. All patients provided written consent to DF/HCC protocol 11-181 (Melanoma Tissue and Blood Collection). Tissue samples were snap frozen in liquid nitrogen and processed to yield RNA, which was stored at −80° C. after extraction. Normal lymph node tissue was used as a positive control for expression of CCL19 and CXCL13. Primers were designed for CXCL13 (Fwd: 5′-GAGGCAGATGGAACTTGAGC-3′ (SEQ ID NO: 1), Rev: 5′-CTGGGGATCTTCGAATGCTA-3′ (SEQ ID NO: 2)) and CCL19 (Fwd: 5′-CCAACTCTGAGTGGCACCAA-3′ (SEQ ID NO: 3), Rev: 5′-TGAACACTACAGCAGGCACC-3′ (SEQ ID NO: 4)), Total RNA was extracted via the QIAGEN RNeasy Mini Kit after being ground with the QIAGEN TissueRuptor. The extraction process was automated via the QIAGEN QIAcube. RNA was stored in 1.5 mL RNAse-free EP tubes and then quantified using the QIAGEN Qubit. cDNA was reverse-transcribed from RNA using the Invitrogen Superscript VILO kit run on an Applied Biosystems 2720 Thermo Cycler and then stored in 1.5 mL tubes in a −40° C. freezer until later use. For qPCR the samples were run in triplicate on a Roche LightCycler 96 using Bio-Rad's SsoAdvanced Universal SYBR Green Supermix in a total volume of 20 μL per well. β-tubulin (Fwd: 5′-CGCAGAAGAGGAGGAGGATT-3′ (SEQ ID NO: 5), Rev: 5′-GAGGAAAGGGGCAGTTGAGT-3′ (SEQ ID NO: 6)) were employed to normalize the expression of target genes. Four runs were performed. RT-PCR was performed in triplicate and values averaged. Effect of PD-1 blockade depicted as log 2 fold change in CCL19 or CXCL13 expression (normalized to β-tubulin) from on-treatment samples relative to pre-treatment samples. For analysis of CCL19/CXCL13 expression in sorted cell populations (FIG. 10H), qRT-PCR was performed according to methods known in the art (e.g., Zhu, Z. et al. Cancer Discov. (2014), the content of which is incorporated herein by reference in entirety) using the following primers: and CXCL13 (Fwd: 5′-CTCTGCTTCTCATGCTGCTG-3′ (SEQ ID NO: 7), Rev: 5-TGAGGGTCCACACACACAAT-3′ (SEQ ID NO: 8)) and CCL19 (Fwd: 5′-ATCCCTGGGTACATCGTGAG-3′ (SEQ ID NO: 9), Rev: 5′-GCTTCATCTTGGCTGAGGTC-3′ (SEQ ID NO: 10)), using 36B4 (Fwd: 5′-CAGATTGGCTACCCAACTGTT-3′ (SEQ ID NO: 11), Rev: 5′-GGAAGGTGTAATCCGTCTCCAC-3′ (SEQ ID NO: 12)) to normalize gene expression.


Immunohistochemistry.


Immunohistochemistry staining was performed on 4 μm formalin-fixed paraffin-embedded sections. All procedures were done on the automated Ventana Discovery Ultra staining system. Sections were first deparaffinized using EZ prep solution and antigen retrieval was achieved using Cell Conditioning solution 1. Sections were blocked with Discovery Inhibitor (all from Ventana). Sections were incubated with primary antibodies for 16 minutes for population markers and 12 hours for CXCL13 and CCL19, then washed and incubated with OmniMap anti-Mouse or anti-Rabbit conjugated with horseradish peroxidase (HRP) (Ventana, cat #760-4310 and 760-4311) for an additional 16 minutes. Discovery Purple or OmiMAP DAB chromogen kits (cat #760-229 or 760-159) was then applied to generate a color reaction. Slides were then counterstained with hematoxylin II followed by bluing reagent (Ventana, cat #790-2208 and cat #760-2037). Primary antibodies used for staining were: anti-CCL19 (RD Systems, cat #MAB361-100; 1:200) and anti-CXCL13 (Abcam, cat #ab112521; 1:150), CD31 (Cell Marque, cat #131M-94; 1:500); αSMA (Abcam, cat #ab5694; 1:400).


Source Data.


Data for differential CCL19 and CXCL13 gene expression analysis were obtained from published reports (e.g., Hugo, W. et al. Cell (2016), Chen, P. L. et al. Cancer Discov. (2016), Van Allen, E. M. et al. Science (2015), Cancer Genome Atlas, N. Cell (2015), the contents of each of which are incorporated herein by reference in entirety). For data from Ilugo et al. and Van Allen et al., transcriptome sequencing data were aligned using TopHat and normalized gene expression, presented as transcripts per million (TPM), was quantified using DESeq2 (e.g., see Kim, D. et al. Genome Biol. (2013), and Love, M. I. et al. Genome Biol. (2014), the contents of each of which are incorporated herein by reference in entirety) (Table S3). NanoString source data (Chen et al.) for PD-1 responders (n=4) and non-responders (n=8) were compared (on-PD-1/pre-PD-1) and expressed as log-2 fold change. For TCGA analysis, raw RNA-Seq data (BAM files) of TCGA SKCM samples was downloaded from Genomic Data Commons and read counts were summarized (featureCounts) and normalized using edgeR, to generate RPKMs. CCL19 and CXCL13, samples were separated into two groups by kmeans clustering of RPKM values: high group and low group, value of center of each group was used to label high or low. The survival curves were constructed according to Kaplan-Meier method on these two groups (high; n=206 and low; n=257) and survival was compared between groups using the logrank (Mantel-Cox) test (α=0.05). Four-way grouping was performed using median cutoff to define high and low expression. Single sample GSEA (ssGSEA) was performed using immune cell signatures according to methods known in the art (e.g., Bindea, G. et al. Immunity (2013), the content of which is incorporated herein by reference in entirety).


Synthesis of Compound 1, 5-(4-((4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)amino)-1,3,5-triazin-2-yl)-2-((tetrahydro-2H-pyran-4-yl)oxy)benzonitrile

Step 1.


To a solution of 2,4-dichloro-1,3,5-triazine (9.5 g, 63 mmol) in N,N-dimethylformamide (150 mL) at 0° C. (flushed with argon balloon) was added a solution of 4-(4-(oxetan-3-yl)piperazin-1-yl)aniline (14.1 g, 60.2 mmol) in N,N-dimethylformamide (100 mL) over 5 minutes via cannula and stirred in an ice-bath for 1 hour. A solution of 40% Methanol/CH2Cl2 (200 mL) was added to the reaction mixture and stirred at room temperature. After 1 hour, the solid formed were filtered and washed twice with diethyl ether. Solids were collected to provide the first lot of product. To the filtrate, diethyl ether (200 mL) was added and stirred overnight at room temperature. The solids were separated by filtration to provide a second lot of product. Both lots were combined to provide a total yield of 20 g (91%) of 4-chloro-N-(4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)-1,3,5-triazin-2-amine which was used without purification. LCMS-ESI+ (m/z): calculated for C16H19ClN6O: 346.1; found: 347.1 (M+H).


Step 2.


To a mixture of 4-chloro-N-(4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)-1,3,5-triazin-2-amine (4.6 g, 13.2 mmol), 2-fluoro-5-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)benzonitrile (3.5 g, 14.5 mmol), Pd(dppf)Cl2CH2Cl2 (1.2 g, 1.6 mmol) and potassium carbonate (3.6 g, 26.4 mmol) under argon was added a mixture of de-gassed solvents (1,2-dimethoxyethane (53 mL)/water (27 mL)) and sonicated until all solids went into solution (˜5 minutes). The mixture was stirred under argon at 100° C. in a heating block for 1 hour. After cooling to room temperature, water (200 mL) was poured into the reaction mixture and the solids were filtered off and washed with diethyl ether (100 mL). The resulting dark brown solids were suspended in Acetonitrile (20 mL) and stirred at reflux (˜2 minutes) and then stirred at room temperature for 2 hours. To this suspension di-ethyl ether (20 mL) was added and the mixture was stirred at room temperature overnight. Solids were taken by filtration to yield crude dark brown product. In 1 g batches, the crude product was suspended in Dichloromethane (150 mL) in a separatory funnel. To the suspension Trifluoroacetic acid was added until all solids had gone into solution. Water was added (150 mL) and mixture was shaken vigorously until black precipitates appeared. The black solids were filtered off. To the filtrate, a saturated aqueous solution of NaHCO3 was added slowly to fully neutralize the mixture. No solids precipitated during this process. The organic phase was dried over MgSO4 and evaporated under reduced pressure to yield a bright yellow material (Total yield 3.1 g, 55% yield). LCMS-ESI+ (m/z): calculated for C23H22FN7O: 431.1; found: 432.2 (M+H).


Step 3.


To a solution of Tetrahydro-2H-pyran-4-ol (4.7 mL, 49 mmol) in THF (200 mL) at 0° C., Potassium t-butoxide (3.8 g, 51 mmol) was added and the reaction mixture was allowed to warm to room temperature. After 30 minutes, solid 2-fluoro-5-[4-([4-[4-(oxetan-3-yl)piperazin-1-yl]phenyl]amino)-1,3,5-triazin-2-yl]benzonitrile (10 g, 23.2 mmol) was added and stirred overnight at 60° C. The reaction mixture was then cooled to 0° C. with a water/ice bath and slowly diluted with water (1.2 L) over 30 minutes and stirred at room temperature for 45 minutes. The solids formed were filtered and dried to give 5-(4-((4-(4-(oxetan-3-yl)piperazin-1-yl)phenyl)amino)-1,3,5-triazin-2-yl)-2-((tetrahydro-2H-pyran-4-yl)oxy)benzonitrile as a yellow solid (10.6 g, 90% yield) LCMS-ESI+ (m/z): calculated for C28H31N7O3: 513.3; found: 514.5 (M+H) 1H NMR (400 MHz, DMSO-d6) δ 10.23 (d, J=19.4 Hz, 1H), 8.80 (s, 1H), 8.74-8.50 (m, 2H), 7.68 (br, 2H), 7.60 (d, J=9.0 Hz, 1H), 7.11 (br, 2H), 4.99 (m, 1H), 4.91-4.74 (m, 4H), 4.52 (m, 1H), 3.91 (m, 2H), 3.59 (ddd, J=11.6, 8.5, 3.0 Hz, 2H), 3.80-3.30 (m, 4H), 3.30-2.90 (m, 4H), 2.09 (m, 2H), 1.87-1.64 (m, 2H).


In Vitro Characterization of Compound 1.


Biochemical single point inhibition and IC50 concentrations for TBK1, IKKε (IKBKE), and off-target kinases were determined at ThermoFisher Scientific using SelectScreen Kinase Profiling Services (Madison, Wis., USA) (Tables S4A and S4B-1-7). To determine cellular potency, the human colorectal cancer carcinoma cell line HCT116 (ATCC, Manassas, Va.) was maintained in T175 flasks in complete RPMI medium; RPMI 1640 supplemented with 10% FBS, 1× Penicillin-Streptomycin solution and 1×MEM (non-essential amino acids). HCT116 cells were grown to 90-95% confluency in T175 flasks containing complete RPMI medium and transfected in bulk using Lipofectamine 2000 (Invitrogen, Carlsbad, Calif.) with 70 μg of ISG54-luciferase reporter plasmid (Elim Biopharmaceuticals Inc., Hayward, Calif.). The reporter plasmid contains a luciferase gene expression cassette under the transcriptional regulation of the promoter of the human interferon stimulated gene 54 (ISG54). Transfection of the cells was allowed to take place for 6 hours, after which the cells were harvested by treatment with 0.25% trypsin EDTA (Corning Inc., Corning, N.Y.). Trypsinized cells were added to 384-well poly-d-lysine treated black clear bottom tissue culture assay plates (Greiner Bio-One GmbH, Kremsmünster, Austria) at a density of 20,000 cells/well in 80 μL of complete RPMI medium and incubated overnight. After 16-18 hours post-transfection, the assay plates were washed with PBS (Corning Inc., Corning, N.Y.), followed by addition of 80 μL/well of serum-free RPMI 1640 medium containing 1× Penicillin-Streptomycin solution, 1×MEM and 350 nL of DMSO or titrations of Compound 1. Compound 1 titrations were generated by 1.5-fold dilution steps in Iwo overlapping serial dilution series to generate a 40-point compound dose range. After incubation at 37° C. for 1 hour, the cells were stimulated with Poly(I:C) (InvivoGen, San Diego, Calif.) at a final concentration of 15 μg/mL in Optimem media (Life Technologies, Rockville, Md.). The assay plates were incubated for 5 hours at 37° C., followed by addition of One-Glo luciferase firefly reagent (Promega, Madison, Wis.) at 1:1 volume/well and luminescence was measured in an EnVision Multilabel Plate Reader (PerkinElmer, Santa Clara, Calif.). The EC50 values were calculated from the fit of the dose-response curves to a four-parameter equation. All EC50 values represent geometric mean values of a minimum of four determinations.


Interleukin-2 and Interferon Gamma Analysis.


Freshly isolated human CD4+ and CD8+ T cells were obtained from AllCells (Alameda, Calif., USA). Cells were spun down and resuspended in serum free Xvivo15 media (Lonza Walkersville, Inc., Chicago, Ill., USA) supplemented with 5 ng/mL IL-17 and incubated overnight at 37° C. Cells were plated on anti-CD3 coated plates (5 μg/mL OKT3, eBioscience, Dallas, Tex., USA, overnight) with 2 μg/mL anti-CD28 (eBioscience, Dallas, Tex., USA). Cells are treated in replicate plates with a dose-titration of Compound 1 for 24 hours for IL-2 and 96 hours for IFNγ. IL-2 and IFNγ in the supernatant were measured using single- or multi-plex immunoassay (Mesoscale Discovery, Rockville, Md., USA). Jurkat T cell leukemia cells (clone E61 obtained from ATCC) plated on anti-CD3 coated plates were treated with a dose titration of Compound 1 for 24 hours. IL-2 in the supernatant was measured as described above.


In Vivo Compound 1 Combination Treatments.


Combination studies were performed by vivoPharm (Hummelstown, Pa., USA). All procedures used in the performance of these studies were carried out in accordance with vivoPharm's Standard Operating Procedures, with particular reference to US_SOPvP_EF0314 “General Procedures for Efficacy Studies.” CT26 colon carcinoma cells (1×106 cells/mouse in 100 μL, passage 2-3) were re-suspended in serum-free DMEM and implanted in the upper right flank of 11-12 week old female Balb/c mice (Charles River Laboratories). Mice were randomized into four groups of 10 using a matched pair distribution method based on tumor size for CT26. Treatment was initiated 12 days post-inoculation with mean tumor volume at start of dosing of 125.85 mm3. Vehicle or Compound 1 (40 mg/kg) was administered by oral gavage daily for 26 days and isotype control or a reverse chimera anti-PD-L1 cloned from literature reports (e.g., Deng, R. et al. MAbs (2016), the content of which is incorporated herein by reference in entirety) and placed into a mouse IgG1 framework (10 mg/kg) was administered every 5 days for a total of six doses. Investigators were not blinded to treatment groups. Mice bearing CT26 tumors with exceptional responses to combination therapy with αPD-L1 and Compound 1 were re-implanted with CT26 cells (1×106, lower left flank) and EMT6 cells (0.5×106, upper left flank) to evaluate development of immunologic memory. MB49 and MC38 in vivo combination studies performed under identical conditions in B6 mice. B16F10 tail vein injection studies were performed in accordance with methods known in the art (e.g., Zhang, J. et al. Cell Rep. (2016), the content of which is incorporated herein by reference in entirety). After tail vein injection (1×105 cells in 100 μL), mice were treated with Vehicle or 40 mg/kg Compound 1 daily for 13 days±anti-PD-L1 (10 mg/kg) or isotype control on Days 0, 5, and 10. Mice were sacrificed on Day 13 and lung metastases were quantified (small<1 mm, medium>1 mm and ≤3 mm, large≥3 mm). No large lung metastases were detected.


Statistical Methods and Data Analysis.


All graphs depict mean±s.d. unless otherwise indicated. Graphs were generated and statistical analysis performed using GraphPad/Prism (v7.0) and R statistical package. Pearson correlation matrix using 21 cell surface markers for MDOTS were calculated with R across tumors and different sized spheroids. Unsupervised hierarchical clustering was performed using GenePattern.


Example 2. Ex Vivo Profiling of PD-1 Blockade Using Organotypic Tumor Spheroids

Existing patient-derived cancer models, including circulating tumor cells (CTCs), organoid cultures, and patient-derived xenografts (PDXs) can guide precision cancer therapy, but take weeks to months to generate and lack the native tumor immune microenvironment. Current approaches to study anti-tumor immune responses in patients are also limited by remote measurements in whole blood or plasma, or static assessment of biopsies. To overcome these challenges and model immune checkpoint blockade (ICB) ex vivo, a 3D microfluidic device was adapted to the short-term culture of murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). Following limited collagenase digestion of fresh tumor specimens, multicellular organotypic spheroids with autologous immune cells were isolated. MDOTS/PDOTS were analyzed by flow cytometry (FIG. 5) or loaded in collagen into the central channel of the device for exposure to anti-PD-1 or anti-CTLA-4 antibodies (FIG. 1A).


Using the MC38 and B16F10 immune competent syngeneic murine tumor models, lymphoid and myeloid immune cell composition of bulk tumor was compared with different spheroid populations (S1>100 μm; S2 40-100 μm; and S3<40 μm). Flow cytometric analysis revealed similar populations across all immune cell fractions examined (FIG. 1B, FIGS. 6A-6C, Tables S2-1 through S2-4). MDOTS (S2) from B16F10 demonstrated fewer CD45+ cells than MC38 and another model, CT26 (Extended Data FIG. 2d), although immune sub-populations were relatively consistent across MC38, B16F10, and CT26 models (FIG. 6E). Since S2 MDOTS were optimally sized for culture in the microfluidic device, this fraction was utilized for subsequent studies.


A large panel of PDOTS (n=40) was immunophenotyped by flow cytometry, enriching for cancers responsive to PD-1 blockade (e.g., melanoma, Merkel cell carcinoma) (FIG. 1C, Tables 1A and 1B). A range of lymphoid (CD19+B cells, CD4+ and CD8+ T cells) and myeloid (CD15+ granulocytic, CD14+ monocytic lineages, CD123+ dendritic cells) populations were consistently detected in PDOTS (FIG. 1C). Variable surface expression of exhaustion markers (PD-1, CTLA-4, TIM-3) was detected on CD4+ and CD8+ T cells (FIG. 6F) and PD-1 ligands (PD-L1 and PD-L2) on myeloid populations, including dendritic cells, myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs) (FIG. 6G). A strong correlation of T-cell profiles was confirmed between PDOTS (S2) and S3 fractions, including antigen-experienced (CD45RO+) (FIG. 1D) and exhausted CD4 and CD8 T cells (FIG. 1E), and overall conservation of immunophenotype regardless of spheroid size (FIGS. 6H-6J). These data demonstrate that PDOTS retain autologous immune cells, including key tumor-infiltrating T lymphocyte populations.


3D microfluidic culture of MDOTS and PDOTS resulted in growth and expansion over time (FIG. 2A) as well as cytokine elaboration in conditioned medium (FIGS. 2B-2C). Tumor/immune cell intermixture in spheroids was further demonstrated by immunofluorescence microscopy (FIGS. 7A-7C). Dynamic cellular interactions were observed by live imaging, and survival of CD45+ immune cells ex vivo in the device was confirmed (FIG. 7D). Thus, short-term culture and cytokine profiling of PDOTS/MDOTS is feasible using this 3D microfluidic device.


MDOTS were exposed to ex vivo PD-1 blockade, starting with MC38 allografts that respond to anti-PD-1 treatment in vivo (FIGS. 2D-2E). MC38 MDOTS were treated with anti-PD-1 antibody (or isotype control) for 3 days or 6 days in the device (FIG. 2F). Dual labeling de-convolution fluorescence microscopy using acridine orange (AO, live cells) and propidium iodide (PI, dead cells) demonstrated >90% viability of MDOTS at the time of spheroid loading (Day 0) and over time in culture with control (FIG. 2G). Treatment with anti-PD-1 resulted in dose- and time-dependent killing of MC38 MDOTS (FIG. 2G, FIG. 2K, FIG. 7E), in contrast to cell line-derived MC38 spheroids lacking autologous immune/stromal cells (FIG. 2H). Modest killing was evident in the intermediately sensitive CT26 model (FIG. 2I), whereas MDOTS derived from the PD-1 resistant B16F10 model exhibited little cell death despite identical treatment (FIGS. 2J-2K). Anti-PD1 induced killing of CT26 MDOTS required CD8+ T cells (FIG. 7F), which varied between tumors of different size, but not between distinct regions from a single tumor (FIG. 7G). These data demonstrate the ability to recapitulate sensitivity and resistance to PD-1 blockade ex vivo using well-defined mouse models.


Responses to PD-1 blockade in PDOTS were evaluated. To perform systematic assessment of ex vivo ICB in PDOTS, acute cytokine production was used as a quantitative measure of early immune activation rather than ex vivo killing, which was more robust in MDOTS. Day 3 cytokine release from PDOTS (n=28)+PD-1 blockade was analyzed, and upregulation of CCL19 and CXCL13 was observed in the majority of samples (23/28) (FIG. 3A, FIG. 3D, FIGS. 8A-8C). CCL19/CXCL13 induction was not observed with isotype IgG control (FIG. 8D), and was comparatively minimal following CTLA-4 blockade (FIG. 4B, FIG. 4E). CCL19/CXCL13 generation was also preserved across a range of spheroid numbers (FIG. 8E) with little intra-assay variability (FIGS. 8F-8G). CCL19 correlated with CXCL13 across PDOTS samples, and required the microfluidic device for robust induction (FIGS. 8H-8I). CCL19/CXCL13 upregulation was also evident following dual PD-1+CTLA-4 blockade (FIG. 3C, FIG. 3F), and accompanied by induction of additional effector cytokines (e.g., IFN-γ, IL-2, and TNF-α) in select samples (FIG. 9).


In consonance with PDOTS profiling results, CCL19/CXCL13 mRNA expression increased in patients treated with PD-1 blockade (FIGS. 3G-3H, Tables S4A and Tables S4B-1 through S4B-7). Although fold induction of CCL19/CXCL13 did not clearly correlate with response (FIG. 10A), higher absolute levels of CCL19 and CXCL13, and their receptors (CCR7 and CXCR5), was evident in banked samples from melanoma patients with clinical benefit (CB) from checkpoint blockade (FIGS. 3I-3J, FIGS. 10B-10C). Pretreatment CCL19/CXCL13 mRNA expression levels alone failed to correlate with responsiveness to PD-1 or CTLA-4 blockade in melanoma RNAseq datasets (FIGS. 10D-10E). NanoString data from matched formalin-fixed and paraffin-embedded tissue or banked plasma was also insufficient to detect correlation with response (FIGS. 10F-10G).


As PD-1 blockade promotes immune cell infiltration in vivo, gene set enrichment analysis (GSEA) was performed using published immune signatures, which revealed enrichment of diverse immune cell populations in patients with CB to checkpoint blockade (FIG. 3K). To evaluate the clinical significance of CCL19/CXCL13, Cancer Genome Atlas melanoma (SKCM) data were analyzed. Improved patient survival was evident in melanoma specimens with higher expression of CCL19/CXCL13 (FIGS. 3L-3M; p<0.001). Evaluation of TCGA data for other cancers (e.g., bladder cancer, head and neck, and breast) revealed similar a pattern (FIG. 10H). Immune GSEA using melanoma TCGA data confirmed enrichment of diverse immune cell gene sets in melanoma patients with high levels of both CCL19 and CXCL13 (FIG. 3N), consistent with their established roles as chemoattractants.


CCL19/CXCL13 coordinate humoral and cell-mediated adaptive immunity in lymph nodes and tertiary lymphoid structures (TLS), and cancer-associated TLS have been associated with improved prognosis. Histologic review of melanoma biopsy specimens pre- and on-anti-PD1 only identified rare TLS (FIG. 11A) likely due to limited sampling by core biopsy. Expression of CCL19 in the melanoma TME has been linked to cancer-associated fibroblasts (CAFs), and CXCL13 to CD8+ exhausted T cells. CCL19 is also strongly expressed in lymph node high endothelial venules. It was noted that strongest induction of CCL19/CXCL13 by anti-PD1 was independent of the number of total CD45+ cells or other immune subpopulations in PDOTS (FIGS. 11B-11D). Therefore, CD45+ and CD45− cell populations from a sample (MGH-16) marked by robust anti-PD1 induced secretion of CCL19 and CXCL13 were sorted, to determine the cellular source of CCL19 and CXCL13 in PDOTS. Indeed, stromal populations including CD90+CD45− cancer-associated fibroblasts, CD31+CD144+ endothelial cells, and tumor cells (CD45−) expressed CCL19 in particular, while CXCL13 was also detected in CD45+ cells (FIG. 11E). Immunohistochemical staining confirmed expression of CCL19 and CXCL13 in stromal elements including cancer-associated fibroblasts (αSMA) and endothelial cells (CD31) (FIG. 11F).


To better understand the relationship between anti-PD1 induced PDOTS cytokine profiles and clinical benefit to ICB, unsupervised hierarchical clustering of cytokine profiles from patients specifically treated with anti-PD-1 therapy was performed. PDOTS from patients with mixed response or progression on anti-PD-1 therapy elaborated multiple immune suppressive cytokines/chemokines (e.g., CCL2) in addition to CCL19/CXCL13 (FIG. 3O). Induction of significantly higher levels of CCL20 and CX3CL1 in patients with no clinical benefit (NCB) to PD-1 blockade (FIG. 12A) was noted, consistent with their lack of association with survival (FIG. 12B) and previous association of CX3CL1 induction with anti-PD-L1 resistance. Several of these immune suppressive cytokines/chemokines induced in PDOTS were also components of an innate PD-1 resistance (IPRES) gene expression signature (FIG. 12B), which correlated with nonresponse but missed statistical significance (p=0.08, FIG. 12C). Serial PDOTS profiling from an individual patient revealed that induction of multiple granulocytic and monocytic chemoattractants predicted infiltration of these respective myeloid populations following disease progression on anti-PD-1 therapy in vivo (FIGS. 12D-12E). These data highlight the potential of this assay to identify cytokines changes associated with ineffective anti-tumor immune responses despite CCL19/CXCL13 induction following ICB.


Higher levels of immune suppressive cytokines were also induced in anti-PD1-resistant B16F10 MDOTS relative to MC38 MDOTS (FIG. 12F), as well as the intermediately resistant CT26 MDOTS model, which elaborated particularly high levels of CCL2 (FIG. 12G). Because of its partial sensitivity to anti-PD1, CT26 model was used to determine whether MDOTS profiling could identify novel combination therapies that overcome resistance. However, neutralization of CCL2 alone failed to enhance PD-1 mediated killing of CT26 MDOTS (FIG. 12H-12I), suggesting the need for alternative strategies that more broadly inhibit immune suppressive signaling within the TME and reactivate T cells.


It was noted that the homologous innate immune signaling kinases TBK1 and IKKε not) only promote autocrine/paracrine cytokine signaling, but also restrain T cell activation, suggesting that a dual impact of TBK1/IKKε inhibition on the TME could enhance anti-tumor activity of PD-1 blockade (FIG. 4A). A novel potent/selective TBK1/IKKε inhibitor Compound 1 (Cmpd1) was synthesized (FIG. 4B, FIGS. 13A-D, Tables S5-1 and S5-2), which lacks JAK inhibitory activity, in contrast to the multitargeted inhibitor momelotinib (CYT387). Cmpd1 effectively blocked immune suppressive cytokine elaboration by CT26 cell line spheroids, without cytotoxic effects (FIG. 4C, FIG. 13E), and enhanced secretion of IL-2 and IFN-γ from purified CD4+ and CD8+ T cells (FIGS. 4D-4E) and IL-2 from Jurkat cells (FIG. 13F). Decreased levels of CCL4, CCL3, and IL-1β with concomitant induction of cytokines involved in activated innate immune responses (e.g., G-CSF) were observed in CT26 MDOTS treated with Cmpd1±anti-PD-1 (FIG. 4F). Ex vivo combination treatment enhanced killing of CT26 MDOTS (FIGS. 4G-4H), which predicted in vivo response with greater tumour control and longer survival than mice treated with Cmpd1 or anti-PD-L1 alone (FIGS. 4I-4K). Reimplantation of CT26 into mice with exceptional responses to combination therapy showed no growth, suggesting immunologic memory for CT26 tumors (FIG. 13F).


Combination treatment in the PD-1 sensitive MC38 MDOTS model enhanced ex vivo killing and in vivo survival, although neither of these reached significance compared to single-agent PD-1/PD-L1 (FIGS. 14A-14D). The intrinsically resistant B16F10 model could not be sensitized with Cmpd1 treatment (FIGS. 14E-14H), possibly due to the relative paucity of immune cells in B16F10 MDOTS compared to CT26 and MC38 MDOTS. Indeed, downregulation of several immune suppressive chemokines (e.g., CCL2, CCL5) in B16F10 MDOTS was observed, but without concomitant induction of G-CSF and related innate immune response cytokines (FIGS. 14A-14B). However, enhanced response to combination treatment with Cmpd1 was confirmed in vivo using a fourth partially anti-PD1 sensitive syngeneic model (MB49 bladder carcinoma), further validating its activity. Importantly, MDOTS responses in three models (CT26, MC38, and B16F10) effectively recapitulated the in vivo response (or lack thereof) to PD-1 blockade+/−TBK1/IKKε inhibition, highlighting the potential of ex vivo screening in MDOTS to develop combination immunotherapies more generally.


Example 3. Transcriptomic Analysis of MDOTS/PDOTS Following Ex Vivo Treatment

RNA is collected from a subset of the MDOTs within the device after the supernatants have been collected and cDNA libraries for RNA sequencing is generated to evaluate global transcriptome changes associated with treatment regimen on single samples per drug treatment. These types of data may be generated from a variety of clinical specimens. The RNA Advance tissue RNA isolation method (Beckman Coulter) is utilized, which is a bead wash based separation technique, which facilitates elution volumes amenable to sample input for RNA-Seq library preparation. Automated library preparation can be performed using as little as 10 ng of good quality RNA. The RNA Access method from Illumina is utilized, which enriches for the coding region of the genome. Libraries are sequenced on the NextSeq500 platform, as 75 bp Single End to generate approximately 20 million reads per sample. With appropriate adaptors, 24 samples are multiplexed on each NextSeq500 run. The concentration [ng/ul], yield [ng] and quality of RNA (high RIN# by bioanalyzer) derived from the MDOTS are more than sufficient to ensure good quality libraries for subsequent sequencing (FIG. 15).


The STAR RNA sequencing alignment tool (Spliced Transcripts Alignment to a Reference) [STAR_2.5.0a]) is utilized to align the data to the genome (RefSeq gene annotations). DeSeq2 is utilized to perform differential expression analysis (±2-fold, P value<0.05). Overlaps between differentially expressed genes and the annotated Immunological gene sets in the Molecular Signature Database or MSigDB (FDR q-value<0.05) are computed. CIBERSORT (Newman A M et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015 May; 12(5):453-7.) is utilized to provide an estimation of the abundances of member cell types in a mixed cell population, including more than 20 immune subsets, using the transcriptomic data generated.


The additional information garnered from whole transcriptome analysis provides a deeper understanding of the biological response to PD-1 immune blockage on its own and in combination with other immune blockade compounds or a MEK inhibitor. This knowledge complements secretion profiling to identify novel mechanisms of both response and resistance. Moreover, computational methods to evaluate the “immunone” including GSEA and CIBERSORT, permit inference of changes in immune cell populations using established gene signatures.


Example 4. RNA-Sequencing of PDOTS/MDOTS for Biomarker Discovery and Novel Target Identification

Bulk RNA-seq was applied to the MDOTS/PDOTS platform as a proof-of-concept to identify candidate biomarkers and potential novel targets for combination therapies in response to inhibition of PD-1.


The patient- and murine-derived organotypic tumor spheroids (PDOTS/MDOTS) platform was utilized to identify novel biomarkers and potential therapeutic targets using RNA-sequencing (RNA-seq). Reproducible induction of cytokines and chemokines (e.g. SOCS3, Pde4b, Pde4d, Adcy5) in response to ex vivo PD-1 blockade using MDOTS and PDOTS was observed (see FIG. 16). Additionally, dual-labeling fluorescence microscopy was used to demonstrate immune-mediated tumor killing. This method for imaging and quantifying immune-mediated tumor killing in combinatorial drug testing represented a novel use of available fluorescent reagents. Evaluation of combinations of different targeted therapies revealed that some therapeutic agents appear to sensitize PDOTS/MDOTS to PD-1 blockade resulting in enhanced immune responses, manifested by alterations in cytokine elaboration, and enhanced tumor killing. In particular, combined TBK1-PD-1 therapy was found to be a novel therapeutic combination to enhance PD-1 response.


Tables with Supportive Data for Example 2:















TABLE S2-1







Tumor
Tumor
Tumor
Tumor
Tumor




1.000
2.000
4.000
5.000
6.000





















Tumor
1
1.000
0.955
0.890
0.752
0.240


Tumor
2
0.955
1.000
0.835
0.712
0.223


Tumor
4
0.890
0.835
1.000
0.907
0.495


Tumor
5
0.752
0.712
0.907
1.000
0.758


Tumor
6
0.240
0.223
0.495
0.758
1.000


S1
1
0.852
0.900
0.619
0.555
0.197


S1
2
0.975
0.963
0.852
0.699
0.129


S1
3
0.948
0.967
0.756
0.611
0.087


S1
4
0.838
0.821
0.915
0.911
0.676


S1
5
0.558
0.549
0.708
0.802
0.860


S1
6
0.461
0.470
0.554
0.691
0.834


S2
1
0.749
0.788
0.603
0.635
0.455


S2
2
0.948
0.936
0.865
0.816
0.367


S2
3
0.881
0.883
0.696
0.634
0.230


S2
4
0.680
0.651
0.836
0.925
0.825


S2
5
0.308
0.310
0.540
0.713
0.925


S2
6
0.183
0.226
0.383
0.590
0.884


S3
1
0.740
0.776
0.569
0.636
0.459


S3
2
0.827
0.856
0.664
0.688
0.407


S3
3
0.790
0.817
0.548
0.510
0.165


S3
4
0.685
0.675
0.792
0.839
0.768


S3
5
0.300
0.278
0.518
0.567
0.793


S3
6
0.226
0.246
0.430
0.499
0.766























TABLE S2-2







S1
S1
S1
S1
S1
S1




1.000
2.000
3.000
4.000
5.000
6.000






















Tumor
1
0.852
0.975
0.948
0.838
0.558
0.461


Tumor
2
0.900
0.963
0.967
0.821
0.549
0.410


Tumor
4
0.619
0.852
0.756
0.915
0.708
0.554


Tumor
5
0.555
0.699
0.611
0.911
0.802
0.691


Tumor
6
0.197
0.129
0.087
0.676
0.860
0.834


S1
1
1.000
0.854
0.932
0.745
0.546
0.553


S1
2
0.854
1.000
0.963
0.776
0.465
0.371


S1
3
0.932
0.963
1.000
0.737
0.447
0.399


S1
4
0.745
0.776
0.737
1.000
0.897
0.803


S1
5
0.546
0.465
0.447
0.897
1.000
0.967


S1
6
0.553
0.371
0.399
0.803
0.967
1.000


S2
1
0.908
0.692
0.778
0.800
0.677
0.672


S2
2
0.862
0.937
0.906
0.863
0.605
0.514


S2
3
0.915
0.849
0.927
0.742
0.493
0.460


S2
4
0.590
0.598
0.547
0.957
0.928
0.835


S2
5
0.290
0.191
0.154
0.749
0.890
0.825


S2
6
0.248
0.081
0.057
0.640
0.822
0.790


S3
1
0.908
0.685
0.776
0.767
0.654
0.666


S3
2
0.937
0.808
0.844
0.808
0.649
0.634


S3
3
0.921
0.764
0.888
0.642
0.428
0.437


S3
4
0.663
0.605
0.580
0.959
0.958
0.889


S3
5
0.283
0.178
0.166
0.720
0.911
0.867


53
6
0.261
0.112
0.101
0.665
0.845
0.794























TABLE S2-3







S2
S2
S2
S2
S2
S2




1.000
2.000
3.000
4.000
5.000
6.000






















Tumor
1
0.749
0.948
0.881
0.680
0.308
0.183


Tumor
2
0.788
0.936
0.883
0.651
0.310
0.226


Tumor
4
0.603
0.865
0.696
0.836
0.540
0.383


Tumor
5
0.635
0.816
0.634
0.925
0.713
0.590


Tumor
6
0.455
0.367
0.230
0.825
0.925
0.884


S1
1
0.908
0.862
0.915
0.590
0.290
0.248


S1
2
0.692
0.937
0.849
0.598
0.191
0.081


S1
3
0.778
0.906
0.927
0.547
0.154
0.057


S1
4
0.800
0.863
0.742
0.957
0.749
0.640


S1
5
0.677
0.605
0.493
0.928
0.890
0.822


S1
6
0.672
0.514
0.460
0.835
0.825
0.790


S2
1
1.000
0.833
0.898
0.735
0.567
0.527


S2
2
0.833
1.000
0.901
0.751
0.425
0.323


S2
3
0.898
0.901
1.000
0.616
0.290
0.184


S2
4
0.735
0.751
0.616
1.000
0.872
0.767


S2
5
0.567
0.425
0.290
0.872
1.000
0.970


S2
6
0.527
0.323
0.184
0.767
0.970
1.000


S3
1
0.984
0.835
0.901
0.707
0.529
0.493


S3
2
0.945
0.920
0.890
0.717
0.481
0.443


S3
3
0.893
0.816
0.976
0.517
0.217
0.139


S3
4
0.779
0.741
0.625
0.970
0.862
0.782


S3
5
0.485
0.327
0.243
0.792
0.894
0.836


S3
6
0.510
0.298
0.201
0.747
0.929
0.920























TABLE S2-4







S3
S3
S3
S3
S3
S3




1.000
2.000
3.000
4.000
5.000
6.000






















Tumor
1
0.740
0.827
0.790
0.685
0.300
0.226


Tumor
2
0.776
0.856
0.817
0.675
0.278
0.246


Tumor
4
0.569
0.664
0.548
0.792
0.518
0.430


Tumor
5
0.636
0.688
0.510
0.839
0.567
0.499


Tumor
6
0.459
0.407
0.165
0.768
0.793
0.766


S1
1
0.908
0.937
0.921
0.663
0.283
0.261


S1
2
0.685
0.808
0.764
0.605
0.178
0.112


S1
3
0.776
0.844
0.888
0.580
0.166
0.101


S1
4
0.767
0.808
0.642
0.959
0.720
0.665


S1
5
0.654
0.649
0.428
0.958
0.911
0.845


S1
6
0.666
0.634
0.437
0.889
0.867
0.794


S2
1
0.984
0.945
0.893
0.779
0.485
0.510


S2
2
0.835
0.920
0.816
0.741
0.327
0.298


S2
3
0.901
0.890
0.976
0.625
0.243
0.201


S2
4
0.707
0.717
0.517
0.970
0.792
0.747


S2
5
0.529
0.481
0.217
0.862
0.894
0.929


S2
6
0.493
0.443
0.139
0.782
0.836
0.920


S3
1
1.000
0.960
0.913
0.746
0.426
0.440


S3
2
0.960
1.000
0.874
0.763
0.387
0.394


S3
3
0.913
0.874
1.000
0.550
0.181
0.146


S3
4
0.746
0.763
0.550
1.000
0.849
0.812


S3
5
0.426
0.387
0.181
0.849
1.000
0.955


S3
6
0.440
0.394
0.146
0.812
0.955
1.000





















TABLE S3












Transcripts Per Million















Normalized Counts


CCL19
CXCL13














ID
Response
CCL19
CXCL13
Pt ID
Response
(ENSG00000172724)
(ENSG00000156234)

















Pt13
R
34.698109
2519.38443
Pt13
R
1.168351014
1.450293862


Pt15
R
368.803957
958.479364
Pt15
R
7.162930953
0.318252625


Pt19
R
1958.97151
620.707828
Pt19
R
13.49446269
0.073098545


Pt2
R
290.527532
1198.6162
Pt2
R
7.401911739
0.522072463


Pt27A
R
209.760872
1416.41918
Pt27A
R
7.057272238
0.814700951


Pt27B
R
127.405123
460.732479
Pt27B
R
4.111967591
0.254217624


Pt28
R
1952.44983
2324.597
Pt28
R
40.56616838
0.825706707


Pt35
R
95.3399393
539.624057
Pt35
R
3.445558222
0.333403426


Pt37
R
97.0628571
349.174174
Pt37
R
2.033195626
0.125043823


Pt38
R
9077.47447
44808.3318
Pt38
R
292.4756557
24.68183797


Pt4
R
158.462804
383.601214
Pt4
R
2.601765411
0.107674982


Pt5
R
0.8957807
94.056973
Pt5
R
0.038933398
0.069888488


Pt6
R
1.44330175
90.2063594
Pt6
R
0.020724471
0.022144073


Pt8
R
617.842921
243.736198
Pt8
R
12.63014518
0.085181314


Pt9
R
1131.85131
641.694215
Pt9
R
35.53789234
0.344448618


Pt1
NR
2340.48615
479.579124
Pt1
NR
99.54999655
0.348730135


Pt10
NR
2.70089632
2584.08255
Pt10
NR
0.098714409
1.614630139


Pt12
NR
292.02708
93.1555918
Pt12
NR
8.617132617
0.046994022


Pt16
NR
14.8144533
421.153742
Pt14
NR
9.131829845
0.112841472


Pt14
NR
221.968265
160.438202
Pt16
NR
0.360470362
0.17519376


Pt20
NR
3001.54512
6437.79678
Pt20
NR
49.36256271
1.810023107


Pt22
NR
1426.52919
960.941811
Pt22
NR
21.09294252
0.242911252


Pt23
NR
15.1942229
2322.92855
Pt23
NR
0.229044285
0.598647058


Pt25
NR
944.629262
879.267764
Pt25
NR
11.4526496
0.182246738


Pt29
NR
420.240506
1498.70041
Pt29
NR
11.97953537
0.73038345


Pt31
NR
39.9689397
296.01996
Pt31
NR
0.909356479
0.115140091


Pt32
NR
4.86573555
259.830278
Pt32
NR
0.18150561
0.165701082


Pt7
NR
217.069727
429.20605
Pt7
NR
4.459248487
0.150737839





15 responders


13 non-resonders













TABLE S4A







Melanoma Patient Samples-Patient Treatment Details









Samples
Treatment
Clinical Benefit/Response





148-S9
pre-PD-1-combo (on trial)
NCB (mixed response →


148-S10
post-PD-1-combo (on trial) (209 days)
progressive disease)


208-S11
pre-CTLA-4; pre-PD-1
NCB (progression)


208-S12
on-CTLA-4 (42 days); pre-PD-1



208-S13
post-CTLA-4 (182 days); pre-PD-1



208-S14
post-CTLA-4 (245 days); on-PD-1 (63 days)



27-S1
post-BRAFi (479 days); pre-PD-1
NCB (progression)


27-S2
post-BRAFi (960 days); on-PD-1 (31 days)



39-S15
post-BRAFi (393 days); post-IL2 (388 days); post-CTLA-4
NCB (mixed response →



(153 days); pre-BRAFi/MEKi; pre-PD-1
progressive disease


39-S16
post-BRAFi (540 days); post-IL2 (535 days); post-CTLA-4




(300 days); post-BRAFi/MEKi (54 days); on-PD-1 (21 days)



39-S17
post-BRAFi (607 days); post-IL2 (602 days); post-CTLA-4




(367 days); post-BRAFi/MEKi (121 days); on-PD-1 (88 days)



42-S3
post-CTLA-4 (176 days); post-BRAFi/MEKi (64 days);
NCB (progression)



pre-PD-1



42-S4
post-CTLA-4 (214 days); post-BRAFi/MEKi (102 days);




on-PD-1 (38 days)



42-S5
post-CTLA-4 (250 days); post-BRAFi/MEKi (138 days);




post-PD-1 (74 days)



62-S6
pre-CTLA-4; pre-PD-1
NCB (stable disease → disease


62-S7
post-CTLA-4 (235 days); on-PD-1 (3 days)
progression)


62-S8
post-CTLA-4 (277 days); on-PD-1 (45 days)



272-S1
pre-CTLA-4
CB (near complete response,


272-S2
post-CTLA-4 (47 days); pre-PD-1
PD-1 stopped due to irAE,


272-S3
post-CTLA-4 (437 days); post-PD-1 (346 days)
eventual progression off therapy)


422-S1
pre-PD-1, pre-CTLA-4
CB (excellent response after ipi-


422-S2
on-PD-1, on-CTLA-4
nivo → nivo)


51-S1
pre-PD-L1
CB (stable disease with a single


51-S2
Post-PD-L1 (224 days)
escape lesion)


98-S1
post-PD-1 (83 days); pre-CTLA-4
CB (mixed response →


98-S2
Post-PD-1 (109 days); post-CTLA-4 (25 days)
response)


98-S3
post-PD-1 (182 days); post-CTLA-4 (98 days)

















TABLE S4B-1








Samples
















148-S9
148-S10
208-S11
208-S12
208-S13
208-S14
27-S1
27-S2









Treatment





















post-

post-




post-PD-


post-
CTLA-4
post-
BRAFi




1-combo

on-
CTLA-4
(245
BRAFi
(960



pre-PD-
(on trial)
pre-
CTLA-4
(182
days); on-
(479
days); on-



1-combo
(209
CTLA-4;
(42 days);
days);
PD-1 (63
days);
PD-1 (31



(on trial)
days)
pre-PD-1
pre-PD-1
pre-PD-1
days)
pre-PD-1
days)


















CCL19
0.15687084
0.41913344
1.98815132
4.59582353
3.45513526
8.77085298
0.1
0.93715502


CXCL13
0.26803097
2.38711763
0.09436038
24.7654719
2.17496489
11.6557472
1.27418346
0.6404927


CCL2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1


CCL7
0.1
0.352523
0.13934883
0.1
0.1
0.32786454
0.1
0.1


CCL8
19.5526419
29.918033
0.90971542
3.97934158
5.89116018
8.66865469
0.36852681
3.80785605


CCL13
24.0118925
82.8961538
3.06991672
9.11382191
6.00656079
10.3634372
0.36047157
0.30199656


IL10
2.70808608
3.17659032
0.41855817
1.41409955
0.68911285
1.88752859
0.09419912
0.23675495


VEGFA
3.53392266
4.83525269
1.29428459
0.86705549
1.65186515
1.23934008
1.5851421
2.89436628


VEGFC
6.12754266
8.3234783
0.81574911
2.3208504
1.85041997
1.47147983
1.248408
2.33787985


CCR7
0.43889039
0.90613397
0.42139498
3.5517162
0.97129671
4.51119789
0.11380507
0.42904724


CXCR5
0.06942884
0.13912696
0.18331834
0.39116295
0.20120982
0.60384444
0.1
0.04147717


AXL
32.5031535
60.0635857
2.91859483
8.55069013
6.30519042
4.63247743
2.56483473
3.61622621


GZMA
2.51550488
9.76148303
3.16280085
53.720088
30.132477
28.5755234
1.53750529
13.8827918


GZMB
3.13000293
3.09735564
0.7346123
33.0483114
4.43469902
8.64210075
3.47191043
10.5267372


IFNGR1
51.4518655
56.8050947
54.1265708
61.4638002
58.8209997
82.2106075
43.6363806
28.2519413


TNF
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1


IL2
0.13457249
0.17977794
0.1
0.1
0.1
0.16720274
0.1
0.1


IFNG
0.26670627
0.23753197
0.1
3.00525274
0.72140516
2.09871115
0.38036581
1.06221195














0.1
Below quantification























TABLE S4B-2








Samples
















39-S15
39-S16
39-S17
42-S3
42-S4
42-S5
62-S6
62-S7









Treatment

















post-
post-









BRAFi
BRAFi









(540
(607









days);
days);









post-IL2
post-IL2








post-
(535
(602








BRAFi
days);
days);








(393 days);
post-
post-

post-
post-





post-IL2
CTLA-4
CTLA-4
post-
CTLA-4
CTLA-4





(388 days);
(300
(367
CTLA-4
(214
(250





post-
days);
days);
(176
days);
days);





CTLA-4
post-
post-
days);
post-
post-

post-



(153 days);
BRAFi/
BRAFi/
post-
BRAFi/
BRAFi/

CTLA-4



pre-
MEKi (54
MEKi (121
BRAFi/
MEKi (102
MEKi (138
pre-
(235



BRAFi/
days); on-
days); on-
MEKi (64
days); on-
days);
CTLA-
days);



MEKi; pre-
PD-1 (21
PD-1 (88
days);
PD-1 (38
post-PD-1
4; pre-
on-PD-1



PD-1
days)
days)
pre-PD-1
days)
(74 days)
PD-1
(3 days)


















CCL19
0.1
7.17238179
0.57691197
1.23267021
5.18691585
6.33513418
0.1
0.19283266


CXCL13
1.62907579
2.78518137
13.80004
0.23401686
21.2470659
3.96889863
0.1
0.98842702


CCL2
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1


CCL7
0.2830323
0.41130796
0.48522669
0.1
0.83895949
1.24327654
0.1
0.1


CCL8
3.97261692
2.50614458
2.32299537
2.93296153
34.1765182
59.2506107
7.98116673
4.1293583


CCL13
2.57546133
5.90954174
1.08446841
3.6412366
67.6625745
58.3524709
5.93524222
8.85494803


IL10
1.9128064
1.50997511
6.1537277
0.34601269
5.87990461
2.48959659
0.16767663
0.64954159


VEGFA
2.44542296
1.59918098
1.08303658
0.29859241
2.57328173
0.92074409
0.72348459
1.68157005


VEGFC
0.99412394
1.76571995
1.00996294
0.60692541
3.9945039
0.90110433
1.56860848
1.77229407


CCR7
0.21397451
0.8706652
0.88040393
0.52253673
0.9133338
0.53710072
0.20257569
0.09809159


CXCR5
0.0372339
0.14429073
0.17022212
0.0909271
0.44147241
0.0934614
0.1
0.1


AXL
3.15217802
5.9937903
5.59225163
2.69996776
10.0967011
3.89711811
4.64898024
4.8257931


GZMA
5.26766769
14.8122602
18.7958475
3.45129418
118.364242
42.5698517
8.66651831
5.88984997


GZMB
3.6058497
22.4059016
21.3166185
3.64372548
109.390225
31.8348999
1.03001359
2.13752208


IFNGR1
81.0920132
110.98998
60.1500121
79.9433286
95.0516258
75.0677163
0.1
35.6153856


TNF
0.1
0.1
0.1
0.1
0.1
0.1
0.1
0.1


IL2
0.14433941
0.1
0.82484505
0.1
0.1
0.36230859
0.1
0.1


IFNG
0.66748061
0.46190268
3.16050183
0.11643014
7.80107938
4.30830872
0.56421667
0.32784729














0.1
Below quantification























TABLE S4B-3








Samples














62-S8
272-S1
272-S2
272-S3
422-S1
422-S2









Treatment














post-


post-





CTLA-4


CTLA





(277

post-
-4 (437





days);

CTLA-
days);
pre-
on-



on-

4 (47
post-
PD-1,
PD-1,



PD-1
pre-
days);
PD-1
pre-
on-



(45
CTLA-
pre-
(346
CTLA-
CTLA-



days)
4
PD-1
days)
4
4





CCL19
0.18082453
30.8026747
81.8439915
30.3310126
49.1698251
569.522382


CXCL13
0.20597232
143.121621
197.444029
42.1785257
88.565516
236.913118


CCL2
0.1
0.1
0.1
0.1
0.1
0.1


CCL7
0.1
2.26838847
2.20958272
4.55339377
27.1500865
0.1


CCL8
0.09928753
38.0092355
21.2212318
12.1190886
142.838439
3.00565688


CCL13
1.16540776
7.7380948
10.0937847
4.97652335
13.0430495
2.22349876


IL10
0.22840994
10.9175298
12.1675798
3.6530185
2.56684581
2.03367129


VEGFA
1.21549229
1.59027526
1.89991979
4.36289443
1.41618926
0.51813138


VEGFC
0.94967388
1.66183682
2.86889762
1.731475
1.96825775
2.46115994


CCR7
0.3219412
8.27974664
12.7854505
4.44863917
5.84631976
95.5634831


CXCR5
0.52019769
1.09942208
2.21362828
0.79868685
0.37596741
48.1180912


AXL
2.4522467
56.6522478
74.8405834
13.3027932
10.9127259
19.1432302


GZMA
3.58999916
80.8064715
125.257307
46.3160997
41.8012
37.8345867


GZMB
7.61677215
17.1664256
16.4009527
3.82328583
10.1578792
4.1352438


IFNGR1
11.8733792
57.0563904
61.1826911
37.3127656
44.6747933
85.6737313


TNF
0.1
1.26258841
1.58476345
0.69407351
1.36758178
2.61714127


IL2
0.1
0.1
0.1
0.1
0.1
0.1


IFNG
0.20495433
10.2969456
11.6529517
2.83209437
2.88850742
1.74662482














Samples















51-S1
51-S2
98-S1
98-S2
98-S3











Treatment


















post-
post-






post-
PD-1
PD-1






PD-1
(109
(182






(83
days);
days);





post-
days);
post-
post-





PD-L1
pre-
CTLA-
CTLA-




pre-
(224
CTLA-
4 (25
4 (98




PD-Ll
days)
4
days)
days)






CCL19
31.365808
32.4152798
0.17967977
0.53928875
47.9201706



CXCL13
16.4200002
79.6634246
1.33034424
1.36021174
68.8004261



CCL2
0.1
0.1
0.1
0.1
0.1



CCL7
0.85296606
0.06224591
0.1511243
0.25919012
0.48076933



CCL8
6.96055707
12.0283136
1.28256651
2.15740095
18.2040065



CCL13
24.9771521
3.04071984
0.79614548
0.49652815
23.4856381



IL10
2.3790281
1.43340819
0.26479124
0.55145316
2.32656264



VEGFA
0.97385307
0.71259811
2.69306142
6.84424133
0.76154607



VEGFC
6.2059211
0.70448349
0.8551934
1.01153397
5.75394032



CCR7
5.96945609
8.15050896
0.13710131
0.05878489
4.26465798



CXCR5
0.30457195
1.75237544
0.01988094
0.01704869
0.92762141



AXL
2.54442739
29.894754
0.48020963
0.52945552
144.038705



GZMA
10.1174052
40.9634229
1.79255175
1.87878039
27.1754305



GZMB
8.29444931
14.8478181
2.44928242
3.15592022
18.753749



IFNGR1
184.213974
47.254564
22.8699314
32.4953981
124.279512



TNF
0.33169142
0.45183519
0.11821037
0.04054803
0.73206497



IL2
0.1
0.1
0.1
0.1
0.1



IFNG
0.12315714
4.90717196
0.0509142
0.04366094
10.0962879















0.1
Below quantification


























TABLE S4B-4





FC
148
208a
208b
208c
27
39a
39b
42a
42b
























CCL19
2.67
2.31
1.74
4.41
9.37
71.72
5.77
4.21
5.14


CXCL13
8.91
262.46
23.05
123.52
0.50
1.71
8.47
90.79
16.96


CCL2
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00


CCL7
3.53
0.72
0.72
2.35
1.00
1.45
1.71
8.39
12.43


CCL8
1.53
4.37
6.48
9.53
10.33
0.63
0.58
11.65
20.20


CCL13
3.45
2.97
1.96
3.38
0.84
2.29
0.42
18.58
16.03


IL10
1.17
3.38
1.65
4.51
2.51
0.79
3.22
16.99
7.20


VEGFA
1.37
0.67
1.28
0.96
1.83
0.65
0.44
8.62
3.08


VEGFC
1.36
2.85
2.27
1.80
1.87
1.78
1.02
6.58
1.48


CCR7
2.06
8.43
2.30
10.71
3.77
4.07
4.11
1.75
1.03


CXCR5
2.00
2.13
1.10
3.29
0.41
3.88
4.57
4.86
1.03


AXL
1.85
2.93
2.16
1.59
1.41
1.90
1.77
3.74
1.44


GZMA
3.88
16.98
9.53
9.03
9.03
2.81
3.57
34.30
12.33


GZMB
0.99
44.99
6.04
11.76
3.03
6.21
5.91
30.02
8.74


IFNGR1
1.10
1.14
1.09
1.52
0.65
1.37
0.74
1.19
0.94


TNF
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00


IL2
1.34
1.00
1.00
1.67
1.00
0.69
5.71
1.00
3.62


IFNG
0.89
30.05
7.21
20.99
2.79
0.69
4.73
67.00
37.00
























TABLE S4B-5





FC
62a
62b
272a
272b
422
51
98a
98b























CCL19
1.93
1.81
2.66
0.98
11.58
1.03
3.00
266.70


CXCL13
9.88
2.06
1.38
0.29
2.68
4.85
1.02
51.72


CCL2
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00


CCL7
1.00
1.00
0.97
2.01
0.00
0.07
1.72
3.18


CCL8
0.52
0.01
0.56
0.32
0.02
1.73
1.68
14.19


CCL13
1.49
0.20
1.30
0.64
0.17
0.12
0.62
29.50


IL10
3.87
1.36
1.11
0.33
0.79
0.60
2.08
8.79


VEGFA
2.32
1.68
1.19
2.74
0.37
0.73
2.54
0.28


VEGFC
1.13
0.61
1.73
1.04
1.25
0.11
1.18
6.73


CCR7
0.48
1.59
1.54
0.54
16.35
1.37
0.43
31.11


CXCR5
1.00
5.20
2.01
0.73
127.98
5.75
0.86
46.66


AXL
1.04
0.53
1.32
0.23
1.75
11.75
1.10
299.95


GZMA
0.68
0.41
1.55
0.57
0.91
4.05
1.05
15.16


GZMB
2.08
7.39
0.96
0.22
0.41
1.79
1.29
7.66


IFNGR1
356.15
118.73
1.07
0.65
1.92
0.26
1.42
5.43


TNF
1.00
1.00
1.26
0.55
1.91
1.36
0.34
6.19


IL2
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00


IFNG
0.58
0.36
1.13
0.28
0.60
39.84
0.86
198.30

























TABLE S4B-6





L2FC
148
208a
208b
208c
27
39a
39b
42a
42b
























CCL19
1.42
1.21
0.80
2.14
3.23
6.16
2.53
2.07
2.36


CXCL13
3.15
8.04
4.53
6.95
−0.99
0.77
3.08
6.50
4.08


CCL2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00


CCL7
1.82
−0.48
−0.48
1.23
0.00
0.54
0.78
3.07
3.64


CCL8
0.61
2.13
2.70
3.25
3.37
−0.66
−0.77
3.54
4.34


CCL13
1.79
1.57
0.97
1.76
−0.26
1.20
−1.25
4.22
4.00


IL10
0.23
1.76
0.72
2.17
1.33
−0.34
1.69
4.09
2.85


VEGFA
0.45
−0.58
0.35
−0.06
0.87
−0.61
−1.18
3.11
1.62


VEGFC
0.44
1.51
1.18
0.85
0.91
0.83
0.02
2.72
0.57


CCR7
1.05
3.08
1.20
3.42
1.91
2.02
2.04
0.81
0.04


CXCR5
1.00
1.09
0.13
1.72
−1.27
1.95
2.19
2.28
0.04


AXL
0.89
1.55
1.11
0.67
0.50
0.93
0.83
1.90
0.53


GZMA
1.96
4.09
3.25
3.18
3.17
1.49
1.84
5.10
3.62


GZMB
−0.02
5.49
2.59
3.56
1.60
2.64
2.56
4.91
3.13


IFNGR1
0.14
0.18
0.12
0.60
−0.63
0.45
−0.43
0.25
−0.09


TNF
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00


IL2
0.42
0.00
0.00
0.74
0.00
−0.53
2.51
0.00
1.86


IFNG
−0.17
4.91
2.85
4.39
1.48
−0.53
2.24
6.07
5.21
























TABLE S4B-7





L2FC
62a
62b
272a
272b
422
51
98a
98b























CCL19
0.95
0.85
1.41
−0.02
3.53
0.05
1.59
8.06


CXCL13
3.31
1.04
0.46
−1.76
1.42
2.28
0.03
5.69


CCL2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00


CCU/
0.00
0.00
−0.04
1.01
−8.08
−3.78
0.78
1.67


CCL8
−0.95
−6.33
−0.84
−1.65
−5.57
0.79
0.75
3.83


CCL13
0.58
−2.35
0.38
−0.64
−2.55
−3.04
−0.68
4.88


IL10
1.95
0.45
0.16
−1.58
−0.34
−0.73
1.06
3.14


VEGFA
1.22
0.75
0.26
1.46
−1.45
−0.45
1.35
−1.82


VEGFC
0.18
−0.72
0.79
0.06
0.32
−3.14
0.24
2.75


CCR7
−1.05
0.67
0.63
−0.90
4.03
0.45
−1.22
4.96


CXCR5
0.00
2.38
1.01
−0.46
7.00
2.52
−0.22
5.54


AXL
0.05
−0.92
0.40
−2.09
0.81
3.55
0.14
8.23


GZMA
−0.56
−1.27
0.63
−0.80
−0.14
2.02
0.07
3.92


GZMB
1.05
2.89
−0.07
−2.17
−1.30
0.84
0.37
2.94


IFNGR1
8.48
6.89
0.10
−0.61
0.94
−1.96
0.51
2.44


TNF
0.00
0.00
0.33
−0.86
0.94
0.45
−1.54
2.63


IL2
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00


IFNG
−0.78
−1.46
0.18
−1.86
−0.73
5.32
−0.22
7.63
















TABLE S5-1







Project SSBK10488_30712; provides data for Cmpd1 (1000 μM).























%
%
%





Dev






In-
In-
In-
Dup
Donor
Acceptor


Reaction






hibition
hibition
hibition
Differ-
Inter-
Inter-

Kinase Part#/
Inter-


ATP
Kinase
mutant
Technology
1
2
Avg
ence
ference
ference
Z′
Lot#
ference






















Km
TBK1

ZLYTE
91
99
95
8
Pass
Pass
0.83
PV3504/857011
Pass


app















CDC7/DBF4

LanthaScreen
100
97
98
3
Pass
Pass
0.84
PV6274/1576890






Binding












MAPK15 (ERK7)

LanthaScreen
100
100
100
0
Pass
Pass
0.93
PV6181/1570972






Binding











Km
IKBKE (IKK

ZLYTE
106
103
105
3
Pass
Pass
0.8
PV4875/853377
Pass


app
epsilon)













Km
CSF1R (FMS)

ZLYTE
91
96
93
6
Pass
Pass
0.79
PV3249/662393
Pass


app















STK17A (DRAK1)

LanthaScreen
101
101
101
0
Pass
Pass
0.9
PV3783/902537






Binding












TGFBR2

LanthaScreen
92
95
93
3
Pass
Pass
0.79
PV6122/862447






Binding












PLK4

LanthaScreen
96
95
96
1
Pass
Pass
0.96
PV6394/1577044






Binding











Km
LRRK2

Adapta
99
100
100
1
Pass
Pass
0.76
PV4873/1106714



app














Km
STK22D (TSSK1)

ZLYTE
99
95
97
3
Pass
Pass
0.88
PV3505/1211826
Pass


app














Km
PRKD2 (PKD2)

ZLYTE
99
97
98
2
Pass
Pass
0.8
PV3758/34015
Pass


app














Km
MKNK1 (MNK1)

ZLYTE
99
100
100
1
Pass
Pass
0.77
PV6023/1405297
Pass


app














Km
PRKD1 (PKC mu)

ZLYTE
100
95
98
5
Pass
Pass
0.86
PV3791/34226
Pass


app














Km
MARK4

ZLYTE
96
93
95
3
Pass
Pass
0.8
PV3851/304213
Pass


app














Km
MARK3

ZLYTE
98
94
96
4
Pass
Pass
0.73
PV4819/830446
Pass


app














Km
PAK4

ZLYTE
91
90
90
1
Pass
Pass
0.73
PV4212/35324
Pass


app















MLCK (MLCK2)

LanthaScreen
92
93
93
0
Pass
Pass
0.56
PV3835/34028






Binding












ULK3

LanthaScreen
101
104
102
3
Pass
Pass
0.82
PV6436/1579414






Binding











Km
IRAK1

Adapta
94
96
95
1
Pass
Pass
0.91
PV4403/880118



app














Km
BRSK1 (SAD1)

ZLYTE
92
89
90
4
Pass
Pass
0.91
PV4333/36097
Pass


app















SIK3

LanthaScreen
98
95
96
2
Pass
Pass
0.73
PV6403/1577057






Binding











Km
PRKCN (PKD3)

ZLYTE
98
96
97
2
Pass
Pass
0.74
PV3692/1252690
Pass


app















STK16 (PKL12)

LanthaScreen
95
93
94
2
Pass
Pass
0.76
PV4311/36847






Binding












ULK2

LanthaScreen
86
90
88
4
Pass
Pass
0.9
PV6433/1579413






Binding











Km
LRRK2 G2019S
y
Adapta
99
100
100
1
Pass
Pass
0.88
PV4881/933637



app














Km
LRRK2 G2019S FL
y
Adapta
100
99
99
1
Pass
Pass
0.81
A15200PT/50078



app














Km
LRRK2 12020T
y
Adapta
100
98
99
2
Pass
Pass
0.84
PV5854/902533



app














Km
LRRK2 FL

Adapta
98
98
98
0
Pass
Pass
0.88
A15197PT/11476



app










93



Km
LRRK2 R1441C
y
Adapta
99
95
97
4
Pass
Pass
0.8
PV5858/902531



app















KIT D816H
y
LanthaScreen
90
94
92
4
Pass
Pass
0.82
PV6196/1570980






Binding












ULK1

LanthaScreen
91
92
92
1
Pass
Pass
0.8
PV6430/1579415






Binding












ACVR1 (ALK2)
y
LanthaScreen
88
93
91
5
Pass
Pass
0.88
PV6232/1578464




R206H

Binding












KIT A829P
y
LanthaScreen
91
90
90
0
Pass
Pass
0.89
PV6193/1570981






Binding











Km
AURKA (Aurora

ZLYTE
91
86
89
5
Pass
Pass
0.84
PV3612/32155
Pass


app
A)














EIF2AK2 (PKR)

LanthaScreen
90
89
89
1
Pass
Pass
0.8
PV4821/374655






Binding












STK17B (DRAK2)

LanthaScreen
94
84
89
10
Pass
Pass
0.6
PV6328/1575526






Binding












CLK4

LanthaScreen
87
89
88
2
Pass
Pass
0.81
PV3839/827665






Binding











Km
SNF1LK2

ZLYTE
88
88
88
0
Pass
Pass
0.66
PV4792/719848
Pass


app















MKNK2 (MNK2)

LanthaScreen
86
88
87
2
Pass
Pass
0.86
PV5607/811381






Binding











Km
MAP4K4 (HGK)

ZLYTE
86
86
86
0
Pass
Pass
0.74
PV3687/792773
Pass


app














Km
MARK1 (MARK)

ZLYTE
85
87
86
3
Pass
Pass
0.89
PV4395/1081574
Pass


app














Km
FYN

ZLYTE
85
85
85
0
Pass
Pass
0.7
P3042/1191778
Pass


app















RIPK2

LanthaScreen
84
86
85
1
Pass
Pass
0.93
PV4213/35334






Binding












ACVR1 (ALK2)

LanthaScreen
85
84
84
1
Pass
Pass
0.92
PV4877/676188






Binding











Km
MARK2

ZLYTE
86
82
84
4
Pass
Pass
0.88
PV3878/877056
Pass


app















KIT D816V
y
LanthaScreen
83
83
83
1
Pass
Pass
0.74
PV6199/1570986






Binding











Km
NUAK1 (ARK5)

Adapta
83
83
83
0
Pass
Pass
0.83
PV4127/1401900



app














Km
PDGFRA V561D
y
ZLYTE
85
81
83
4
Pass
Pass
0.84
PV4680/1113217
Pass


app















TLK2

LanthaScreen
84
81
83
3
Pass
Pass
0.91
PV6424/1578677






Binding











Km
FLT3 D835Y
y
ZLYTE
83
81
82
2
Pass
Pass
0.81
PV3967/308809
Pass


app














Km
PHKG2

ZLYTE
83
79
81
4
Pass
Pass
0.85
PV4555/37321
Pass


app














Km
PDK1 Direct

ZLYTE
85
74
79
11
Pass
Pass
0.71
P3001/1394674
Pass


app














Km
CHEK1 (CHK1)

ZLYTE
78
78
78
1
Pass
Pass
0.74
P3040/28702
Pass


app















DMPK

LanthaScreen
76
79
78
2
Pass
Pass
0.84
PV3784/802854






Binding











Km
PAK7 (KIAA1264)

ZLYTE
77
79
78
2
Pass
Pass
0.84
PV4405/36846
Pass


app














Km
PLK3

ZLYTE
80
76
78
5
Pass
Pass
0.8
PV3812/38812
Pass


app














Km
PDGFRA D842V
y
ZLYTE
77
73
75
4
Pass
Pass
0.89
PV4203/26969
Pass


app














Km
JAK3

ZLYTE
73
73
73
1
Pass
Pass
0.86
PV3855/1017963
Pass


app















CDK16

LanthaScreen
70
73
71
3
Pass
Pass
0.81
PV6379/1577049




(PCTK1)/cyclin Y

Binding











Km
MAP3K9 (MLK1)

ZLYTE
68
73
70
5
Pass
Pass
0.84
PV3787/1095726
Pass


app














Km
NEK1

ZLYTE
68
70
69
3
Pass
Pass
0.82
PV4202/880120
Pass


app














Km
RET V804L
y
ZLYTE
71
66
69
5
Pass
Pass
0.85
PV4397/36640
Pass


app














Km
MINK1

ZLYTE
66
70
68
4
Pass
Pass
0.76
PV3810/1081579
Pass


app















ABL1 M351T
y
LanthaScreen
65
69
67
4
Pass
Pass
0.67
PV6151/1570962






Binding











Km
JAK2

ZLYTE
67
68
67
1
Pass
Pass
0.8
PV4210/784633
Pass


app















KIT N822K
y
LanthaScreen
66
67
66
1
Pass
Pass
0.71
PV6310/1576886






Binding











Km
TYK2

ZLYTE
65
64
64
1
Pass
Pass
0.88
PV4790/884908
Pass


app















FLT3 ITD

LanthaScreen
64
62
63
2
Pass
Pass
0.72
PV6190/1570961






Binding











Km
MYLK2

ZLYTE
65
60
63
5
Pass
Pass
0.67
PV3757/36606
Pass


app
(skMLCK)













100
BRAF V599E
y
ZLYTE
63
61
62
2
Pass
Pass
0.92
PV3849/910409
Pass


Km
FLT4 (VEGFR3)

ZLYTE
64
60
62
5
Pass
Pass
0.87
PV4129/38454
Pass


app














Km
PLK2

ZLYTE
60
64
62
4
Pass
Pass
0.9
PV4204/38798
Pass


app














Km
ABL1 G250E
y
ZLYTE
60
61
60
1
Pass
Pass
0.9
PV3865/34529
Pass


app















ABL1 H396P
y
LanthaScreen
58
60
59
2
Pass
Pass
0.74
PV6148/1570966






Binding












MAP3K10 (MLK2)

LanthaScreen
58
60
59
2
Pass
Pass
0.96
PV3877/1138344






Binding












BMPR1B (ALK6)

LanthaScreen
56
60
58
3
Pass
Pass
0.81
PV6235/1578462






Binding











Km
CHUK (IKK alpha)

Adapta
65
50
58
15
Pass
Pass
0.79
PV4310/1110228



app















DDR2 T654M
y
LanthaScreen
56
57
57
1
Pass
Pass
0.79
PV6175/1570973






Binding












MAP4K1 (HPK1)

LanthaScreen
59
55
57
3
Pass
Pass
0.72
PV6355/1575528






Binding












MAPK8 (JNK1)

LanthaScreen
57
56
57
1
Pass
Pass
0.83
PV3319/1354818






Binding











Km
SRC N1

ZLYTE
54
60
57
6
Pass
Pass
0.91
P2904/21068
Pass


app















STK33

LanthaScreen
59
55
57
4
Pass
Pass
0.91
PV4343/798867






Binding












TGFBR1 (ALK5)

LanthaScreen
56
58
57
2
Pass
Pass
0.91
PV5837/562479






Binding












DAPK2

LanthaScreen
60
53
56
7
Pass
Pass
0.64
PV3614/32159






Binding












SIK1

LanthaScreen
57
54
56
2
Pass
Pass
0.93
PV6445/1601253






Binding











Km
AMPK A1/B1/G1

ZLYTE
58
53
55
5
Pass
Pass
0.9
PV4672/1046028
Pass


app














Km
ABLI Y253F
y
ZLYTE
61
48
54
12
Pass
Pass
0.92
PV3863/34531
Pass


app















CDK14

LanthaScreen
56
51
54
5
Pass
Pass
0.56
PV6382/1577046




(PFTK1)/cyclin Y

Binding












DYRK2

LanthaScreen
54
53
54
1
Pass
Pass
0.57
PV6331/1578676






Binding











Km
FGR

ZLYTE
53
53
53
0
Pass
Pass
0.94
P3041/26670
Pass


app















KIT Y823D
y
LanthaScreen
47
59
53
12
Pass
Pass
0.67
PV6322/1579412






Binding











Km
LYN B

ZLYTE
56
50
53
6
Pass
Pass
0.8
P2907/21076
Pass


app















NUAK2

LanthaScreen
54
52
53
1
Pass
Pass
0.65
PV6376/1607389






Binding












TEK (TIE2)
y
LanthaScreen
53
52
53
0
Pass
Pass
0.6
PV6229/1570987




Y1108F

Binding











Km
YES1

ZLYTE
55
51
53
4
Pass
Pass
0.84
A15557/50645
Pass


app















BRAF V599E
y
LanthaScreen
50
53
52
3
Pass
Pass
0.89
PV3849/910409






Binding











Km
JAK2 JH1 JH2

ZLYTE
54
50
52
4
Pass
Pass
0.84
PV4336/463344
Pass


app
V617F













Km
KDR (VEGFR2)

ZLYTE
51
53
52
2
Pass
Pass
0.85
PV3660/1223246
Pass


app














Km
ABL1 E255K
y
ZLYTE
53
50
51
3
Pass
Pass
0.79
PV3864/34528
Pass


app














Km
AURKB (Aurora

ZLYTE
54
48
51
6
Pass
Pass
0.78
PV6130/857013
Pass


app
B)














BMPR1A (ALK3)

LanthaScreen
51
51
51
0
Pass
Pass
0.82
PV6038/670004






Binding











Km
DAPK3 (ZIPK)

ZLYTE
52
49
51
3
Pass
Pass
0.68
PV3686/1083962
Pass


app















PKN2 (PRK2)

LanthaScreen
51
52
51
2
Pass
Pass
0.93
PV3879/555959






Binding











Km
RET Y791F
y
ZLYTE
57
43
50
14
Pass
Pass
0.91
PV4396/36639
Pass


app















STK38 (NDR)

LanthaScreen
51
49
50
2
Pass
Pass
0.81
PV6370/1575531






Binding











Km
ABL1

ZLYTE
48
51
49
4
Pass
Pass
0.88
P3049/1012910
Pass


app















BMPR2

LanthaScreen
50
47
49
3
Pass
Pass
0.8
PV6256/1579470






Binding












MAPK10 (JNK3)

LanthaScreen
48
49
49
1
Pass
Pass
0.93
PV4563/1075329






Binding











Km
LYN A

ZLYTE
48
48
48
0
Pass
Pass
0.91
P2906/827663
Pass


app















KIT V559D T670I
y
LanthaScreen
46
49
47
3
Pass
Pass
0.94
PV6316/1579472






Binding












MET D1228H
y
LanthaScreen
46
48
47
2
Pass
Pass
0.78
PV6208/1570985






Binding












ABL1 Q252H
y
LanthaScreen
52
41
46
11
Pass
Pass
0.76
PV6154/1570960






Binding












AMPK (A1/B2/G1)

LanthaScreen
49
43
46
5
Pass
Pass
0.96
PV6244/1578463






Binding











Km
AMPK A2/B1/G1

ZLYTE
47
46
46
2
Pass
Pass
0.93
PV4674/568101
Pass


app















BRAF

LanthaScreen
44
47
46
2
Pass
Pass
0.89
PV3848/1258788






Binding











Km
JAK2 JH1 JH2

ZLYTE
46
47
46
1
Pass
Pass
0.81
PV4393/311662
Pass


app














Km
NEK9

ZLYTE
46
45
46
1
Pass
Pass
0.89
PV4653/38162
Pass


app














Km
SYK

ZLYTE
44
49
46
5
Pass
Pass
0.85
PV3857/756818
Pass


app















AMPK (A2/B2/G2)

LanthaScreen
44
45
45
1
Pass
Pass
0.93
PV6250/1578465






Binding











Km
FLT3

ZLYTE
42
49
45
7
Pass
Pass
0.78
PV3182/1012909
Pass


app














Km
IKBKB (IKK beta)

ZLYTE
52
39
45
13
Pass
Pass
0.9
PV3836/1445179
Pass


app














Km
SRC

ZLYTE
45
44
45
1
Pass
Pass
0.89
P3044/1255538
Pass


app















TNIK

LanthaScreen
46
43
45
3
Pass
Pass
0.8
PV6427/1578672






Binding











Km
RET

ZLYTE
46
42
44
4
Pass
Pass
0.89
PV3819/853376
Pass


app















TAOK1

LanthaScreen
45
43
44
2
Pass
Pass
0.82
PV6415/1576240






Binding











Km
DAPK1

Adapta
42
43
43
2
Pass
Pass
0.83
PV3969/32654



app














Km
PDGFRA (PDGFR

ZLYTE
43
43
43
0
Pass
Pass
0.82
PV3811/1269727
Pass


app
alpha)













Km
BLK

ZLYTE
41
42
42
1
Pass
Pass
0.8
PV3683/33635
Pass


app















CDK2/cyclin O

LanthaScreen
39
42
41
4
Pass
Pass
0.75
PV6286/1576891






Binding












TEK (TIE2)
y
LanthaScreen
40
41
41
1
Pass
Pass
0.92
PV6226/1570990




R849W

Binding











Km
TYRO3 (RSE)

ZLYTE
42
39
41
4
Pass
Pass
0.9
PV3828/682475
Pass


app














Km
ABL2 (Arg)

ZLYTE
40
39
40
1
Pass
Pass
0.92
PV3266/850069
Pass


app















AMPK (A1/B1/G2)

LanthaScreen
40
40
40
0
Pass
Pass
0.97
PV6238/1578461






Binding











Km
LCK

ZLYTE
41
38
40
3
Pass
Pass
0.79
P3043/850070
Pass


app















LIMK1

LanthaScreen
40
39
40
1
Pass
Pass
0.87
PV4337/367810






Binding












AMPK (A1/B1/G3)

LanthaScreen
37
42
39
5
Pass
Pass
0.92
PV6241/1578466






Binding











Km
MST1R (RON)

ZLYTE
38
38
38
0
Pass
Pass
0.83
PV4314/765277
Pass


app














Km
PHKG1

ZLYTE
39
37
38
2
Pass
Pass
0.75
PV3853/830447
Pass


app














Km
CDK2/cyclin A

ZLYTE
38
36
37
1
Pass
Pass
0.88
PV3267/924344
Pass


app















DDR2 N456S
y
LanthaScreen
33
42
37
9
Pass
Pass
0.86
PV6172/1570968






Binding











Km
RPS6KB1

ZLYTE
37
36
37
1
Pass
Pass
0.84
PV3815/38944
Pass


app
(p70S6K)














CDK2/cyclin A1

LanthaScreen
33
39
36
6
Pass
Pass
0.89
PV6289/1576888






Binding











Km
PDGFRA T674I
y
ZLYTE
40
32
36
8
Pass
Pass
0.67
PV3847/35891
Pass


app















ACVRL1 (ALK1)

LanthaScreen
33
38
35
5
Pass
Pass
0.79
PV4883/511550






Binding












AMPK (A2/B2/G1)

LanthaScreen
35
35
35
0
Pass
Pass
0.94
PV6247/1578460






Binding












FGFR3 K650M
y
LanthaScreen
33
38
35
5
Pass
Pass
0.82
PV6187/1573650






Binding











Km
ITK

ZLYTE
37
32
34
4
Pass
Pass
0.71
PV3875/1430640
Pass


app















STK38L (NDR2)

LanthaScreen
30
38
34
9
Pass
Pass
0.54
PV6373/1575530






Binding











Km
CLK1

ZLYTE
33
34
33
0
Pass
Pass
0.88
PV3315/943590
Pass


app














Km
EPHB1

ZLYTE
34
31
33
3
Pass
Pass
0.91
PV3786/34225
Pass


app















RET V804M
y
LanthaScreen
35
31
33
4
Pass
Pass
0.82
PV6223/1570988






Binding












TTK

LanthaScreen
33
34
33
1
Pass
Pass
0.77
PV3792/558743






Binding











Km
PDGFRB (PDGFR

ZLYTE
34
30
32
4
Pass
Pass
0.78
P3082/27567
Pass


app
beta)














WEE1

LanthaScreen
28
36
32
7
Pass
Pass
0.64
PV3817/784632






Binding











Km
CSNK2A2 (CK2

ZLYTE
32
30
31
2
Pass
Pass
0.81
PV3624/32653
Pass


app
alpha 2)













Km
EGFR (ErbB1)
y
ZLYTE
34
29
31
4
Pass
Pass
0.9
PV4879/1189155
Pass


app
T790M L858R













Km
MET (cMet)

ZLYTE
30
33
31
4
Pass
Pass
0.79
PV3143/625156
Pass


app














Km
TXK

ZLYTE
27
36
31
9
Pass
Pass
0.86
PV5860/750657
Pass


app














Km
MET M1250T
y
ZLYTE
26
34
30
8
Pass
Pass
0.86
PV3968/34718
Pass


app














Km
NEK2

ZLYTE
29
30
30
0
Pass
Pass
0.81
PV3360/1086245
Pass


app















SLK

LanthaScreen
29
32
30
4
Pass
Pass
0.95
PV3830/34390






Binding











Km
ABL1 T315I
y
ZLYTE
30
29
29
1
Pass
Pass
0.84
PV3866/39639
Pass


app















ACVR2B

LanthaScreen
27
31
29
4
Pass
Pass
0.86
PV6049/877066






Binding











Km
DYRK1A

ZLYTE
30
27
28
4
Pass
Pass
0.9
PV3785/683159
Pass


app















NLK

LanthaScreen
26
29
28
3
Pass
Pass
0.88
PV4309/35323






Binding











Km
ROS1

ZLYTE
30
26
28
4
Pass
Pass
0.81
PV3814/479684
Pass


app















AXL R499C
y
LanthaScreen
28
27
27
1
Pass
Pass
0.89
PV6253/1578673






Binding











Km
CHEK2 (CHK2)

ZLYTE
27
27
27
0
Pass
Pass
0.84
PV3367/1033750
Pass


app














Km
EPHA1

ZLYTE
29
14
27
5
Pass
Pass
0.85
PV3841/1138343
Pass


app














Km
HCK

ZLYTE
26
18
27
2
Pass
Pass
0.87
PV6128/862448
Pass


app














Km
SGK (SGK1)

ZLYTE
28
26
27
2
Pass
Pass
0.88
PV3818/1088196
Pass


app















CDK2/cyclin A2

LanthaScreen
24
29
26
5
Pass
Pass
0.7
PV6292/1576892






Binding












MAP3K11 (MLK3)

LanthaScreen
24
29
26
5
Pass
Pass
0.93
PV3788/869925






Binding












MERTK (cMER)
y
LanthaScreen
24
27
26
3
Pass
Pass
0.92
PV6325/1578675




A708S

Binding











Km
PRKX

ZLYTE
22
30
26
8
Pass
Pass
0.87
PV3813/34283
Pass


app














Km
DYRK3

ZLYTE
26
24
25
2
Pass
Pass
0.89
PV3837/290370
Pass


app














Km
EGFR (ErbB1)
y
ZLYTE
25
25
25
0
Pass
Pass
0.85
PV4803/1123633
Pass


app
T790M













100
MAPK8 (JNK1)

ZLYTE
33
18
25
15
Pass
Pass
0.79
PV3319/1354818
Pass



TNK2 (ACK)

LanthaScreen
25
26
25
1
Pass
Pass
0.92
PV4807/407338






Binding











Km
AXL

ZLYTE
22
25
24
3
Pass
Pass
0.86
PV3971/873922
Pass


app















LATS2

LanthaScreen
23
25
24
1
Pass
Pass
0.91
PV6364/1575533






Binding











Km
MERTK (cMER)

ZLYTE
27
22
24
5
Pass
Pass
0.82
PV3627/32658
Pass


app















PRKACG (PRKAC

LanthaScreen
28
19
24
9
Pass
Pass
0.66
PV6391/1577047




gamma)

Binding











Km
AURKC (Aurora

ZLYTE
23
23
23
0
Pass
Pass
0.66
PV3856/1078206
Pass


app
C)














FGFR1 V561M
y
LanthaScreen
20
25
23
5
Pass
Pass
0.91
PV6343/1578678






Binding











Km
MELK

ZLYTE
25
22
23
3
Pass
Pass
0.85
PV4823/819467
Pass


app














Km
NEK4

ZLYTE
23
23
23
0
Pass
Pass
0.88
PV4315/924342
Pass


app















ACVR2A

LanthaScreen
23
21
22
2
Pass
Pass
0.76
PV6124/862446






Binding












ICK

LanthaScreen
22
21
22
0
Pass
Pass
0.86
PV6358/1577056






Binding












MAP3K14 (NIK)

LanthaScreen
20
24
22
3
Pass
Pass
0.91
PV4902/1296958






Binding












MAP3K7/MAP3K7

LanthaScreen
22
22
22
0
Pass
Pass
0.89
PV4394/930475




IP1 (TAK1-TAB1)

Binding











Km
GSK3A (GSK3

ZLYTE
20
22
21
2
Pass
Pass
0.91
PV6126/862449
Pass


app
alpha)













Km
GSK3B (GSK3

ZLYTE
21
21
21
0
Pass
Pass
0.79
PV3365/371501
Pass


app
beta)













Km
CDK9/cyclin T1

Adapta
18
22
20
4
Pass
Pass
0.88
PV4131/1370615



app














Km
EPHA4

ZLYTE
18
21
20
2
Pass
Pass
0.9
PV3651/32933
Pass


app














Km
HIPK2

ZLYTE
21
19
20
2
Pass
Pass
0.93
PV5275/452552
Pass


app














100
MAPK10 (JNK3)

ZLYTE
20
21
20
0
Pass
Pass
0.9
PV4563/1075329
Pass


Km
CAMK2D

ZLYTE
18
19
19
1
Pass
Pass
0.91
PV3373/31647
Pass


app
(CaMKII delta)














CAMK2G

LanthaScreen
18
19
18
1
Pass
Pass
0.77
PV6268/1576884




(CaMKII gamma)

Binding












FYN A

LanthaScreen
16
21
18
6
Pass
Pass
0.81
PV6346/1575529






Binding












KIT D820E
y
LanthaScreen
18
19
18
2
Pass
Pass
0.97
PV6307/1576885






Binding












MAP4K3 (GLK)

LanthaScreen
16
21
18
6
Pass
Pass
0.87
PV6349/1579471






Binding












MYO3B (MYO3

LanthaScreen
17
20
18
3
Pass
Pass
0.95
PV6367/1577055




beta)

Binding











Km
NTRK1 (TRKA)

ZLYTE
16
20
18
3
Pass
Pass
0.73
PV3144/1347534
Pass


app














Km
NTRK3 (TRKC)

ZLYTE
17
19
18
3
Pass
Pass
0.85
PV3617/708766
Pass


app















RAF1 (cRAF)
y
LanthaScreen
15
20
18
4
Pass
Pass
0.91
PV3805/1293604




Y340D Y341D

Binding












RET G691S
y
LanthaScreen
19
18
18
1
Pass
Pass
0.8
PV6214/1570982






Binding












BRSK2

LanthaScreen
16
17
17
1
Pass
Pass
0.87
PV6259/1576239






Binding












LIMK2

LanthaScreen
14
19
17
5
Pass
Pass
0.95
PV3860/355434






Binding












PRKACB (PRKAC

LanthaScreen
16
18
17
2
Pass
Pass
0.82
PV6388/1577048




beta)

Binding











Km
CDK1/cyclin B

ZLYTE
16
15
16
1
Pass
Pass
0.85
PV3292/873341
Pass


app















CDK2/cyclin E1

LanthaScreen
15
17
16
2
Pass
Pass
0.66
PV6295/1576887






Binding











Km
EPHB2

ZLYTE
14
17
16
3
Pass
Pass
0.91
PV3625/1386867
Pass


app














Km
HIPK4

ZLYTE
18
14
16
4
Pass
Pass
0.89
PV3852/719847
Pass


app














100
MAPK9 (JNK2)

ZLYTE
12
21
16
9
Pass
Pass
0.73
PV3620/32388
Pass


Km
PIK3CD/PIK3R1

Adapta
22
9
16
12
Pass
Pass
0.88
PV5273/1147693



app
(p110 delta/p85














alpha)













Km
RPS6KA6 (RSK4)

ZLYTE
14
17
16
3
Pass
Pass
0.63
PV4557/37496
Pass


app














Km
CDK7/cyclin

Adapta
17
14
15
2
Pass
Pass
0.8
PV3868/1427412



app
H/MNAT1













Km
EPHB4

ZLYTE
15
14
15
2
Pass
Pass
0.73
PV3251/29241
Pass


app














100
MAP3K8 (COT)

ZLYTE
19
11
15
7
Pass
Pass
0.89
PV4313/1111069
Pass


100
PDK1

ZLYTE
14
16
15
1
Pass
Pass
0.81
P3001/1394674
Pass


Km
RPS6KA2 (RSK3)

ZLYTE
17
13
15
4
Pass
Pass
0.89
PV3846/34468
Pass


app















TLK1

LanthaScreen
13
17
15
4
Pass
Pass
0.88
PV6421/1576241






Binding












EGFR (ErbB1)
y
LanthaScreen
14
13
14
1
Pass
Pass
0.78
PV6178/1570967




d746-750

Binding












EPHA6

LanthaScreen
9
20
14
11
Pass
Pass
0.63
PV6337/1575527






Binding











Km
PRKG2 (PKG2)

ZLYTE
16
13
14
3
Pass
Pass
0.87
PV3973/273926
Pass


app














Km
RPS6KA3 (RSK2)

ZLYTE
17
10
14
7
Pass
Pass
0.83
PV3323/1361669
Pass


app














Km
TEK (Tie2)

ZLYTE
11
17
14
6
Pass
Pass
0.59
PV3628/34398
Pass


app















ALK F1174L
y
LanthaScreen
12
14
13
2
Pass
Pass
0.91
PV6160/1570964






Binding











Km
HIPK3 (YAK1)

ZLYTE
15
11
13
4
Pass
Pass
0.92
PV4209/I076022
Pass


app















MAPK9 (JNK2)

LanthaScreen
12
14
13
3
Pass
Pass
0.91
PV3620/32388






Binding











Km
ROCK2

ZLYTE
12
14
13
2
Pass
Pass
0.74
PV3759/843703
Pass


app














Km
RPS6KA1 (RSK1)

ZLYTE
15
11
13
4
Pass
Pass
0.83
PV3680/880119
Pass


app














Km
STK22B (TSSK2)

ZLYTE
12
14
13
1
Pass
Pass
0.79
PV3622/32396
Pass


app














Km
BMX

ZLYTE
12
13
12
1
Pass
Pass
0.89
PV3371/953336
Pass


app














Km
CAMK1D (CaMKI

ZLYTE
12
13
12
1
Pass
Pass
0.85
PV3663/1042984
Pass


app
delta)













Km
CSK

ZLYTE
13
10
12
2
Pass
Pass
0.88
P2927/1205898
Pass


app














Km
FGFR2

ZLYTE
12
11
12
1
Pass
Pass
0.93
PV3368/31517
Pass


app














Km
FRK (PTK5)

ZLYTE
11
13
12
2
Pass
Pass
0.84
PV3874/34553
Pass


app














Km
HIPK1 (Myak)

ZLYTE
11
13
12
1
Pass
Pass
0.89
PV4561/1126221
Pass


app















MAP3K3

LanthaScreen
10
13
12
3
Pass
Pass
0.79
PV3876/702480




(MEKK3)

Binding











Km
MAP4K5 (KHS1)

ZLYTE
11
12
12
0
Pass
Pass
0.65
PV3682/1383139
Pass


app














Km
MUSK

ZLYTE
15
8
12
7
Pass
Pass
0.67
PV3834/1217900
Pass


app















RET M918T
y
LanthaScreen
10
13
12
3
Pass
Pass
0.64
PV6217/1570989






Binding











Km
DYRK1B

ZLYTE
14
9
11
5
Pass
Pass
0.91
PV4649/877059
Pass


app















EPHA7

LanthaScreen
10
12
11
2
Pass
Pass
0.62
PV3689/33790






Binding











Km
PLK1

ZLYTE
12
9
11
3
Pass
Pass
0.89
PV3501/39441
Pass


app














Km
CAMK2B

ZLYTE
11
8
10
3
Pass
Pass
0.81
PV4205/35330
Pass


app
(CaMKII beta)













Km
CDC42 BPB

ZLYTE
6
13
10
7
Pass
Pass
0.88
PV4399/36845
Pass


app
(MRCKB)














CDK9 (Inactive)

LanthaScreen
8
13
10
5
Pass
Pass
0.93
PV6304/1579469






Binding












CDK9/cyclin K

LanthaScreen
11
9
10
2
Pass
Pass
0.74
PV4335/35774






Binding











Km
CSNK2A1 (CK2

ZLYTE
13
7
10
7
Pass
Pass
0.73
PV3248/1240448
Pass


app
alpha 1)













Km
JAK1

ZLYTE
11
10
10
2
Pass
Pass
0.62
PV4774/1240449
Pass


app















MAP3K2

LanthaScreen
11
9
10
2
Pass
Pass
0.75
PV3822/1171755




(MEKK2)

Binding











Km
PRKCB2 (PKC

ZLYTE
12
8
10
4
Pass
Pass
0.82
P2251/930444
Pass


app
beta II)













Km
PRKCH (PKC eta)

ZLYTE
12
8
10
4
Pass
Pass
0.62
P2633/25587
Pass


app














Km
ROCK1

ZLYTE
6
14
10
8
Pass
Pass
0.78
PV3691/37178
Pass


app














Km
SGK2

ZLYTE
7
12
10
5
Pass
Pass
0.78
PV3858/1099019
Pass


app















STK39 (STLK3)

LanthaScreen
10
9
10
1
Pass
Pass
0.54
PV6412/1608283






Binding












ALK C1156Y
y
LanthaScreen
7
12
9
5
Pass
Pass
0.98
PV6157/1570963






Binding











Km
EGFR (ErbB1)

ZLYTE
10
9
9
2
Pass
Pass
0.89
PV3872/1004026
Pass


app














Km
EPHA8

ZLYTE
11
7
9
4
Pass
Pass
0.81
PV3844/36870
Pass


app















KIT V654A
y
LanthaScreen
7
10
9
3
Pass
Pass
0.82
PV4132/35129






Binding











100
MAP2K6 (MKK6)

ZLYTE
0
19
9
19
Pass
Pass
0.85
PV3318/884909
Pass


Km
NEK6

ZLYTE
12
6
9
7
Pass
Pass
0.76
PV3353/30778
Pass


app














Km
PIK3CG (p110

Adapta
11
8
9
3
Pass
Pass
0.92
PV4786/1153861



app
gamma)














CAMKK2

LanthaScreen
7
9
8
2
Pass
Pass
0.93
PV4206/35319




(CaMKK beta)

Binding












CASK

LanthaScreen
6
10
3
4
Pass
Pass
0.75
PV6271/1576243






Binding











Km
FES (FPS)

ZLYTE
9
7
8
2
Pass
Pass
0.84
PV3354/35734
Pass


app















FGFR3 G697C
y
LanthaScreen
13
4
8
9
Pass
Pass
0.74
PV6184/1570969






Binding











Km
FGFR3 K650E
y
ZLYTE
11
6
8
5
Pass
Pass
0.85
PV4392/36445
Pass


app















MAP2K1 (MEK1)
y
LanthaScreen
10
7
8
2
Pass
Pass
0.92
P3099/38541




S218D S222D

Binding











100
MAP2K2 (MEK2)

ZLYTE
13
2
8
10
Pass
Pass
0.92
PV3615/32519
Pass


Km
MAPK13 (p38

ZLYTE
7
9
8
2
Pass
Pass
0.83
PV3656/36817
Pass


app
delta)













Km
PAK1

ZLYTE
8
8
8
0
Pass
Pass
0.86
PV3820/35463
Pass


app















ZAK

LanthaScreen
6
10
8
4
Pass
Pass
0.92
PV3882/34603






Binding











10
CAMK1 (CaMK1)

Adapta
7
8
7
1
Pass
Pass
0.86
PV4391/36046




CDK1/cyclin A2

LanthaScreen
2
12
7
11
Pass
Pass
0.73
PV6280/1579468






Binding











Km
CLK2

ZLYTE
5
9
7
4
Pass
Pass
0.81
PV4201/873335
Pass


app














Km
DCAMKL2

ZLYTE
11
3
7
8
Pass
Pass
0.63
PV4297/869931
Pass


app
(DCK2)













Km
FER

ZLYTE
4
9
7
5
Pass
Pass
0.71
PV3806/38946
Pass


app














Km
FRAP1 (mTOR)

ZLYTE
2
12
7
10
Pass
Pass
0.8
PV4753/873345
Pass


app















MAP2K3 (MEK3)

LanthaScreen
5
8
7
4
Pass
Pass
0.61
PV3662/357368






Binding












MAP3K5 (ASK1)

LanthaScreen
7
8
7
1
Pass
Pass
0.72
PV3809/666419






Binding











Km
PIM1

ZLYTE
11
3
7
9
Pass
Pass
0.76
PV3503/811382
Pass


app















CDK3/cyclin E1

LanthaScreen
2
9
6
7
Pass
Pass
0.62
PV6298/1579411






Binding











Km
EPHA2

ZLYTE
1
12
6
12
Pass
Pass
0.77
PV3688/36904
Pass


app














Km
ERBB4 (HER4)

ZLYTE
8
5
6
4
Pass
Pass
0.74
PV3626/32657
Pass


app














Km
FLT1 (VEGFR1)

ZLYTE
7
4
6
3
Pass
Pass
0.81
PV3666/33924
Pass


app














Km
IRAK4

ZLYTE
5
8
6
3
Pass
Pass
0.78
PV3362/1088346
Pass


app














Km
KIT T6701
y
ZLYTE
6
7
6
2
Pass
Pass
0.71
PV3869/34504
Pass


app














Km
LTK (TYK1)

ZLYTE
5
7
6
1
Pass
Pass
0.78
PV4651/768522
Pass


app














Km
MAPK1 (ERK2)

ZLYTE
6
6
6
0
Pass
Pass
0.86
PV3313/904347
Pass


app














Km
MAPKAPK5

ZLYTE
6
7
6
1
Pass
Pass
0.78
PV3301/880117
Pass


app
(PRAK)













Km
NTRK2 (TRKB)

ZLYTE
5
7
6
1
Pass
Pass
0.93
PV3616/35706
Pass


app














Km
PAK6

ZLYTE
9
4
6
5
Pass
Pass
0.8
PV3502/625425
Pass


app














Km
PRKC1 (PKC iota)

ZLYTE
5
7
6
2
Pass
Pass
0.77
PV3183/28662
Pass


app














Km
PTK2B (FAK2)

ZLYTE
8
4
6
4
Pass
Pass
0.8
PV4567/883370
Pass


app















TESK2

LanthaScreen
14
−3
6
16
Pass
Pass
0.74
PV6418/1576242






Binding











Km
ADRBK1 (GRK2)

ZLYTE
3
7
5
4
Pass
Pass
0.88
PV3361/883372
Pass


app














Km
ADRBK2 (GRK3)

ZLYTE
6
4
5
2
Pass
Pass
0.71
PV3827/38897
Pass


app















ALK L1196M
y
LanthaScreen
1
9
5
8
Pass
Pass
0.92
PV6166/1570971






Binding











Km
BTK

ZLYTE
3
6
5
3
Pass
Pass
0.89
PV3363/1405298
Pass


app














Km
CDK5/p35

ZLYTE
7
2
5
5
Pass
Pass
0.89
PV3000/25348
Pass


app














Km
EGFR (ErbB1)
y
ZLYTE
6
5
5
1
Pass
Pass
0.89
PV3873/34562
Pass


app
L861Q













Km
FGFR3

ZLYTE
6
4
5
2
Pass
Pass
0.84
PV3145/28459
Pass


app















GRK1

LanthaScreen
7
2
5
5
Pass
Pass
0.96
PV6352/1577053






Binding











100
MAP2K1 (MEK1)

ZLYTE
7
3
5
4
Pass
Pass
0.82
PV3303/1081576
Pass



MAP2K1 (MEK1)

LanthaScreen
6
5
5
1
Pass
Pass
0.95
PV3303/1081567






Binding












MAP2K2 (MEK2)

LanthaScreen
5
5
5
0
Pass
Pass
0.94
PV3615/32519






Binding












MAP2K6 (MKK6)
y
LanthaScreen
5
5
5
0
Pass
Pass
0.91
PV3293/877061




S207E T211E

Binding











Km
MAPK11 (p38

ZLYTE
6
4
5
2
Pass
Pass
0.85
PV3679/1131827
Pass


app
beta)













Km
PAK3

ZLYTE
7
2
5
4
Pass
Pass
0.86
PV3789/34118
Pass


app














Km
PI4KB (PI4K beta)

Adapta
7
3
5
4
Pass
Pass
0.95
PV5277/943589



app














Km
STK3 (MST2)

ZLYTE
5
6
5
1
Pass
Pass
0.7
PV4805/371195
Pass


app















STK32B (YANK2)

LanthaScreen
1
8
5
7
Pass
Pass
0.9
PV6406/1577058






Binding











Km
TAOK2 (TAO1)

ZLYTE
3
6
5
3
Pass
Pass
0.8
PV3760/1011094
Pass


app















ALKR1275Q
y
LanthaScreen
0
7
4
7
Pass
Pass
0.89
PV6169/1570970






Binding











Km
CDC42 BPA

ZLYTE
4
4
4
0
Pass
Pass
0.7
PV4398/1314130
Pass


app
(MRCKA)













Km
EGFR (ErbB1)
y
ZLYTE
6
3
4
3
Pass
Pass
0.72
PV4128/279551
Pass


app
L858R














EPHA3

LanthaScreen
6
3
4
4
Pass
Pass
0.82
PV3359/673524






Binding











Km
GRK7

ZLYTE
3
5
4
2
Pass
Pass
0.86
PV3823/34013
Pass


app














Km
INSRR (IRR)

ZLYTE
5
4
4
1
Pass
Pass
0.91
PV3808/34272
Pass


app














100
MAPK14 (p38

ZLYTE
−1
9
4
10
Pass
Pass
0.87
PV3304/1475037
Pass



alpha)














MYLK (MLCK)

LanthaScreen
5
3
4
2
Pass
Pass
0.91
PV4339/36152






Binding











Km
PRKCB1 (PKC

ZLYTE
5
3
4
2
Pass
Pass
0.71
P2291/299686
Pass


app
beta I)













100
RAF1 (cRAF)
y
ZLYTE
5
3
4
2
Pass
Pass
0.91
PV3805/1293604
Pass



Y340D Y341D













Km
RPS6KA5 (MSK1)

ZLYTE
6
3
4
2
Pass
Pass
0.84
PV3681/380935
Pass


app














Km
SRMS (Srm)

ZLYTE
5
3
4
2
Pass
Pass
0.84
PV4214/1110226
Pass


app














Km
ZAP70

ZLYTE
4
4
4
0
Pass
Pass
0.86
P2782/843705
Pass


app














Km
AKT2 (PKB beta)

ZLYTE
3
2
3
1
Pass
Pass
0.81
PV3184/28770
Pass


app














Km
EPHA5

ZLYTE
3
4
3
1
Pass
Pass
0.74
PV3840/34383
Pass


app














Km
EPHB3

ZLYTE
3
3
3
0
Pass
Pass
0.94
PV3658/33066
Pass


app














Km
FGFR4

ZLYTE
7
−2
3
9
Pass
Pass
0.65
P3054/26967
Pass


app














Km
KIT

ZLYTE
1
5
3
4
Pass
Pass
0.76
P3081/1344384
Pass


app














Km
MAPK12 (p38

ZLYTE
4
3
3
1
Pass
Pass
0.87
PV3654/1140849
Pass


app
gamma)













Km
NEK7

ZLYTE
5
2
3
3
Pass
Pass
0.81
PV3833/34387
Pass


app














Km
PAK2 (PAK65)

ZLYTE
6
−1
3
7
Pass
Pass
0.87
PV4565/924347
Pass


app














Km
PIM2

ZLYTE
−1
7
3
7
Pass
Pass
0.76
PV3649/32930
Pass


app














Km
PRKACA (PKA)

ZLYTE
4
1
3
3
Pass
Pass
0.8
P2912/37377
Pass


app














Km
PRKG1

ZLYTE
2
5
3
3
Pass
Pass
0.9
PV4340/893283
Pass


app














Km
SGKL (SGK3)

ZLYTE
3
4
3
1
Pass
Pass
0.87
PV3859/38954
Pass


app














Km
AKT1 (PKB alpha)

ZLYTE
1
3
2
2
Pass
Pass
0.89
P2999/1159806
Pass


app














Km
AKT3 (PKB

ZLYTE
3
1
2
2
Pass
Pass
0.88
PV3185/28771
Pass


app
gamma)













Km
CAMK2A

ZLYTE
4
0
2
4
Pass
Pass
0.89
PV3142/28192
Pass


app
(CaMKII alpha)













Km
CDK5/p25

ZLYTE
3
1
2
2
Pass
Pass
0.79
PV4676/907645
Pass


app














Km
CLK3

ZLYTE
1
3
2
1
Pass
Pass
0.88
PV3826/939820
Pass


app















DDR1

LanthaScreen
3
2
2
1
Pass
Pass
0.95
PV6047/693053






Binding











Km
GRK6

ZLYTE
2
2
2
1
Pass
Pass
0.84
PV3661/37437
Pass


app















KIT T670E
y
LanthaScreen
2
2
2
1
Pass
Pass
0.9
PV6313/1575536






Binding











Km
MAP4K2 (GCK)

ZLYTE
6
−1
2
8
Pass
Pass
0.88
PV4211/748356
Pass


app














Km
MATK (HYL)

ZLYTE
1
2
2
0
Pass
Pass
0.83
PV3370/31553
Pass


app














Km
MST4

ZLYTE
2
3
2
0
Pass
Pass
0.76
PV3690/1205875
Pass


app














Km
PASK

ZLYTE
3
1
2
2
Pass
Pass
0.68
PV3972/762487
Pass


app














Km
STK23 (MSSK1)

ZLYTE
2
1
2
1
Pass
Pass
0.86
PV3880/1214750
Pass


app















TAOK3 (JIK)

LanthaScreen
3
1
2
2
Pass
Pass
0.86
PV3652/32935






Binding











Km
ALK

ZLYTE
4
2
1
5
Pass
Pass
0.86
PV3867/1542512
Pass


app















CDK8/cyclin C

LanthaScreen
0
3
1
4
Pass
Pass
0.94
PV4402/1177216






Binding











Km
CSNK1A1 (CK1

ZLYTE
2
1
1
1
Pass
Pass
0.84
PV3850/1004025
Pass


app
alpha 1)













Km
CSNK1E (CK1

ZLYTE
−2
4
1
6
Pass
Pass
0.75
PV3500/866725
Pass


app
epsilon)













Km
CSNK1G3 (CK1

ZLYTE
4
−2
1
6
Pass
Pass
0.85
PV3838/1140848
Pass


app
gamma 3)













Km
IGF1R

ZLYTE
1
2
1
2
Pass
Pass
0.78
PV3250/924345
Pass


app















MAP2K6 (MKK6)

LanthaScreen
−2
4
1
6
Pass
Pass
0.86
PV3318/884909






Binding











Km
MAPK14 (p38

ZLYTE
2
1
1
1
Pass
Pass
0.94
PV3304/1475037
Pass


app
alpha) Direct













Km
PTK2 (FAK)

ZLYTE
0
2
1
2
Pass
Pass
0.79
PV3832/1378055
Pass


app














Km
RPS6KA4 (MSK2)

ZLYTE
0
2
1
3
Pass
Pass
0.84
PV3782/990109
Pass


app














Km
STK24 (MST3)

ZLYTE
−5
8
1
14
Pass
Pass
0.7
PV3650/32932
Pass


app















TEC

LanthaScreen
0
2
1
2
Pass
Pass
0.93
PV3269/910411






Binding












WNK2

LanthaScreen
−4
5
1
9
Pass
Pass
0.86
PV4341/35976






Binding












CAMKK1

LanthaScreen
2
−1
0
2
Pass
Pass
0.8
PV4670/406782




(CAMKKA)

Binding












DDR2

LanthaScreen
0
1
0
2
Pass
Pass
0.94
PV3870/916220






Binding











Km
INSR

ZLYTE
−1
1
0
3
Pass
Pass
0.81
PV3781/1314127
Pass


app














Km
MAPK3 (ERK1)

ZLYTE
3
−2
0
5
Pass
Pass
0.86
PV3311/1255534
Pass


app














Km
MAPKAPK2

ZLYTE
0
−1
0
1
Pass
Pass
0.82
PV33I7/36559
Pass


app














10
PI4KA (PI4K

Adapta
3
−3
0
6
Pass
Pass
0.81
PV5689/1131829




alpha)













Km
PRKCD (PKC

ZLYTE
4
−4
0
8
Pass
Pass
0.73
P2293/39038
Pass


app
delta)














RIPK3

LanthaScreen
−1
1
0
2
Pass
Pass
0.84
PV6397/1610742






Binding











Km
SPHK1

Adapta
10
−9
0
19
Pass
Pass
0.77
PV5214/933639



app














Km
STK4 (MST1)

ZLYTE
0
0
0
0
Pass
Pass
0.73
PV3854/38395
Pass


app















CDK5 (Inactive)

LanthaScreen
1
−2
−1
3
Pass
Pass
0.68
PV6301/1576893






Binding











Km
DNA-PK

ZLYTE
2
−4
−1
7
Pass
Pass
0.69
PV5864/1594760
Pass


app














Km
DYRK4

ZLYTE
−2
0
−1
1
Pass
Pass
0.82
PV3871/37361
Pass


app














Km
EEF2K

ZLYTE
−1
0
−1
1
Pass
Pass
0.87
PV4559/1075327
Pass


app














Km
ERBB2 (HER2)

ZLYTE
0
−3
−1
3
Pass
Pass
0.74
PV3366/1185123
Pass


app














Km
PTK6 (Brk)

ZLYTE
−1
−1
−1
0
Pass
Pass
0.86
PV3291/1205876
Pass


app















STK32C (YANK3)

LanthaScreen
−4
3
−1
6
Pass
Pass
0.68
PV6409/1577045






Binding











Km
CAMK4

ZLYTE
−2
−2
−2
0
Pass
Pass
0.84
PV3310/1103512
Pass


app
(CaMKIV)














LATS1

LanthaScreen
−5
1
−2
6
Pass
Pass
0.62
PV6361/1575532






Binding











10
PIK3C2B (PI3K-

Adapta
3
−7
−2
9
Pass
Pass
0.87
PV5374/1223244




C2 beta)













Km
PRKCA (PKC

ZLYTE
0
−5
−2
6
Pass
Pass
0.71
P2232/38479
Pass


app
alpha)













Km
SRPK1

ZLYTE
−1
−2
−2
2
Pass
Pass
0.94
PV4215/1182336
Pass


app














Km
STK25 (YSK1)

ZLYTE
0
−4
−2
4
Pass
Pass
0.8
PV3657/33163
Pass


app















WNK3

LanthaScreen
−3
0
−2
2
Pass
Pass
0.83
PV4342/36047






Binding











Km
CSNK1D (CK1

ZLYTE
−1
−5
−3
5
Pass
Pass
0.83
PV3665/843704
Pass


app
delta)













Km
FGFR1

ZLYTE
−5
−2
−3
3
Pass
Pass
0.8
PV3146/28427
Pass


app














Km
GRK5

ZLYTE
5
−10
−3
15
Pass
Pass
0.82
PV3824/879275
Pass


app














Km
MAPKAPK3

ZLYTE
1
−8
−3
9
Pass
Pass
0.86
PV3299/38895
Pass


app














Km
PRKCE (PKC

ZLYTE
1
−6
−3
8
Pass
Pass
0.83
P2292/37717
Pass


app
epsilon)













Km
SRPK2

ZLYTE
−2
−4
−3
2
Pass
Pass
0.91
PV3829/900365
Pass


app















CDK11 (Inactive)

LanthaScreen
−1
−7
−4
7
Pass
Pass
0.71
PV6283/1576889






Binding











Km
GRK4

ZLYTE
−4
−5
−5
1
Pass
Pass
0.86
PV3807/618977
Pass


app














Km
PIK3CA/PIK3R1

Adapta
−5
−4
−5
1
Pass
Pass
0.79
PV4788/616250



app
(p110 alpha/p85














alpha)













Km
PKN1 (PRK1)

ZLYTE
−6
−4
−5
2
Pass
Pass
0.68
PV3790/356552
Pass


app














Km
PRKCG (PKC

ZLYTE
−9
−1
−5
8
Pass
Pass
0.73
P2233/39126
Pass


app
gamma)













Km
CSNK1G1 (CK1

ZLYTE
−14
2
−6
16
Pass
Pass
0.77
PV3825/34360
Pass


app
gamma 1)













Km
GSG2 (Haspin)

Adapta
7
−20
−6
26
Pass
Pass
0.71
PV5708/869949



app














Km
ACVR1B (ALK4)

ZLYTE
−10
−4
−7
6
Pass
Pass
0.9
PV4312/919690
Pass


app














Km
PIK3C3 (hVPS34)

Adapta
−5
−9
−7
4
Pass
Pass
0.91
PV5126/853378



app














Km
PIK3C2A (PI3K-

Adapta
−7
−9
−8
2
Pass
Pass
0.88
PV5586/1123632



app
C2 alpha)













10
SPHK2

Adapta
−16
−2
−9
14
Pass
Pass
0.56
PV5216/1296957



Km
CSNK1G2 (CK1

ZLYTE
−7
−16
−11
9
Pass
Pass
0.79
PV3499/1120155
Pass


app
gamma 2)













Km
PRKCQ (PKC

ZLYTE
−6
−17
−12
11
Pass
Pass
0.76
P2996/26231
Pass


app
theta)













100
BRAF

ZLYTE
−18
−10
−14
8
Pass
Pass
0.83
PV3848/1258788
Pass


Km
PRKCZ (PKC zeta)

ZLYTE
−18
−16
−17
2
Pass
Pass
0.7
P2273/31602
Pass


app






















TABLE S5-2










fold selectivity
fold selectivity


Technology
ATP
IC50 (nM)
Hillslope
R2
(TBK1)
(IKBKE)





















ZLYTE
Km app
1.04
1.12
0.9966
1.0
0.2


LanthaScreen

2.71
0.8
0.9917
2.6
0.5


Binding








LanthaScreen

4.35
1.27
0.9998
4.2
0.8


Binding








ZLYTE
Km app
5.59
1.06
0.9955
5.4
1.0


ZLYTE
Km app
14.2
0.55
0.9914
13.7
2.5


LanthaScreen

14.8
1.25
0.9989
14.2
2.6


Binding








LanthaScreen

30.9
0.84
0.9797
29.7
5.5


Binding








LanthaScreen

31.5
0.88
0.9956
30.3
5.6


Binding








Adapta
Km app
34.9
0.99
0.9945
33.6
6.2


ZLYTE
Km app
35.1
1
0.9994
33.8
6.3


ZLYTE
Km app
35.8
1.11
0.9993
34.4
6.4


ZLYTE
Km app
41.5
1.49
0.9978
39.9
7.4


ZLYTE
Km app
45.6
1.01
0.9981
43.8
8.2


ZLYTE
Km app
47.7
0.84
0.9995
45.9
8.5


ZLYTE
Km app
55
0.96
0.9993
52.9
9.8


ZLYTE
Km app
59
0.69
0.9971
56.7
10.6


LanthaScreen

74.1
1
0.9972
71.3
13.3


Binding








LanthaScreen

78.7
0.86
0.9971
75.7
14.1


Binding








Adapta
Km app
80.6
1
0.9983
77.5
14.4


ZLYTE
Km app
81.3
1.12
0.9991
78.2
14.5


LanthaScreen

81.6
1.42
0.9789
78.5
14.6


Binding








ZLYTE
Km app
90.9
1.11
0.9974
87.4
16.3


LanthaScreen

104
1.22
0.997
100.0
18.6


Binding








LanthaScreen

156
0.95
0.9986
150.0
27.9


Binding









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EQUIVALENTS AND SCOPE

While several inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/ac used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.


All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.


All references, patents, and patent applications disclosed herein are incorporated by reference with respect to the subject matter for which each is cited, which in some cases may encompass the entirety of the document.


The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”


The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.


As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.


As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.


It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.


In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. It should be appreciated that embodiments described in this document using an open-ended transitional phrase (e.g., “comprising”) are also contemplated, in alternative embodiments, as “consisting of” and “consisting essentially of” the feature described by the open-ended transitional phrase. For example, if the disclosure describes “a composition comprising A and B,” the disclosure also contemplates the alternative embodiments “a composition consisting of A and B” and “a composition consisting essentially of A and B.”

Claims
  • 1. A method for evaluating primary patient-derived tumor cell spheroids in a three-dimensional microfluidic device, the method comprising: obtaining primary patient-derived tumor cell spheroids from an enzyme treated tumor sample,suspending a first aliquot of the primary patient-derived tumor cell spheroids in a biocompatible gel,suspending a second aliquot of the primary patient-derived tumor cell spheroids in a biocompatible gel,placing the first aliquot of the primary patient-derived tumor cell spheroids in the biocompatible gel in a first three-dimensional microfluidic device,contacting the first aliquot with a first fluorophore dye selective for dead cells, the first fluorophore dye emitting fluorescence at a first wavelength when bound to a dead cell,contacting the first aliquot with a second fluorophore dye selective for live cells, the second fluorophore dye emitting fluorescence at a second wavelength different from the first wavelength when bound to a live cell,quantitating total fluorescence emitted by each of the first and second fluorophore dyes in primary patient-derived tumor cell spheroids in the first aliquot within the first three-dimensional microfluidic device,placing the second aliquot of the primary patient-derived tumor cell spheroid in the biocompatible gel in a second three-dimensional microfluidic device,contacting the second aliquot with the first fluorophore dye,contacting the second aliquot with the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye,quantitating total fluorescence emitted by each of the first and second fluorophore dyes in primary patient-derived tumor cell spheroids in the second aliquot within the second three-dimensional microfluidic device, andassessing a ratio of live to dead cells in each aliquot based on the total fluorescence quantitated in each three-dimensional microfluidic device.
  • 2. The method of claim 1, further comprising: culturing the second aliquot of the primary patient-derived tumor cell spheroids in the second three-dimensional microfluidic device in the presence of a first test compound;isolating RNA from the first aliquot and second aliquot of primary patient-derived tumor cell spheroids after total fluorescence emitted is measured; andanalyzing gene expression of the first aliquot and second aliquot of primary patient-derived tumor cell spheroids based on the isolated RNA.
  • 3. The method of claim 2, wherein the second aliquot is cultured in the presence of the first test compound and a second test compound during the culturing step.
  • 4. The method of claim 3, wherein the second aliquot is further cultured in the presence of a third and/or fourth test compound during the culturing step.
  • 5. The method of claim 3, wherein the first and/or second test compound is a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof.
  • 6. The method of claim 3, wherein the first test compound is an immune checkpoint inhibitor and the second test compound is a small molecule compound.
  • 7. The method of claim 6, wherein the small molecule compound is a TBK-1 inhibitor.
  • 8. The method of claim 3, wherein the first and/or second test compound is a chemical from a test compound library.
  • 9. The method of claim 3, wherein the first test compound is an immune checkpoint inhibitor and the second test compound is a chemical from a test compound library.
  • 10. The method of claim 2, further comprising: culturing a third aliquot of the primary patient-derived tumor cell spheroids in a third three-dimensional microfluidic device in the presence of the first test compound and a second test compound;isolating RNA from the third aliquot of primary patient-derived tumor cell spheroids; andanalyzing gene expression of the third aliquot of primary patient-derived tumor cell spheroids based on the isolated RNA.
  • 11. The method of claim 10, wherein the third aliquot is further cultured in the presence of a third and/or fourth test compound during the step of culturing the third aliquot.
  • 12. The method of claim 2, wherein the RNA is isolated from the supernatant or from the cell culture of the first aliquot and second aliquot of the primary patient-derived tumor cell spheroids.
  • 13. The method of claim 2, wherein the gene expression of the first aliquot and second aliquot of the primary patient-derived tumor cell spheroids is analyzed by performing RNA sequencing (RNA-seq) on the isolated RNA.
  • 14. The method of claim 2, wherein the primary patient-derived tumor cell spheroids are from an enzyme treated tumor sample derived from a patient.
  • 15. The method of claim 2, wherein the first test compound is an immune modulator.
  • 16. The method of claim 15, wherein the immune modulator comprises immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of CTLA-4, PD-1, PD-L1, TIM3, LAGS, B7-H3 (CD276), B7-H4, 4-1BB (CD137), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GALS, A2aR, and VISTA.
  • 17. The method of claim 16, wherein the immune checkpoint inhibitor inhibits PD-1.
  • 18. The method of claim 2, wherein the first and/or second aliquots are further cultured in the biocompatible gel.
  • 19. The method of claim 18, wherein the first and/or second aliquots are suspended in the biocompatible gel in a fluid channel of the three-dimensional microfluidic device before culturing.
RELATED APPLICATIONS

This application is a continuation-in-part of International Application No. PCT/US2018/025390, filed Mar. 30, 2018, and entitled “METHODS FOR EVALUATING TUMOR CELL SPHEROIDS USING 3D MICROFLUIDIC CELL CULTURE DEVICE,” which claims the benefit of U.S. provisional application No. 62/480,192, filed on Mar. 31, 2017, the entire contents of which is incorporated by reference herein.

FEDERALLY SPONSORED RESEARCH

This invention was made with government support under K08 CA138918-01A1 and R01 CA190394-01 awarded by the National Institutes of Health. The government has certain rights in the invention.

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Related Publications (1)
Number Date Country
20190112666 A1 Apr 2019 US
Provisional Applications (1)
Number Date Country
62480192 Mar 2017 US
Continuation in Parts (1)
Number Date Country
Parent PCT/US2018/025390 Mar 2018 US
Child 15999230 US