Patent Application
20230287316
This disclosure relates to a modular microphysiological system including two or more wells having its own microenvironment or tissue-specific niche and bioengineered human tumors cultured in the integrated modular microphysiological system.
This invention was made with government support under grants EB025765 and EB027062, and awarded by the National Institutes of Health. The government has certain rights in the invention.
Current projections show that 40% of men and women can be diagnosed with cancer within their lifetime. Moreover, despite major advances in diagnosis and therapy, many patients do not respond or relapse after treatment. For example, cancer drugs, such as endostatin, have yielded promising results in mice, such as full tumor elimination when used alone, to subsequently show only minimal results in human patients. On the other hand, tamoxifen, a selective estrogen-receptor modulator, has been successfully used to treat breast cancer for years. However, if its predisposition to cause liver tumor in rats had been discovered in preclinical tests, the drug would have been eliminated during developmental testing. Other drugs have passed preclinical trials and then withdrawn, due to the side effects detected only during clinical trials or even after entering the market and being used by large numbers of patients. This is particularly true for cardiac side effects, as successful preclinical and clinical screening still allowed cardiotoxic drugs to enter the market. Rofecoxib, a COX-2 inhibitor used as an analgesic and antiinflammatory drug, was approved by the FDA in 1999 and then removed from market in 2004 because of side effects not seen in preclinical and clinical trials. Unfortunately, by that time, the drug had already caused an estimated 140,000 heart attacks associated with 60,000 deaths. Results like these illustrate the need for more predictive models of drug safety and efficacy, which would enable thorough testing of cardiac side effects. While regulatory changes have prevented drugs causing lethal arrhythmia from reaching the market, the current screening models are often oversensitive to proarrythymic side effects and result in elimination of numerous drugs. To date, as high as 60% of new drugs test positive for proarrhythmic events, based on assessing the rapid component of the delayed rectifier potassium current (IKr) for its blocking liability. The false positives are responsible for preventing the potentially lifesaving compounds from reaching the market.
Meanwhile, metastatic progression - a major determinant of poor outcome in treatment—is difficult to study both in patients and in existing tumor models. Cell lines present significant mutational and transcriptional drifts, abnormal ploidy, and loss of heterogeneity, compared to tumor cells in patients. These differences are compounded by poor recapitulation of the original pathophysiological milieu and growth conditions, including 2D vs. 3D-growth, lack of extracellular matrix (ECM), lack of surrounding cells (stromal, vascular, immune), as well as lack of molecular signals and physical constraints. Indeed, tumorigenesis strongly depends on cancer cell interactions with the environment. Animal models provide a more physiological environment, but are laborious, expensive, and do not support fine-grain control of exogenous factors. Over the last decade, bioengineering has entered the field of cancer research, by introducing more physiologically relevant 3- dimensional (3D) models of cancer growth: tumor spheroids and organoids, vascularization and scaffolds. These models fail to recapitulate critical aspects of human pathophysiology, such as the interactions of the tumor compartment with other cells (paracrine interactions) and organs (endocrine interactions). In addition, no currently available bioengineered model is able to model the full complexity of tumor progression, from primary tumor growth to intravasation in the blood stream, and seeding a distal organ site. Indeed, a human tissue model that would accurately model these aspects of metastatic progression would be transformative to cancer research. There is, thus, a need to understand human biology and system wide pathology - so we can predict which drugs can work for which patients before clinical trials. While this need is partly addressed using in vitro and animal models for most therapeutic areas, their lack of utility in modeling systemic diseases significantly prohibits the development of drugs for many diseases affecting more than one tissue system.
What is needed is a preclinical model that could more accurately predict both the efficacy and the safety of new drugs in humans that could enable more reliable drugs to progress through the developmental pipeline. While the development of human induced pluripotent stem (iPS) cells provides a human cell source for preclinical testing, the relative immaturity and the lack of biological fidelity limit their use.
Generally, in one aspect of the disclosed subject matter provides a highly advanced “cancer patient on a chip” model that uses vascular perfusion to physiologically integrate bioengineered human tumors with the target tissues to which they preferentially metastasize (lung, liver, bone), all derived from same-patient cells. In one aspect the subject matter provides to a platform with bioengineered human tissue niches linked by vascular perfusion can recapitulate effects and biomarkers of multi-organ drug toxicities. The platform allows systemic level tissue communication, maintains the engineered tissue phenotypes, and can thereby facilitate clinical translation. The platform provides a human, systemic model of patient specific disease “on-a-chip” or “in-a-dish” - benefiting drug developers, patients, clinicians, and the healthcare economy.
The disclosure provides a method for co-culturing two or more differentiated cell phenotypes, the method comprising
Embodiments include the following, alone or in any combination:
The method wherein the differentiated phenotypes are selected from the group consisting of heart, liver, bone, lung and skin phenotypes.
The method wherein the differentiated phenotypes are co-cultured for up to 4 weeks.
The method further comprising assessing the fidelity of the co-cultured phenotypes by proteomic analysis.
The method further comprising circulating a test compound through the vascular network.
The method wherein the test compound comprises a pharmaceutical agent.
The method wherein the pharmaceutical agent comprises dofetilide, epinephrine or doxorubicin
In another aspect, the present disclosure is directed to a composition comprising bioengineered tumor. The bioengineered tumor comprises osteosarcoma cells derived from a patient. In another embodiment, the bioengineered tumor comprises breast adenocarcinoma cells derived from a patient.
The present disclosure is also directed to a composition comprising at least one host tissue.
The present disclosure is also directed to a system of bioengineered tumor and at least one host tissue.
In an embodiment, the at least one host tissue comprises bone, liver, lung, and heart tissue, wherein the bone, liver, lung, and heart tissue are separated by an endothelial barrier. The endothelial barrier is exposed to flow/shear stress.
A detailed description of various aspects, features and embodiments of the subject matter described herein is provide with reference to the accompanying drawings, which are briefly described below. The drawings are illustrative and are not necessarily drawn to scale, with some components being exaggerated for clarity. The drawings illustrate various aspects and features of the present subject matter and may illustrate one or more embodiment(s) or example(s) of the present subject matter in whole or in part. Together with the description, the drawings serve to explain the principles of the disclosed subject matter.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only, and are not restrictive of the invention, as claimed. In this description, the use of the singular includes the plural, the word “a” or “an” means “at least one,” and the use of “or” means “and/or,” unless specifically stated otherwise. Furthermore, the use of the term “including,” as well as other forms, such as “includes” and “included” is not limiting. Also, terms such as “element” or “component” encompass both elements or components comprising one unit and elements or components that comprise more than one unit unless specifically stated otherwise. The use of the term “or” in the claims and the present disclosure is used to mean “and/or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive.
Use of the term “about”, when used with a numerical value, is intended to include +/-10%. For example, if a number of amino acids is identified as about 200, this would include 180 to 220 (plus or minus 10%).
The terms “patient,” “individual,” and “subject” are used interchangeably herein, and refer to a mammalian subj ect to be treated, with human patients being preferred. In some cases, the methods of the invention find use in experimental animals, in veterinary application, and in the development of animal models for disease, including, but not limited to, rodents including mice, rats, and hamsters, and primates.
Bioengineered tissue systems offer a new paradigm for modeling human pathophysiology and testing drug efficacy and safety. However, establishing physiological communication between multiple tissues while also preserving their individual phenotypes is a major challenge due to the conflicting requirements for maintaining each tissue-specific regulatory niche. We describe herein a biomimetic InterOrgan bioreactor system in which each tissue can be cultured in its own specific optimized environment within the system. Each environment is a specific tissue niche that is separated by a selectively permeable endothelial barrier from recirculating flow containing circulating monocytes. The specific tissues, however, are linked by vascular perfusion in the system. The tissues maintain their molecular, structural and functional phenotypes over four weeks of culture. The system, thus, defines a plurality of bioengineered human tissue niches that are linked by vascular perfusion to enable recapitulated effects and biomarkers of multi-organ drug toxicities. In the system described herein, multiple tissues can be connected without sacrificing their individual biological fidelity. The tissues cultured in this manner recapitulate the clinically observed multi-organ toxicity of doxorubicin, and allow identification of miRNA biomarkers of cardiotoxicity. Overall, the bioreactor system (also referred to herein as InterOrgan platform) allows systemic level tissue communication, maintains the engineered tissue phenotypes, and can thereby facilitate clinical translation.
Other approaches are unable to maintain individual tissue health and functionality/gene expression/proteomics/drug responses when connecting multiple tissues together. For example, current methods rely either on transferring supernatant between tissues or the use of “common media” containing the factors required by all tissues. In contrast, the organs in our body maintain their own environments while being linked by vasculature lined with selectively permeable endothelium.
The system enables: 1) maintaining biological fidelity of tissues (engineered or patient derived) over long and short term culture times, 2) maintaining tissues in their niche while allowing communication via secreted factors, 3) allow cells and biologics (secreted factors, exosomes) to move between compartments, 4) allow circulating cells to preferentially extravasate from the vasculature into tissues as biologically appropriate (metastasis to expected tissue site, immune infiltration into damaged tissues, cell therapy), 5) drug studies in the integrated platform that has more clinical relevance as an integrated system versus the sum of their parts, qualifying its use as a clinical human correlate for disease modeling and drug testing.
All of the above can be done in a patient specific manner, using patient derived cells in healthy and diseased states with ability to also include genetically engineered cells of induced disease or health.
The system’s versatility lies in connecting millimeter-sized engineered tissues via vascular perfusion, with each tissue in its own optimized microenvironment, while still allowing for natural, selectively permeable cytokine and cellular cross-talk across the vascular endothelium separating the tissue and perfusion spaces. In one aspect, the system is modular and various different tissues, organoids, or patient biopsies can be combined as desired. In one aspect, the system of the present disclosure enables multiple tissues to be plugged directly into a platform of the system configured to receive the tissues, to enable multi-tissue studies in a way that tissues are connected through a vascular network but maintain their own tissue-specific niche for enhanced functionality, transcriptomics, and clinically relevant drug responses. Additionally, the ability to include human immune interactions and cellular movement from one compartment to another, as within the human body, is a major innovation facilitating the platforms translational impact. I
Referring to
Tissue cross-talk between the liver 101a, heart 101b, bone 101c and skin 101d is depicted in
In another aspect, the bioreactor system, as shown in
In one embodiment, as shown in
Referring now to
In
In another embodiment, a configurable, modular kit 200 as shown in
In some embodiments, the system is designed for real-time readouts, and can be manufactured of biocompatible, inert materials. The individual culture chambers could be connected in any desired order to model different contexts (
In another embodiment, referring to
In some embodiments, system 300 may include an onboard pump 400 as shown in
Referring to
Referring back to
In some embodiments, the vascular barrier 105, 205, 305 comprises a mesh insert coated with endothelial cells and supporting mesenchymal stromal cells (MSCs) serving as pericytes. The tissue specific niche defined by the tissue culture chambers vascular is designed to enable crosstalk of drugs, nutrients, secreted factors and cells via pulsatile circulatory flow via pump (e.g., 218400). Referring back to
Tissue maturity, a necessary condition for recapitulating physiological tissue responses in an adult human, has been notoriously difficult to achieve using iPSC-derived cells. Therefore, multi-cellular, millimeter-sized human tissues were formed and matured over 4-6 weeks of culture before being transferred into the system, allowing different maturation regimens and culture durations and a quality control step before integration.
For example, adult-like human iPSC-derived cardiac muscle displayed mature ultrastructure, metabolism and calcium signaling compared to non-matured controls.
Maturation appeared to be regulated by myocardin, GATA4 and HAND2 that activated genes related to adult-like cardiac function (
The system described herein containing tissues connected by vascular perfusion and endothelial barrier between tissues and perfusate (InterOrgan) was systematically compared to the identical system without endothelial barriers (Mixed conditions corresponding to the co-culture in common medium), and tissues cultured in isolation, without perfusion (Isolated condition, benchmark for phenotype stability) over 4 weeks. In the InterOrgan platform, the selectively permeable endothelial barriers enabled tissue communication while preserving tissue-specific biological fidelity. In contrast, the Mixed condition normalized the medium composition throughout all compartments (Table 1 below). This condition failed to preserve tissue-specific structural, functional, and molecular markers, demonstrating the need for maintaining tissues in their individual niches. Thus, the system embodied and claimed herein exhibited unexpected superior results.
Overall, each tissue in the InterOrgan bioreactor system group, and markedly exceeded the corresponding properties of the Mixed group (
By whole proteome analysis, we detected thousands of proteins expressed in each engineered tissue (heart: ~6,000; liver: ~4,000; bone: ~5,000; skin: ~2,000), and differentially expressed between the InterOrgan and Mixed media conditions (
Through Ingenuity Pathway Analysis (IPA) and gene ontology (GO), we identified common genes expressed in all tissues among the three conditions (InterOrgan, Mixed, Isolated) (
Tissue-specific proteins expressed in adult and engineered tissues were identified and tertiled using the Human Protein Atlas. All engineered tissues in the InterOrgan platform matched well to the published correlates from adult donors (
Having established the maintenance of tissue-specific functionality along with tissue cross-talk over 4 weeks of culture, the system described herein provided a high-fidelity in vitro mimic of human physiology for drug testing or disease modeling. To mimic injection, drugs were delivered from the reservoir to the tissues by vascular circulation. The platform incorporated first-pass liver metabolism and on- and off-target drug effects on all tissues.
Addition of dofetilide, a selective hERG K+ channel blocker, decreased beat rate of cardiac muscle and metabolic drug clearance in the liver (
The InterOrgan platform allows screening for both on-target and off-target drug effects. We chose to demonstrate the off-target effects of a common anti-cancer therapeutic doxorubicin (Dox), which shows cardiotoxicity in subsets of patients, limiting its broad clinical use.
Treatment with 30 µM Dox, corresponding to the clinically administered cumulative dosage shown to induce cardiotoxicty, was delivered to tissues in the InterOrgan platform through the vascular channel and compared against the Isolated condition (
We also evaluated miRNAs as early biomarkers of Dox cardiotoxicity, as suggested by recent clinical studies that identified 17 miRNA that were differentially expressed in pediatric cancer patients treated with Dox. We used the GeneChip™ miRNA 4.0 Array (ThermoFisher) to measure differential expression of miRNAs in heart tissues following Dox treatment. Differential miRNA expression in the InterOrgan platform more closely matched the published data (
We then recapitulated the differential activities of miRNAs observed in pediatric study and clinical study in adults, by assessing enrichment of their repressed targets in differentially expressed genes, following Dox treatment. miR-6192 did not have enough target for enrichment analysis. Differential expressions of all other miRNAs were highly significant in the InterOrgan platform, based on Normalized Enrichment Scores (NES), showing activity consistent with published clinical results for 20 out of the 22 miRNAs (
In contrast, while all miRNAs showed significant differences in the Isolated platform, only 12 were in agreement with published results, while 10 showed opposite differential activity (
Indeed, in adult patients, miR-1273a was reported as a biomarker of high centrality for Doxorubicin-induced heart failure, with an “Energe” of -31.32. Consistently, dramatic reductions in the fold change and activity were detected in the InterOrgan platform (FC = -30.6, NES = -21.31, p = 2.3E-22), while the Isolated platform showed statistically significant opposite behavior, inconsistent with published data (FC = +1.32, NES +1.21). Taken together, these data show that the InterOrgan platform outperformed the Isolated culture, as evidenced by higher enrichment scores and fold changes consistent with those seen clinically (
Other cell types can be cultured in the platform, for example bone marrow models that include more cell types. This model may also be used to study a variety of different genetic blood disorders. Other applications include: Systemic disease modeling, cancer metastasis, human models of aging, human immune models/inflammation models, human fibrosis models, potency assays for biologics during drug development and manufacturing, bioreactor to grow engineered tissues/organs and cells for regenerative medicine, patient-specific avatars for patient centered modeling of health and disease risks/treatment valuation, human infection model, bioreactor for maintenance of engineered tissues, bioreactor for maturation of engineered tissues and microphysiological system for long-term disease modeling. The InterOrgan system could be used to physiologically mature tissue specific iPS cells for downstream use in regenerative medicine.
In summary, microphysiological systems containing human tissues bioengineered from iPS cells have long promised advantages towards modeling human physiology in vitro, as compared to cell monolayers and animal models. Although tissues in isolation can recapitulate some aspects of physiological function, studies of multi-organ, systemic interactions require communication of engineered tissues. The InterOrgan bioreactor system maintains the tissue and vascular niches that preserve mature tissue phenotypes and facilitate tissue communication by vascular perfusion, while separating the interstitial and intravascular compartments via a selectively permeable endothelial barrier. The platform recapitulated clinically observed off-target effects of several drugs, and enabled identification of early miRNA biomarkers of drug toxicity.
The bioreactor system described herein, interchangeably referred to as “The InterOrgan platform” or “InterOrgan bioreactor system,” is designed to support the culture and communication of multiple types of engineered tissues. Each tissue is maintained within its own optimal medium and communication between tissues occurs via exchange to a recirculating shared vascular medium across an endothelium that serves as a selectively permeable barrier. The platform is sized to fit onto a standard glass microscope slide. In some embodiments, it includes four culture chambers that can each contain up to 1.5 mL of tissue specific medium, and a reservoir for access to the recirculating vascular medium. Two ports and a channel are included to enable recirculating flow of the shared vascular medium via a pump. A plate or a glass slide establishes the bottom boundary of the flow channel and enables real time imaging. Inserts for each chamber include a porous nylon mesh that serves as a substrate for the endothelial layer. The mesh pore size (20 µm) was selected to ensure the endothelial barrier is the primary regulator of exchange of various factors or cells.
System fabrication: The reservoir and flow channel component of the platform were fabricated from polysulfone (McMaster-Carr) using a 3-axis CNC milling machine (Haas OM2). The clamps and tubing transfer lid were machined in the same manner from polycarbonate (McMaster-Carr). The mesh barrier inserts were made via an overmolding process using an injection molding machine (A.B. Plastic Injectors, AB-200) and polypropylene thermoplastic (Flint Hills Resources P9M7R-056). An aluminum tool (alloy 7075, McMaster-Carr) was CNC machined for this process and a 20 um nylon net filter (Millipore) was laser cut (ULS VersaLaser 3.50) into 11 mm circles using a 30 W CO2 laser. The cut nylon filters were clamped into a multicavity aluminum tool, and polypropylene was injected to form the structure of the mesh insert. An o-ring was installed around the structure to provide a seal (Viton, dash 011, 60A durometer, McMaster-Carr).
The remaining components of the platform include: 100 mm cell culture dish, 1×25×75 mm glass slide, Pharmed tubing (1/16″ inner diameter, Cole-Parmer), peristaltic pump tubing (2.29 mm inner diameter, Pharmed, Cole-Parmer), 3-way stopcock valve (Smiths Medical ASD MX9311L), luer elbow connectors (Cole-Parmer EW-45501-84), and a peristaltic pump (Cole-Parmer EW-07557-00 and EW-07519-25). Connections between tubing components were made with appropriately sized barbed luer connectors (polypropylene, McMaster-Carr). Post-fabrication cleaning was done via ultrasonic cleaning and autoclaving on a wet cycle.
Platform assembly: Platform components were removed from sterile packaging in a biosafety cabinet and assembled sterily. A standard glass microscope slide was placed onto the bottom surface of the polysulfone reservoir flow array using a silicone o-ring. Two polycarbonate clamps are press-fit around the slide, silicone o-ring, and platform chambers to provide a compression seal. Luer elbow components are press-fit into luer-taper ports at the top of the platform. A loop of Phramed tubing was attached to a peristaltic section and 3-way valve, to connect the luer elbows at the inlet and outlet ports. The entire assembly was inserted into a 100 mm petri dish and a tubing-transfer lid was placed on top. Tubing is installed into the slots of the lid, while a standard lid is used to protect the platform from the above. With the tubing assembly completed, endothelial medium was infused via the 3-way valve to prime the flow loop and remove air. Once primed, the endothelialized mesh inserts were installed into each tissue well, and the assembly was then moved to an incubator and connected to a peristaltic pump.
Additional information about the components and assembly of the platform are in International Patent Application serial number PCT/US2019/43722, incorporated in its entirety herein.
System validation: The InterOrgan systems were autoclave-sterilized as individual components and then assembled in a biosafety cabinet. The platforms were primed via syringe with 12 mL of endothelial media through a luer-lock and 3-way stopcock valve. The vascular flow rates corresponded to hydrodynamic shear stresses of 1-5 dynes/cm2, with potential to extend to 10 dynes/cm2, if needed. Endothelial barrier was responsive to physiologic vasoactive agents such as thrombin. Platforms were connected to a peristaltic pump and operated at a shear stress of 1.88 dynes/cm2. 1.5 mL of tissue specific media was added to the corresponding tissue chamber.
Engineered tissue designs: Cardiac tissues were formed from hiPSC-derived cardiomyocytes with supporting human fibroblasts in fibrin matrix stretched between two auxotonic flexible pillars, and electromechanically matured at an increasing intensity. Liver tissues were formed from aggregates of hiPSC-derived hepatocytes and supporting human fibroblasts that were encapsulated in fibrin hydrogel. Bone tissues were made by seeding human bone marrow-derived mesenchymal stromal cells (MSCs) in a decellularized bovine bone matrix scaffold and inducing the cells towards the osteoblastic phenotype; to recapitulate osteolytic bone, primary CD14+ monocytes were seeded into the osteoblastic bone and differentiated into osteoclasts, thereby forming mature bone with matrix secretion and resorption. Skin tissues were formed by seeding human dermal fibroblasts in layered 3D collagen matrix and then adding human keratinocytes onto the matrix. Skin tissues were cultured at air-liquid-interface to form matured stratified epidermis.
Platform validation over 4 weeks of culture: To validate the platform, we studied three different configurations: (1) “InterOrgan” system (n = 12), where the multi-chamber platforms contain endothelialized mesh inserts to separate tissue-specific niches from perfusion flow; (2) “Mixed″system, containing mesh inserts without endothelial barrier, allowing tissue and vascular culture media to mix rapidly, a condition equivalent to the use of common media for all tissues (n =6); and (3) “Isolated” system (n = 6), with each tissue cultured separately in the same volume of tissue-specific medium (~1.5 mL). Conditions (1) and (2) had a perfusate flow channel running on a peristaltic pump at hydrodynamic shear at the mesh of1.88 dynes/cm2. Monocytes (50,000 CD14+ cells) were added into the reservoir for conditions (1) and (2) at t = 0 and 14 days; recirculating flow was maintained for 28 days. Every other day, 1 mL of medium was changed in each culture chamber and in the vascular reservoir; medium samples were immediately frozen at -20° C. for subsequent analysis. Similarly, 1 mL of media from Isolated tissues was taken and replenished every other day. At the end of the 4-week study, tissues were harvested and sectioned for proteomics (and immediately flash frozen), and histology (and immediately fixed in 4% paraform aldehyde).
Doxorubicin-induced toxicity (
In addition to the tissues described below, one of ordinary skill in the art would appreciate that other tissues and fibroblasts may be used. For example, cardiac or iPS fibroblasts may be used instead of dermal fibroblasts. Further iPS derived versions of tissues are within the scope of the invention.
Heart: Cardiac tissues were formed and matured as described previously. Briefly, a ratio of 75% iPSC-derived cardiomyocytes were combined with 25% supporting normal human dermal fibroblasts (NHDF, Lonza) in 84 µL of 33.3 mg/mL human fibrinogen (Sigma-Aldrich, F3879) and crosslinked with 16 µL of 100 U/mL thrombin from human plasma (Sigma -Aldrich, T6884) to form a hydrogel between two flexible pillars. After 20 minutes of crosslinking at 37° C. in 5% CO2, cardiac media was added (RPMI 1640 (Thermo Fisher Scientific, 11875-093), B27 supplement (serum free, Thermo Fisher Scientific, 17504044), ascorbic acid (Sigma-Aldrich, A8960) and penicillin/streptomycin (Gibco by Life Technologies, 15070063)) supplemented with 0.02 mg/mL of aprotinin (Sigma-Aldrich, A3428). After 1 week of compaction, cardiac tissues were transferred to the maturation platform where they were subjected to electromechanical conditioning at a frequency increasing from 2 Hz to 6 Hz (biphasic stimulation, 2 ms pulse duration, 4.5 V/cm field intensity).
Liver: Human iPSC-derived hepatocytes were purchased from Cellular Dynamics International (CDI, iCell Hepatocytes 2.0) and thawed at room temperature. An AggreWell plate with 400 µm microwells (STEMCELL Technologies) was prepared according to the manufacture’s protocol. Hepatocytes (10 million cells) were mixed with NHDF (10 million cells) in hepatocyte culture medium (HCM, Lonza). The dual cell suspension was then added to 20 wells (approximately 500,000 hepatocytes and 500,000 NHDF in each well) with 2 mL of HCM per well). After 48 hours of culture at 37° C. and 5% CO2, the formed cell aggregates were harvested and encapsulated in a fibrin hydrogel formed from fibrinogen (84% of total volume) and thrombin (16%). The cells in hydrogel were placed into 48-well tissue culture-treated cell culture plates (Corning), using 200 µL per well. The hydrogel was allowed to cross-link in a cell culture incubator for 20 minutes, after which 1 mL hepatocyte media supplemented with 1 mg/mL of aprotinin were added. Tissues were allowed to polymerase for at least 12 hours before being used in experiments.
Bone: Bovine calf metacarpals were purchased in bulk and stored at -40° C. (Lampire Biological Laboratories, #19D24003). A band saw was used to cut approximately 4 cm tall trabecular bone sections from the distal end of metacarpal. A CNC Milling machine was then used to generate bone cores with a cross section of 4 mm × 8 mm that were cut into 1 mm thick sections using an IsoMet low speed watering saw. Each section (4 mm wide × 8 mm long × 1 mm thick), was decellularized using our previously established protocols, to remove all cellular material while preserving the bone matrix composition and architecture. Bone scaffolds were processed in batch by following the following step-wise protocol on an orbital shaker: (i) PBS with 0.1 % EDTA (w/v) for 1 hour at room temperature; (ii) 10 mM tris, 0.1% EDTA (w/v) in DI water overnight at 4° C.; (iii) 10 mM Tris, 0.5% sodium dodecyl sulfate (w/v) in DI water for 24 hours at room temperature; (iv) 100 U/ml DNase, 1 U/ml RNase, 10 mM Tris in DI water for 6 hours at 37° C. The resulting bone matrix scaffolds were lyophilized and weighed to ensure that each piece had an appropriate matrix density for cell seeding (12 - 18 mg per scaffold). For sterilization, bone scaffolds were subjected to 70% ethanol treatment overnight under ultraviolet light, and then incubated in DMEM overnight.
Bone-marrow derived MSCs (Lonza) were expanded and seeded into the bone matrix scaffolds using 4 × 105 cells per scaffold suspended in 40 µL of medium (DMEM supplemented with 10% (v/v) HyClone FBS, 1% penicillin/streptomycin, and 1 ng/mL of basic fibroblast growth factor b, bFGF), according to established protocols [8]). The cells were allowed to attach for 2 hours, and then supplemented with additional medium (DMEM supplemented with 10% (v/v) HyClone FBS, 1% penicillin/streptomycin, and 1 ng/mL of basic fibroblast growth factor b, bFGF) overnight. The following day, osteogenic differentiation was initiated by changing the media to osteogenic media consisting of low glucose DMEM supplemented with 1 µm dexamethasone (Sigma Aldrich), 10 mm β-glycerophosphate (Sigma Aldrich), and 50 µm L-ascorbic acid-2-phosphate (Sigma Aldrich). Each scaffold was incubated in 4 mL of osteogenic media, with media changes 3 times a week, for 3 weeks, allowing for the MSCs to differentiate into functional, maturing osteoblasts.
Primary monocytes were expanded, seeded into the bone scaffolds, and differentiated into functional, mature osteoclasts using our previously developed protocols. Briefly, peripheral blood mononuclear cells (PBMC) were isolated from buffy coats of human blood (fully deidentified samples obtained from the New York Blood Center) by density gradient centrifugation with Ficoll-Paque PLUS (GE Healthcare, 17-1440-02). Following manufacturer’s protocol, immunomagnetic isolation of monocytes (Big Easy EasySep Magnet, Stem Cell Technologies, 180001) using negative selection (EasySep Human Monocyte Isolation Kit, Stem Cell Technologies, 19359) was performed. For the following 2 days, 8 × 106 monocytes were cultured on 25 cm2 ultralow attachment flasks (Corning, 3815) with 10 mL of maintenance medium (RPMI 1640, ATCC, 30-2001) supplemented with 10% heat-inactivated human serum (Corning, 35-060), 1% penicillin/streptomycin, and 20 ng/mL Recombinant Human M-CSF (PeproTech, 300-25) at 37° C. in a humidified incubator at 5% CO2. Human CD14+ monocytes were then seeded at a concentration of 4 × 105 cells per scaffold, using 40 µL of medium, allowed to attach for 2 hours at 37° C. in a humidified incubator at 5% CO2, and subsequently differentiated for 2 weeks into osteoclasts in Minimum Essential Medium Eagle Alpha modification (α-MEM, Sigma, M4526) supplemented with 10% (v/v) heat-inactivated HyClone FBS, 1% penicillin/streptomycin, 1-Glutamine (Gibco, 25030-081), 20 ng/mL Recombinant Human M-CSF (PeproTech, 300-25) and 40 ng/mL Recombinant Human sRANK Ligand (PeproTech, 310-01). Cytokines were replenished every 3 days. Cells were maintained at 37° C. in a humidified incubator at 5% CO2.
Skin: 3D skin tissues were formed following a previously described protocol. Briefly, 1.5 × 105 human dermal fibroblasts (NHDF)n were embedded in 1 mL of 3 mg/mL type I collagen matrix (Millipore, 08-115) and the polymerized cell-containing gel was incubated on a transwell mesh (BD Biosciences) for 5 to 7 days in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% FBS. Then, 2.5 × 105 keratinocytes were seeded onto the matrix, and incubated in epidermalization medium containing a 3:1 mixture of DMEM and HAM’S F12, 0.1 % FBS, 2 nM triiodothyronine (T3) (Sigma, T5516), 5 ng/ml insulin (Sigma, I9278), 0.4 µg/ml hydrocortisone (Sigma, H0888) and 10 ng/ml EGF (Millipore, 01-107) for an additional 6 days to ensure keratinocytes were confluent enough to cover the surface. The composite culture was raised to the air-liquid interface for 7 days in a cornification medium with high calcium concentration (1.8 mM), without growth factors, to induce epidermal differentiation.
Endothelial barriers: Custom mesh inserts were fabricated as described above, autoclaved on a wet cycle, coated with fibronectin (1:100 from 10 ug/mL stock, Sigma, F4759) for 45 minutes and washed twice with PBS. Human MSCs were expanded in monolayers and dissociated with trypsin between passage 5 and 8, and were then seeded using 150,000 cells in 50 µL volume to the top of each insert. The MSC cell suspension (50 µL) was left on each mesh insert for 1 hour to enable cell attachment. After 1 hour, additional media was added to each well (2 mL/well), fully immersing the cell coated meshes within the wells of the ultra-low attachment plate (Corning, 3473), and cultured at 37° C. with 5 % CO2 for 24 hours. Human umbilical venous endothelial cells (HUVEC) were expanded to passage 5 - 8. The bottom surface of each MSC-coated inset was coated by 400,000 HUVEC and an additional 50,000 MSC. To this end, the MSC media was removed, allowing for each insert to stay only slightly hydrated and flipped over to the bottom side. A 20 µL cell suspension of HUVEC/MSC was added twice, 15 minutes apart, to the bottom surface of each insert and incubated at 37° C. and 5% CO2 in-between the two cell additions, allowing for incremental attachment of cells prior to addition of endothelial media (EGM-2, Lonza). Each insert was estimated to have a total of 400,000 HUVECs and 200,000 MSCs, to mimic the dynamics between vascular populations, represented by the endothelium and perivascular supporting cells (pericytes) in blood vessels. After 48 hours, mesh inserts with adherent cells were placed into the platforms, and exposed to hydrodynamic shear stress of 0.31 dynes/cm2 for 12 hours, 0.63 dynes/cm2 for 24 hours, and 1.88 dynes/cm2 for 24 hours. To validate the barrier function of these endothelial/MSC coatings, FITC/TRITC-tagged 3 kDa and 70 kDa Dextran molecules (ThermoFisher, D3307, D1864) were flowed through the platforms for 72 hours and collected from the top chambers to read their fluorescent output using a 96-well plate reader (BioTex, Synergy HTX).
Immune cells: Primary human CD14+ monocytes were isolated by using magnetic activated cell sorting (MACS) using CD14+ sorting beads (Miltenyi Biotec) from a human leukopak sample (New York Blood Center). The isolated cells were maintained in a buffer solution on ice for less than 3 hours prior to introduction into the platform. CD14+ monocytes (50,000 cells) were introduced into the vascular perfusion reservoir and circulated through the platform for the duration of the experiment. At day 14, monocytes were replenished by introducing an additional 50,000 CD14+ cells into circulation through the reservoir.
Cardiac cryoinjury studies: Vascularized InterOrgan platforms were assembled as described above, and each platform contained only cardiac tissues in the middle two chambers (first and last chamber remained empty). One of the two cardiac tissues was then exposed to cryoinjury by touching the tissue with dry ice for 5 seconds, while the other served as a control. Immune cells (200,000 CD14+ monocytes) were labeled with Vybrant™ DiD Cell-Labeling Solution (ThermoFisher) to enable tracking over time, introduced into the reservoir and circulated in the platform for the duration of the experiment. The platforms were maintained for 7 days without media change, and the cardiac tissues were imaged with an IVIS Spectrum Optical Imaging System (Perkin-Elmer), in the Columbia’s Oncology Precision Therapeutics and Imaging Core (OPTIC). For imaging, the cardiac tissues were removed from the InterOrgan platform to avoid autoflourescent signals. The healthy and injured tissues were aligned next to one another in the same field of view and compared directly from multiple imaging views (top, side) using an IVIS 200 Spectrum device. The IVIS software was used to analyze the images by converting the signal to the normalized Radiant Efficiency (Emission light [photons/sec/cm2/str]/ Excitation light [µW/cm2]). The fluorescence signal was measured by selecting the same region of interest for each tissue and subsequently quantifying the sum of the Radiant Efficiency of all fluorescent pixels within the region of interest. The results were graphed using GraphPad prism. Exported images showing the Radiant Efficiency as a heat map were generated within the IVIS Spectrum software (Perkin-Elmer).
Supernatant collection: Every 2 days, supernatant samples (1 mL volume) were collected from each chamber and reservoir, frozen immediately, and subsequently thawed and used for several assays as described below. Supernatant samples were stored at -20° C. for less than three months before use; once thawed, no supernatant sample was left at 4° C. for more than one week and thawed no more than 2 times.
Cytokine profiles: MIP3a and SDF1a readings were obtained from 50 µL of tissue supernatant taken after 28 days of culture using the Immune Monitoring 65-Plex Human ProcartaPlex™ Panel (Thermo Fisher Scientific, EPX650-10065-901), according to the manufacturer’s instructions. Samples were allowed to incubate overnight at 4° C., run on a Luminex-200 and analyzed through the Luminex software by comparing to the included standards.
Heart function assays: Cardiac excitability, force, and beat rate were obtained using our previously established protocols. Cardiac troponin secretion was determined using the Human Cardiac Troponin I ELISA Kit (Abcam, ab200016) according to the manufacturer’s instructions.
Liver function assays: To assess liver function, supernatant samples from each condition at the beginning and after 28 days of culture were analyzed for albumin and urea secretion using a Human ELISA kit (Bethyl, E88-129) and a Urea Nitrogen Test Kit (Fisher Scientific, SB-0580-250), respectively. Comparing these samples to the provided standard, concentrations of albumin and urea were calculated and compared to the secretion for each tissue at Day 0. Assays were performed according to the manufacturer’s instructions.
Bone function assays: To assess the bone’s ability to remodel its matrix, supernatant samples were analyzed for Telomer Repiceated Amplification Protocol, (TRAP,, Kamiya Biomedical Company, KT-008) and bone sialoprotein (Human Bone Sialoprotein ELISA Kit, Mybiosource, cat. no. MBS261861) after 28 days of culture. These assays were performed according to the manufacturer’s instructions.
Skin functional assays: For drug-induced toxicity studies, electrical current was run through the tissues by placing electrodes on either side of the skin tissue and the change in resistance was subsequently measured and read as a function of the barrier. All tissues were analyzed using the same electrode holder setup to standardize the positions of electrodes with respect to the tissue. To analyze the transport of molecules through the skin barrier, Fluorescein (FITC, ThermoFisher, D3306) powder was added to the epidermis of skin tissues. After 3 hrs, 100 µl of supernatant from the dermal region below the skin tissue was sampled and assayed on a plate reader (BioTex Synergy HTX).
Metabolic Assays: Glucose, lactate, glutamate and glutamine were measured in parallel using the bioluminescent Glucose-Glo™ (Promega, cat. no. J6021), Lactate-Glo™ (Promega, cat. No. J5021), Glutamine/Glutamate-Glo™ (Promega, cat. no. J8021) and Glutamate-Glo™ (Promega, cat. no. J7021) assays according to the manufacturer’s protocols. Supernatants were thawed and 2.5 µl of sample was diluted in 97.5 µl PBS and the following volumes were used from this mixture for each assay: 25 µl for lactate, 12.5 µl plus an additional 12.5 µl PBS for glucose, 12.5 µl for glutamine and 12.5 µl for glutamate, as suggested by the manufacturer.
Tissue preparation: Collected tissue samples were bisected for proteomic and histologic analyses. One half of the sample was snap frozen using liquid nitrogen and stored at -80° C. for less than one month before being analyzed for proteomics. The second half of each tissue sample was fixed for 24 hours in PFA, washed in PBS, and submitted to the Herbert Irving Comprehensive Cancer Center (HICCC) Molecular Pathology Lab at Columbia University for paraffin-embedding and sectioning.
Immunostaining: Heart, bone, liver, and skin constructs were fixed in 4 % PFA for 24 hours, embedded in paraffin, and sectioned for histological and immunofluorescence examination at 5 µm. All tissues were processed for hematoxylin & eosin (H&E), trichrome, and bone tissues were processed for picrosirius red staining by the HICCC Molecular Pathology Lab at Columbia University. Paraffin-embedded tissue blanks were hydrated, processed for antigen-retrieval using a 10 mM sodium citrate buffer for 20 min in heat, and permeabilized with 0.25% (v/v) Triton-X for 20 minutes. Samples were then blocked for 2 hours with 10% FBS, and individual staining protocols for each tissue. Heart: Samples were incubated with a primary antibody for alpha-actinin-2 (Invitrogen, 701914) overnight at 4° C. Liver: Samples were incubated with primary antibodies for albumin and cytochrome P450 enzyme CYP3A4 (Millipore, AB1254) overnight at 4° C. Skin: Samples were incubated with primary antibodies for keratin 14 (Biolegend, PRB-155P) and vimentin (Santa Cruz Biotechnology, sc-6260) overnight at 4° C. After washing with PBS, samples were incubated with fluorophore-conjugated secondary antibodies (Invitrogen) for 2 hours at room temperature. Slides were covered with cover-slips using mounting medium containing 4′,6-diamidino-2-phenylindole (DAPI) (Prolong Mountant with NucBlue, Invitrogen, P36981) and examined using either a Zeiss LSM 5 Exciter confocal laser scanning microscope or Nikon Ti Eclipse inverted confocal microscope.
Endothelial layers were fixed in PFA at 37° C. for 10 minutes. After aspirating fixation solution, samples were washed delicately using PBS supplemented with 1 mM CaCl2 and 0.5 mM MgCl2. Samples were subsequently permeabilized using 0.5 % Triton X-100 at 37° C. for 10 minutes. Once washed using supplemented PBS, endothelial barriers were stored at 4° C. for less than three weeks prior to staining. For staining, a dilution of 1:250 for VE-Cadherin (Sino Biological, 10433-MM01) in 2 % BSA was added to each sample at 4° C. overnight. Samples were subsequently washed with supplemented PBS three times for 5 minutes each. For secondary staining, 1:400 488 Goat anti-mouse IgG in 2 % BSA, 1:400 Phalloidin, and 1:1000 DAPI were added to each endothelial barrier sample. Samples were kept in the dark on a shaker overnight and washed three times for 5 minutes each the next day prior to imaging.
Quantitative Proteomics: Proteomics sample preparation and tandem mass tag (TMT) labeling were performed as described earlier (1), with minor modifications. Briefly, frozen tissues were lysed by bead-beating in 8 M urea, 1% SDS, 200 mM EPPS (pH 8.5) and protease inhibitor. Samples were reduced with 5 mM TCEP and alkylated with 10 mM iodoacetamide (IAA) that was quenched with 10 mM DTT. A total of 50 µg of protein was chloroform-methanol precipitated. Protein pellets were reconstituted in 200 mM EEPS (pH 8.5) and protein concentration determined using a BCA assay (Pierce). Total protein from each sample (2 to 25 µg) was digested overnight at room temperature with Lys-C protease at a 50:1 protein-to-protease ratio while shaking. Trypsin was then added at a 100:1 protein-to protease ratio, and the reaction was incubated 6 hours at 37° C. Digested peptides were quantified using a Nanodrop at 280 nm and 2 to 25 µg of peptide from each sample were labeled with 200 µg TMT reagent using 10-plex TMT kit. TMT labels were checked by pooling 100 ng of each sample and were bulk mixed at 1:1 across all channels using normalization factor samples. Bulk samples were fractionated with using Pierce™ High pH Reversed-Phase Peptide Fractionation Kit and each fraction was dried down in a speed-vac. Dried peptides were dissolved in 10 µl of 3% acetonitrile/ 0.1% formic acid and injected using SPS-MS3.
LC-MS/MS proteomics: Fractioned peptides were separated using Thermo Scientific™ UltiMate™ 3000 RSLCnano system and Thermo Scientific EASY Spray™ source with Thermo Scientific™ Acclaim™ PepMap™100 2 cm × 75 µm trap column and Thermo Scientific™ EASY-Spray™ PepMap™ RSLC C18. 50 cm × 75 µm ID column with a 5-30% acetonitrile gradient in 0.1% formic acid over 127 min at a flow rate of 250 nL/min. After each gradient, the column was washed with 90% buffer B for 5 min and re-equilibrated with 98% buffer A (0.1% formic acid, 100% HPLC-grade water) for 40 minutes. For BPRP-separated proteome fractions, the full MS spectra were acquired in the Orbitrap at a resolution of 120,000. The 10 most intense MS1 ions were selected for MS2 analysis. The isolation width was set at 0.7 Da and isolated precursors were fragmented by CID at a normalized collision energy (NCE) of 35 % and analyzed in the ion trap using “turbo” scan speed. Following acquisition of each MS2 spectrum, a synchronous precursor selection (SPS) MS3 scan was collected on the top 10 most intense ions in the MS2 spectrum. SPS-MS3 precursors were fragmented by higher energy collision-induced dissociation (HCD) at an NCE of 65% and analyzed using the Orbitrap.
Proteomic data analysis: Raw mass spectrometric data were analyzed using Proteome Discoverer 2.2 to perform database search and TMT reporter ions quantification. TMT tags on lysine residues and peptide N termini (+229.163 Da) and the carbamidomethylation of cysteine residues (+57.021 Da) was set as static modifications, while the oxidation of methionine residues (+15.995 Da) and deamidation (+0.984) on asparagine and glutamine were set as a variable modification. Data were searched against UniProt Human database with peptide-spectrum match (PSMs) and protein-level FDR at 1% FDR. The signal-to-noise (S/N) measurements of each protein were normalized so that the sum of the signal for all proteins in each channel was constant, to account for equal protein loading. Protein identification and quantification were imported into Perseus for multiple-sample tests for statistical analysis (FDR<0.05 or FDR<0.01) to identify proteins demonstrating statistically significant changes in abundance.
Proteomic data benchmarking of engineered against adult tissues: The identified proteins demonstrating statistically significant changes in abundance were compared to published adult tissue datasets from the Human Protein Atlas, as follows. Because the methodology used to generate each dataset varies greatly, direct comparisons could not be made. Instead, within each tissue dataset, individual protein expression levels were exported into Excel and subsequently tertiled into “Low”, “Medium”, and “High” expression levels, as is done in the Human Protein Atlas. Proteins that were not expressed were labelled as “Not detected” to avoid skewing comparisons with false low counts.
The percent of shared proteins was calculated by determining the number of proteins expressed (at any level) in the engineered tissue dataset versus the published adult tissue dataset, as a percentage of shared proteins (expressed in both tissues) within the total number of proteins. To further determine the correlation of the shared protein expression levels between the engineered tissues and the corresponding published data, the number of matching genes expressed as “Low”, “Medium”, or “High” in both tissue sets were calculated as a percentage over the total number of shared proteins expressed overall.
Heatmaps were generated using the tertiled data, by manually selecting a list of proteins according to two criteria: (1) the protein should be considered “tissue enriched” by the Human Protein Atlas and (2) the protein should be expressed in both datasets to enable comparisons. The lists of proteins for each heatmap were generated using only the proteins listed as highly expressed within each tissue per Human Protein Atlas. However, when the suggested protein was not expressed in one of the datasets, we continued down the list until finding data for 15 proteins per tissue. Comparisons between engineered and adult tissues were made according to tissue type, with engineered bone notably lacking a proper comparison. Bone is deemed a “rare” tissue by the Human Protein Atlas, and further literature searches did not yield more closely matching datasets, therefore the engineered bone protein data was compared to adult bone marrow protein data, the closest tissue comparison.
Proteomic data gene ontology (GO), KEGG, differential expression and pathway analysis: The identified proteins demonstrating statistically significant changes in abundance were subsequently used to perform gene ontology (GO) and KEGG pathway analyses as follows. GO analysis of shared highly expressed proteins in all tissues within each culture condition (InterOrgan, Mixed, Isolated) was performed using ShinyGO v0.61. First, gene lists were assembled using Microsoft Excel by filtering for genes (as determined from the corresponding proteins in the description corresponding to each protein accession number) listed as highly expressed in the heart, liver, skin, and bone tissues, according to the previous methodology where each data set was tertiled within Excel. This list was uploaded to the ShinyGO v0.61 server with the following settings: “Human” as the “Best matching species”, “0.05” as the “P-value cutoff (FDR)”, and “30” as the “# of most significant terms to show”. The resulting networks were directly exported from the site and used without editing. Tissue specific GO analysis was conducted using PANTHER (Protein Analysis Through Evolutionary Relationships) Classification System using lists in Excel, by filtering for genes (determined from the corresponding proteins in the description corresponding to each protein accession number) listed as highly expressed in the engineered tissue (e.g., heart) for each of the culture conditions (InterOrgan, Mixed, Isolated). The input genes were compared against all genes within the Homo sapiens reference list and a PANTHER Overrepresentation Test for GO cellular component complete was performed using a FISHER test with FDR correction. The resulting lists were exported, and GraphPad Prism software was used to graph cellular components associated with cardiac maturity. Further expression analysis for engineered tissues was performed using iDEP (integrated Differential Expression and Pathway analysis), where the protein expression datasets generated for each engineered tissue were uploaded and pathway analysis was performed, using the Human reference dataset, using PGSEA on for GO Biological Process and KEGG pathways for the top 30 pathways with a pathway significance cutoff (FDR) of 0.2 and a geneset minimum of 15 and maximum of 2000.
RNA sequencing: Cardiac tissues were flash frozen in RNAlater (ThermoFisher, AM7021) and sent to GENEWIZ for Standard RNA-seq with polyA selection using an Illumina HiSeq, 2×150bp configuration, single index, per lane and subsequent analysis as described below. Sequence reads were trimmed to remove possible adapter sequences and nucleotides with poor quality using Trimmomatic v.0.36. The trimmed reads were mapped to the Homo sapiens GRCh38 reference genome available on ENSEMBL using the STAR aligner v.2.5.2b. The STAR aligner is a splice aligner that detects splice junctions and incorporates them to help align the entire read sequences. BAM files were generated as a result of this step. Unique gene hit counts were calculated by using feature Counts from the Subread package v.1.5.2. Only unique reads that fell within exon regions were counted. After extraction of gene hit counts, the gene hit counts table was used for downstream differential expression analysis. Using DESeq2, a comparison of gene expression between the Control tissues and Matured tissues was performed. The Wald test was used to generate p-values and log2 fold changes. Genes with a p-value < 0.05 and absolute log2 fold change >1 were called as differentially expressed genes for each comparison. The differentially expressed genes bi-clustering heat map was generated to visualize the expression profile of the top 30 genes sorted by their adjusted p-values. This analysis was useful for identifying co-regulated genes across the treatment conditions. A second plot was generated to include only the top statistically significant differentially expressed genes if two or more were identified. This Volcano plot shows the global transcriptional change across the groups compared. All the genes are plotted and each data point represents a gene. The log2 fold change of each gene is represented on the x-axis and the log10 of its p-value is on the y-axis. Genes with a p-value less than 0.05 and a log2 fold change greater than 1 are indicated by red dots. These represent upregulated genes. Genes with a p-value less than 0.05 and a log2 fold change less than -1 are indicated by blue dots. These represent downregulated genes.
Ingenuity Pathway Analysis: Data were analyzed through the use of IPA (QIAGEN Inc., https://www.qiagenbioinformatics.com/products/ingenuitypathway-analysis).
Networks, functional analyses, and canonical pathways were exported directly and used without further modification.
Cardiac dose response studies: Cardiac tissues and strips of fetal cardiac tissue (FCT, purchased as surgical waste from Advanced Bioscience Resources (Alameda, CA)) were imaged at baseline and at each sequential dosage for 20 seconds at 100 frames per second under brightfield illumination using a Zyla 4.2 sCMOS camera (Andor) and NIS software (Nikon) or Pike F-032b (Allied Vision Technologies) camera. The resulting videos were analyzed for pixel movement in a custom MATLAB code described previously.
Responses to epinephrine, dofetilide, doxorubicin, and doxorubicinol: The comcentrations of epinephrine, dofetilide, doxorubicin, and doxorubicinol were measured in cell culture supernatant using ultra performance Liquid Chromatography-tandem Mass Spectrometry (UPLC-MSMS). For epinephrine, samples were spiked with the internal standard (norepinephrine-d6), and mixed with 1.2 M perchloric acid, followed by 1 M sodium bicarbonate. After mixing, 0.1% dansyl chloride was added, vortexed and heated at 60° C. for 10 minutes. After being chilled on ice for 3 minutes, the samples were centrifuged at 13,000 rpm for 5 minutes. The supernatant was mixed with ethyl acetate, centrifuged and the upper layer was evaporated under a nitrogen stream and suspended in acetonitrile for further analysis. Chromatographic separation of epinephrine was done on a Waters ACQUITY UPLC HHS C18 column (2.1× 100 mm, 1.8 µm), and maintained at 40° C. and at a flow rate of 300 µL/min. LC-MS/MS was performed using positive ESIwith a multiple reaction monitoring (MRM) mode (transition: 883.3>170.2) on a triple quadrupole Waters Xevo TQ-S (Waters, Milford, MA) mass spectrometer integrated with a Waters Acquity UPLC controlled by Mass Lynx Software 4.1.
Dofetilide concentration in the media samples was measured after spiking the samples with the internal standard (Dofetilide d4) and separated on a Poroshell 120EC, 2.1×50 mm, 2.7 µm column. Samples were measured using Agilent 6410 triple quad mass spectrometer connected to Agilent 1290 Infinity UHPLC (Agilent Technologies, Santa Clara, CA). MRM transition used was as follows: 442.2>198.0. Doxorubicin and doxorubicinol were assayed simultaneously in samples spiked with internal standard (daunorubicin) using Agilent 6410 LCMS/MS under positive ESI MRM mode (Transitions used: doxorubicin 544.2>398.1; doxorubicinol: 546.2>400.1). All compounds were quantitated by comparing the integrated peak areas of unknown against those of known amounts of purified standards.
miRNA was isolated using miRNeasy Mini Kit from (Qiagen, 217004). Samples were shipped on dry ice to Advanced BioMedical Laboratories and assayed using the miRNA 4.0 Genechip Array (ThermoFisher). Results were analyzed using the TAC 4.0 software (ThermoFisher). Additional Ingenuity Pathway Analysis was performed using the methodology described above.
To assess the activity of miRNAs, gene set enrichment analysis (GSEA) was performed of their targets, as determined by MultiMiR (release 3.11) and RBio-mirGS (update 0.2.12) biocoductor packages (in R) for genes that were differentially expressed after Dox treatment. Since miRNAs generally repress their targets, the sign of the normalized enrichment score was reversed to correctly report their change in activity. For instance, a positive target enrichment for miR-1273a’s targets was reported as a negative NES (NES = -21.31) because it is consistent with its downregulation. Since the analytical form of the null distribution for the NES statistic is not known, a p-value was computed by using an empirical null distribution, generated by random gene sampling. GSEA was performed using fgsea (v1.13.5) package in R.
Data were analyzed in Excel (Microsoft) and graphed in Prism (GraphPad). Data are shown as mean ± standard deviation, for a given number of biological replicates. Significant differences were defined by P<0.05 for all statistical methods, unless otherwise noted. Differences between the experimental groups were analyzed by one-way or multi-way ANOVA. Post hoc pairwise analysis was done using Tukey’s HSD test.
In another aspect of the disclosed subject matter, we established a metastatic niche with interstitial flow, oxygen gradients, and regulatory factors that emulated drug resistance of metastatic cells. We have also bioengineered primary human tumors. Bone sarcoma was formed within bioengineered human bone, subjected to mechanical stimuli and used to link RUNX2 expression to poor survival of sarcoma patients. The bioengineered vascularized neuroblastoma functionally recapitulated vasculogenic mimicry and drug resistance. Bioengineered tumors recapitulated the size and cargo of tumor EVs found in patients, and the tumor mRNA (e.g., EZH2 mRNA) was transferred into the surrounding tissue cells. C ritically, we have shown that, once the matched metastatic and primary tissue is available, we can use network-based methodologies- such as the VIPER algorithm to identify the master regulator proteins that are mechanistically responsible for progression and the FDA approved and investigational compounds that can effectively invert their activity. We have also shown that these analyses can be conducted in single cells, without loss of reproducibility, using meta VIPER, an algorithm that virtually eliminates gene dropout effects associated with low profiling depth.
In another aspect, the system is used for modeling targeted metastasis of breast carcinoma (BRCA). In this regard, the system can initially contain circulating tumor cells, followed by a 3D primary tumor model with patient-derived organoids, all of which can be functionally connected to metastatic target sites (lung, liver, bone; heart as a negative control), all derived from the cells of the same patient, by vascular flow while separated with endothelial barriers. This method can be used to support identification of master regulators of metastatic progression and the drugs specifically targeting metastatic progression, by capturing and analyzing single cells in the primary, vascular, and target organ sites.
In one embodiment, the system comprises: bioengineered metastatic target tissues (lung, bone, liver; heart as negative control) and a 3D breast tumor model based on patient-derived organoids. Patient-specific modeling of metastatic progression via quasi-physiologic integration of tumors and healthy tissues cultured in organotypic conditions by vascular flow can be achieved. We refer to this as “cancer patient on a chip”.
In some embodiments, direct comparative analysis of bioengineered tumors and surgical specimens by single-cell RNAseq in longitudinal studies is performed to establish rigorous methodologies for assessment/validation of biological fidelity. The method can be used for a period of time. For example, long term studies (4-12 weeks) that integrate bioengineering and systems biology approaches to elucidate the mechanistic basis of metastatic progression and drug sensitivity/resistance at the single cell level. Regulatory network based inference and experimental validation of cell-type-specific drug sensitivity in primary and metastatic tumors within a bioengineered tumor context can be performed, if desired.
The availability of predictive in vitro models of human tumors designed to accurately recapitulate key aspects of human pathophysiology is transformative to cancer research and pre-clinical validation of new therapeutic modalities. A tumor can be physiologically integrated with their cognate metastatic sites (lung, liver, bone) via vascular perfusion containing circulating cells. The tumor compartment can be established directly from surgical specimens grown in 3D, organotypic conditions while target metastatic sites and vasculature can be established from blood-derived, patient-matched iPS cells.
By engineering in vitro the patient-specific tumors and host tissues to which they preferentially metastasize, and by physiologically connecting these tissues by vascular flow, we can dramatically improve the ability to investigate mechanisms presiding over metastatic progression in a context bioengineered to recapitulate key aspects of human tumor pathophysiology. The model can provide a biologically meaningful and tightly controllable environment to validate mechanistic drivers and therapeutic predictions of human tumor pathophysiology. The model can provide a biologically meaningful and tightly controllable environment to elucidate mechanistic drivers and therapeutic predictions using bioengineered tumors validated against matched native tumor samples. Our approach is to bioengineer and characterize the native physiologic milieu relevant to the metastatic progression of a patient specific breast carcinoma (BRCA). We can bioengineer host tissues relevant to metastatic progression of BRCA, using patient-matched tumor cells and blood-derived iPS cells. Our focus is on bioengineering BRCA of two molecular subtypes: (a) hormone receptor positive (ER+/PR+) tumors, which prevalently metastasize to bone, liver and lung, and (b) triple-negative breast cancer (TNBC), which prevalently metastasize to lung (low rate to liver and bone).
Tumors can be physiologically integrated with their potential cognate metastatic sites (lung, liver, bone) via vascular perfusion. The tumor compartment can be established directly from surgical specimens grown in 3D, organotypic conditions while target metastatic sites and vasculature can be established from blood-derived, patient-matched iPS cells, under an active institutional review board protocol. The system is imaging compatible and supports long- term culture (4-12 weeks). Biological fidelity and heterogeneity of primary and metastatic sites, as implemented in the context of such vascularized multi-tissue platform, can be validated by single-cell analyses vs. the corresponding native tumor. For these studies, we can recruit a cohort of patients with metastatic tumors. Our ultimate goal is to demonstrate utility of the platform in elucidating mechanisms of tumor progression and drug resistance, by testing drug panels predicted by a novel RNA-seq-based, NY CLIA certified methodology (OncoTreat). Our system can recapitulate key properties of human tumors and enable identification of target proteins that mechanistically drive tumor progression and drug sensitivity/resistance. Thus, the system coupled with the method of use can have broad utility in cancer research and in patient-specific testing of new therapeutic modalities.
In the “cancer patient on a chip” model the system includes vascular perfusion that physiologically integrates circulating tumor cells/bioengineered human tumors with their canonical target tissues to which they preferentially metastasize (lung, liver, bone), all derived from same-patient cells. An exemplary embodiment is a model of breast cancer metastasis, particularly the hormone positive (HR+) and triple negative (TN) invasive ductal carcinomas (IDC), as they are the most common aggressive cancers in women, which lack effective therapeutic modalities. Our 3D BRCA model derived from patient-specific tumor organoids focuses on two molecular subtypes: HR+(ER+/PR+) tumors that prevalently metastasize to bone, liver and lung and triple-negative breast cancer (TNBC), which prevalently metastasize to lung. Samples from chemo-naïve patients presenting with metastatic tumors at diagnosis can be used, resulting in a validated patient-specific model of primary and metastatic breast carcinoma, enabling new insights into patient and tumor-specific drug sensitivity, and providing a platform for cancer research and precision medicine.
In one embodiment, human tumors (osteosarcoma and breast carcinoma)—grown in 3D organotypic conditions—are linked by vascular flow to their canonical metastatic sites (lung, liver, bone). The entire platform can be derived from individual patient cells (both tumor related and normal), support cultures up to 12 weeks, and can be both tunable and imaging-compatible. The platform can be used to study critical dependencies and drug sensitivity of cells representing all steps of metastatic progression. We believe our system can effectively recapitulate critical properties of human tumors and enable assessment of target proteins involved in drug sensitivity/resistance.
Recapitulation of critically relevant pathophysiological parameters of individual tumors include: (i) preservation of genetic, epigenetic, and transcriptional heterogeneity at the single cell level; (ii) minimization of time-dependent genomic and transcriptomic drift for up to 12 weeks (iii) recapitulation of macroscopic parameters, such as hypoxia, vascularization, and stromal representation, and (iv) consistency of drug sensitivity prediction in primary and engineered samples. In one embodiment, we focused on the breast carcinoma, which is characterized by substantial inter-tumor variability, thus testing the platform’s ability to address these goals over multiple genetically and epigenetically distinct backgrounds in female patients.
Method of use 1: Bioengineering patient-specific human tumors and host tissues. Using native scaffolds and bioreactors, we can engineer two primary tumors: osteosarcoma and breast carcinoma. Fluorescently labeled tumor cells and tumor slices (for authentication) can be derived from patient biopsies. Blood-derived iPS cells from the same patient can be used to engineer three normal tissues representing the most frequent metastatic sites for these tumors: bone, lung, and liver. Heart tissue can be used as a negative control for tissue specificity. All tissues can be 1 mm thick, providing a 3D architecture for cells and internal vasculature, while allowing imaging. We can demonstrate that tumor and target tissue cultures recapitulating critical properties and heterogeneity of their human counterparts can be maintained for 4 weeks (routinely) and up to 12 weeks (as needed). Engineered tumors and target metastatic tissues can be characterized/authenticated by exome profiling and single-cell RNA-seq and responses to drugs.
Method of use 2: Establishing a human model of metastasis in an integrated multi-tissue platform. We provide a multi-tissue platform for modeling non-cell-autonomous human pathologies, with all tissues derived from same-patient iPS cells and connected by vascular perfusion.
To provide each tissue with its physiological niche, individual tissue compartments are independently regulated and separated from the vascular perfusion compartment by an endothelial barrier. We can adapt this platform to physiologically integrate primary human tumors (osteosarcoma and breast carcinoma), their canonical metastatic sites (lung, liver, bone), and negative controls (heart). The system can be used to investigate the tissue specificity of vascular endothelium and modulate its permeability by optogenetic methods to investigate its role in each metastatic progression step. A model of metastatic progression of BC cell lines (TNBC, HR+) introduced into circulation under flow and exposed to target host tissues separated by endothelialized barriers within our established multi-tissue platform can be established; (2) we can recapitulate the targeted metastasis previously demonstrated in a mouse xenotransplant model, using cell lines that selectively home to bone or lung; (3)iInvestigate the intravasation potential of patient-derived BC cells from our 3D breast tumor model with patient-derived organoids, metastatic extravasation into host tissues using the methods established by BC cell lines in our platform and the role of patient diversity in metastatic progression via generation of patient-matched, iPSC-derived target tissues. Two metastasis models can be established: (i) circulating tumor cell (CTCs) homing into interconnected host tissues, and (ii) intravasation of tumor cells from the bioengineered primary into the circulation followed by extravasation into host tissues. For both tumors, we can assess whether their preferential metastatic sites are recapitulated in the bioengineered platform, study patient specific metastatic progression over up to 12 weeks, and track the migration of aggressive cells across all three compartments (i.e., primary, CTCs, and metastases).
To model metastasis, we can use our platform that integrates metastatic target tissues (liver, bone and lung; heart as a negative control) via vascular flow mediated by an endothelial barrier. Host tissues can be plugged into the platform, in a desired combination and order, and physicochemical parameters can be optimized to mimic metastatic progression. The heart module can be included both (α) as a negative control for nonselective cell migration, and (b) to extend the platform capability as a cardiotoxic side effect screening device, a major complication of chemotherapy. Initially, TNBC (MDA-MB231) and HR+/HER2-(MDA-MB175, MCF7) cell lines can be used to establish a proof of principle for targeted metastasis for each subtype of breast tumor. Then, lung and bone targeting TNBC cells lines (MDA-MB231-LM, MDA-MB231-BoM can be used to validate the in vitro multi-tissue platform for its ability to recapitulate in vivo phenomena. This can be followed by the introduction of patient specific iPSC-derived host tissues and patient-derived organoid-grown metastatic BC cells to elucidate patient specific effects on intravasation, extravasation, metastatic site BC development and potential drug resistance.
Method of use 3: Elucidating master regulators and key dependencies of metastatic cells in all compartments and predicting/validating their drug sensitivity using the “cancer patient on a chip” model. We can validate/authenticate bioengineered primary tumors and tumor metastases in the “cancer-patient-on-a-chip” platform by directly comparing single-cell RNA-seq and exome profile data for engineered tumors and matched patient biopsies. We can first identify and experimentally validate cryptic tumor dependencies implemented by Master Regulator (MR) proteins responsible for implementing and maintaining the transcriptional state of cancer cells representing different stages of progression (primary, CTCs, and metastases). We can then study unique drug sensitivities/resistance of the same cells—by targeting MR dependencies—to develop new translationally relevant therapies for metastasis, a key challenge in cancer research. This can be accomplished by analyzing single-cell RNA sequencing data with established, NY CLIA certified regulatory network algorithms. Patient-specific drugs identified by these analyses can be experimentally validated on the patient-matched platform.
These methods include: (1) Performing Master Regulator (MR) analysis using scRNASeq signatures of engineered primary tumors, vascular flow CTCs, and tumor metastases in host tissues, to identify (i) MR proteins that mechanistically determine tumor cell priming for metastatic progression and (ii) unique CTC and metastatic cell dependencies. (2) Performing OncoTreat analysis, using the same scRNASeq signatures, to identify small molecule inhibitors capable of reversing the activity of subpopulation-specific MR proteins to induce cell demise or reprogramming to a non-invasive state. (3) Experimental validation of these findings in the “cancer patient on a chip.”
We have pioneered the use of lineage-specific regulatory networks, inferred de novo from large-scale molecular profile data, for the identification of MR proteins that mechanistically implement (i.e., via the transcriptional targets they regulate) cell state transitions. These methodologies, integrated into the VIPER algorithm, were successful in elucidating novel mechanisms of tumorigenesis and drug sensitivity in glioma, leukemia, lymphoma, prostate, neuroblastoma, neuroendocrine tumors, and breast cancer, among others. Relevant to this proposal, VIPER identified MR proteins controlling metastatic progression of ER+ and TNBC breast carcinoma, whose inhibition in vivo caused 100 to 1,000-fold reduction in lung metastasis burden. By coupling VIPER analysis with large-scale RNASeq profiles of tumor cells treated with ~400 compounds (FDA-approved or phase ⅔ clinical trials), we were able to identify drugs that revert the activity of MR proteins, on an individual tumor basis, thus inducing tumor state collapse and loss of tumor viability. The corresponding algorithm (OncoTreat), which was CLIA certified by NY State Dept. of Health and recently tested in an N-of-1 study at Columbia (IRB-AAAN7562). Out of 39 inferred drugs that were evaluated in PDX models from patients with 6 different aggressive/metastatic malignancies and failed 3 to 6 lines of therapy, 23 induced stable disease or partial remission, vs. none of the 28 drugs in the negative control arm (p<10-128). Overall, these methodologies have yielded six clinical studies. The PLATESeq RNASeq technology developed jointly by the Sims and Califano labs was used to generate comprehensive RNASeq profiles of drug perturbations for >10 tumors including breast cancer. The meta VIPER algorithm, designed for scRNASeq analysis, supports MR and OncoTreat analysis from single cell profiles with no loss of sensitivity and increased specificity compared to bulk tumors. Indeed, we showed that drugs predicted at the single cell level by OncoTreat successfully depleted the predicted subpopulations in patient derived GBM explants.
To assess clonal heterogeneity, we can systematically authenticate tumor tissues (primary and metastatic) cultured in the bioengineered platform, at the single cell level. Specifically, we can compare gene expression and MR-activity profiles of single cells and bulk exomes from bioengineered tumors and surgical specimens, across three compartments: (a) primary tumors (Method of Use 1), (b) CTCs - infused or intravasated from the primary tumor compartment, and (c) bone, lung and liver metastases (Method of Use 2). Due to metaVIPER’s ability to effectively reduce batch effects and other technical artifacts, these analyses can help identify cross-compartment subpopulations of related cells, by MR overlap analysis. For instance, we can use meta VIPER to identify primary tumor cells that most closely match to CTCs and metastases, assess potential priming for metastatic progression, and validate by lineage-tracking. In addition, cells from all three compartments can be analyzed by OncoTreat to identify drugs and drug combinations most likely to invert MR protein activity, thus inducing cell demise or reprogramming to a non-invasive state (Method of Use 3).
Predictions can be tested in the engineered platform over 4-12 weeks of culture, by assessing drug-mediated depletion of cellular compartments and overall reduction of metastatic cells in target tissues. We can thus be able to isolate and study the individual processes that comprise metastatic progression, identify critical cell subpopulations manifesting sensitivity to orthogonal treatments, and test panels of drugs predicted by scRNASeq. We envision offering this platform for broad use in studies of human cancer, and demonstrating its utility, predictability and reproducibility.
In one embodiment, bioengineering of osteosarcoma and breast cancer using patient’s tumor cells and a native-like matrix is provided. The method can include patient-specific platforms to study metastatic progression to canonical target tissues (lung, bone and liver; heart as a negative control), with patient-matched, iPS-derived vasculature and target tissues, and matched extracellular matrix and regulatory signals; Patient-specific modeling of metastatic progression via quasi-physiologic integration of tumors and healthy tissues cultured in organotypic conditions by vascular flow - the “cancer patient on a chip” platform; Establishment of a physiological endothelial barrier between tissue compartments and vascular flow, whose vascular permeability can be modulated via optogenetic methods; Direct comparative analysis of bioengineered tumors and surgical specimens by single-cell RNA-seq, in longitudinal studies, to establish rigorous methodologies for assessment/validation of biological fidelity; Long term (4 weeks) studies integrating bioengineering and systems biology approaches to elucidate the mechanistic basis of metastatic progression and drug sensitivity/resistance at the single cell level; Regulatory-network-based inference and experimental validation of cell-type-specific drug sensitivity in primary and metastatic tumors in a bioengineered tumor context. In vitro tumor platform for drug testing.
The bioreactor system, for example 100, 200, 300 described herein, can be used to enable modeling of metastatic progression, comprising a complex sequence of dynamic events that are difficult to recapitulate in existing models and surgical specimens. Tumor cells invade and disseminate via the vasculature, colonizing perivascular tissue niches around the capillaries in tumor-specific target tissues. Vascular flow brings the gradients of shear, oxygen, nutrients and signaling factors into the tumor tissue, thereby maintaining the tumor niche, while the extracellular matrix (ECM), endothelial cells (EC), stromal and immune cells regulate intravasation, extravasation and metastatic homing.
We validate the system utility in studies of two types of highly metastatic tumors: breast carcinoma (BRCA) and osteosarcoma (OS), in “organs on a chip” platforms. The platform can contain a bioengineered human tumor and metastatic target sites (lung, liver, bone; heart as a negative control), all derived from the cells of the same patient, and functionally connected by vascular flow. The studies can be designed to support identification of master regulators of metastatic progression and the drugs specifically targeting cells during metastatic progression, by capturing and analyzing single cells in the primary, vascular, and target organ sites. We can validate metastatic progression models over a period of 4-12 weeks, by directly comparing gene expression and VIPER-inferred protein activity profiles of cells in matching native and bioengineered tumors at various time points.
By engineering in vitro both the patient-specific tumors and host tissues to which they preferentially metastasize, and by physiologically connecting these tissues by vascular flow, we can dramatically improve our ability to investigate multiple mechanisms presiding over metastatic progression in a physiologically-relevant human tumor context. These models provide a meaningful and highly controllable environment to validate mechanistic drivers and therapeutic predictions derived from bioengineered and patient-matched tumor samples. We can bioengineer host tissues relevant to metastatic progression of breast carcinoma and osteosarcoma, using patient-matched tumor and iPS cells. Generally, tumor and host tissues are engineered, then the engineered tumors can be validated by comparison to the patient samples. We can integrate the tumor and host tissues by vascular flow and investigate tissue-specific intra/extravasation of track-labeled tumor cells, under tight EC barrier control in the system described herein. Single-cell RNA seq of native and bioengineered tumors can be used to infer mechanistic determinants of metastasis and drug sensitivity in “cancer patient on a chip” model.
All data including outlier values can be documented. The criteria to accept data can be stated. Blind measurements and quality control metrics can be used systematically to ensure unbiased study designs, data collection and interpretation. Furthermore, use of patient-matched iPS and tumor cells can enable rigorous studies of metastatic progression in an isogenic background, with each patient treated as an independent study (N = 1).
Consideration of relevant biological variables. Rather than addressing the broad diversity of tumor progression and drug sensitivity mechanisms in a diverse population - an impossible task given the relatively small cohort size, our goal can be to demonstrate the proposed platform’s ability to faithfully recapitulate critically relevant pathophysiological parameters of individual tumors. These include, among others, (i) preservation of genetic, epigenetic, and transcriptional heterogeneity at the single cell level; (ii) minimization of time-dependent genomic and transcriptomic drift for up to 12 weeks (iii) recapitulation of macroscopic parameters, such as hypoxia, vascularization, and stromal representation, and (iv) consistency of drug sensitivity prediction in primary and engineered samples. With this in mind, we focused on two tumors characterized by substantial inter-tumor variability, thus supporting the platform’s ability to address these goals over multiple genetically and epigenetically distinct backgrounds with >50% representation by female patients.
In one embodiment the method includes (1) Bioengineering breast adenocarcinomas (BRCA) and osteosarcomas (OS) from primary tumor cells with infiltrating stromal/immune compartments established from patient-matched iPSCs. (2) Validating the fidelity of engineered vs. patient tumors. (3) Bioengineering and validating metastatic host tissue models, including lung and liver (for BRCA and OS), bone (for OS) and heart (as a negative control).
The tumor microenvironment plays a critical role in controlling tumor initiation, progression, and drug resistance, via mechanisms ranging from angiogenesis and reprograming to immunoevasion. This understanding has been seminal in fostering convergence of cancer biology and tissue engineering, towards developing more faithful and physiologically relevant models of human cancer, where the tumor compartment co-exists with stroma and vasculature. Yet, faithful modeling of complex multi-organ processes, underlying metastatic progression, is beyond the capabilities of tumor spheroids and similar systems. There is a critical need to better understand the key drivers of metastatic progression and the pharmacologically accessible dependencies of metastatic tumors. By co-engineering patient-specific tumor and normal tissues, the platform can provide a quasi-physiologic environment for lineage-tracking of aggressive cell subpopulations and allow identification of novel, pharmacologically actionable drug targets and therapies.
Collection of tumor and blood samples. Operable tumors, ≥1.5 cm3 in size, can be collected from 20 patients diagnosed with metastatic disease under our active IRB protocols (IRB-AAAN7562, AAAB2667) and fully characterized by high-depth (120X) exome and RNASeq profiling. Both the primary site and one or more metastatic sites can be biopsied. 1-mm tumor slices can be sectioned using a Vibratome (Molecular Pathology Shared Resource, Herbert Irving Comprehensive Cancer Center) and cultured in our platform as an organotypic benchmark for validation of bioengineered tumors. The tumor mass can be dissociated into single cells, labeled for cell tracking (bioluminescence, fluorescence), and used to bioengineer tumors. Dissociated cells can be analyzed by single-cell RNA-seq (scRNASeq) for later comparison with bioengineered tumors. We can also collect blood samples (8 mL) from the same patients, to (a) characterize the patient-specific secretome using our established methods, and (b) generate patient-specific iPS cells. Tumor-associated exosomes from the patient’s blood can be compared to those secreted by bioengineered tumors for fidelity assessment.
Bone is the most common site for metastatic relapse of breast tumors, particularly of the HR+ subtypes and tends to be the first site of metastasis in a significant proportion of patients [22-24]. Bone tissue can be formed from iPS-derived MSCs (giving rise to osteoblasts) and monocytes (giving rise to osteoclasts), in perfused bone scaffolds, to display the physiologic osteolytic cycle and active remodeling. (
Liver tissue, is the second frequent metastatic site for HR+ BRCA whereas liver metastases are less common for TNBC but are associated with poor prognosis. Engineered liver tissues can be formed by aggregating hepatocytes and fibroblasts (iPS-derived) into phenotypically stabilized hepatic units. Hepatic aggregates are then encapsulated in decellularized liver matrix to form the engineered liver tissues and matured in culture. Liver tissues displayed consistent production of urea (
Heart muscle is formed from iPS-derived cardiomyocytes and fibroblasts in hydrogel around flexible pillars, and exposed to an electrical pacing regime optimized to induce tissue maturation. After only 4 weeks of culture, these tissues achieved adult-like gene expression, ultrastructure with networks of t-tubules, oxidative metabolism, positive force-frequency relationship, and functional Ca handling (
Lung tissue—the main metastatic site for TNBC—can be formed using decellularized lung matrix with fully preserved matrix architecture and composition by following two different methods established in our lab. Human bronchial epithelial cells (BEAS2B line, primary hBECs or iPS-derived lung progenitors can be either seeded on lung ECM-coated transwells of our multi-tissue platform (lung 2D model) or embedded in lung ECM hydrogels. The cells can be cultured as submerged in medium for a proliferation phase of 3-5 days followed by air-liquid interface (ALI) culturing up to 4 weeks. In both models, bronchial epithelial cells show a fully differentiated phenotype after 4 weeks of ALI culture. Immunofluorescence staining revealed b-tubulinIV positive ciliated cells, Muc5b positive goblet cells and p63 positive basal cells (
Our lab has established several strategies for lung decellularization, through the use of human and porcine lungs. Our 3-[(3-Cholamidopropyl) dimethylammonio]-1-propanesulfonate (CHAPS)-based decellularization protocol was optimized to fully preserve the lung matrix architecture and composition (
Osteosarcoma Model: Tissue-engineered osteosarcoma models (TE-OS) were successfully established by culturing osteosarcoma cell lines in a bioengineered human bone generated by differentiation of human iPSC-derived mesenchymal stromal cells into osteoblasts and human iPSC-derived monocytes into osteoclasts. Osteosarcoma cell aggregates were infused into the bone niche, cultured for 2 weeks, and shown to recapitulate key features of their human counterpart. These tumors displayed marker proteins of differentiated osteoblasts and osteoclasts, including osteopontin (OPN), bone scaffold protein (BSP), osteocalcin (OCN), and tartrate-resistant acid phosphatase (TRAP). Staining for alkaline phosphatase and von Kossa indicated bone differentiation. Quantitative PCR (qPCR) detected markedly elevated gene expression, compared to cell monolayers, for markers of osteoblasts and osteoclasts. Fluorescent pimonidazole staining identified a hypoxic core, an important feature of OS microenvironment.
To vascularize TE-OS, it is critical to induce vascular development prior to osteogenesis (
Breast carcinoma model: Native ECM can be processed into tunable scaffolds and used as a niche for patient-derived tumor cells retrieved from biopsies of primary and matched metastatic sites of chemo-naive patients (metastatic at diagnosis), and supporting cells (
We can focus on two molecular subtypes: estrogen receptor positive (ER+) tumors, which prevalently metastasize to bone, and triple-negative breast cancer (TNBC), which prevalently metastasize to lung and liver. Fibroglandular mammary tissue can be extracted following surgical excision, to derive breast tissue ECM for the engineered tumor matrix. Our lab has established protocols for the production of ECM hydrogels and scaffolds that span 24 organs including lung, liver, heart, bone, and breast tissue. To provide a spectrum tumor-like matrix characteristics, we can integrate the native ECM within interpenetrating networks that can support independent modulation of stiffness, composition, and dynamics (
Mechanical properties of tumor and normal-related tissue are distinctly different. Elevating stiffness alone, independent of composition, may be sufficient to induce malignant transformation of mammary epithelial cells. Breast carcinoma can develop from alterations in multiple pathways and manifest a range of mechanical properties that also depend on the spatial scale at which they are probed. For instance, indentation testing of 169 breast tumors, using a 5 mm probe, showed tumor stiffness ranging from 10 kPa - 50 kPa, depending on tumor grade and structural makeup. At the other extreme, atomic force microscopy revealed significant nanoscale-level mechanical heterogeneity within normal breast tissue and malignant lesions. We aim to recapitulate this mechano-complexity by local matrix stiffness modulation. Our ECM hydrogel allows three crosslinking mechanisms: thermal and enzymatic gelation of fibrillar collagen; enzymatic and light-mediated crosslinking of tyramine-modified biopolymers (hyaluronan, heparin, chondroitin sulfate). Oxidation of rosebengal and eosin Y-activated tyramine moieties induced by visible light was shown to enable multi-photon patterning and can allow local changes in ECM stiffness and recapitulation of stiffness heterogeneity.
Vascularization. Primary tumor cells enriched by iPSC-derived supporting fibroblasts, EC, and macrophages, can be encapsulated in ECM hydrogels, and cultured for ≥4 weeks to allow monitoring of key variables: cell growth, DNA and RNA profiles, metabolic activity, cell morphology and cytoskeleton, proliferation (Ki67) and proteins to characterize subtype-specific breast malignancy. Patient-derived EC and primary tumor cells can be co-cultured in the ECM-hydrogel matrix.
Cell-matrix reciprocal interactions. While ECM mechanics and composition can modulate tumor behavior, tumor cells can reciprocally alter their microenvironment. Independent control of ECM parameters can help disentangle the relative contribution of cell-mediated ECM changes from those resulting from modulation of ECM by genetic, environmental, and pathogenic factors. Such cell-matrix feedback loop has been established in several models. Here, we can validate that our model captures the dynamics of interactions that are important for the study of vascular permeability and intra/extravasation.
Validation. Engineered tumors can be validated against native tumors via scRNASeq, mutational and exome profiling, IHC, metabolic, and secretome analyses. Cellular and macroscale changes in bioengineered tumor mechanics can be measured in real time, using optical elastography and compared to the native tumors.
Establishment of patient-specific host tissues: Host tissues can be engineered using iPSCs-derived cells, within a native, biomimetic ECM environment designed to promote phenotypic maturation. For bone - a metastatic site for ER+ breast tumors and osteosarcoma, we can incorporate EC, osteoblasts, and osteoclasts into decellularized bone matrix, thus recapitulating bone formation, maintenance, and regeneration. To engineer liver - a metastatic site for both TNBC and OS, we can combine aggregates of iPSC-derived hepatocytes and fibroblasts (in a 3:2 ratio) into fibrin hydrogel. Such culture supports maturation of liver tissue, and enables sustained production of urea and albumin. We engineer from iPSCs heart tissue with unprecedented level of maturity, displaying: positive force-frequency response, t-tubule networks, oxidative respiration, and physiologic drug responses. In the proposed design, heart tissue can provide a negative control for metastatic progression, ensuring that observed metastases result from tumor-specific homing mechanisms rather than from nonselective cell migration into any tissue.
To further increase the proposed platform’s relevance, we can also engineer lung tissue—a metastatic site for both TNBC and OS. 3-[(3-Cholamidopropyl) dimethylammonio]-1-propanesulfonate (CHAPS)-based decellularization protocol fully preserves the lung matrix architecture and composition (
We can apply methods for targeted removal of lung epithelium while preserving intact pulmonary vasculature and interstitium in our engineered lung models and increase complexity through inclusion of customized ECM components and multiple cell types. To enhance biological fidelity of engineered lung tissue, hydrogel-based lung ECM, supports encapsulation of pulmonary cells in a “tunable” microenvironment ideally-suited to cell-matrix interaction studies. Alginate-reinforced, decellularized lung hydrogels allows double-crosslinking (thermal and calcium-mediated) and manipulation of ECM mechanics, thus supporting both physiologic and pathologic-grade lung ECM stiffness (
Another pathological alteration in lung ECM composition is an increase in sulfated glycosaminoglycans, which commonly follows lung inflammation and interstitial pulmonary fibrosis. A biomimetic model of pathological lung tissue formed by interpenetrating lung ECM networks using sulfated glycosaminoglycan-mimetic alginate sulfate, through tunable sulfation and precise control of hydrogel mechanics, enable studies of aberrant GAG content effects on pulmonary cell phenotype and function. Our preliminary data show that such increases in GAG contents of the ECM drive pathological growth of bronchial epithelial cells and lung adenocarcinoma cells with onset of epithelial-mesenchymal transition (
We can use native tumor benchmarks to show that engineered tumors recapitulate key hallmarks of metastatic progression, including expression of proliferative and metastatic markers. We believe breast tumor progression can increase as a function of matrix stiffness, collagen fiber alignment, and angiogenesis. Rigorous characterization of these cells can be performed to understand any aberrant behavior of the bioengineered models due to phenotypic heterogeneity. If extended tumor culture (>4 weeks) poses challenges, we can adjust perfusion conditions to improve long-term control of nutrients, oxygen and regulatory factors.
To establish a model of metastasis in an integrated human multi-tissue platform, the method includes (1) Physiological integration of tumor and metastatic host tissues via vascular flow; (2) Modeling metastatic progression into the circulation and the host tissues, by tracking labeled tumor cells. (3) Investigating the mechanistic role of the endothelial barrier in tumor progression.
To model metastasis, the platform that integrates engineered tumors and metastatic homing tissues (liver, bone and lung; heart as a negative control) via vascular flow mediated by an endothelial barrier. Tumors and host tissues can be plugged into the platform, as described above,, in any desired combination or order and physicochemical parameters can be optimized to mimic metastatic progression. The heart module can be included both (a) as a negative control for nonselective cell migration, and (b) to extend the platform capability as a cardiotoxic side effect screening device, a major complication of chemotherapy.
A stable endothelial barrier such as 105, 205, 305, can be established by placing iPSC-derived ECs onto an elastic membrane and exposing them to physiological flow shear. To physiologically integrate engineered tumors and host tissues by vascular flow, they can be connected in modular format by placement into chambers above the endothelium-like membrane that separates tissue and vascular media, thus enabling vasculature-mediated tissues crosstalk (
Tracking extravasation and seeding of circulating tumor cells (CTC): We label tumor cells using fluorescent/bioluminescent tags and infuse them into the circulation to study their extravasation through endothelial barrier and seeding into host tissues. In the absence of the endothelial barrier, cells non-selectively colonize all host tissues. We characterize tumor cells and their preferential homing to specific host tissues to assess the model’s ability to mimic physiologically-relevant metastatic progression. A patient-specific platform, with tunable mechanical and biochemical host tissue properties, may support preferential metastasis of TNBC, ER+, and OS cells into lung /liver, bone, and bone/lung compartments, respectively, but not to the heart compartment. We can further manipulate physicochemical properties of host tissues (stiffness, inflammatory fibrosis, aberrant glycosaminoglycan content, to mimic organ conditions of high-risk patients, due to age, or inflammation, and study their effects on CTC efficiency and specificity. We can also control the cellular complexity of engineered host tissues and assess which stromal environments favor metastatic cell homing. We can thus evaluate a variety of stromal cells (tissue-specific endothelium, fibroblasts, and stroma; tissue-resident macrophages). We can characterize the effects of angiogenic factors (VEGF, FGF, EGF) on metastatic cell homing (
The cells that invade the host tissues can be characterized by single-cell RNA sequencing (see method of use 3 for details), to determine their phenotypes associated with metastatic seeding into the specific host tissues. The pathology of host tissues colonized with tumor cells can be characterized by histology/IHC-staining, and compared with clinical specimens. We can also conduct secretome analyses for tumor-specific, metastasis- driving extracellular vesicles (EVs) before and after the tumor cells are introduced into the circulation, before and after homing, to understand what signaling events could underlie the metastatic phenomena. The cells that metastasized into the host can provide a reference for tracking of tumor cells during metastasis, where we can investigate tumor cell intravasation into circulation and extravasation into host tissues. To validate the model, we can compare metastasis in the platform with the metastatic bone tumors from patients as benchmarks, and evaluate the tissue specificity and colonization potential of metastatic cells in the platform.
Modeling tumor metastasis into the host tissues.. Primary tumor cells can be labeled (bioluminescence to track cell motion and proliferation; fluorescence to monitor cell colonization and seeding). The tumor model can be connected by vascular flow to the lung, liver, bone and heart tissues. We can assess whether tumor cells (i) migrate out of the engineered tumors, intravasate through the EC barrier and enter circulation, (ii) arrest along the vascular wall of the specific host tissue, (iii) extravasate through the EC barrier and (iv) seed and colonize the host tissue. Important variables can be tumor characteristics, the host tissue type, order of vascular flow through the platform, and endothelial permeability. We can manipulate tumor characteristics as discussed (method of use 1), to enable monitoring of cellular events and testing the effects of engineered tumor ECM and cell types on metastatic potential along the four main steps of metastasis. Similarly, the effects of host tissue properties (ECM stiffness and composition, cellular composition) can be investigated. We can first focus on studies of tumor cell intravasation and metastatic potential as a function of endothelial stability and permeability.
Investigating the mechanistic role of the endothelial barrier in tumor metastasis: Cancer progression and treatment depend on the tumor cell ability to migrate to distant sites, and on drug transport from vascular circulation to these sites. Blood vessels have dynamic and heterogeneous barriers that select which entities can pass through. Since blood vessel permeability is highly variable across organs, tumors, and patients, it is critical to reproduce such heterogeneity in cancer models. By tracking labeled tumor cells and controlling vascular permeability, we can study the mechanistic role of the vascular barrier in metastasis.
Assessing specification and permeability of vascular endothelium: Vascular permeability is regulated by EC lining of the vessels, serving as a gatekeeper for the exchange of cells and molecules between tissue and blood. Tumor cells increase endothelial permeability, suggesting their role in intra/extravasation. While some organs (e.g. heart and lung) have tight endothelium allowing passage of only small molecules (<2 nm), inflamed and tumor-related tissues present large endothelial gaps and high permeability. Vascular permeability also influences the maximum achievable drug concentration in tumors. To be predictive, tumor models must recapitulate the biological complexity and heterogeneity of tissue/blood- vessel interactions. We can investigate specification of endothelium (using IHC for lineage-specific endothelial markers), and changes in permeability (using fluorescently labeled dextrans).
Manipulating permeability of tumor endothelium:
We can incorporate spatiotemporal control of endothelial permeability via a RhoA pathway optogenetic switch (
Validation of tumor metastasis phenotypes: Cells that successfully migrate from an engineered tumor to host tissues can be collected and characterized via single-cell (sc) RNAseq, to serve as an input for elucidation of novel targets and pathways, and for predicting therapeutic treatment options in method of use 3. Investigating the cellular subpopulation most likely to metastasize, via track-labeling and scRNASeq profiling in the engineered platform, can enable characterization of “pro-metastatic” cell phenotypes within the heterogeneous populations derived from the tumor. Metastases in the platform can be similarly characterized and by comparisons with the patient-matching clinical samples. Circulating secretome can be analyzed at different time points - when tumor and hosts are first integrated, during intravasation, tumor cell circulation, extravasation and colonization, to identify possible signaling events related to tumor EVs involved in metastatic progression.
Method of use 3: Elucidate master regulators and predict drug sensitivity in metastatic cells using the “cancer patient on a chip” model
The method includes (1) Master Regulator (MR) analysis using scRNASeq signatures of the engineered primary tumors, CTC in vascular flow, and tumor metastases in host tissues, to identify (i) MR proteins that mechanistically determine tumor cell priming for metastatic progression and (ii) unique dependencies of CTC and metastatic cells. (2) OncoTreat analysis using the same scRNASeq signatures to identify small molecule inhibitors capable of reversing the activity of subpopulation-specific MR proteins to induce cell demise or reprogramming to a non-invasive state. (3) Experimental validation of these findings in the “cancer patient on a chip.”
To assess clonal heterogeneity, we can systematically authenticate tumor tissues (primary and metastatic) cultured in the bioengineered platform, at the single cell level. Specifically, we can compare gene expression and MR-activity profiles of single cells and bulk exomes from bioengineered tumors and surgical specimens, across three compartments: (a) primary tumors (method of use 1), (b) CTCs - infused or intravasated from the primary tumor compartment, and (c) bone, lung and liver metastases (method of use 2). Due to metaVIPER’s ability to effectively reduce batch effects and other technical artifacts, these analyses can help identify cross-compartment subpopulations of related cells, by MR overlap analysis. For instance, we can use meta VIPER to identify primary tumor cells that most closely match to CTCs and metastases, assess potential priming for metastatic progression, and validate by lineage-tracking. In addition, cells from all three compartments can be analyzed by OncoTreat to identify drugs and drug combinations most likely to invert MR protein activity, thus inducing cell demise or reprogramming to a non-invasive state (method of use 3). Predictions can be tested in the engineered platform over 4-12 weeks of culture, by assessing drug-mediated depletion of cellular compartments and overall reduction of metastatic cells in target tissues. We can thus be able to isolate and study the individual processes that comprise metastatic progression, identify critical cell subpopulations manifesting sensitivity to orthogonal treatments, and test panels of drugs predicted by scRNASeq. We envision offering this platform for broad use in studies of human cancer, and demonstrating its utility, predictability and reproducibility.
To characterize the biological relevance of bioengineered tumors from method of uses 1 and 2, tissue from both primary and metastatic site can be dissociated, exome/RNA-Sequenced, and compared to patient-matched surgical samples. To demonstrate the utility of the “cancer patient on a chip” for systems biology studies, we can experimentally test OncoTreat-predicted drug responses as inferred by meta VIPER.
Large-scale single-cell analysis for tumor model validation, tracking metastatic populations and inferring drug responses. Throughout the proposed studies, we can take advantage of recent advances in large-scale scRNASeq for three main purposes: (a) Validating and studying primary tumor models (OS and breast cancer); (b) Analyzing metastases in host tissues (bone, liver, lung); and (c) Inferring single-cell-specific drug sensitivity for primaries, CTCs, and metastases by OncoTreat analysis. A computer- controlled microfluidic platform for scRNASeq, ideally suited to complex tumors analysis can parallel-profile ~ 10,000 cells with rapid, high-efficiency cell capture (>50%), using optical microscopy for on-chip analysis of markers, cell viability, and cell lysis. The device has a simple flow cell with an array of microwells on a glass slide and is fabricated by soft lithography. In a typical experiment, cells are gravity- loaded, one cell per microwell, followed by loading of polymer beads coated with oligonucleotide primers that contain a universal adapter sequence, a bead-specific barcode sequence, a unique molecular identifier (UMI), and oligo(dT) for mRNA capture. Cell lysis and reverse transcription occur automatically, following introduction of strongly denaturing lysis buffer and a perfluorinated oil to seal the array. On-chip fluorescence imaging facilitates control of cell viability, lysis, sealing, and counting. Following mRNA capture, we introduce a detergent-containing buffer to rapidly remove sealant and lysate, such that barcoded beads with hybridized mRNA are exposed, allowing reverse transcription to occur automatically. cDNA-coated beads are pooled, harvested, and 3′-end RNA-Seq libraries are generated using the SCRB-Seq protocol and the Nextera transposition system (Illumina), at a cost as low as $0.05/cell.
We sequence the pooled libraries with paired-end sequencing, where the first read contains both the cell- identifying barcode and a unique molecular identifier (UMI) barcode, and the second read contains transcript sequences. For the proposed studies, we can align read two to the human genome using the STAR aligner with a transcriptome annotation, to take advantage of its splice-awareness. By combining the alignment with the forming barcode in the first read, we assign an address to each read that aligns uniquely to a locus that can be unambiguously assigned to an annotated gene. Given the strand-specific nature of the libraries, strand information can be used to ensure proper alignment. The address includes the read ID, cell-identifying barcode, UMI, and gene symbol. This algorithm gives us an estimate of the number of captured mRNA molecules associated with each gene in each cell.
Application of our technology to a large-scale analysis of human glioblastoma (GBM) surgical specimens yielded a number of interesting findings. Because transformed glioma cells in GBM typically resemble glia at the level of gene expression, identifying malignantly transformed cells from scRNASeq data is non-trivial, and this is an issue we can face in the proposed studies. Fortunately, previous studies have shown that large copy number variants (CNVs) and aneuploidies are readily detectable by scRNASeq of tumor tissues. Principal component analysis (PCA) of the chromosomal expression matrix for each patient consistently revealed an axis of variation that separated putatively transformed cells, which harbor known expression patterns associated with GBM, from those that expressed common markers of cells in the microenvironment (
Similarly, metaVIPER-inferred protein activity profiles successfully traced differentiation of single cells from five distinct breast cancer patients from their breast cancer stem-like progenitor (BCSLP) state to a fully differentiated one (
Testing of OncoTreat predicted drugs in the patient-specific engineered platform: The bioengineered primary tumor (OS, TNBC, ER+) connected by vascular flow with bone, lung, liver and heart tissue can be used to study activity of OncoTreat predicted drugs. We can focus on drugs targeting progression steps from each compartment. Specifically, we can analyze differential expression signatures between CTCs and primary cells, between metastatic and primary cells, and between metastatic cells and CTCs, using metaVIPER. Cell signatures can be generated between the subpopulations in each compartment and the closest-matching subpopulation in earlier compartments, based on MR protein overlap (e.g., a CTC subpopulation and its closest match in the G primary tumor). This can identify drugs targeting MR associated with metastatic progression processes, as shown in. Standard approaches for measuring dose response curves in the engineered system, in target and control cells can be used to test drug activity.
We tested the drug Linsitinib—a potent tyrosine kinase inhibitor targeting the IGF-1 receptor (IGF-1R) —in metastatic and non-metastatic OS models (
We developed two different organs-on-chips to evaluate anti-cancer drug efficacy (using a bioengineered human Ewing sarcoma tumor) and cardiac safety (using a bioengineered human cardiac tissue). Both organs were generated with human cells and characterized and validated before being exposed to linsitinib, a novel anti-cancer therapeutic agent, in isolated culture and within the novel platform with microfluidic perfusion.
In another embodiment of the system, a PDMS-free, modular and integrated two-tissue system 2400 is provided.
In one embodiment, the system has four main components: (i) the platform with tissue chambers and medium reservoir, (ii) first and second housing clamps, (iii) an o-ring, and (iv) a glass slide or plate at the bottom (
The system may utilize a single channel of a peristaltic pump to recirculate the media at a desired flow rate and shear stress (
The system sterility was confirmed by 4-week incubation with soybean casein digest medium that is specific for the growth of aerobic bacteria and fungi.
In some embodiments, the central piece of the bioreactor platform is made of polysulfone, which is a tough, stable, and biocompatible thermoplastic polymer that does not absorb hydrophobic molecules and is being used for the fabrication of new organ-on-a-chip platforms. Fluorescein isothiocyanate (FITC), a small molecule, hydrophobic, fluorescent dye, was circulated for 72 hours, without any measurable absorption by the platform, as compared to multi-well plates (
The computational fluid dynamics software CoBi was used for simulations of linsitinib transport across the porous nylon mesh membranes separating the individual tissue chambers and flow channel. CoBi has been used previously to simulate drug analog transport in the eye and air flow in the lung.
We found that linsitinib introduced into the circulation at a 3.3 mL/min flow rate reached uniform concentration between the connection channel and both tissue chambers within 12 hours, and that it diffused into the tissues within 6 hours (
We also circulated fluorescent FITC, which has similar chemical properties as linsitinib including hydrophobicity and molecular weight, and measured its distribution across the 2 tissue chambers in the platform (
In the platform, the tissues are cultured with a transwell located at the bottom of the chamber. Because of the location of the transwell, it was difficult to visualize the tissue with the inverted microscope we had available in our lab. Thus, we created an in-house microscope with an upright objective (Mitutoyo Inc., Magnification: 2X) and a working distance of 34 mm allowing visualization of the tissue (
Both types of primary ES tumor cells for our models: metastatic (SK-N-MC cell line) and non-metastatic (RD-ES cell line) maintained their native-like tumor morphology and expression of the ES cell marker CD99, following cultivation within engineered bone tissues (
Gene expression analysis by qRT-PCR of linsitinib target IGF-1R in TE-ES models revealed levels similar to those in engineered bone controls (
Both in the bloodstream and in the tissues, the IGF binding protein (IGFBP) family has a high affinity for the IGF-1 ligand, thus being a critical regulator of the IGF-1R signaling pathway. For this reason, any predictive drug studies of IGF-1R inhibitors would need to be conducted at native-like concentrations of these binding proteins. Proteomic analysis of secreted IGFBPs showed significantly higher expression of IGFBP-1, 3, and 6 in both the TE-ES models and engineered bone tissue as compared to the corresponding tumor cell monolayers, which showed only traces of IGFBP (
The cardiac tissue model was generated from iPS-derived cardiomyocytes and fibroblasts encapsulated in fibrin hydrogel, as in our previous studies. The tissue was formed between two elastic pillars causing cell elongation and alignment, and subjected to electrical stimulation to synchronously contract and work against the pillars. The tissues were matured over 4 weeks of culture, and validated by exposure to drugs with known cardiac effects.
When exposed to caffeine, an inducer of ryanodine receptor-mediated calcium release with tachycardic side effect, cardiac tissues demonstrated physiologic increases in beat frequency (
When exposed to doxorubicin, a chemotherapeutic with known and well documented cardiotoxic side effects (initial sinus tachycardia, supraventricular tachycardia, chronic dilated cardiomyopathy), the beat frequency initially increased, and then decreased following prolonged exposure to the drug (
The Phase II clinical trial of linsitinib administered for 3 weeks at the blood plasma concentration of 12 µM to patients with refractory or relapsed ES served as a basis for this study. To assess the drug efficacy and safety, we studied the engineered tissues under the same drug regimen used in the clinical study. We first confirmed the maintenance of engineered bone tissue environment over the entire duration of tumor maturation and drug treatment (5 weeks).
Immunohistochemical (IHC) staining of TE-ES samples showed sustained expression of functional osteoblast markers osteocalcin and bone sialoprotein (
In ES cell monolayers, MTT viability assay resulted in the IC50 for linsitinib that was two orders of magnitude lower than the effective plasma concentration observed in patients (
Having determined that luminescence of the transduced cancer cells could serve as a reliable indicator of ES cell viability in monolayers, we next verified that this method can be used for the TE-ES models, by exposing the non-metastatic TE-ES to 1 µM of doxorubicin for 72 hours (
The effects of linsitinib were studied in an experiment performed according to the 3-week treatment cycle used in the clinical trial (3 days of drug administration followed by 4 days without the drug, in 3 cycles), with luminescence signal serving as an indicator of cancer cell viability within the TE-ES. A dose-dependent response was observed for the non-metastatic TE-ES model, with significant reduction in cell viability at linsinitib concentration of 12 µM (Fig). TUNEL assay showed increases in apoptosis, corroborating the luminescence viability findings (Fig).
In order to better understand the linsitinib response for metastatic and non-metastatic tumors, luminescence signals were measured following 3, 7, and 21 days of treatment. Already after 3 days, a significant drug response was observed in both TE-ES tumor models, just as it has been observed in monolayers of cancer cells (
Determining the effects of linsitinib on ES cells and osteoblasts within the engineered ES bone tumors across a 3-week clinical drug treatment regimen is shown in
Lactic acid dehydrogenase (LDH) secretion indicated that cytotoxicity spiked in both models immediately following drug administration, but significantly more so in the responsive, non-metastatic ES model (
After establishing the capability of TE-ES tumors to model drug efficacy, we evaluated the ability of cardiac tissues to determine the cardiotoxicity of linsitinib. Cardiac tissues were exposed to the same therapeutic concentration of linsitinib as bone tumors. The cardiac model responded with increased beating frequency after 3 days of exposure to the drug. Cardiotoxicity of linsitinib has been observed in clinical trials of other types of cancer, with patients presenting proarrhythmic events, like tachycardia (3.75-5 % of patients) and atrial fibrillation (3.75 - 5 %). We observed higher beat frequency and higher rate of proarrhythmic events per beat (around 36%) than in clinical studies (
Overall, when bioengineered cardiac tissues were exposed to linsitinib in an isolated setting, we observed induction of tachycardia, proarrhythmic events, and altered physiological responses to isoproterenol. The occurrence of proarrhythmic events at a rate higher than seen clinically, and the increased sensitivity observed for beat frequency and isoproterenol response suggest that this model on its own fails to predict clinical responses. The same can be said for the non-metastatic TE-ES model, which showed significant drug response for the duration of the 3 weeks drug treatment regimen despite the lack of success in the Phase II clinical trial.
In patients, bone tumor and cardiac tissue do not exist in isolation, and are not necessarily exposed to the same drug concentrations. Tissue-tissue communication would further increase the physiological relevance of these models. Towards this goal, and in order to demonstrate that an integrated model (with the tumor and cardiac tissues connected by microfluidic perfusion) is more physiologically relevant for predictive drug screening, we studied the effects of linsitinib on the heart and bone tumor tissues simultaneously cultured and exposed to the drug in the integrated platform.
First, we determined the effects of the combined culture medium (1:1 mixture of bone tumor and cardiac media in the platform) on each engineered tissue. Importantly, the base media for both tissues are identical, except for one supplement (fetal bovine serum or B-27™) To this end, we cultured the non-metastatic TE-ES tumor (which responded to linsitinib treatment and therefore deviated from the clinically relevant observations) in bone tumor media (isolated culture), 1:1 mixed media (integrated platform), and in cardiac media (as a control) for the duration of the clinical drug treatment regimen (3 weeks).
No significant differences were observed in the osteoblast bone niche, and the osteocalcin levels were also similar for the bone tumor media and the mixed media (
The TE-ES models with mixed media were subjected to the same 12 µM linsitinib treatment regimen as the isolated cultures. Luminescence readings of cancer cell viability within the engineered tissues showed that despite significant increases in cancer cell proliferation in the mixed media, the drug was still effective at killing cancer cells and maintaining their population at a significantly lower level (~30 % of their starting population) (
Engineered cardiac tissues in mixed media showed no change in beat frequency (
The TE-ES and cardiac tissues were then cultured in the integrated platform with perfusion of mixed media. Linsitinib was introduced into the reservoir and delivered to tissues via circulation of perfusate and diffusion into the tissues.
Following 3 days of treatment, luminescence signals from the engineered non-metastatic ES bone tumor tissues revealed insignificant drug response (as observed in clinical studies) and in contrast to both the monolayer cell cultures and isolated TE-ES culture (
ES cells, when co-cultured with mesenchymal stem cells and exposed to physiological shear-stress in a perfusion bioreactor, can become resistant to IGF-1R inhibitors. Therefore, we evaluated the role of flow derived shear stress in this newly found resistance of non-metastatic TE-ES bone tumor tissues to the IGF-1R inhibitor linsitinib. Linsitinib was introduced into the platform (12 µM, 3 days), either via circulation or directly into the TE-ES tissue chamber (
In the cardiac tissue model, we did not observe linsitinib-mediated changes in beat frequency, suggesting that the occurrence of false responses was reduced (
Overall, in the integrated platform, linsitinib induced no change in beat frequency, was associated with a rate of proarrhythmic events similar to clinical data, and retained the physiologically healthy response to isoproterenol, suggesting mild cardiotoxicity.
The potential of the platform we present here is in their ability to better agree with clinical results than the traditional preclinical models. The integrated platform contained the Ewing sarcoma tumor (formed by introducing primary cancer cells into the engineered human bone) and the engineered human cardiac muscle (formed by electromechanical conditioning of iPS-derived cardiomyocytes and supporting fibroblasts in fibrin gel), connected by microfluidic circulation. This platform recapitulated unexpected results of a Phase II clinical trial of linsitinib, a small-molecule tyrosine kinase inhibitor of the insulin-like growth factor receptor (IGF-1R).
The platform design allowed real-time in situ monitoring of cancer cell growth and simultaneous assessment of the drug efficacy and cardiotoxicity. The platform’s flexibility and ease of use allow the design to be tailored to the questions being asked.
Also, the use of polysulfone as the main device fabrication material (instead of the widely utilized PDMS) avoids uncontrollable absorption of hydrophobic compounds, which most chemotherapeutics are. The open setting also allows for imaging and sampling of tissues and culture media.
Referring back to
The biological fidelity of the engineered tumor and heart tissues was documented by a battery of the known responses to standard drugs. We also demonstrated clear advantages of engineered tissues over the monolayer culture, and of the tissues connected by microfluidic circulation over isolated tissue culture in recapitulating clinical data.
Breast tumor biopsies are digested with collagenase, and isolated BC cells are embedded within Cultrex® basement membrane matrix for expansion as organoids in 3D culture. Organoids made using these protocols have demonstrated a high degree of biological fidelity to their corresponding native patient tumors. Followingly, we have built an in-house panel of HR+ and TNBC patient-derived organoids.
Morphologically, a majority of BC organoids matched the histopathology and hormone receptor status of their donors. The patients’ genetic diversity was also largely captured by these organoids, which recapitulated key copy number alterations, mutational load and signatures, and mutations in well-established cancer driver genes. When gene expression profiles of BC organoids were compared to those of >1,100 BC from The Cancer Genome Atlas (TCGA), they clustered with the corresponding subtypes. Importantly, it was shown that the BC organoids responded to drug screening in predictable ways, namely with HER2+ organoids being significantly more sensitive to drugs blocking the HER signaling pathway and organoids with high BRCA½ signatures being more responsive to Poly(ADP-ribose)polymerase inhibitors (PARPis) that haven proven successful in patients with such a defective pathway. Missing thus far is a comprehensive comparative gene expression and clonal development analysis between the organoids and matched patient samples. To generate BC organoids for such analysis, we can continue to rely on biopsies of primary and matched metastatic sites of chemo-naive patients (metastatic at diagnosis), with focus on HR+ tumors (that metastasize to bone, liver, lung), and TNBC tumors that prevalently metastasize to lung. As controls, we can analyze patient-matched normal breast tissue.
Validation Engineered tumors can be validated against native tumors via scRNAseq, mutational and exome profiling, IHC, metabolic, and secretome analyses.
Anticipated results, potential difficulties, and alternate approaches: We can use native tumor benchmarks to show that engineered tumors recapitulate key hallmarks of metastatic progression, including expression of proliferative and metastatic markers. We expect that breast tumor progression can increase as a function of matrix stiffness and angiogenesis. Given our previous success with these models, challenges may be limited to isolation of well-defined cell populations from primary tumors. Rigorous characterization of these cells can be performed to understand any aberrant behavior of the bioengineered models due to phenotypic heterogeneity. If extended tumor culture (>4 weeks) poses challenges, we can adjust perfusion conditions to improve long-term control of nutrients, oxygen and regulatory factors.
Vascularization The generation of a patient-specific vascular barrier is critical for functionally connecting tissue compartments while maintaining each tissues, as well as vascular perfusion, under optimal culture conditions resulting in phenotypic stability and maturation, analogous to the separation of interstitial and intravascular compartments in vivo. Transwell mesh inserts in each tissue chamber were coated with fibronectin and seeded with ECs and supporting MSCs with 2:1 ratio (
To physiologically integrate circulating metastatic BC cells and host tissues by vascular flow (first using primary cells and BC cell lines, then matched patient-derived BC cells and iPSC-derived tissues), they can be connected in modular format by placement into chambers above the endothelialized membrane that separates tissue and vascular media, thus enabling vasculature-mediated tissue crosstalk (
Modeling extravasation and survival of circulating BC tumor cells (CTC): Cancer progression and treatment depend on the tumor cell ability to migrate to distant sites, and on drug transport from vascular circulation to these sites. Blood vessels have dynamic and heterogeneous barriers that select which entities can pass through. Vascular permeability is regulated by the EC lining of the vessels, serving as a gatekeeper for the exchange of cells and molecules between tissue and blood, and it also influences the maximum achievable drug concentration in primary and secondary tumors. Previous studies have shown that tumor cells increase endothelial permeability, suggesting its role in intra/extravasation. By tracking labeled CTCs, we can be able to study the mechanistic role of the vascular barrier in metastasis. We can initially use HR+ and TNBC cell lines labeled with fluorescent and bioluminescent tags and infused into the circulation to study their extravasation through the endothelial barrier and seeding into host tissues. Important variables can be BC cell line used, the host tissue type, order of vascular flow through the platform, and endothelial permeability.
Preliminary studies support the critical role of the endothelial barrier for selective metastatic homing of circulating TNBC cells. In its absence, luminescent TN MDA-MB231 BC cells non-selectively colonized all host tissues, and at a pace that is physiologically irrelevant (data not shown), demonstrating the importance of a physiological vascular barrier to ensure host tissue maturity and faithfully recapitulate metastatic extravasation and homing of tumor cells into target tissues. Moreover, we showed that homing to specific host tissues relies on more than just tissue specific media and tissue-derived ECMs, as this leads to non-specific accumulation in all tissues including the negative control heart tissue (data not shown). In fact, we only observed physiologically relevant metastatic progression when using a combination of a functional vascular barrier and mature primary cell derived tissues within our integrated perfused platform, suggesting that secretion of target-specific chemo-attractants (chemokines, cytokines, extracellular vesicles) is critical for this process (
Proliferation of metastasized breast cancer cell lines within their target tissues: Based on our preliminary results, we hypothesize that continued culture would allow for growth of the surviving metastasized cells to an extent amenable to their further investigation, including by re-isolation, scRNAseq, and subsequent drug targeting . We can establish luminescence-based online readout of metastasized BC cell populations, based on methods already in use for in vivo mouse xenotransplants. We can also vary the cellular complexity of engineered host tissues and assess which stromal environments favor metastatic cell homing, by evaluating a variety of stromal cells (tissue-specific endothelium, fibroblasts, and stroma; tissue-resident macrophages). We have previously demonstrated that supporting cells, including EC and MSC, mediate metastatic homing of breast cancer cells into bone, and can thus characterize the effects of angiogenic factors (VEGF, FGF, EGF) on metastatic cell homing. Given our established functional cardiac tissue, we can investigate why cardiac tissues may not support metastatic growth (e.g., due to the heart beating or unique secretome signature), with possible new insights that may have therapeutic potential. Also, we have recently introduced into our multi-tissue platform the circulating immune cells (monocytes, macrophages), and showed their ability to penetrate through endothelial barriers into the tissues (e.g., following cryo-injury or inflammation,
Recapitulation in vitro of the targeted BC metastasis already observed in vivo: From a bioengineering validation perspective, a major weakness of the TN MDA-MB231 BC cell line is its ability to disseminate non-specifically, across a wide variety of tissue models (liver, lung, bone, brain). We can thus also rely on tissue-specific metastatic TNBC cell lines that have been shown to selectively target either the lung or the bone, when injected into tail veins of mouse xenotransplants. Bioluminescent lung targeting LM2 and bone targeting BoM-1833 variants of the MDA-MB231 cell line, kindly provided to us by the pioneering J. Massague lab through an MTA, can be introduced into circulation within our integrated tissue platform and their dissemination to the appropriate target tissues can be monitored. Extravasated LM2 and BoM-1833 cells can be sequenced for gene expression and compared to the results found in vivo. Additionally, we can use the approach used by the Massague lab in mouse models to establish tissue specific cell sub-lines but within the in vitro human tissue context. Therefore, we can isolate the extravasated MDA-MB231 cells from lung and bone tissues and re-introduce them into circulation to determine whether they have gained target specificity (i.e. if those isolated from bone would preferentially target bone). Gene expression profiling can be performed on these extravasated cells to determine phenotypic changes linked to tissue specific metastasis, such as to genes like ADAMTS1, FGF5, FST, PRG, CTGF, IL11, MMP1 and CXCR4 that have been shown to govern bone extravasation.
Generation of the “patient on a chip” in vitro model of BC metastasis: We have already demonstrated in our previous and preliminary studies the capability for generating a broad range of human tissues from iPSCs and for modeling metastatic progression in vitro using cell lines. A patient-specific platform, with tunable mechanical and biochemical host tissue properties, can allow investigation of preferential metastasis of fluorescently labeled patient tumor cells into lung, liver or bone, but not into the heart. Boyden chamber style transendothelial migration assays can be initially be used to screen the patient cells for their intravasation and extravasation potential prior to both their introduction to the multi-tissue platform and to the development and integration of iPSC-derived host tissues. For intravasation studies, we can culture the patient-derived BC organoids in a basement membrane based 3D tumor model that can be integrated by vascular perfusion to the engineered host tissues. Intravasation of tumor cells can be monitored by tracking fluorescently labeled tumor cells, and the extent of intravasating tumor cells and their lifetime in circulation can be assessed. The potential extravasation of these cells in circulation into the target tissue chambers can then be monitored and quantified for different patients of HR+ or TNBC breast tumor subtypes.
We can further manipulate physicochemical properties of the host tissues (for example ECM stiffness) to mimic organ conditions in high-risk patients (age, inflammation), and study their effects on CTC seeding efficiency and specificity. The cells that invade the host tissues can be characterized by single-cell RNA sequencing, to determine their phenotypes associated with metastatic seeding into the specific host tissues.
Investigating the cellular subpopulation most likely to metastasize, via track-labeling and scRNASeq profiling in the engineered platform, can enable characterization of “pro-metastatic” cell phenotypes within the heterogeneous populations derived from the tumor and perhaps across the heterogeneous patients. These data can serve as input for elucidation of novel targets and pathways, and for predicting therapeutic treatment options. The pathology of host tissues colonized with tumor cells can be characterized by histology/IHC staining, and compared with clinical specimens. We can also conduct secretome analyses for tumor-specific metastasis-driving EVs before and after the organoid-grown tumor cells are introduced into the circulation, and before and after homing, to understand what signaling events could underlie the metastatic phenomena. To validate the model, we can benchmark metastasis in the platform with the metastatic bone tumors from patients, and evaluate the tissue specificity and colonization potential of metastatic cells.
To characterize the biological relevance of bioengineered tumors, tissue from both primary and metastatic site can be dissociated, exome/RNA-Sequenced, and compared to patient-matched surgical samples. To demonstrate the utility of the “cancer patient on a chip” for systems biology studies, we can experimentally test OncoTreat-predicted drug responses as inferred by meta VIPER.
Large-scale single-cell analysis for tumor model validation, tracking metastatic populations and inferring drug responses. Throughout the proposed studies, we can take advantage of recent advances in large-scale scRNASeq for three main purposes: (a) Validation and study of primary tumor model; (b) Analysis of metastases in host tissues (bone, liver, lung); and (c) Inferring single-cell-specific drug sensitivity for primaries, CTCs, and metastases by OncoTreat analysis. We have established a computer-controlled microfluidic platform for scRNASeq that can parallel-profile ~10,000 cells with rapid, high-efficiency cell capture (>50%), using optical microscopy for on-chip analysis of markers, cell viability, and cell lysis.
The device has a simple flow cell with an array of insertable devices, i.e., microwells on a glass slide. Typically, one cell per microwell is gravity-loaded, followed by loading of polymer beads coated with oligonucleotide primers that contain a universal adapter sequence, a bead-specific barcode sequence, a unique molecular identifier (UMI), and oligo(dT) for mRNA capture. Cell lysis and reverse transcription occur automatically, following introduction of strongly denaturing lysis buffer and a perfluorinated oil to seal the array. On-chip fluorescence imaging facilitates control of cell viability, lysis, sealing, and counting. Following mRNA capture, we introduce a detergent-containing buffer to rapidly remove sealant and lysate, such that barcoded beads with hybridized mRNA are exposed, allowing reverse transcription to occurs automatically. cDNA-coated beads are pooled, harvested, and 3′-end RNA-Seq libraries are generated using the SCRB-Seq protocol and the Nextera transposition system (Illumina), at a cost as low as $0.05/cell.
We sequence the pooled libraries with paired-end sequencing, where the first read contains both the cell-identifying barcode and a unique molecular identifier (UMI) barcode, and the second read contains transcript sequences. For the proposed studies, we can align read two to the human genome using the STAR aligner with a transcriptome annotation, to take advantage of its splice-awareness. By combining the alignment with the forming barcode in the first read, we assign an address to each read that aligns uniquely to a locus that can be unambiguously assigned to an annotated gene. Given the strand-specific nature of the libraries, strand information can be used to ensure proper alignment. The address includes the read ID, cell-identifying barcode, UMI, and gene symbol. This algorithm gives us an estimate of the number of captured mRNA molecules associated with each gene in each cell.
We have also developed a computational pipeline for scRNASeq data analysis that includes unsupervised clustering, data visualization, and differential expression. “Drop-out” events, i.e., genes present in a given cell may be undetected, are exploited to identify markers of cell subpopulations, because genes detected in fewer cells than expected are likely markers of specific cell subpopulations. Using “drop-out” analysis for unsupervised identification of markers, we can generate a correlation matrix that is then used to identify clusters of cells with similar patterns of gene expression. These clusters can be visualized using various methods, including t-stochastic neighborhood embedding (t-SNE), UMAP, and diffusion component analysis.
Once single-cell clustering is completed, we can conduct differential expression and meta VIPER analysis to identify cross-compartment cellular subpopulations with conserved gene expression or protein activity signatures. While gene expression clustering is useful to identify molecularly distinct subpopulations, it is less adept at capturing quantitative gene expression differences between cells. For this, we can employ the SCDE algorithm that models the over-dispersion in scRNASeq counting data with the negative binomial distribution, as in bulk RNA-Seq, but also integrates a Bayesian probabilistic treatment of transcript drop-out. MR dependencies can be validated by pooled, barcoded CRISPR/Cas9 silencing of top candidate MRs in the population of interest, and by measuring depletion of barcoded cells in the progressed populations.
Sample preparation can be technically challenging, due to incomplete dissociation, low viability, and low-quality RNA. Our microfluidic system allows diagnosis of dissociation quality and viability on-the-fly. However, issues with a sample type or component are encountered, single-nucleus RNA-Seq is an alternative approach compatible with the device, which accommodates the lysis conditions required to disrupt nuclei, and circumvents.
The main manifold of the platform was machined using a 3-axis computer numerical control (CNC) milling machine from polysulfone and incorporated reservoirs for individual tissues and an additional reservoir and fluidic ports for circulating media. The connection channel was defined by a recessed slot within the main manifold and was sealed against a glass slide with machined polycarbonate clamps and an o-ring gasket. Each tissue reservoir was separated from the recirculation channel by a polypropylene insert over-molded onto a nylon mesh porous membrane. The membrane insert itself created a seal with the main manifold through the use of an elastomer o-ring. The plugs used to isolate tissue chambers (for culture in isolation) were machined from polycarbonate to create a seal via a fluoroelastomer o-ring.
The platform was connected to a peristaltic pump with a luer taper connector, with media flowing underneath through the connection channel. The media exited the channel into a reservoir, which also functions as a bubble trap. The reservoir was connected to the pump with a luer taper connector. PharmaMed pump tubing (Cole Parmer) routed the media back to the peristaltic pump (Cole Parmer) for recirculation.
To platform was contained within a 100 mm polystyrene dish that incorporated a secondary spacer between the dish and the lid to pass tubing in and out of the assembly without introducing gaps that would compromise sterility.
Software and equipment used for machined components include Solidworks for 3D design, Mastercam for toolpath generation, and a Haas OM2 3 axis milling machine for physical manufacturing. Polycarbonate and polysulfone materials were sourced from McMaster-Carr. For injection molding of porous membrane inserts, nylon meshes were sourced from Millipore, polypropylene pellets (Flint Hills Resources P9M7R-056) sourced from PolyOne Distribution, and molds were machined in aluminum using above fabrication equipment. Nylon mesh inserts were cut using a 40 W CO2 laser cutter and inserted into the mold. Injection molding was performed on an AB-200 Semi-Automatic Plastic Injector (AB Machinery).
The customized microscope was assembled on an optical breadboard (12″ × 12″). The system includes a 2X plan apochromat objective lens that allows a lager field of view, a CMOS monochromatic camera, and exchangeable LED light sources. The camera is mounted vertically on a motorized optical rail that enables focus of different horizontal plains of the tissues with enhanced precision. The LED light source provides either a white light or a light with a specific wavelength when coupled with an optical filter allowing bright-field or fluorescent imaging. All optomechanical components were obtained from Thorlabs, while the objective lens was purchased from Edmund Optics.
The platform was incubated for 4 weeks, at 25° C., with Soybean casein digest medium (SCDM), an aerobic bacteria and fungi specific medium. After the incubation period, any changes in the medium turbidity and the presence of microorganisms were assessed.
Human iPS cells were obtained through material transfer agreements from B. Conklin, Gladstone Institute (WTC11 line), maintained in mTeSR™1 medium (STEMCELL Technologies), supplemented with 1% penicillin/streptomycin, changed on a daily basis, on 1:60 growth-factor-reduced Matrigel (Corning) and passaged when 85-90 % confluent using 0.5 mm EDTA (Invitrogen). For the first 24 hours after passaging, the culture medium was supplemented with 5 µm Y-27632 dihydrochloride (Tocris).
Human mesenchymal stem cells (MSCs) were isolated from commercially obtained fresh bone marrow aspirates (Cambrex) by attachment to the plastic surface, as previously described. Cells were expanded to the fourth passage in mesenchymal stem cell medium consisting of high glucose Dulbecco’s modified Eagle’s medium (DMEM; Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (FBS; Thermo Fisher Scientific), 1% penicillin-streptomycin (Life Technologies), and 0.1 ng/ml bFGF (Life Technologies).
The metastatic SK-N-MC (HTB-10) and non-metastatic RD-ES (HTB-166) ES cell lines were purchased from the American Type Culture Collection (ATCC). SK-N-MC cells were cultured in Eagle’s Minimum Essential Medium (EMEM; ATCC) and RD-ES cells were cultured in RPMI-1640 Medium (ATCC), according to the manufacturer’s specifications. Both culture media were supplemented with 10% FBS and 1 % penicillin/streptomycin.
All cells were maintained at 37° C. and 5% CO2 in Heracell 150 incubators (Thermo Fisher Scientific). The cultures were maintained with 2 ml of medium per 10 cm2 of surface area and were routinely checked for mycoplasma contamination using a MycoAlert Plus Kit (Lonza). Pluripotent cells were routinely checked for expression of pluripotent markers.
A LentiSuite for HIV-based system (System Biosciences) was used according to the manufacturer’s instructions to generate stable CMV-GFP-T2A-Luciferase vector expressing ES (SK-N-MC and RD-ES). Briefly, HEK-293T (CRL-3216) cells were transfected with lentiviral and the GFP-Luciferase vector of interest, viral particles were purified and concentrated using a PEG-it Virus Precipitation Solution (System Biosciences). Cancer cell lines were transduced with the virus at MOI = 10 using Lipofectamine 3000 reagent (Thermo Fisher Scientific), according to the manufacturer’s protocols. GFP+ transduced cancer cells were selected and sorted for using an Influx cell sorter (BD Biosciences) in collaboration with the Columbia Center for Translational Immunology (CCTI) Flow Cytometry Core at Columbia University Irving Medical Center.
Decellularized bone scaffolds were generated using a previously established protocol 50 and cut into 2 mm thick axial sections. Sections to fabricate scaffolds were cleaned under high-pressure water beam, dried, and machined using a standard two-flute endmill to the final geometry of 6 mm × 3 mm × 1 mm (length x depth x thickness). To remove cellular material, the scaffolds were subjected to serial washes in 0.1 % EDTA in phosphate-buffered saline (PBS; Santa Cruz Biotechnology), 0.1 % EDTA in 10 mm Tris, and 0.5% SDS in 10 mm Tris, and a solution of 100 U/mL DNase and 1 U/mL RNase in 10 mM Tris buffer. Scaffolds were thoroughly rinsed in deionized water and freeze-dried. The scaffolds were selected within the density range of 0.37-0.45 mg/mm3 where sterilized overnight in 70 % ethanol and conditioned in mesenchymal stem cell medium overnight before seeding with cells. To monitor the effectiveness of the decellularization protocol, DNA content of the bone before and after decellularization was quantified using Quant-iT™ PicoGreen™ dsDNA Assay Kit (Thermo Fisher Scientific) following the manufacturer’s protocol.
Using an established protocol, expanded MSCs were seeded into the bone matrix scaffolds at a concentration of 106 cells per scaffold, using 40 µL of medium. The cells were allowed to attach for 2 hours, and then supplemented with additional mesenchymal stem cell medium overnight. After 24 hours, osteogenic differentiation was initiated by addition of low glucose DMEM supplemented with 1 µm dexamethasone(Sigma-Aldrich), 10 mm β-glycerophosphate (SigmaAldrich), and 50 µm L-scorbic acid-2-phosphate (Sigma Aldrich). Each scaffold was incubated in 4 mL of osteogenic media, with media changes 3 times a week, for 3 weeks, allowing MSCs to differentiate into functional, maturing osteoblasts.
Two weeks following the initiation of osteogenic differentiation, aggregates of ES tumor cells were prepared as described previously, using 0.3 × 106 cells per aggregate. After 1 week of culture, corresponding to the end of bone tissue culture (3 weeks), the primary ES cell aggregates were placed into the engineered bone constructs (3 aggregates per construct, placed apart of each other). Tumor models were established for two different types of primary ES cells: non-metastatic (RD-ES) and metastatic (SK-N-MC). Tissue engineered RD-ES and SK-N-MC tumors were cultured in the RPMI and EMEM media, respectively, supplemented with 10% FBS and 1% penicillin/streptomycin. Bone constructs cultured without tumor cell aggregates (TE-bone) in RPMI and EMEM media were used as controls.
Upon maturation, bone tumors in the platform were exposed to a 1:1 mixture of the bone tumor and cardiac tissue media, supplemented by 12 µM linsitinib in the treated groups. Two experimental conditions were systematically compared: isolated culture (no communication between the tissue chambers) and integrated culture (tissue chambers connected by microfluidic perfusion).
Using a previously established protocol, cardiac differentiation of human iPS cells was initiated in 90% confluent cell monolayers by replacing the mTeSR™1 medium with CDM3 (chemically defined) medium with 3 components: RPMI Medium 1640 (1X, Gibco), 500 µg/mL of recombinant human albumin (Sigma-Aldrich) and 213 µg/mL of L-Ascorbic Acid 2-phosphate (Sigma-Aldrich)), supplemented with 1% penicillin/streptomycin.56 Medium was changed every 48 hours. For the first 48 hours, medium was supplemented with 3 µm of glycogen synthase kinase 3-b inhibitor CHIR99021 (Tocris). On day 2, the culture was switched to CDM3 medium supplemented with 2 µm of the Wnt inhibitor Wnt-C59 (Tocris). After day 4 of differentiation, medium was changed to CDM3 with no supplements. Contracting cells were noted around day 10, when medium was changed to RPMI 1640 supplemented the with B-27™ (50X; Gibco) and were used in experiments without selection for cardiomyocytes.
Using a methodology established in our previous studies, cardiac tissues were formed between two elastic pillars (1 mm in diameter, 9 mm in length, 6 mm axis-to-axis distance) that were over-molded onto a polycarbonate support frame. The pillars were formed using Delrin (polyoxymethylene) molds fabricated by CNC machining. PDMS was centrifugal casted at 400 relative centrifugal force (RCF) for 5 minutes through the polycarbonate support structures inserted into the molds. After centrifugation, PDMS was cured in an oven at60° C. for 1 hour and used at a 10:1 ratio of silicone elastomer base/curing agent. The resulting component pair of pillars to support the formation of one tissue, was inserted into the platform chamber by press-fitting. An array of 6 reservoirs accommodates formation of 6 individual pillar/tissue modules.
Human iPS cell-derived cardiomyocytes at day 13 of differentiation were combined with normal human dermal fibroblasts (NHDF; Lonza) at a ratio of 75% human iPS-derived cardiomyocytes and 25 % NHDF, for a total of 1 million cells per tissue. The hydrogel was formed by mixing 33 mg/mL of human fibrinogen (Sigma-Aldrich) with 25 U/mL of human thrombin (Sigma-Aldrich), at an 84:16 ratio. The cell suspension in hydrogel was dispensed into each well and allowed to polymerize around the pillars at 37° C. for 15 minutes before adding RPMI Medium 1640 supplemented with B-27™ containing 0.2 mg/ml aprotinin (Sigma-Aldrich).
Tissues were formed by inserting the pillars into a formation reservoir (9 mm length × 3.2 mm width × 4.3 mm depth) and can be filled with 100 µL of cell suspension in hydrogel. Hydrogel compaction caused passive tension of the tissues stretched between the two pillars, inducing elongation and alignment. Medium was changed every other day and supplemented with 0.2 mg/ml aprotinin for the first 7 days. Cardiac tissues were transferred into the platform chambers and cultured in either isolation or integrated by perfusion.
To evaluate drug transport in the blank platform, we performed computational fluid dynamics using a simultaneous finite volume solver (CoBi) that solves complex mass (continuity), momentum, energy, and drug conservation equations in two-dimensional discretization with heterogeneous properties (Equations 1-3)
The transport equations account for convection, diffusion, fluid-solid interaction, electrostatic drift and interfacial friction
where P is the pressure, t is time, p is the fluid density,
Transwell membrane porosity was calculated by definition:
where Vvoidis the void volume, and VTotal is the total membrane volume. Using manufactirer’s information for the total surface area, pore density, and pore size in the membrane, its porosity was calculated to 5%.
The Polson equation (Equation 5) was used to predict the diffusion coefficient:
where the parameters are dynamic viscosity (µ) at absolute temperature (T), and molecular weight (MW). Linsitinib diffusion in media in media was calculated to 4.4×10-10 m2/s.
Fluorescein isothiocyanate (FITC, 10 mM in DMSO; Sigma Aldrich) was circulated for the integrated platform to determine potential hydrophobic small molecule absorption, given its physical and chemical properties. FITC was added at a concentration of 10 µM to 8 mL of 1:1 bone tumor/cardiac mixed media and introduced into the platform. The control was the FITC-containing media in a standard 24-multiwell plate (Corning). Aliquots from the reservoir, bone tumor, and cardiac tissue chambers were taken at 12, 24, 48 and 72 hours and measured for fluorescent signal using a spectrophotometer (Biotek).
Measurements of FITC concentrations were used to estimate the spread of linsitinib within the platform via diffusive circulating transport. Four independent platforms were filled with 8 mL of 1:1 mixed media each, after which 10 µM of FITC was injected into the reservoir. The platforms were connected to the peristaltic pumps run at 100 rpm to generate physiologically relevant fluid flow rate and shear stress. Aliquots were taken from the reservoir, bone and cardiac chambers at 0, 2, 4, 6, and 12 hours post injection, and assayed for fluorescence signal on a spectrophotometer (Biotek).
Cardiac tissues were studied using caffeine (50 mM in water; Sigma-Aldrich), amiodarone hydrochloride (2.418 µM in DMSO; Sigma-Aldrich), isoproterenol hydrochloride (a series of drug concentrations in water; Sigma-Aldrich) or doxorubicin hydrochloride (1 µM in DMSO; Sigma-Aldrich), all diluted in RPMI Medium 1640 supplemented with B-27™. Response to isoproterenol was analyzed 10 minutes after exposure to 1 µm isoproterenol hydrochloride, diluted in RPMI Medium 1630 supplemented with B27™. ES bone tumor cell lines and tissues were studied using either doxorubicin hydrochloride (10 mM in water; Sigma-Aldrich), linsitinib (OSI-906) (10 mM in DMSO; Santa Cruz Biotechnology), all diluted in either non-metastastic media (RPMI Medium 1640, 10% FBS, 1% PenStrep) or metastatic media (EMEM, 10% FBS, 1% PenStrep). Specifically, linsitinib was dissolved at a 10 mM concentration in DMSO (Corning) and mixed in with the respective cell medium at a 12 µm concentration unless otherwise noted. Vehicle treatments involved just the addition of DMSO at identical volumes as a control. Tissues were randomly assigned to experimental groups. Medium was changed every day.
Tissue samples were washed in PBS, fixed in 10% formalin at room temperature for 24 hours, and decalcified for 24 hours with Immunocal solution (Decal Chemical Corp.). Samples were then dehydrated in graded ethanol solutions, paraffin embedded, and sectioned to 5-µm thick.
For immunohistochemistry, tissue sections were deparaffinized with CitriSolv (Thermo Fisher Scientific) and rehydrated with graded ethanol washes. Antigen retrieval was performed by incubation in citrate buffer (pH 6) at 90° C. for 30 minutes, while endogenous peroxidase activity was blocked with 3% H2O2. After washing with PBS, sections were blocked with horse serum (Vector Labs) and stained with primary antibodies overnight in a humidified environment. The primary antibodies used were polyclonal rabbit IgG to CD99 (1:500; ab108297), polyclonal rabbit IgG to Ki67 (1:100; ab15580), polyclonal rabbit IgG to osteopontin (1:500; ab1870), and polyclonal rabbit IgG to bone sialoprotein 2 (1:500, ab1854).
After washing with PBS, samples were incubated with anti-rabbit secondary antibodies for 1 hour at 25° C. and developed as described previously (Vector Laboratories) and counterstained with Hematoxylin QS (Vector Labs). The images of histological sections were obtained by digitizing the tissue sections using the Olympus dotSlide 2.4 digital virtual microscopy system (Olympus) at a resolution of 0.32 µm.
To assess apoptosis, paraffin embedded tissue sections were first deparaffinized with CitriSolv, rehydrated with graded series of ethanol washes, and then stained with a Click-iT® TUNEL Alexa Fluor® imaging assay (Thermo Fisher Scientific). Following nuclear counterstaining with DAPI (Life Technologies), the TUNEL labelled slides were imaged with an IX81 inverted fluorescent microscope (Olympus) and a Pike F032B camera (ALLIED Vision), using NIS-Elements AR software, and processed using ImageJ (NIH). Four representative images per condition were then analyzed using the previously developed automatic TUNEL cell counter plugin for ImageJ to quantify DAPI+ cells and TUNEL+ cells.
To view the transduced fluorescent bone tumor aggregates in situ, the TE-ES samples were captured using a Nikon A1 scanning confocal microscope on an Eclipse Ti microscope stand (Nikon Instruments, Melville, NY) using a 10x/0.3 Plan Fluor (Nikon) objective. The confocal pinhole was set at 1 Airy unit, to produce an optical section of approximately 17 µm. GFP was excited at 488 nm and emission was collected from 500-550 nm. Z series were collected through the depth of the tissue section and maximum projections renderings were generated using NIS Elements software (Nikon). Images were collected in the Confocal and Specialized Microscopy Shared Resource of the Herbert Irving Comprehensive Cancer Center.
Total RNA was isolated using Trizol (Life Technologies), following the manufacturer’s instructions. RNA preparations (2 µg) were treated with a High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems) to generate cDNA. Quantitative real-time PCR was performed using Fast SYBR™ Green Master Mix (Applied Biosystems). mRNA expression levels were quantified applying the ΔCt method, ΔCt = (Ct of gene of interest - Ct of β-Actin). Primer sequences were those that have been previously reported.
To measure the cardiac contractility online, we took contractility videos of the tissues that were analyzed using the native MATLAB code we previously developed. Tissue contractility was measured by tracking the change in tissue area as a function of time. Acquired video frames were inverted and an automated intensity threshold was used to identify cell location in the video frame. First, a baseline time point in the video corresponding to a relaxed tissue state was selected. Absolute differences in cell area from the baseline frame were then calculated to create a time course of cell area changes over time. The resulting time courses were analyzed using a native MATLAB (MATHWorks) automated peak finding algorithm to determine locations of maximum cell contractions in the time profiles. Beat period lengths were determined from the length of time between the pairs of local maxima, and the beat frequencies were determined by inverting beat periods. The rate of proarrhythmic events was calculated by the ratio of the number of proarrhythmic events over the total number of beats.
Cell viability was analyzed using a previously established protocol.59 Cancer cell viability was measured for GFP-Luciferase labelled cancer cells using ONE-Glo luciferase substrate that was prepared according to manufacturer’s protocol (Promega). Samples were collected following 3, 7, and 21 days cycles of linsitinib treatment. Where noted, longitudinal cell viability was also assessed using luminescence, though at the cost of signal strength. Briefly, in vivo grade VivoGlo™ Luciferin (Promega) was made at a 200x stock concentration (30 mg/ml) in water, added to sample culture media at a 1:200 dilution, and scanned using a spectrophotometer (Biotek). Some of the IC50 values were determined using cell viability data generated using an MTT assay (RealTime-Glo™ MT Cell Viability Assay, Promega) that were analyzed according to manufacturer’s protocol.
Proteomic analysis of secreted IGF-BPs was performed using supernatants isolated from RD-ES and SK-N-MC monolayers as well as both non-metastatic and metastatic TE-ES samples. A Pierce™ BCA Protein Assay Kit (ThermoFisher) was used to quantify protein amounts across the samples, after which equivalent amounts were loaded and processed onto a Human IGF Signaling Array (RayBiotech) according to manufacturer’s instructions. The samples were shipped to RayBiotech for quantification.
In order to confirm linsitinib mechanism of action in ES cells, both RD-ES and SK-N-MC monolayers were treated with 12 µM linsitinib for 6 hours, lysed, measured for protein quantity using a Pierce™ BCA Protein Assay Kit (ThermoFisher), and loaded equally onto a Human Phospho-IGF1R ELISA (RayBiotech) to semi-quantitatively determine phosphorylated levels of the IGF-1 receptor, according to manufacturer’s instructions. Osteocalcin (OCN), osteopontin (OPN), and lactic acid dehydrogenase (LDH) secreted levels were all measured using a similar approach. Supernatants were isolated from controls and drug treated TE-ES and equal amounts were used in each assay according to the manufacturer’s instructions. For OCN a Human Osteocalcin QuantikineR ELISA (R&D Systems) was used, while for OPN it was a Human Osteopontin QuantikineR ELISA (R&D Systems). LDH secretion was determined using a Lactate Dehydrogenase Assay Kit (Colorimetric; Abcam).
Data were analyzed in Excel (Microsoft) and graphed in Prism (GraphPad). Data are presented as mean ± s.e.m. Differences between experimental groups were analyzed by unpaired, two-tailed Student’s t-test or two-way ANOVA with Bonferroni post-test. Significant differences defined by P < 0.05 for all statistical methods unless otherwise noted. No blinding or randomization was used.
In another aspect, present disclosure relates to an engineered bone marrow system to study a variety of human diseases, toxicity responses, and immune functions in vitro. Derived from multiple cell sources, we have engineered an all induced pluripotent stem cell (iPSC) bone marrow model comprised of osteoblasts, mesenchymal stem/stromal cells, endothelial cells, and hematopoietic stem and progenitor cells (HSPCs). Using decellularized bone, iPSC-derived cells, and fibrin hydrogels in combination, we are able to study the progression, proliferation, and differentiation of hematopoietic cells in an in vitro setting. In addition to iPSC-derived sources, we are able to create the same bone marrow model using primary human samples (see overview in
Referring to
The “organ on a chip” provies fast track for translation of tissue engineering. Mature tissues are maintained within their own special niches. We tested physiological responses to radiation and simulated microgravity. Themesurements of readation damge and responses to radioprotective agents. Individualized models using iPSC derived platforms were used. Drugs were dosed and radation according to predictd levels in space were tested. Then validation against pre-clincial modles (mice) and clinical outfcomes (astronauts) was attempted.
In the radiation studies, we included a control and photon sources at 2 Gy, 4 Gy and 6 Gy to bone marrow for two weeks.
This application is a continuation of PCT/US2021/033833, filed May 24, 2021 which claims the benefit of U.S. Provisional Application Nos. 63/028,945, filed May 22, 2020 and 63/030,660, filed May 27, 2020, the contents of each of which are incorporated herein in their entirety.
| Number | Date | Country | |
|---|---|---|---|
| 63030660 | May 2020 | US | |
| 63028945 | May 2020 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/US2021/033833 | May 2021 | WO |
| Child | 17992779 | US |
