Patent Application
20210283211
This application contains a Sequence Listing, which was submitted in ASCII format via EFSWeb, and is hereby incorporated by reference in its entirety. The ASCII copy, created on Feb. 26, 2021, is named 8198US01_SequenceListing.txt and is 5 KB in size.
Lung cancer is the most frequently diagnosed cancer and a leading cause of cancer-related deaths worldwide (Bray et al, 2018). Approximately 85% of patients have a group of histological subtypes collectively known as non-small cell lung cancer (NSCLC), of which lung adenocarcinoma (LUAD) and lung squamous cell carcinoma are the most common subtypes, followed by squamous cell carcinoma and less so, large-cell carcinoma (Salgia, 2016; Herbst et al, 2018). LUAD accounts for ˜40% of all lung cancers. These histologies possess different clinical characteristics, and there are potential differences in response to cytotoxic chemotherapies. Approximately 40-50% of patients with NSCLC will be diagnosed with advanced or metastatic disease and are not candidates for curative therapy. Recent advances have transformed lung cancer care with a percentage of patients receiving first-line tyrosine kinase inhibitors based on their genomic-informed markers (Tan et al, 2017). However, immunotherapy alone or in combination with platinum-based chemotherapy is now the recommended first-line treatment option for the remainder of these patients.
Cisplatin [Cis-diamminedichloroplatinum(II)] is a widely prescribed platinum-based compound that exerts clinical activity against a wide spectrum of solid neoplasms, including testicular, bladder, ovarian, colorectal, lung, and head and neck cancers (Galluzzi et al, 2012; Galluzzi et al, 2014). Cisplatin treatment is generally associated with high rates of clinical responses. However, in the vast majority of cases, malignant cells exposed to cisplatin activate a multipronged adaptive response that renders them less susceptible to the anti-proliferative and cytotoxic effects of the drug, and eventually resume proliferation. Thus, a large number of cisplatin-treated patients experience therapeutic failure and tumor recurrence. However, the exact mechanism(s) underlying the emergence of drug resistance remains poorly understood and a bewildering plethora of targets have been implicated in different cancer types. For example, in NSCLC alone, dysregulation of genes involved in cell cycle arrest and apoptosis namely, mouse double minute 2 homolog (MDM2), xeroderma pigmentosum complementation group C, stress inducible protein and p21 (Sarin et al, 2017), cytoplasmic RAP1 that alters NF-κB signaling, upregulation of antiapoptotic factor BCL-2 (Xiao et al, 2017), enhanced Stat3 and Akt phosphorylation, high expression of survivin (Hu et al, 2016), hypoxia factor HIF-1α and mutant p53 (Deben et al, 2018), have been implicated in cisplatin resistance. Furthermore, although changes in administration schedules, choice of methods, and frequency of toxicity monitoring have all contributed to incremental improvements, chemoresistance limits the clinical utility of cisplatin (Fennell et al, 2016). Therefore, there is a dire need for a deeper understanding of chemoresistance and the identification of prognostic and predictive markers to discern responders from non-responders.
In sum, certain potent chemotherapeutic agents such as cisplatin are used to treat a variety of solid tumors, including lung adenocarcinoma (LUAD). Unfortunately, almost all patients develop resistance to the drug in the long term. Therefore, there is a need in the field to resolve chemoresistance to expand the currently limited therapeutic options.
In one aspect, disclosed herein is a method of alleviating resistance to chemotherapy in a subject, the method includes administering to the subject a composition comprising one or more therapeutic agents that perturb the interaction between integrin β4 (ITGB4) and paxillin (PXN), e.g., by inhibiting the expression of ITGB4, PXN, or both. In some embodiments, the one or more therapeutic agents include an anti-ITGB4 antibody, an siRNA that inhibits ITGB4 expression, an anti-PXN antibody, and/or an siRNA that inhibits PXN expression. In some embodiments, the composition comprises one or more compounds selected from carfilzomib, ixazomib, and CUDC-101. In some embodiments, the subject suffers from one or more solid tumors. In some embodiments, the subject suffers from testicular cancer, ovarian cancer, cervical cancer, breast cancer, bladder cancer, head and neck cancer, esophageal cancer, lung cancer such as non-small cell lung cancer, mesothelioma, brain tumor and neuroblastoma. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to platinum-based chemotherapy. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to cisplatin or carboplatin.
In another aspect, disclosed herein is a composition for alleviating resistance to chemotherapy in a subject. The composition comprises one or more therapeutic agents that perturb the interaction between integrin β4 (ITGB4) and paxillin (PXN), e.g., by inhibiting the expression of ITGB4, PXN, or both. In some embodiments, the one or more therapeutic agents include an anti-ITGB4 antibody, an siRNA that inhibits ITGB4 expression, an anti-PXN antibody, and/or an siRNA that inhibits PXN expression. In some embodiments, the composition comprises one or more compounds selected from carfilzomib, ixazomib, and CUDC-101. In some embodiments, the subject suffers from one or more solid tumors. In some embodiments, the subject suffers from testicular cancer, ovarian cancer, cervical cancer, breast cancer, bladder cancer, head and neck cancer, esophageal cancer, lung cancer such as non-small cell lung cancer, mesothelioma, brain tumor and neuroblastoma. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to platinum-based chemotherapy. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to cisplatin or carboplatin.
In a related aspect, disclosed herein is a method of treating cancer in a subject, the method includes administering to the subject a chemotherapeutic agent, and a composition comprising one or more therapeutic agents that perturb the interaction between integrin β4 (ITGB4) and paxillin (PXN), e.g., by inhibiting the expression of ITGB4, PXN, or both. In some embodiments, the one or more therapeutic agents include an anti-ITGB4 antibody, an siRNA that inhibits ITGB4 expression, an anti-PXN antibody, and/or an siRNA that inhibits PXN expression. In some embodiments, the chemotherapeutic agent includes cisplatin and carboplatin. In some embodiments, the chemotherapeutic agent is administered at a reduced dose when administered in combination with the composition comprising the one or more therapeutic agents that perturb the interaction between integrin β4 (ITGB4) and paxillin (PXN) comparing to the dose of the chemotherapeutic agent administered alone. In some embodiments, administering the combination of the chemotherapeutic agent and the therapeutic agents that perturb the interaction between integrin β4 (ITGB4) and paxillin (PXN) achieves a synergistic effect. In some embodiments, the composition comprises one or more compounds selected from carfilzomib, ixazomib, and CUDC-101. In some embodiments, the subject suffers from one or more solid tumors. In some embodiments, the subject suffers from testicular cancer, ovarian cancer, cervical cancer, breast cancer, bladder cancer, head and neck cancer, esophageal cancer, lung cancer such as non-small cell lung cancer, mesothelioma, brain tumor and neuroblastoma. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to platinum-based chemotherapy. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to cisplatin or carboplatin.
In another aspect, disclosed herein is a method of detecting resistance to chemotherapy in a subject who is subjected to chemotherapy. The method entails measuring the expression level of ITGB4, PXN, or both in a sample obtained from the subject, and comparing the expression level of ITGB4, PXN, or both with the expression level of ITGB4, PXN, or both in a sample obtained from a healthy control, wherein an elevated expression level of ITGB4, PXN, or both comparing to the healthy control indicating resistance to chemotherapy in the subject. Alternatively, the method entails measuring the expression level of ITGB4, PXN, or both in a sample obtained from the subject before and after the subject is subjected to chemotherapy, and comparing the expression level of ITGB4, PXN, or both after chemotherapy with the expression level of ITGB4, PXN, or both before chemotherapy, wherein an elevated expression level of ITGB4, PXN, or both after chemotherapy indicating resistance to chemotherapy in the subject. In some embodiments, the sample is serum. In some embodiments, the sample is exosomes isolated from serum. In some embodiments, the expression level is measured by Western Blot. In some embodiments, the subject suffers from one or more solid tumors. In some embodiments, the subject suffers from testicular cancer, ovarian cancer, cervical cancer, breast cancer, bladder cancer, head and neck cancer, esophageal cancer, lung cancer such as non-small cell lung cancer, mesothelioma, brain tumor and neuroblastoma. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to platinum-based chemotherapy. In some embodiments, the subject has developed or is at an elevated risk of developing resistance to cisplatin or carboplatin.
This application contains at least one drawing executed in color. Copies of this application with color drawing(s) will be provided by the Office upon request and payment of the necessary fees.
Disclosed herein is a method of alleviating resistance to chemotherapy in a subject, the method includes administering to the subject a composition comprising one or more therapeutic agents that perturb the interaction between ITGB4 and PXN, e.g., by inhibiting the expression of ITGB4, PXN, or both. Also disclosed is a combinational therapy, comprising co-administration of a chemotherapy, e.g., a platinum-based chemotherapy such as cisplatin or carboplatin, and one or more therapeutic agents that perturb the interaction between ITGB4 and PXN such as carfilzomib, ixazomib, and CUDC-101. As used herein, “co-administration” means that the chemotherapeutic agent and the composition are administered simultaneously or within a short interval (e.g., within a few hours, a few days, or a few weeks) before or after the subject has developed or shows sign of resistance to chemotherapy. Moreover, the composition can be administered before or after administration of the chemotherapeutic agent.
This disclosure identifies a new therapeutic target and FDA-approved drugs that can potentially be repurposed to alleviate cisplatin resistance together with a minimally invasive biomarker assay, can have a significant impact on LUAD. These findings also underscore an alternate, non-genetic mechanism underlying the evolution of chemoresistance, which can alter the treatment of advanced-stage lung cancers that present with limited therapeutic options.
In lung adenocarcinoma (LUAD), PXN is associated with cisplatin resistance. As demonstrated herein, a significant region of the N-terminal half of PXN is intrinsically disordered and interacts with integrin beta 4 (ITGB4). Silencing PXN or ITGB4 augments cisplatin sensitivity and silencing both molecules has a synergistic effect. Immunologically neutralizing ITGB4 activity also improves cisplatin resistance. By screening an FDA-approved compound library, identified are compounds that interact with PXN in silico and attenuate cisplatin resistance in LUAD cells. RNAseq analysis identified a double negative feedback loop between ITGB4 and microRNA miR-1-3p, suggesting that bistability can lead to stochastic switching between cisplatin-sensitive and resistant states in these cells. The data highlight an alternate, non-genetic, mechanism underlying chemoresistance in lung cancer.
The role of the focal adhesion (FA) complex in cisplatin resistance was investigated in this study. The FA complex is a large macromolecular assembly through which mechanical force and regulatory signals are transmitted between the extracellular matrix and an interacting cell (Chen et al, 2003). Paxillin (PXN), integrins, and focal adhesion kinase (FAK) are among the major components of this complex. Human PXN is a 68 kDa (591 amino acids) protein (Salgia et al, 1995) and is a recognized contributor to cisplatin resistance in lung cancer (Wu et al, 2014). The N-terminus contains a proline-rich region that anchors SH3-containing proteins and five leucine-rich LD domains (LD1-LD5) with a consensus sequence LDXLLXXL (SEQ ID NO:1) (Turner, 1998; Turner, 2000; Kanteti et al, 2016). The LD2-LD4 region includes sequences for the recruitment of signaling and structural molecules, such as FAK, vinculin, and Crk. This region has also been reported to interact with integrin α, more specifically, integrin α4 (ITGA4) (Liu et al, 1999; Liu and Ginsburg, 2000). The C-terminal region is also involved in the anchoring of PXN to the plasma membrane and its targeting to FAs. It contains four cysteine-histidine-enriched LIM domains that form zinc fingers, suggesting that PXN could bind DNA and act as a transcription factor. Consistently, PXN is reported to locate to the nucleus which is regulated by phosphorylation (Dong et al, 2009; Ma and Hammes, 2018). In LUAD, expression of PXN is correlated with tumor progression and metastasis (Song et al, 2010; Mackinnon et al, 2011). Further, phosphorylation of PXN activates the ERK pathway, increased Bcl-2 expression, and cisplatin resistance (Wu et al, 2014). Finally, specific PXN mutants, through their interactions with Bcl-2 and dynamin-related protein 1, also regulate cisplatin resistance in human lung cancer cells (Kawada et al, 2013).
Integrins are transmembrane receptors that facilitate cell-extracellular matrix adhesion; they form a critical link between the extracellular matrix and the cell interior by interacting with the FA via PXN. Upon ligand binding, integrins activate signal transduction pathways that mediate cellular signals, such as regulation of the cell cycle, organization of the intracellular cytoskeleton, and movement of new receptors to the cell membrane (Giancotti and Rusolahti, 1999; Maziveyi and Alahari, 2107). Integrins are obligate heterodimers of one α and one β subunit. In mammals, there are 24 α and 9 β subunits (Alberts et al, 2014). Among the various β subunits, β1 is ubiquitously expressed in most cell types and can dimerize with multiple a subunits, forming receptors for various matrixes. On the other hand, integrin β4 (ITGB4) is reported to be quite selective and heterodimerizes only with the α6 subunit and binds to laminin (Mainiero et al, 1997). ITGB4 is also unique because of its >1000 amino acid-long cytoplasmic domain compared to ˜50 amino acid-long domain of other β forms (Su et al, 2008). Interaction of ITGA6/B4 and Shc leads to activation of the RAS-MAPK signaling pathway for cell cycle progression and proliferation (Mainiero et al, 1995). ITGA6/B4 can also activate the PI3 kinase pathway followed by Rac1 to promote tumor invasion (Shaw et al, 1997). In NSCLC, the receptor tyrosine kinase MET interacts with ITGA6/B4 and this interaction is required for HGF-dependent tumor invasion (Trusolino et al, 2001). In addition, the presence of the ITGA6/B4 heterodimer in tumor-derived exosomes facilitates the creation of the microenvironment for lung metastasis (Hoshino et al, 2015). Together, these observations underscore the importance of the FA complex in NSCLC pathophysiology. However, how the interactions of the individual components of the FA complex may contribute to cisplatin resistance remains poorly understood.
It is generally held that the antineoplastic effects of cisplatin are due to its ability to generate unrepairable DNA lesions hence inducing either a permanent proliferative arrest (cellular senescence) or cell death due to apoptosis. The drug enters cells via multiple pathways and forms multiple DNA-platinum adducts which results in dramatic epigenetic and/or genetic alternations. Such changes have been reported to occur in almost every mechanism supporting cell survival, including cell growth-promoting pathways, apoptosis, developmental pathways, DNA damage repair, and endocytosis (Shen et al, 2012; Rocha et al, 2018). Therefore, at a single cell level, the genetic underpinning involved in cisplatin resistance is obvious; however, the exact molecular mechanism(s) underlying the emergence of cisplatin resistance remains poorly understood and a bewildering plethora of targets have been implicated in different cancer types.
On the other hand, drug resistance is also thought to be strongly influenced by intratum oral heterogeneity and changes in the microenvironment (Alvarez-Arenas et al, 2019). Again, while prevailing wisdom advocates that the heterogeneity arises from genetic mutations, and analogous to Darwinian evolution, selection of tumor cells results from the adaptation to the microenvironment (Gerlinger M, Swanton, 2010), it is now increasingly evident that non-genetic mechanisms may also play an important role and information transfer can occur horizontally via a Lamarckian mode of evolution (Álvarez-Arenas et al, 2019). Thus, a population of isogenic cells in the same environment can exhibit single-cell-level stochastic fluctuations in gene expression. Such fluctuations, known as gene expression noise or transcriptional noise, can result in isogenic cells ‘making’ entirely different decisions with regard to their phenotype and hence, their ability to adapt themselves to the same environmental perturbation (Balázsi et al, 2011; Farquhar et al, 2019; Engl, 2019). Transcriptional noise can arise from the intrinsic randomness of underlying biochemical reactions or processes extrinsic to the gene (Swain et al, 2002). Regardless, two main characteristics of gene expression noise are its amplitude and memory. Amplitude, often measured by the coefficient of variation, defines how far cells deviate from the average. Memory describes the time for which cells remain deviant once they depart from the average (Acar et al, 2005; Charlebois et al, 2011). Thus, it follows that the effect noise produces is likely reversible and hence, underscores its importance in phenotypic switching.
Yet another source of noise that can be confounding in phenotypic switching is conformational noise (Mahmoudabadi et al, 2013) that stems from the ‘structural’ plasticity of the IDPs that lack rigid 3D structure and exist as conformational ensembles instead (Wright and Dyson, 2015; Turoverov et al, 2019). Because of their conformational dynamics and flexibility, IDPs can interact with multiple partners and are typically located in ‘hub’ positions in protein interaction networks. The collective effect of conformational noise is an ensemble of protein interaction network configurations, from which the most suitable can be explored in response to perturbations. Moreover, the ubiquitous presence of IDPs as transcriptional factors (Staby et al, 2017; Tsafou et al, 2018), and more generally as hubs (Patil et al, 2010; Hu et al, 2017), underscores their role in propagation of transcriptional noise. As effectors of transcriptional and conformational noise, IDPs rewire protein interaction networks and unmask latent interactions (Mahmoudabadi et al, 2013). Thus, noise-driven activation of latent pathways appears to underlie phenotypic switching events such as drug resistance.
As demonstrated herein, a significant portion of the N-terminal half of PXN is intrinsically disordered and that the interaction between ITGB4 and PXN is critical for cisplatin resistance. ITGB4 and PXN double knockdown affects the expression of >300 genes which are constituents of various pathways required for lung cancer proliferation and survival. USP1 and VDAC1 are two of the top ten genes that are downregulated by the double knockdown that are essential for inducing DNA damage repair induced by cisplatin and for maintaining the mitochondrial function, respectively. Via an in silico screen designed to identify small molecule compounds that can bind to PXN, candidate drugs were obtained from a library of FDA-approved compounds. Several of these compounds are efficacious in alleviating cisplatin resistance in LUAD cell lines expressing high levels of ITGB4/PXN. Furthermore, using tumor-derived exosomes isolated from patient blood, ITGB4/PXN were identified as potential biomarkers for cisplatin response. Moreover, RNAseq analysis identified a double negative feedback loop between ITGB4 and the microRNA miR-1-3p, suggesting that bistability can lead LUAD cells to stochastically switch between cisplatin-resistant and sensitive phenotypes, underscoring a non-genetic mechanism driving the evolution of chemoresistance.
The present data imply that cisplatin resistance in LUAD can arise stochastically in response to drug treatment. While it is possible that such resistance that is spontaneously, or randomly, acquired during the course of treatment can be due to random genetic mutations or stochastic non-genetic phenotype switching (Pisco et al, 2013), these observations strongly support a non-genetic mechanism. A double negative feedback loop between ITGB4 and miR-1-3p results in bistability, facilitating a reversible phenotypic switch between cisplatin-sensitive and resistant states. A recent study on oxaliplatin chemotherapy in pancreatic ductal adenocarcinoma (Kumar et al, 2019) where a coarse-grained stochastic model to quantify phenotypic heterogeneity in a population of cancer cells was studied. The present findings suggest that the phenomenon may be applicable to many different cancers. Furthermore, a random population of cisplatin-resistant LUAD cells is heterogeneous and comprises individuals that either express high or low levels of ITGB4. These cells therefore are either more resistant or less resistant to cisplatin, respectively. However, when purified to homogeneity (>99%) and plated separately, the purified population recreates the heterogeneity. Taken together, these observations not only corroborate the bistability predicted by the model but also highlight the role of phenotypic switching in generating population heterogeneity in cancer.
Additionally, the interaction of ITGB4 with the intrinsically disordered PXN is critical since perturbing this interaction renders the cells sensitive. It is important to note that, in addition to the LD domains and the LIM domains, PXN also contains an SH3 domain-binding site and SH2 domain-binding sites (Salgia et al, 1995). Together, these motifs serve as docking sites for cytoskeletal proteins, tyrosine kinases, serine/threonine kinases, GTPase activating proteins, and a host of other adaptor proteins that recruit additional enzymes into complex with PXN. Thus, consistent with the functions of an IDP in a hub position, PXN serves as a docking protein to recruit signaling molecules to the FA complex and thereby, coordinate downstream signaling (Schaller, 2001, Oncogene). It is now well recognized that cellular protein interaction networks are organized as scale-free networks and hence, are remarkably resilient to perturbations (Barabasi and Albert, 1999; Barabasi, 2009). Thus, while disabling minor nodes does not significantly affect the continuity and hence, functionality of the network, attacking the critical nodes can incapacitate the entire network (Schwartz et al, 2002). Thus, it follows that PXN appears to constitute a critical hub and its malfunction accounts for the failure of the cisplatin-resistant cells to tolerate the drug.
Although, IDPs in general have not been much appreciated as therapeutic targets since their inability to adopt well-defined structures provides significant obstacles for developing ligands that regulate their behaviors, emerging evidence indicates that indeed, they can be specifically targeted (Wojcik et al, 2018; Neira et al, 2017; Martin-Yken et al, 2016; Yu et al, 2016; Berg, 2011; Jung et al, 2015; Ambadipudi and Zweckstetter, 2016). In fact, even transcription factors that were never the favorite drug targets, are now emerging as tractable to drug development (Tsafou et al, 2018). Identified herein are a series of FDA-approved drugs including carfilzomib that perturb interactions involving an IDP and may be repurposed for alleviating cisplatin resistance in LUAD. By extrapolation, it is likely that some of these drugs may be effective in several other cancer types in which cisplatin therapy is administered. Thus, carfilzomib and the other drugs identified in this study can not only hasten clinical trials in future, but may make the availability of the drug more cost effective as well. Additionally, using the antibody-drug conjugation technology, carfilzomib or any of the other drugs identified in this study can be conjugated to the ITGB4 antibody and delivered to the tumor site with high specificity (Yao et al, 2016).
The role of the FA complex in serving as a conduit through which mechanical force and regulatory signals are transmitted between the extracellular matrix and an interacting cell is well established (Chen et al, 2003). Furthermore, the role of PXN in cisplatin resistance has also been recognized (Wu et al, 2014). However, the involvement of ITGB4 and the interaction between these molecules with FAK in modulating cisplatin resistance has not been reported. The findings disclosed herein support a new role for the FA complex in cancer, particularly LUAD. Thus, these FA components may serve as drug response predictors using a blood-based assay, and the identification of FDA-approved drugs that can be used to address drug resistance, which has a significant impact on LUAD and other types of cancers that respond to cisplatin.
The following examples are provided to better illustrate the claimed invention and are not to be interpreted as limiting the scope of the invention. To the extent that specific materials are mentioned, it is merely for purposes of illustration and is not intended to limit the invention. It will be apparent to one skilled in the art that various equivalents, changes, and modifications may be made without departing from the scope of invention, and it is understood that such equivalent embodiments are to be included herein. Further, all references cited in the disclosure are hereby incorporated by reference in their entirety, as if fully set forth herein.
Cell lines and reagents: Lung cancer cell lines (H23, H358, SW1573, H441, H2009, H522, H1650, H596, H1437, and H1993) were obtained from American Type Culture Collection (ATCC) (Manassas, Va., USA). All cell lines were cultured in RPMI 1640 medium (Corning) supplemented with fetal bovine serum (FBS) (10%), L-glutamine (2 mM), penicillin/streptomycin (50 U/ml), sodium pyruvate (1 mM), and sodium bicarbonate (0.075%) at 37° C., 5% CO2. Cisplatin was provided by City of Hope National Medical Center clinics. Anti-integrin beta 4 antibody, clone 8 was purchased from MilliporeSigma (Burlington, Mass., USA). FDA-approved drugs were purchased from Selleck Chemicals (Houston, Tex., USA).
Antibodies: Antibodies against ITGB4, FAK, phospho-FAK (Y397), γH2AX, p27, phospho-Rb (S807/811), USP1 were purchased from Cell Signaling Technology (Danvers, Mass., USA). Antibodies against ITGA7, ITGA6, PXN, MET, G3BP1, VDAC1, and agarose-conjugated antibodies (ITGB4, FAK, PXN) were purchased from Santa Cruz Biotechnology (Dallas, Tex., USA). Cyclin D1 antibody was purchased from Invitrogen (Waltham, Mass., USA). Phospho-PXN (Y31) and PARP antibodies were purchased from Abcam (Cambridge, UK). CD63 antibody was purchased from System Biosciences (Palo Alto, Calif., USA). β-actin antibody was purchased from Sigma-Aldrich (St. Louis, Mo., USA).
West blotting: Cell lysates were prepared with 1×RIPA buffer (MilliporeSigma) and denatured in 1× reducing sample buffer at 95° C. for 5 minutes. Protein samples (15 μg) were run on 4-15% TGX gels (Bio-Rad, Hercules, Calif., USA) and transferred onto nitrocellulose membranes (Bio-Rad). Blots were blocked with 5% non-fat milk in TBS-T for 1 hour at room temperature and probed with primary antibody diluted in 2.5% BSA in TBS-T overnight at 4° C. After three washes with TBS-T, blots were incubated with HRP-conjugated secondary antibodies for 2 hours at room temperature. After three more washes, bands of interest were visualized via chemiluminescence using Western Bright ECL HRP substrate (Advansta, Menlo Park, Calif., USA) and imaged with the ChemiDoc MP imager (Bio-Rad).
Quantitative real-time PCR: Quantitative real-time PCR (qPCR) reactions were performed using TaqMan Universal PCR Master Mix (Thermo Fisher Scientific, Waltham, Mass.) and analyzed by the Quant Studio7 Real-time PCR system (Life Technologies, Grand Island, N.Y.). Total RNA isolation and on-column DNase digestion from cells were performed basing on the manufacturer's protocol RNeasy Plus Mini Kit (Qiagen Cat #: 74134). 1 ug of RNA was used to synthesize the cDNA according to the one step cDNA synthesis kit from QuantaBio (Cat #: 101414-106). TaqMan probes for HS99999905-GAPDH, HS00236216-ITGB4, HS01104424-PXN, H500174397-ITGB1, H500164957-ITGB2, H501001469-ITGB3, H501565584-MET, HS04978484-VDAC1, HS00428478-G3BP1 and HS00163427-USP1 were purchased from ThermoFisher (Waltham, Mass.). The mRNA expression was analyzed using multiplex PCR for the targeted gene of interest and GAPDH as reference using two independent detection dyes FAM probes and VIC probes respectively. Relative mRNA expression was normalized to GAPDH signals and calculated using the ddCt method.
siRNA Transfection: Knockdown of ITGB4 (Cat #: SR302473C), FAK (Cat #: SR303877C), USP1 (Cat #: SR305052B), and VDAC1 (Cat #: SR305067C) at the mRNA level was executed using siRNAs purchased from OriGene Technologies (Rockville, Md., USA). Knockdown of PXN was achieved by siRNA purchased from Life Technologies Corporation (Cat #: 4392421). JetPRIME transfection reagent (Polyplus Transfection, Illkirch, France) was used to transfect the siRNAs according to the manufacturer's protocol. Cells were seeded in 6-well plates (200,000 cells/well) and allowed to adhere overnight. Next day, 10 nM siRNA was transfected with 4 μl jetPRIME reagent in complete growth medium for each well. Cell growth medium was changed the next day and expression was detected 72 hours post-transfection by immunoblot.
Cell viability assay: Cell Counting Kit-8 (CCK-8) was purchased from Dojindo Molecular Technologies (Rockville, Md., USA). Cells were seeded on a 96-well plate and allowed to adhere in complete medium for 24 hours. Test compounds were added to 100 μl of medium at the indicated concentrations for 72 hours. Ten μl of the CCK-8 reagent were added to each well and absorbance at 450 nm was measured using a Tecan Spark 10M multimode microplate reader.
Scratch wound healing assay. Cells were seeded on a 96-well Image Lock (Essen BioScience, Ann Arbor, Mich., USA) plate to reach 90% confluence by the next day. After cell adherence, 96 uniform wounds were created simultaneously using the WoundMaker (Essen BioScience) tool. Cells were washed once with serum-free medium and replenished with complete medium. To monitor wound healing, the plate was placed in the IncuCyte S3 Live-Cell Analysis System (Essen BioScience) and images were acquired every hour. Data analysis was generated by the IncuCyte software using a set confluence mask to measure relative wound density over time.
Cell proliferation and apoptosis assay. Cell proliferation assays were performed using cell lines stably transfected with NucLight Red Lentivirus (Essen Bioscience) to accurately visualize and count the nucleus of a single cell. Cells were seeded on a 96-well plate and allowed to adhere for 24 hours. Test compounds were added at indicated concentrations. Caspase-3/7 Green Apoptosis Reagent (Essen Bioscience) was also added as a green fluorescent indicator of caspase-3/7-mediated apoptotic activity. To monitor cell proliferation and apoptosis over time, the plate was placed in the IncuCyte S3 Live-Cell Analysis System (Essen BioScience) and images were acquired every 2 hours. Data analysis was generated by the IncuCyte software using a red fluorescence mask to accurately count each cell nucleus and a green fluorescence mask to measure apoptosis over time.
Immunoprecipitation (IP): Cells were lysed in the Pierce™ IP Lysis Buffer purchased from Thermo Fisher Scientific and 1 mg of protein was allowed to bind overnight in 4° C. to agarose-conjugated antibodies (Santa Cruz Biotechnology): ITGB4 (Cat #: sc-13543 AC), FAK (Cat #: sc-271195 AC), PXN (Cat #: sc-365379 AC). IP beads were washed 5 times with 1×RIPA buffer and denatured in 2× reducing sample buffer at 95° C. for 5 minutes. Western blots according to aforementioned protocol were performed to determine IP results.
3D spheroid assay. 3D spheroid experiments were performed using cell lines stably transfected with NucLight Red Lentivirus (Essen Bioscience) to visualize red fluorescence as an indicator of cell viability. Cells were seeded on a 96-well ultra-low attachment plate and allowed to form spheroids overnight. Drug treatment was added as indicated along with Cytotox Green Reagent (Essen BioScience), used as a green fluorescence indicator of cell death due to loss of cell membrane integrity. To monitor cell proliferation and apoptosis over time, the plate was placed in the IncuCyte S3 Live-Cell Analysis System (Essen BioScience) and images were acquired every 2 hours. Data analysis was generated by the IncuCyte software using a red fluorescence mask to accurately measure intensity and area of red fluorescence, indicating spheroid viability and a green fluorescence mask, indicating cell death.
Cell cycle analysis: H2009 cells were harvested and pelleted after 72 hours following siRNA transfection. Ice cold 70% ethanol was added to the pellet with mild vortexing to fix the cells. The fixed cells were kept at 4° C. for PI staining. FxCycle™ PI/RNase Staining solution from Invitrogen was used for staining the DNA according to the manufacturer's protocol prior the FACS analysis. Univariate model of Watson (Pragmatic) was used for cell cycle analysis.
Confocal microscopy. 3D spheroids were seeded and imaged in 96-well clear ultra-low attachment microplates (Corning) using Zeiss LSM 880 confocal microscope with Airyscan at the Light Microscopy/Digital Imaging Core Facility at City of Hope. Images were processed using ZEN software and analyzed using ImageJ (Schneider, C. A.; Rasband, W. S. & Eliceiri, K. W. (2012), “NIH Image to ImageJ: 25 years of image analysis”, Nature methods 9(7): 671-675, PMID 22930834).
Seahorse XF Cell Mito Stress Test metabolic assay. Cells were seeded in complete growth medium on a Seahorse XF Cell Culture Microplate (Agilent Technologies, Santa Clara, Calif., USA) to reach 90% monolayer confluence by the next day. One day prior to assay, 5 μM cisplatin was added for 24 hours. On the day of the assay, mitochondrial inhibitor compounds were added to injection ports of the XFe96 FluxPak sensor cartridge at a final concentration of: oligomycin 1 μM, FCCP 1 μM, rotenone/antimycin A 1 μM each. Culture medium was changed to assay medium: Seahorse XF RPMI medium supplemented with 1 mM sodium pyruvate, 2 mM L-glutamine, and 10 mM glucose. After completion of assay, cells were immediately stained with Hoechst dye and imaged using BioTek. Images were analyzed with QuPath (Bankhead, P. et al. (2017). QuPath: Open source software for digital pathology image analysis. Scientific Reports. doi.org/10.1038/s41598-017-17204-5) to obtain number of cells in each well and normalize data according to cell number.
ROS production assay: Cells were seeded in a 96-well plate and placed in an incubator at 37° C. for 72 hours. 50 μl of medium from each well was transferred to another 96-well plate to measure ROS production with ROS-Glo™ H2O2 Assay (Promega, Madison, Wis., USA). Remaining plate with cells were used to perform CellTiter-Glo® Luminescent Cell Viability Assay (Promega) to normalize ROS data to number of viable cells. Luminescence was measured using a Tecan Spark 10M multimode microplate reader.
γH2AX foci staining and analysis: Cells were seeded (50,000 cells/well) on glass cover slips coated with 0.1% gelatin (Millipore) in a 12-well plate. Next day, 5 μM cisplatin was added for 24 hours. Cells were fixed in 4% formaldehyde for 30 minutes at room temperature and blocked. Primary antibody against γH2AX (Cell Signaling Technology) was incubated in 4° C. overnight. Then secondary antibody was incubated for 2 hours at room temperature. Cover slips were mounted on glass slides and imaged with Zeiss LSM 880 confocal microscope at the Light Microscopy/Digital Imaging Core Facility at City of Hope. Using QuPath (Bankhead, P. et al. (2017). QuPath: Open source software for digital pathology image analysis. Scientific Reports. doi. org/10.1038/s41598-017-17204-5), green fluorescent subcellular particles were counted in each nucleus to obtain γH2AX foci count per cell.
Exosome isolation and analysis: 200 μl of serum from patient or healthy donor was taken and diluted with PBS to 5 ml. The diluted serum was filtered through 0.22-micron syringe filter and ultra-centrifuged at 90,000×g for 90 minutes. The supernatant was decanted, and the pellet was washed and centrifuged in 15 ml of PBS as before. The PBS was decanted, and pellet was suspended in 50 μl of 1×RIPA buffer containing protease inhibitors for 30 minutes on ice and transferred to 1.5 ml tube for quantification and denaturation as mentioned above.
Chromatin Immunoprecipitation: Briefly, five million formaldehyde-fixed cells were lysed in 200 ul of SDS lysis buffer and diluted to 2 ml in ChIP dilution buffer in the presence of protease inhibitors. Lysates were sonicated using Bioruptor PICO for 3 cycles and each cycle has 10 repeats of 30 seconds pulse and 30 seconds break. Lysates were precleared in salmon sperm DNA and protein A agarose by centrifugation. Prior to addition of antibody, 10% of the lysate was used for input and the remaining lysate was divided into two equal parts, one for IgG control and other for H3K27 acetylated antibody from Diagenode. Downstream processing of the chromatin bound antibody was done as per the manufacturer's protocol for EZ-magna ChIP A/G (Millipore, Temecula, Calif.). The extracted DNA was used for SYBR green based qPCR assay using the primers sequences Upstream USP 1R-5′-AGGTTCACAGCATTCTCAATCC-3′ (SEQ ID NO:2), Upstream USP1F-CAGTGCCTGTGAAACTTTGGA (SEQ ID NO:3), Promoter USP1F-CTCAGCTCTACAGCATTCGC (SEQ ID NO:4) and Promoter USP1R-GGCCATCCAATGAGACAAGG (SEQ ID NO:5). The data was analyzed based on the percentage of input.
In-silico prediction of paxillin conformational ensemble: Using in-silico modeling and enhanced sampling MD simulations, the conformational ensemble of Paxillin N-terminal domain between LD2 and LD4 bound to FAK was predicted. Starting from the crystal structures of FAK bound to the LD2 and LD4 motifs of Paxillin (pdb IDs 1OW8 and 1OW7), the disordered region of Paxillin (˜110 residues) between LD2 and LD4 as a random coil was modeled using Modeller. The N and the C termini of Paxillin and FAK were capped by the acetyl and N-methyl acetamide groups respectively. This structure was subjected to temperature replica exchange simulations (REMD) using the AMBER ff14SBonlysc force-field and the implicit solvation model GBneck2, as recommended in the AMBER16 manual. 26 replicas were used between 280K-480K and the individual temperatures were chosen to maintain an exchange success rate of 20%. To maintain structural integrity when subjected to high temperature during REMD, the backbone atoms of the helical regions of FAK and the bound LD2 and LD4 domains of Paxillin were position-restrained with a force of 5 kcal/mol. During REMD, the temperature was maintained using the Langevin thermostat with a collision frequency of 1.0. To accelerate the MD, the system was subjected to hydrogen mass repartitioning, which allowed a 4 femtosecond timestep to be used. The replicas were initially minimized using the conjugate gradient method followed by gradual heating to their respective temperatures over 1 ns. The REMD simulation was carried out for 1.15 μs for each replica, followed by clustering of the lowest temperature conformations by the Paxillin Ca atoms using hierarchical agglomerative clustering. The representative structures from the top 3 most populated clusters were used for virtual screening.
Virtual ligand screening to identify small molecule inhibitors of Paxillin-FAK interaction: The top Paxillin conformations obtained from REMD were scanned for druggable pockets using the program FindBindSite (FBS). The top ranked pockets in each Paxillin conformation were further screened by proximity to the FAK interface. In total, 4 pockets among 3 Paxillin conformations were selected for virtual screening. The protein structures were prepared using Maestro (Schrodinger™, LLC). The SelleckChem FDA-approved drug library containing approximately 1400 compounds was then docked to each pocket separately using Glide standard precision. The ligand library was prepared using the LigPrep module of Maestro and all possible protonation states at neutral pH were generated. During docking, the protein atoms were scaled by 0.8 and 10 docked poses per ligand were retained. Next, the best docked pose for each ligand was selected by Glide score and was optimized by reassigning the side chains within 5 Å of the docked ligand using Prime followed by minimization of the entire complex using MacroModel (Schrodinger™, LLC). Using MacroModel, a crude binding energy score was generated for each docked complex by subtracting the sum of individually solvated protein and ligand energies from the energy of the solvated complex. This score was used to select the top 50 ligands from each binding pocket, which were then subjected to thorough optimization and binding free energy calculation using the MMGBSA method in PrimeX. The top 10 compounds by binding free energy from each binding pocket were selected for experimental testing.
Fluorescence-activated cell sorting (FACS) and analysis: Cells were trypsinized and resuspended (5 million) in PBS with 2% FBS. Cells were stained with ITGB4 antibody conjugated to Alexa Fluor® 488 (5 μl/1 million cells) (R&D Systems, Minneapolis, Minn., USA) and Propidium Iodide Ready Flow™ Reagent (1 drop/1 million cells) (Invitrogen) for 30 minutes at 4° C. The Analytical Cytometry Core Facility at City of Hope carried out and assisted all FACS sorting and analysis experiments. Gates were set to sort cell populations having low 10% and high 10% expression of ITGB4 using the FACSAria™ Fusion (BD Biosciences, San Jose, Calif., USA). Sorted cells were immediately cultured in 12-well plates and treated with cisplatin (1 μM) for 48 hours. Then, equal number of untreated and treated cells were collected and stained with same reagents as above. FACS analysis was performed to determine shifts in cell population using the Attune NxT Flow Cytometer (Invitrogen).
Mathematical modeling: Bifurcation diagram was obtained MATCONT (cite: dl.acm.org/citation.cfm?id=779362). Next, Random circuit perturbation (RAC IPE) algorithm was run on the two-node network—ITGB4/miR-1-3p. The continuous gene expression levels were obtained as output with randomly chosen parameters for the regulatory links. The algorithm was used to generate 100,000 mathematical models, each with a different set of parameters for the following ODEs:
u=G
u
H
s(I,I0u′nlu,λ−lu)−kuu
I=G
l
H
s(u,u0l′nul,λ−ul)−kll
where, u denotes miR-1-3p and I denotes ITGB4. Gu and Gl are the maximum production rates of miR-1-3p and ITGB4 respectively. And, ku and kl are their innate degradation rates respectively.
Additional equations are provided as follows:
μ*=gμ3pHs(I,λl,μ3p)−MlYμ(μ3p)−kμ3pμ3p
m
l
*=g
ml
H
s(C,λc,ml)−mlYm(μ3p)−kmlml
l*=g
l
m
l
L(μ3p)−lll
where HS is the shifted Hill function, defined as HS (B,λ)=H−(B)+λH+(B), H− (B)=1/[1+(B/B0)nB], H+ (B)=1−H− (B) and A is the fold change from the basal synthesis rate due to protein B. λ>1 for activators, while λ<1 for inhibitors.
The total translation rate:
m
l
L(μ3p)=mΣi=0nllCniMni(μ)
The total mRNA active degradation rate:
m
l
Y
m(μ3p)=mΣi=0nγmiCniMni(μ)
The total miR active degradation rate is
m
l
Y
μ(μ3p)=mΣi=0nγμ
Parameters used in
The parameters for microRNA-mediated dynamics were estimated from our previous models for microRNA-mediated regulation of EMT (Lu et al. 2013), shown in Table 2 below.
To identify the genes upregulated in cisplatin resistance in LUAD cell lines, GSEA analysis was performed on RNAseq data from the Molecular Signatures Database v6.2 (MSigDB), a collection of annotated gene sets (Broad Institute) using the Gene Set Enrichment Analysis (GSEA) software. GSEA is a computational method that determines whether an a priori defined set of genes shows statistically significant concordant differences between two biological states. A set of eleven genes that were upregulated in cisplatin-resistant non-small lung cancer cells compared to sensitive cells were identified (Table 3).
Four of these eleven genes namely, PXN, ITGB4, ITGA7, and Rac Family Small GTPase 1, are constituents of the FA complex activation, formation, and downstream signaling pathways. Therefore, to verify the correlation of these genes with cisplatin resistance, five LUAD cell lines that harbored wild type (WT) KRAS and five that carried a mutant (MT) version of KRAS were randomly selected (Table 4), treated with 10 μM cisplatin for 72 hours, and cell viability was determined using the CCK-8 viability assay.
Among the KRAS WT cell lines, H1437 and H1993 were significantly more resistant while amongst the KRAS MT cell lines, H441 and H2009 were relatively more resistant than the other three cell lines (
Next, the protein expression of PXN, ITGB4, ITGA7, and FAK in these cell lines was determined by immunoblotting. Rac1 expression was undetectable in these cell lines. However, PXN and FAK were expressed in all the cell lines tested regardless of whether they were cisplatin-sensitive or resistant (
Since LUAD cell lines overexpressing PXN appeared sensitive to cisplatin treatment when they did not express ITGB4, it is possible that there is an interaction between PXN and ITGB4. Gene expression profiles of the patients diagnosed with “Lung Adenocarcinoma” were extracted from The Cancer Genome Atlas (TCGA) database and analyzed for expression of ITGB4 and PXN (
Immunohistochemistry on needle biopsy specimens obtained from 2 cases was performed. PXN staining was detected using yellow and ITGB4 with pink color. Thus, the coexpression of the t2 molecules would generate an orange or bright red color based on the expression level. Indeed, significant coexpression of ITGB4 and PXN was observed in various regions of the tumor (
The effect of knocking down ITGB4 on cell proliferation was determined using H1993 and H2009 cells. Cells were transiently transfected with a control (scrambled) and ITGB4-specific siRNA, and the effect of silencing its expression on cell proliferation was determined using the IncuCyte Live Cell Imaging System (Essen Bioscience, Ann Arbor, Mich.). To facilitate live cell analysis, stable cell lines with nuclear expression of the red fluorescence protein (RFP) mKate2 were generated (
To discern the effect of knocking down ITGB4 on cell migration, H1993 and H2009 cells were transfected with the control or ITGB4-specific siRNA in 6-well plates and 12 hours post transfection, the cells were trypsinized and reseeded at high density in a 96-well plate. A scratch wound was generated using the WoundMaker from Essen Bioscience and wound healing was observed in real time using the IncuCyte Live Cell Imaging System (
To determine whether the inhibition in cell proliferation associated with ITGB4 knockdown was due to enhanced apoptosis or reduced cell division (cytostatic), the Essen Bioscience Caspase-3/7 Green apoptosis assay in live cells was conducted. The NucView™633, a DNA intercalating dye was used to enable quantification of apoptosis over time. The dye is impermeable and non-toxic to cells but once the cell membrane is permeabilized by caspase-3/7, the dye enters the cell and gets activated due to change in pH leading to the generation of green fluorescence that is then detected in real time and quantified using the IncuCyte System (
To address this, H1993 and H2009 cells were treated with cisplatin for 3 days and the changes were analyzed by immunoblotting. A reduction in the expression of phosphorylated as well as total FAK and PXN was observed, but not in ITGB4 expression (
It has been shown that the cytoplasmic domain of ITGB4 acts as a scaffold for various kinases involved in activating the MAPK, PI3k or Akt pathways (Trusolino et al, 2001). MET Proto-Oncogene, Receptor Tyrosine Kinase (MET) is also one of the interacting partners of ITGB4 and is responsible for HGF-dependent phosphorylation and activation of ITGB4 (Trusolino et al, 2001). Of the two cell lines used in the present study, H1993 is known to harbor MET amplification. Thus, whether ITGB4 knockdown disrupts MET activity was investigated. Indeed, a decrease in MET expression in ITGB4 knocked down cells at the protein level was observed but there was no significant change in the mRNA expression, suggesting that ITGB4 may be involved in MET protein stability in these cells (
Having demonstrated that silencing ITGB4 expression can have a significant effect on response to cisplatin, whether blocking the ITGB4 extracellular epitope with an antibody would have a similar effect was tested. H1993 cells were first incubated with anti-ITGB4 antibody for 6 hours in ultra-low attachment tissue culture plates and then plated on tissue culture-treated plates. As expected, antibody-treated cells were unable to attach to the plate, indicating neutralization of ITGB4 epitopes by the antibody. The cells were allowed to grow for 72 hours and proliferation was determined using red fluorescence count. It was observed that antibody-treated cells proliferated slower than untreated or control IgG-treated cells. However, ITGB4 antibody treatment induced 5- to 7-fold higher caspase activity than untreated cells (
Next, the effect of combining the antibody and cisplatin treatments was investigated to determine potential synergy between the two modalities. Indeed, combining the two treatments showed an additive effect on cell proliferation and caspase-3/7 activity compared to either treatment alone. Furthermore, a synergistic effect was also observed even when a much lower dose (2.5 μM instead of 10 μM) of cisplatin was used (
Since cisplatin treatment caused changes in expression of FAK and PXN but not ITGB4 (
To mimic conditions closer to in vivo, the effect of knocking down PXN or ITGB4 was discerned in spheroids (3D) formed from the cell lines used in 2D culture. H2009 cells engineered to express RFP (mKate2) were first transfected with scrambled or PXN/ITGB4-specific siRNA and then seeded in an ultra-low attachment round bottom plate for generating spheroids. Within 4 hours of seeding, spheroid formation in wells seeded with cells that were transfected with the control siRNA was observed but not in the cell transfected with ITGB4 and PXN siRNA (
To identify the effect of knocking down ITGB4/PXN on the expression of the genes involved in signaling, the changes in global gene expression patterns were determined using RNAseq. RNA was extracted from both single and double knockdown cells 48 hours post siRNA transfection and total RNAseq was performed as described in Example 1. In all, 30 million reads were analyzed for each condition. In all, 237 genes were downregulated when ITGB4 was knocked down and 158 genes were downregulated upon knocking down PXN. In the case of the double knockdown, 329 genes that were downregulated were identified (
The Hallmark pathways represent specific well-defined biological processes and exhibit coherent expression. Of these 10 genes, G3BP1, USP1, and VDAC1 were the top 3 downregulated genes constituting the MYC1 Hallmark pathway. To validate the RNAseq data, western blotting and qPCR experiments were performed. These results confirmed that knocking down either PXN or ITGB4, or both, resulted in the decreased expression of all 3 genes at both protein level (
USP1 knockdown inhibited cell proliferation >2-fold by 72 hours of seeding and simultaneously increased caspase activity. Furthermore, USP1 knockdown in H2009 cells also sensitized them to a lower (2 μM) dose of cisplatin (
Taken together, these data suggest that USP1 and VDAC1 are downstream of PXN and ITGB4 and thus, knocking down USP1 and VDAC1 should recapitulate the phenotype of PXN and ITGB4. Therefore, H2009 cell line was transfected with 10 nM of siRNA against ITGB4 and PXN or siRNA against USP1 and VDAC1 and changes in proliferation rates were compared. Cell proliferation was 50% reduced by knocking down either of the combination. Addition of cisplatin to either combination had an additive effect. Interestingly, there was significant difference between either gene combinations (
VDAC1 is an ion channel pump located in the mitochondrial and plasma membranes. To discern the role of VDAC1 in mitochondrial function, VDAC1 as well as PXN and ITGB4 was knocked down in H2009 cells and mitochondrial respiration in absence and presence of cisplatin was analyzed using the Seahorse XF Analyzer (Agilent, Santa Clara, Calif.). The raw data was normalized to the live cell count. Knocking down VDAC1 or ITGB4/PXN changed the oxygen consumption rate (OCR) of cells which is measured by the basal as well as maximal mitochondrial OCR compared to the control, and these rates were further increased in presence of cisplatin (
Oxidative phosphorylation is an efficient but slow process of ATP production in comparison to glycolytic pathway and is more preferably used by tumor cells. Pyruvate generated during glycolysis is oxidized by mitochondria for oxidative phosphorylation leading to mitochondrial ATP production which is required for ATP-linked respiration (Ajit et al.). Treating cells with Oligomycin which can inhibit the electron transport chain and block mitochondrial ATP generation, can inhibit ATP-linked respiration. On one hand, increase in ATP-linked respiration is indicative of the availability of more substrates like pyruvate to drive oxidative phosphorylation. On the other hand, it also suggests an increase in ATP demand of the cell. Therefore, ATP-linked respiration was calculated and an increase in the linked respiration was observed in double knockdown cells which increased further upon addition of cisplatin. Control (scramble siRNA treated) cells, in the presence of cisplatin showed increased ATP-linked respiration which is indicative of a stress-induced increase in ATP demand. The same increase in ATP demand was also seen in these cells upon VDAC1 knockdown or double knockdown (
Mitochondria maintain a proton motive potential for ATP generation under ideal conditions. A proton leak can affect the membrane potential and consequently, a decrease in ATP production. To maintain the proton motive force intact, mitochondria increase their respiration and oxygen consumption rate as measured by increase in basal and maximal respiration. An increase was observed in the proton leak for ITGB4 and PXN double knockdown which may explain their increase in respiration to compensate for the loss in membrane potential (
Increased mitochondrial respiration is also known to cause an increase in the generation of reactive oxygen species (ROS). Therefore, the production of ROS was tested using ROS glow kit form Promega in 2 cisplatin-resistant cell lines by knocking down either USP1/VDAC1 or ITGB4/PXN. Increase in mitochondrial oxygen consumption rate (OCR) is associated with increase in mitochondrial ROS post irradiation leading to cell death (Tohru Yamamori et al). An increase in generation of ROS was observed after knocking down ITGB4/PXN or USP1/VDAC1 which was higher compared to cells treated with cisplatin which may lead to increase in ROS induced DNA damage and apoptosis (
Furthermore, USP1 as a deubiquitinase is known to increase DNA repair activity in cisplatin-treated cells (Iraia et al). Therefore, changes in the γH2AX foci were measured as a measure of DNA damage in the double knockdown or USP1 knockdown cells. It was observed that double knockdown cells had significantly higher γH2AX foci counts compared to control or USP1 knockdown. Addition of cisplatin in conjunction with USP1 knockdown further increased the extent of DNA damage (
Finally, since double knockdown silenced USP1 expression alluding to possible transcriptional regulation, the upstream sequence of USP1 promoter region was analyzed using genome browser and two potential histone H3K27 acetylation sites were identified. To determine the functional significance of these sites, both PXN and ITGB4 were knocked down and after 72 hours, chromatin immunoprecipitation was performed using a histone H3K27 antibody. In the double knockdown samples, reduced histone H3K27 acetylation at the promoter was observed suggesting that USP1 expression is induced by hyper acetylation. Of note, the data also suggest that ITGB4 and PXN involvement is not limited to migration and invasion; they may also be involved in controlling the epigenetic land scape of lung cancer. However, additional studies are needed at global level and with other histone acetylation forms (
From the foregoing, it follows that PXN and ITGB4 interact with each other and also with FAK and that this interaction is important in cisplatin resistance. To determine these interactions, co-immunoprecipitation experiments were performed with an ITGB4 antibody as well as with FAK or PXN antibodies in separate experiments. Immunoblotting with ITGA6 antibody served as a positive control as it is known to interact with ITGB4 (Aydin et al). Surprisingly, the ITGA6 protein was not detected in H2009 and H1993 cell lines. However, the pulldown showed the presence of ITGA7 (
Since PXN, especially the LD1-LD5 domain, is implicated in interacting with multiple proteins in the FA complex, it is suspected that this region may be intrinsically disordered. Bioinformatics analysis using the PONDR prediction algorithm showed that indeed, the N-terminal half of the molecule, especially the regions connecting the LD domains, is predicted to be significantly disordered while the C-terminal half comprising the LIM domains is predicted as highly ordered (
A virtual screen of a library of 1440 FDA-approved drugs using binding pockets in the N-terminal domain of PXN (
Eleven potential compounds were identified, which showed a significant effect with IC50s ranging from 0.8 nM to 1.54 μM. Then a sublethal dose was used to determine the effect of these compounds on ITGB4 and PXN expression and caspase activity (
The experiments described above were done using 2D monolayer cultures. H2009 spheroids were employed to discern the effect of the drug in 3D cultures. The spheroids were treated with different doses (150-600 nM) for 72 hours and spheroid integrity was analyzed by measuring the red and green intensities using confocal microscopy. Consistent with the 2D data, a significant increase in caspase activity and decrease in cell proliferation was observed (
Next, drug efficacy in patient tumor tissue-derived organoids was determined. Approximately 5000 cells/sample from 2 surgical samples were seeded in an ultra-low attachment plate and incubated at 37° C. Once organoids formed, carfilzomib and caspase assay dye were added, and the organoids were observed in real time using the IncuCyte Live Cell Analysis System. In one of the patient-derived organoids, cisplatin treatment alone decreased spheroid area and increased apoptosis as measured by green intensity (
Next, the organoids were treated with cisplatin alone or carfilzomib at 2.5 mM and 5 mM for 48 hours and the samples were processed for immunoblotting. A decrease in the expression of ITGB4, USP1, PXN and VDAC1 was observed, which were found to be associated with cisplatin resistance in the present study (
Analysis of RNAseq data revealed that several microRNAs were also differentially regulated in response to single or double knockdown (Table 9).
In particular, miR-1-3p was upregulated both in ITGB4 single knockdown as well as in the ITGB4/PXN double knockdown by 3.1-fold and 2.54-fold, respectively. Furthermore, it was reported that overexpressing ITGB4 downregulates miR-1-3p (Gerson et al, 2012). Together, these observations suggested that there exists a double negative feedback loop between ITGB4 and miR-1-3p. Therefore, integrating these observations, a mathematical model was developed to simulate the dynamics of ITGB4/miR-1-3p feedback loop (
Next, to investigate whether this co-existence of two states is a robust feature that can be expected from the given network topology, the algorithm RAC IPE (Random Circuit Perturbation) was implemented, which generates an ensemble of mathematical models with varying parameter sets (Huang et al, 2017). The results from this ensemble (n=100,000) were then plotted together to identify robust dynamical features of the underlying regulatory network; each mathematical model can represent one cell, and this ensemble represents a cell population with varying levels of genetic/phenotypic heterogeneity. The feedback loop was constructed based on data reported in the manuscript (ITGB4 inhibits miR-1-3p) and publicly available data (miR-1-3p inhibits ITGB4)—www.genecards.org/cgi-bin/carddisp.pl?gene=ITGB4. RAC IPE results for the ITGB4/miR-1-3p feedback loop showed that both ITGB4 and miR-1-3p exhibit bimodality, i.e., two subpopulations (
To test the predictions made by the model, H2009 cells were treated with cisplatin for 4 days. On day 5, they were subjected to FACS analysis using an ITGB4 antibody. A 15% decrease in ITGB4 low-expressing cells was observed compared to untreated cells, suggesting that the H2009 cells are inherently a mix population with variable expression of ITGB4. In presence of stress, the cells either increased the expression of ITGB4 or the cells having high ITGB4 get selected (
Since ITGB4 and PXN are upregulated in cisplatin-resistant cells, a minimally invasive method could be developed to determine the expression of ITGB4 and PXN in LUAD patients. To this end, 500 μl of serum from healthy donors and LUAD patients was used and exosomes were isolated by ultracentrifugation as described in Example 1. Exosomes were lysed and analyzed for ITGB4 and PXN expression by western blotting. CD63 served as an exosomal marker protein. Indeed, of six patients that were tested, three patients had higher expression of ITGB4 and PXN. Interestingly, USP1 which was identified as being regulated by ITGB4 showed a similar pattern corresponding to ITGB4 (
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The present application claims priority to U.S. Provisional Application No. 62/904,195, filed Sep. 23, 2019, the content of which is incorporated herein by reference in its entirety, including drawings.
| Number | Date | Country | |
|---|---|---|---|
| 62904195 | Sep 2019 | US |
