Systematic identification of molecular subtype-selective vulnerabilities in non-small-cell lung cancer.

Context-specific molecular vulnerabilities that arise during tumor evolution represent an attractive intervention target class. However, the frequency and diversity of somatic lesions detected among lung tumors can confound efforts to identify these targets. To confront this challenge, we have applied parallel screening of chemical and genetic perturbations within a panel of molecularly annotated NSCLC lines to identify intervention opportunities tightly linked to molecular response indicators predictive of target sensitivity. Anchoring this analysis on a matched tumor/normal cell model from a lung adenocarcinoma patient identified three distinct target/response-indicator pairings that are represented with significant frequencies (6%-16%) in the patient population. These include NLRP3 mutation/inflammasome activation-dependent FLIP addiction, co-occurring KRAS and LKB1 mutation-driven COPI addiction, and selective sensitivity to a synthetic indolotriazine that is specified by a seven-gene expression signature. Target efficacies were validated in vivo, and mechanism-of-action studies informed generalizable principles underpinning cancer cell biology.

Dek overexpression in murine epithelia increases overt esophageal squamous cell carcinoma incidence.

Esophageal cancer occurs as either squamous cell carcinoma (ESCC) or adenocarcinoma. ESCCs comprise almost 90% of cases worldwide, and recur with a less than 15% five-year survival rate despite available treatments. The identification of new ESCC drivers and therapeutic targets is critical for improving outcomes. Here we report that expression of the human DEK oncogene is strongly upregulated in esophageal SCC based on data in the cancer genome atlas (TCGA). DEK is a chromatin-associated protein with important roles in several nuclear processes including gene transcription, epigenetics, and DNA repair. Our previous data have utilized a murine knockout model to demonstrate that Dek expression is required for oral and esophageal SCC growth. Also, DEK overexpression in human keratinocytes, the cell of origin for SCC, was sufficient to cause hyperplasia in 3D organotypic raft cultures that mimic human skin, thus linking high DEK expression in keratinocytes to oncogenic phenotypes. However, the role of DEK over-expression in ESCC development remains unknown in human cells or genetic mouse models. To define the consequences of Dek overexpression in vivo, we generated and validated a tetracycline responsive Dek transgenic mouse model referred to as Bi-L-Dek. Dek overexpression was induced in the basal keratinocytes of stratified squamous epithelium by crossing Bi-L-Dek mice to keratin 5 tetracycline transactivator (K5-tTA) mice. Conditional transgene expression was validated in the resulting Bi-L-Dek_K5-tTA mice and was suppressed with doxycycline treatment in the tetracycline-off system. The mice were subjected to an established HNSCC and esophageal carcinogenesis protocol using the chemical carcinogen 4-nitroquinoline 1-oxide (4NQO). Dek overexpression stimulated gross esophageal tumor development, when compared to doxycycline treated control mice. Furthermore, high Dek expression caused a trend toward esophageal hyperplasia in 4NQO treated mice. Taken together, these data demonstrate that Dek overexpression in the cell of origin for SCC is sufficient to promote esophageal SCC development in vivo.

Graphical data mining of cancer mechanisms with SEMA.

MOTIVATION: An important goal of cancer genomics initiatives is to provide the research community with the resources for the unbiased query of cancer mechanisms. Several excellent web platforms have been developed to enable the visual analyses of molecular alterations in cancers from these datasets. However, there are few tools to allow the researchers to mine these resources for mechanisms of cancer processes and their functional interactions in an intuitive unbiased manner. RESULTS: To address this need, we developed SEMA, a web platform for building and testing of models of cancer mechanisms from large multidimensional cancer genomics datasets. Unlike the existing tools for the analyses and query of these resources, SEMA is explicitly designed to enable exploratory and confirmatory analyses of complex cancer mechanisms through a suite of intuitive visual and statistical functionalities. Here, we present a case study of the functional mechanisms of TP53-mediated tumor suppression in various cancers, using SEMA, and identify its role in the regulation of cell cycle progression, DNA repair and signal transduction in different cancers.SEMA is a first-in-its-class web application designed to allow visual data mining and hypothesis testing from the multidimensional cancer datasets. The web application, an extensive tutorial and several video screencasts with case studies are freely available for academic use at https://sema.research.cchmc.org/. AVAILABILITY AND IMPLEMENTATION: SEMA is freely available at https://sema.research.cchmc.org. The web site also contains a detailed Tutorial (also in Supplementary Information), and a link to the YouTube channel for video screencasts of analyses, including the analyses presented here. The Shiny and JavaScript source codes have been deposited to GitHub: https://github.com/msolmazm/sema. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Platelet-derived growth factor receptor alpha (PDGFRα) targeting and relevant biomarkers in ovarian carcinoma.

OBJECTIVE: Platelet-derived growth factor receptor alpha (PDGFRα) is believed to be associated with cell survival. We examined (i) whether PDGFRα blockade enhances the antitumor activity of taxanes in ovarian carcinoma and (ii) potential biomarkers of response to anti-PDGFRα therapy. METHODS: PDGFRα expression in 176 ovarian carcinomas was evaluated with tissue microarray and correlated to survival outcome. Human-specific monoclonal antibody to PDGFRα (IMC-3G3) was used for in vitro and in vivo experiments with or without docetaxel. Gene microarrays and reverse-phase protein arrays with pathway analyses were performed to identify potential predictive biomarkers. RESULTS: When compared to low or no PDGFRα expression, increased PDGFRα expression was associated with significantly poorer overall survival of patients with ovarian cancer (P=0.014). Although treatment with IMC-3G3 alone did not affect cell viability or increase apoptosis, concurrent use of IMC-3G3 with docetaxel significantly enhanced sensitization to docetaxel and apoptosis. In an orthotopic mouse model, IMC-3G3 monotherapy had no significant antitumor effects in SKOV3-ip1 (low PDGFRα expression), but showed significant antitumor effects in HeyA8-MDR (high PDGFRα expression). Concurrent use of IMC-3G3 with docetaxel, compared with use of docetaxel alone, significantly reduced tumor weight in all tested cell lines. In protein ontology, the EGFR and AKT pathways were downregulated by IMC-3G3 therapy. MAPK and CCNB1 were downregulated only in the HeyA8-MDR model. CONCLUSION: These data identify IMC-3G3 as an attractive therapeutic strategy and identify potential predictive markers for further development.

A Multimodal Drug-Diet-Immunotherapy Combination Restrains Melanoma Progression and Metastasis.

The genetic landscape of cancer cells can lead to specific metabolic dependencies for tumor growth. Dietary interventions represent an attractive strategy to restrict the availability of key nutrients to tumors. In this study, we identified that growth of a subset of melanoma was severely restricted by a rationally designed combination therapy of a stearoyl-CoA desaturase (SCD) inhibitor with an isocaloric low-oleic acid diet. Despite its importance in oncogenesis, SCD underwent monoallelic codeletion along with PTEN on chromosome 10q in approximately 47.5% of melanoma, and the other SCD allele was methylated, resulting in very low-SCD expression. Although this SCD-deficient subset was refractory to SCD inhibitors, the subset of PTEN wild-type melanoma that retained SCD was sensitive. As dietary oleic acid could potentially blunt the effect of SCD inhibitors, a low oleic acid custom diet was combined with an SCD inhibitor. The combination reduced monounsaturated fatty acids and increased saturated fatty acids, inducing robust apoptosis and growth suppression and inhibiting lung metastasis with minimal toxicity in preclinical mouse models of PTEN wild-type melanoma. When combined with anti-PD1 immunotherapy, the SCD inhibitor improved T-cell functionality and further constrained melanoma growth in mice. Collectively, these results suggest that optimizing SCD inhibitors with diets low in oleic acid may offer a viable and efficacious therapeutic approach for improving melanoma treatment. Significance: Blockade of endogenous production of fatty acids essential for melanoma combined with restriction of dietary intake blocks tumor growth and enhances response to immunotherapy, providing a rational drug-diet treatment regimen for melanoma.

Identification of novel driver tumor suppressors through functional interrogation of putative passenger mutations in colorectal cancer.

Cancer genome sequencing efforts are leading to the identification of genetic mutations in many types of malignancy. However, the majority of these genetic alterations have been considered random passengers that do not directly contribute to tumorigenesis. We have previously conducted a soft agar-based short hairpin RNA (shRNA) screen within colorectal cancer (CRC) candidate driver genes (CAN-genes) using a karyotypically diploid hTERT- and CDK4-immortalized human colonic epithelial cell (HCEC) model and discovered that depletion of 65 of the 151 CAN-genes enhanced anchorage-independent growth in HCECs with ectopic expression of K-Ras(V12) and/or TP53 knockdown. We now constructed an interaction map of the confirmed CAN-genes with CRC non-CAN-genes and screened for functional tumor suppressors. Remarkably, depletion of 15 out of 25 presumed passenger genes that interact with confirmed CAN-genes (60%) promoted soft agar growth in HCECs with TP53 knockdown compared to only 7 out of 55 (12.5%) of presumed passenger genes that do not interact. We have thus demonstrated a pool of driver mutations among the putative CRC passenger/incidental mutations, establishing the importance of employing biological filters, in addition to bioinformatics, to identify driver mutations.

Modeling community-wide molecular networks of multicellular systems.

MOTIVATION: Multicellular systems, such as tissues, are composed of different cell types that form a heterogeneous community. Behavior of these systems is determined by complex regulatory networks within (intracellular networks) and between (intercellular networks) cells. Increasingly more studies are applying genome-wide experimental approaches to delineate the contributions of individual cell types (e.g. stromal, epithelial, vascular cells) to collective behavior of heterogeneous cell communities (e.g. tumors). Although many computational methods have been developed for analyses of intracellular networks based on genome-scale data, these efforts have not been extended toward analyzing genomic data from heterogeneous cell communities. RESULTS: Here, we propose a network-based approach for analyses of genome-scale data from multiple cell types to extract community-wide molecular networks comprised of intra- and intercellular interactions. Intercellular interactions in this model can be physical interactions between proteins or indirect interactions mediated by secreted metabolites of neighboring cells. Applying this method on data from a recent study on xenograft mouse models of human lung adenocarcinoma, we uncover an extensive network of intra- and intercellular interactions involved in the acquired resistance to angiogenesis inhibitors. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The glucose-deprivation network counteracts lapatinib-induced toxicity in resistant ErbB2-positive breast cancer cells.

Dynamic interactions between intracellular networks regulate cellular homeostasis and responses to perturbations. Targeted therapy is aimed at perturbing oncogene addiction pathways in cancer, however, development of acquired resistance to these drugs is a significant clinical problem. A network-based computational analysis of global gene expression data from matched sensitive and acquired drug-resistant cells to lapatinib, an EGFR/ErbB2 inhibitor, revealed an increased expression of the glucose deprivation response network, including glucagon signaling, glucose uptake, gluconeogenesis and unfolded protein response in the resistant cells. Importantly, the glucose deprivation response markers correlated significantly with high clinical relapse rates in ErbB2-positive breast cancer patients. Further, forcing drug-sensitive cells into glucose deprivation rendered them more resistant to lapatinib. Using a chemical genomics bioinformatics mining of the CMAP database, we identified drugs that specifically target the glucose deprivation response networks to overcome the resistant phenotype and reduced survival of resistant cells. This study implicates the chronic activation of cellular compensatory networks in response to targeted therapy and suggests novel combinations targeting signaling and metabolic networks in tumors with acquired resistance.

Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes.

The epithelial-to-mesenchymal transition (EMT) produces cancer cells that are invasive, migratory, and exhibit stem cell characteristics, hallmarks of cells that have the potential to generate metastases. Inducers of the EMT include several transcription factors (TFs), such as Goosecoid, Snail, and Twist, as well as the secreted TGF-beta1. Each of these factors is capable, on its own, of inducing an EMT in the human mammary epithelial (HMLE) cell line. However, the interactions between these regulators are poorly understood. Overexpression of each of the above EMT inducers up-regulates a subset of other EMT-inducing TFs, with Twist, Zeb1, Zeb2, TGF-beta1, and FOXC2 being commonly induced. Up-regulation of Slug and FOXC2 by either Snail or Twist does not depend on TGF-beta1 signaling. Gene expression signatures (GESs) derived by overexpressing EMT-inducing TFs reveal that the Twist GES and Snail GES are the most similar, although the Goosecoid GES is the least similar to the others. An EMT core signature was derived from the changes in gene expression shared by up-regulation of Gsc, Snail, Twist, and TGF-beta1 and by down-regulation of E-cadherin, loss of which can also trigger an EMT in certain cell types. The EMT core signature associates closely with the claudin-low and metaplastic breast cancer subtypes and correlates negatively with pathological complete response. Additionally, the expression level of FOXC1, another EMT inducer, correlates strongly with poor survival of breast cancer patients.

Mechanism of inert inflammation in an immune checkpoint blockade-resistant tumor subtype bearing transcription elongation defects.

The clinical response to immune checkpoint blockade (ICB) correlates with tumor-infiltrating cytolytic T lymphocytes (CTLs) prior to treatment. However, many of these inflamed tumors resist ICB through unknown mechanisms. We show that tumors with transcription elongation deficiencies (TEdef+), which we previously reported as being resistant to ICB in mouse models and the clinic, have high baseline CTLs. We show that high baseline CTLs in TEdef+ tumors result from aberrant activation of the nucleic acid sensing-TBK1-CCL5/CXCL9 signaling cascade, which results in an immunosuppressive microenvironment with elevated regulatory T cells and exhausted CTLs. ICB therapy of TEdef+ tumors fail to increase CTL infiltration and suppress tumor growth in both experimental and clinical settings, suggesting that TEdef+, along with surrogate markers of tumor immunogenicity such as tumor mutational burden and CTLs, should be considered in the decision process for patient immunotherapy indication.

NetWalker: a contextual network analysis tool for functional genomics.

BACKGROUND: Functional analyses of genomic data within the context of a priori biomolecular networks can give valuable mechanistic insights. However, such analyses are not a trivial task, owing to the complexity of biological networks and lack of computational methods for their effective integration with experimental data. RESULTS: We developed a software application suite, NetWalker, as a one-stop platform featuring a number of novel holistic (i.e. assesses the whole data distribution without requiring data cutoffs) data integration and analysis methods for network-based comparative interpretations of genome-scale data. The central analysis components, NetWalk and FunWalk, are novel random walk-based network analysis methods that provide unique analysis capabilities to assess the entire data distributions together with network connectivity to prioritize molecular and functional networks, respectively, most highlighted in the supplied data. Extensive inter-operability between the analysis components and with external applications, including R, adds to the flexibility of data analyses. Here, we present a detailed computational analysis of our microarray gene expression data from MCF7 cells treated with lethal and sublethal doses of doxorubicin. CONCLUSION: NetWalker, a detailed step-by-step tutorial containing the analyses presented in this paper and a manual are available at the web site http://netwalkersuite.org.

Drug resistance mechanisms create targetable proteostatic vulnerabilities in Her2+ breast cancers.

Oncogenic kinase inhibitors show short-lived responses in the clinic due to high rate of acquired resistance. We previously showed that pharmacologically exploiting oncogene-induced proteotoxic stress can be a viable alternative to oncogene-targeted therapy. Here, we performed extensive analyses of the transcriptomic, metabolomic and proteostatic perturbations during the course of treatment of Her2+ breast cancer cells with a Her2 inhibitor covering the drug response, resistance, relapse and drug withdrawal phases. We found that acute Her2 inhibition, in addition to blocking mitogenic signaling, leads to significant decline in the glucose uptake, and shutdown of glycolysis and of global protein synthesis. During prolonged therapy, compensatory overexpression of Her3 allows for the reactivation of mitogenic signaling pathways, but fails to re-engage the glucose uptake and glycolysis, resulting in proteotoxic ER stress, which maintains the protein synthesis block and growth inhibition. Her3-mediated cell proliferation under ER stress during prolonged Her2 inhibition is enabled due to the overexpression of the eIF2 phosphatase GADD34, which uncouples protein synthesis block from the ER stress response to allow for active cell growth. We show that this imbalance in the mitogenic and proteostatic signaling created during the acquired resistance to anti-Her2 therapy imposes a specific vulnerability to the inhibition of the endoplasmic reticulum quality control machinery. The latter is more pronounced in the drug withdrawal phase, where the de-inhibition of Her2 creates an acute surge in the downstream signaling pathways and exacerbates the proteostatic imbalance. Therefore, the acquired resistance mechanisms to oncogenic kinase inhibitors may create secondary vulnerabilities that could be exploited in the clinic.

Comprehensive mapping of the human kinome to epidermal growth factor receptor signaling.

Disregulation of epidermal growth factor receptor (EGFR) signaling directly promotes bypass of proliferation and survival restraints in a high frequency of epithelia-derived cancer. As such, much effort is currently focused on decoding the molecular architecture supporting EGFR activation and function. Here, we have leveraged high throughput reverse phase protein lysate arrays, with a sensitive fluorescent nanocrystal-based phosphoprotein detection assay, together with large scale siRNA-mediated loss of function to execute a quantitative interrogation of all elements of the human kinome supporting EGF-dependent signaling. This screening platform has captured multiple novel contributions of diverse protein kinases to modulation of EGFR signal generation, signal amplitude, and signal duration. As examples, the prometastatic SNF1/AMPK-related kinase hormonally upregulated Neu kinase was found to support EGFR activation in response to ligand binding, whereas the enigmatic kinase MGC16169 selectively supports coupling of active EGFR to ERK1/2 regulation. Of note, the receptor tyrosine kinase MERTK and the pyrimidine kinase UCK1 were both found to be required for surface accumulation of EGFR and subsequent pathway activation in multiple cancer cell backgrounds and may represent new targets for therapeutic intervention.

Use of data-biased random walks on graphs for the retrieval of context-specific networks from genomic data.

Extracting network-based functional relationships within genomic datasets is an important challenge in the computational analysis of large-scale data. Although many methods, both public and commercial, have been developed, the problem of identifying networks of interactions that are most relevant to the given input data still remains an open issue. Here, we have leveraged the method of random walks on graphs as a powerful platform for scoring network components based on simultaneous assessment of the experimental data as well as local network connectivity. Using this method, NetWalk, we can calculate distribution of Edge Flux values associated with each interaction in the network, which reflects the relevance of interactions based on the experimental data. We show that network-based analyses of genomic data are simpler and more accurate using NetWalk than with some of the currently employed methods. We also present NetWalk analysis of microarray gene expression data from MCF7 cells exposed to different doses of doxorubicin, which reveals a switch-like pattern in the p53 regulated network in cell cycle arrest and apoptosis. Our analyses demonstrate the use of NetWalk as a valuable tool in generating high-confidence hypotheses from high-content genomic data.

Mechanisms of stearoyl CoA desaturase inhibitor sensitivity and acquired resistance in cancer.

The lipogenic enzyme stearoyl CoA desaturase (SCD) plays a key role in tumor lipid metabolism and membrane architecture. SCD is often up-regulated and a therapeutic target in cancer. Here, we report the unexpected finding that median expression of SCD is low in glioblastoma relative to normal brain due to hypermethylation and unintentional monoallelic co-deletion with phosphatase and tensin homolog (PTEN) in a subset of patients. Cell lines from this subset expressed undetectable SCD, yet retained residual SCD enzymatic activity. Unexpectedly, these lines evolved to survive independent of SCD through unknown mechanisms. Cell lines that escaped such genetic and epigenetic alterations expressed higher levels of SCD and were highly dependent on SCD for survival. Last, we identify that SCD-dependent lines acquire resistance through a previously unknown FBJ murine osteosarcoma viral oncogene homolog B (FOSB)-mediated mechanism. Accordingly, FOSB inhibition blunted acquired resistance and extended survival of tumor-bearing mice treated with SCD inhibitor.

Inherited DNA Repair Defects Disrupt the Structure and Function of Human Skin.

Squamous cell carcinoma (SCC) is a global public health burden originating in epidermal stem and progenitor cells (ESPCs) of the skin and mucosa. To understand how genetic risk factors contribute to SCC, studies of ESPC biology are imperative. Children with Fanconi anemia (FA) are a paradigm for extreme SCC susceptibility caused by germline loss-of-function mutations in FA DNA repair pathway genes. To discover epidermal vulnerabilities, patient-derived pluripotent stem cells (PSCs) conditional for the FA pathway were differentiated into ESPCs and PSC-derived epidermal organotypic rafts (PSC-EORs). FA PSC-EORs harbored diminished cell-cell junctions and increased proliferation in the basal cell compartment. Furthermore, desmosome and hemidesmosome defects were identified in the skin of FA patients, and these translated into accelerated blistering following mechanically induced stress. Together, we demonstrate that a critical DNA repair pathway maintains the structure and function of human skin and provide 3D epidermal models wherein SCC prevention can now be explored.

Suppression of tumor antigen presentation during aneuploid tumor evolution contributes to immune evasion.

Anti-tumor immune responses impede tumor formation, and cancers have evolved many mechanisms of immune evasion. Confirming earlier findings, we show that human tumors with high chromosomal instability (CIN+) are significantly less immunogenic, as judged by tumor lymphocyte infiltration, compared to those with more stable genomes (CIN-). This finding is paradoxical, as genomic instability is expected to evoke an innate immune response. Importantly, CIN+ tumors and cell lines exhibited suppressed expression of proteins involved in MHC class I antigen presentation at least partly due to DNA hypermethylation of the corresponding genes. Using a mouse model of the in vivo evolution of aneuploid tumors, we found that the induction of chromosomal instability in tumor cells is highly immunogenic due to the activation of the STING/TBK1 pathway and consequent increased interferon signaling and antigen presentation. However, tumors evolving under immune pressure suppress the STING/TBK1 and antigen presentation pathways and evade anti-tumor immune responses. In contrast, CIN+ tumors that develop under low immune pressure in both humans and mice retain efficient MHC class I antigen presentation and immunogenicity. Altogether, this study identifies an important mechanism of immune evasion in chromosomally unstable tumors.

U2AF1 mutations induce oncogenic IRAK4 isoforms and activate innate immune pathways in myeloid malignancies.

Spliceosome mutations are common in myelodysplastic syndromes (MDS) and acute myeloid leukaemia (AML), but the oncogenic changes due to these mutations have not been identified. Here a global analysis of exon usage in AML samples revealed distinct molecular subsets containing alternative spliced isoforms of inflammatory and immune genes. Interleukin-1 receptor-associated kinase 4 (IRAK4) was the dominant alternatively spliced isoform in MDS and AML and is characterized by a longer isoform that retains exon 4, which encodes IRAK4-long (IRAK4-L), a protein that assembles with the myddosome, results in maximal activation of nuclear factor kappa-light-chain-enhancer of B cells (NF-κB) and is essential for leukaemic cell function. Expression of IRAK4-L is mediated by mutant U2 small nuclear RNA auxiliary factor 1 (U2AF1) and is associated with oncogenic signalling in MDS and AML. Inhibition of IRAK4-L abrogates leukaemic growth, particularly in AML cells with higher expression of the IRAK4-L isoform. Collectively, mutations in U2AF1 induce expression of therapeutically targetable 'active' IRAK4 isoforms and provide a genetic link to activation of chronic innate immune signalling in MDS and AML.

Revealing static and dynamic modular architecture of the eukaryotic protein interaction network.

In an effort to understand the dynamic organization of the protein interaction network and its role in the regulation of cell behavior, positioning of proteins into specific network localities was studied with respect to their expression dynamics. First, we find that constitutively expressed and dynamically co-regulated proteins cluster in distinct functionally specialized network neighborhoods to form static and dynamic functional modules, respectively. Then, we show that whereas dynamic modules are mainly responsible for condition-dependent regulation of cell behavior, static modules provide robustness to the cell against genetic perturbations or protein expression noise, and therefore may act as buffers of evolutionary as well as population variations in cell behavior. Observations in this study refine the previously proposed model of dynamic modularity in the protein interaction network, and propose a link between the evolution of gene expression regulation and biological robustness.

Tumor Cell Autonomous RON Receptor Expression Promotes Prostate Cancer Growth Under Conditions of Androgen Deprivation.

Current treatment strategies provide minimal results for patients with castration-resistant prostate cancer (CRPC). Attempts to target the androgen receptor have shown promise, but resistance ultimately develops, often due to androgen receptor reactivation. Understanding mechanisms of resistance, including androgen receptor reactivation, is crucial for development of more efficacious CRPC therapies. Here, we report that the RON receptor tyrosine kinase is highly expressed in the majority of human hormone-refractory prostate cancers. Further, we show that exogenous expression of RON in human and murine prostate cancer cells circumvents sensitivity to androgen deprivation and promotes prostate cancer cell growth in both in vivo and in vitro settings. Conversely, RON loss induces sensitivity of CRPC cells to androgen deprivation. Mechanistically, we demonstrate that RON overexpression leads to activation of multiple oncogenic transcription factors (namely, ß-catenin and NF-κB), which are sufficient to drive androgen receptor nuclear localization and activation of AR responsive genes under conditions of androgen deprivation and support castration-resistant growth. In total, this study demonstrates the functional significance of RON during prostate cancer progression and provides a strong rationale for targeting RON signaling in prostate cancer as a means to limit resistance to androgen deprivation therapy.