Somatic tissue engineering in mouse models reveals an actionable role for WNT pathway alterations in prostate cancer metastasis
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ABSTRACT: To study genetic factors that influence the progression and therapeutic response of advanced prostate cancer, we developed a fast and flexible system that introduces genetic alterations relevant to human disease directly into the prostate glands of mice using tissue electroporation. These electroporation based genetically engineered mouse models (EPO-GEMM) recapitulate features of traditional germline models and, by modeling genetic factors linked to late stage human disease, can produce tumors that are metastatic and castration resistant. Unexpectedly, a subset of particularly metastatic tumors acquired WNT pathway alterations, which are also associated with metastatic prostate cancer in humans. Harnessing features linked to the EPO-GEMM approach, we validate the WNT pathway as a key event in driving metastatic disease, a finding that we confirm in an orthogonal approach using mouse prostate organoids. Moreover, we show that tumors harboring WNT pathway alterations are sensitive to pharmacological WNT pathway inhibition. Thus, by leveraging the power of EPO-GEMMs, our studies reveal a functional role for WNT signaling in driving prostate cancer metastasis and validate the WNT pathway as an actionable therapeutic target in metastatic prostate cancer.
Project description:To study the genetic factors that influence the immune landscape of castration-resistant prostate cancer (CRPC), we utilized a flexible, electroporation-based system to introduce genetic alterations relevant to human disease directly into the prostate glands of mice. These electroporation-based genetically engineered mouse models (EPO-GEMM) recapitulate features of traditional models, and allow us to investigate distinct genetic subtypes of prostate cancer within an intact tumor-immune microenvironment. We observed differences between genetic subtypes of CRPC, with MYC-driven subtypes exhibiting a "cold" immune landscape compared to others. Interestingly, we found that the compound loss of different tumor suppressors such as Pten or p53 with MYC further impacts the inflammatory profile of prostate cancer, with MYC and p53 (MP) alterations cooperating to drive VEGF expression and immune suppression. VEGF signaling blockade resulted in re-activation of cytotoxic T cell anti-tumor immunity and restored sensitivity to immunotherapy in MP CRPC. Thus, by leveraging the power of EPO-GEMMs to generate distinct subtypes of CRPC, our studies reveal a functional role for VEGF signaling in driving prostate cancer immune evasion and validate the VEGF pathway as an actionable therapeutic target in MYC and p53 altered prostate cancer.
Project description:Analysis of the transcriptome of mouse models of prostate cancer to assemble a mouse prostate cancer interactome. To assemble the mouse prostate cancer interactome, we collected 13 distinct mice or genetically-engineered mouse models (GEMMs), which together represent the full spectrum of prostate cancer phenotypes including: normal epithelium (i.e., wild-type), low-grade PIN (i.e., Nkx3.1 and APT), high-grade PIN and adenocarcinoma (i.e., APT-P; APC; Myc; NP; Erg-P; and NP53), castration-resistant prostate cancer (i.e., NP-AI), and metastatic prostate cancer (i.e., NPB; NPK; and TRAMP). To further enhance the heterogeneity afforded by this diversity of mouse models, we pharmacologically perturbed each GEMM using 13 different drugs (or appropriate vehicle). The resulting mouse prostate tissue/tumor dataset encompassed 384 expression profiles Total RNA obtained from prostate tumors/tissues of 13 mouse models of prostate cancer treated with 13 different drugs for 5 consecutive days. Prostate tumors/tissues were harvested and processed for RNA isolation and transcriptome analysis.
Project description:An integrative analysis of this compendium of proteomic alterations and transcriptomic data was performed revealing only 48-64% concordance between protein and transcript levels. Importantly, differential proteomic alterations between metastatic and clinically localized prostate cancer that mapped concordantly to gene transcripts served as predictors of clinical outcome in prostate cancer as well as other solid tumors. Keywords: prostate cancer progression 13 individual benign prostate, primary and metastatic prostate cancer samples and 6 pooled samples from benign,primary or metastatic prostate cancer tissues.
Project description:We sought to determine whether molecular alterations in tumor stroma influence prostate cancer progression and metastatic potential. To accomplish this, we compared mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for both common and GEMM-specific transcriptional programs. These are conserved between mouse models and human prostate cancers with the same genomic drivers. The transcriptional profiles of the stroma of murine models of advanced disease were similar to those of human prostate cancer bone metastases, with periostin expression by stromal cells influencing invasion and neuroendocrine differentiation. These profiles were then used to build a robust gene signature that can predict metastatic progression in localized disease independent of Gleason score. Taken together, this offers new evidence that the stromal microenvironment mediates prostate cancer progression.
Project description:We sought to determine whether molecular alterations in tumor stroma influence prostate cancer progression and metastatic potential. To accomplish this, we compared mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for both common and GEMM-specific transcriptional programs. These are conserved between mouse models and human prostate cancers with the same genomic drivers. The transcriptional profiles of the stroma of murine models of advanced disease were similar to those of human prostate cancer bone metastases, with periostin expression by stromal cells influencing invasion and neuroendocrine differentiation. These profiles were then used to build a robust gene signature that can predict metastatic progression in localized disease independent of Gleason score. Taken together, this offers new evidence that the stromal microenvironment mediates prostate cancer progression.
Project description:We sought to determine whether molecular alterations in tumor stroma influence prostate cancer progression and metastatic potential. To accomplish this, we compared mesenchymal cells from four genetically engineered mouse models (GEMMs) of prostate cancer representing different stages of the disease to their wild-type (WT) counterparts by single-cell RNA sequencing (scRNA-seq) and, ultimately, to human tumors with comparable genotypes. We identified 8 transcriptionally and functionally distinct stromal populations responsible for both common and GEMM-specific transcriptional programs. These are conserved between mouse models and human prostate cancers with the same genomic drivers. The transcriptional profiles of the stroma of murine models of advanced disease were similar to those of human prostate cancer bone metastases, with periostin expression by stromal cells influencing invasion and neuroendocrine differentiation. These profiles were then used to build a robust gene signature that can predict metastatic progression in localized disease independent of Gleason score. Taken together, this offers new evidence that the stromal microenvironment mediates prostate cancer progression.
Project description:Background: Metastases result in 90% of all cancer deaths. Prostate cancer primary tumors evolve to become metastatic through selective alterations, such as amplification and deletion of genomic DNA. Methods: Genomic DNA copy number alterations were used to develop a gene signature that measured the metastatic potential of a prostate cancer primary tumor. We studied the genomic landscape of these alterations in 294 primary tumors and 49 metastases from 5 independent cohorts. Receiver-operating characteristic cross-validation and Kaplan-Meier survival analysis were performed to assess the accuracy of our predictive model. The signature was measured in a panel of 337 cancer cell lines from 29 different tissue origins. Results: We identified 399 copy number alterations around genes that were over-represented in metastases and predictive of whether a primary tumor will metastasize. Cross-validation analysis resulted in a predictive accuracy of 80.5% and log rank analysis of the metastatic potential score was significantly related to the endpoint of metastasis-free survival (p=0.014). The metastatic signature was observed in cell lines originating from lung, breast, colon, thyroid, rectum, pancreas and melanoma. The signature was comprised in part of genes of known or putative metastatic role — 8 solute carrier genes, 6 Cadherin family genes and 5 potassium channel genes — that function in metabolism, cell-to-cell adhesion and escape from anoikis/apoptosis. Conclusions: Somatic Copy number alterations are an independent predictor of metastatic potential. The data indicate a prognostic utility for using primary tumor genomics to assist in clinical decision making and developing therapeutics for prostate and likely other cancers. genomic DNA from 29 prostate cancer tumors with matched normals run on Affymetrix 6.0 SNP arrays.
Project description:Prioritizing cancer treatments at the individual patient level remains challenging, and performing co-clinical studies using patient-derived models in real-time is often not unfeasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework to predict and validate drug sensitivity sensitivity in both a human tumors and in its their pre-existing high est-fidelity (cognate) (cognate) model(s)—for contextual in vivo validation—) by leveraging perturbational profiles of clinically-relevant oncology drugs. As proof-of-concept, we applied OncoLoop to prostate cancer (PCa) using a series of genetically engineered mouse models (GEMMs) that capture the broad spectrum of disease states, including metastatic, castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of published cohorts revealed that most patients were represented by at least one cognate GEMM-derived tumor (GEMM-DT), based on upon Master Regulator (MR) conservation analysis. Drugs recurrently predicted to recurrently invert MR protein activity in patients and their cognate GEMM-DTs were successfully validated, including in two cognate allografts and one cognate patient derived xenograft (PDX). OncoLoop is highly generalizable and can be extended to other cancers and potentially other pathologdiseasesies.
Project description:Current smokers develop metastatic prostate cancer more frequently than nonsmokers, suggesting that a tobacco-derived factor induces metastasis. To identify smoking-induced alterations in human prostate tumors, we analyzed gene and protein expression of tumors from current, past, and never smokers and observed distinct molecular alterations in current smokers. Specifically, an immune and inflammation signature was identified in prostate tumors of current smokers that was either attenuated or absent in past and never smokers. Key characteristics of this signature included augmented immunoglobulin expression by tumor-infiltrating B cells, NF-kB activation, and increased interleukin-8 in tumor and blood. In an alternate approach to characterize smoking-induced oncogenic alterations, we explored the effects of nicotine in prostate cancer cells and prostate cancer-prone TRAMP mice. These experiments showed that nicotine increases both invasiveness of human prostate cancer cells and metastasis in tumor-bearing TRAMP mice, indicating that nicotine can induce a phenotype that resembles the epidemiology of smoking-associated prostate cancer progression. In summary, we describe distinct oncogenic alterations in prostate tumors from current smokers and show that nicotine can enhance prostate cancer metastasis. Prostate tissues of cancer patients were selected for RNA extraction and hybridization on Affymetrix microarrays. Gene expression profiles of current, past and never smokers were compared.
Project description:Current smokers develop metastatic prostate cancer more frequently than nonsmokers, suggesting that a tobacco-derived factor induces metastasis. To identify smoking-induced alterations in human prostate tumors, we analyzed gene and protein expression of tumors from current, past, and never smokers and observed distinct molecular alterations in current smokers. Specifically, an immune and inflammation signature was identified in prostate tumors of current smokers that was either attenuated or absent in past and never smokers. Key characteristics of this signature included augmented immunoglobulin expression by tumor-infiltrating B cells, NF-kB activation, and increased interleukin-8 in tumor and blood. In an alternate approach to characterize smoking-induced oncogenic alterations, we explored the effects of nicotine in prostate cancer cells and prostate cancer-prone TRAMP mice. These experiments showed that nicotine increases both invasiveness of human prostate cancer cells and metastasis in tumor-bearing TRAMP mice, indicating that nicotine can induce a phenotype that resembles the epidemiology of smoking-associated prostate cancer progression. In summary, we describe distinct oncogenic alterations in prostate tumors from current smokers and show that nicotine can enhance prostate cancer metastasis. TRAMP mice in five replicates received either tap water or a solution of 250 µg/ml of nicotine [nicotine tartrate salt (Sigma-Aldrich, St. Louis, MO)] in tap water