Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Distinct mesenchymal cell states mediate prostate cancer progression (human)

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE244267 | GEO | 2023/10/10

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Distinct mesenchymal cell states mediate prostate cancer progression (mouse)

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.

2023-10-10 | GSE244269 | GEO

Distinct mesenchymal cell states mediate prostate cancer progression [Spatial Transcriptomics]

2023-12-01 | GSE248466 | GEO

Somatic tissue engineering in mouse models reveals an actionable role for WNT pathway alterations in prostate cancer metastasis

Project description: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.

2020-04-28 | GSE139340 | GEO

Cross-species analysis of genome-wide regulatory networks identifies a synergistic dependency between FOXM1 and CENPF that drives prostate cancer malignancy

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.

2014-05-12 | E-GEOD-53202 | biostudies-arrayexpress

Cross-species analysis of genome-wide regulatory networks identifies a synergistic dependency between FOXM1 and CENPF that drives prostate cancer malignancy

2014-05-12 | GSE53202 | GEO

Drug perturbation RNA sequencing of 2 prostate cancer cell lines

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.

2022-10-31 | GSE199800 | GEO

GEMM CRC collection analysis

Project description:A collection of genetically engineered mouse models (GEMM) of colorectal cancer (CRC) were created, and primary tumors from these GEMMs were analyzed. Primary CRC tumors from these GEMMs were genotyped to confirm that they contain the core genetic lesions of interest, including APC, P53, KRAS, and BRAF. Primary tumors from GEMMs with combinations of lesions of interest were analyzed by whole genome expression, and their expression profiles were compared to determine how they segregate. Signatures were then generated from GEMM tumors of interest and compared to human clinical datasets with expression and outcome data. Primary tumors from CRC GEMMs with different combinations of mutant alleles of interested were generated and analyzed. Alleles include mutant forms of APC (A), P53 (P), KRAS (K) and BRAF (B).

2014-07-01 | E-GEOD-50794 | biostudies-arrayexpress

Predicting drug responsiveness in humans cancers using genetically engineered mice

Project description:Anti-cancer drug testing is challenging, but genetically engineered mouse models (GEMMs) and orthotopic, syngeneic transplants (OSTs) may offer advantages for pre-clinical testing including an intact microenvironment. We examined the efficacy of six chemotherapeutic or targeted anti-cancer drugs, alone and in combination, using over 500 GEMMs/OSTs representing three distinct breast cancer subtypes: Basal-like (C3(1)-T-antigen GEMM), Luminal B (MMTV-Neu GEMM), and Claudin-low (T11/TP53-/- OST). While a few single agents offered exceptional efficacy like lapatinib in the Neu/ERBB2 driven model, combination therapies tended to be more active and life prolonging. Using expression profiling of chemotherapy treated murine tumors, we identified an expression signature that was able to predict pathological complete response to neoadjuvant anthracycline-taxane treated human breast cancer patients, even after accounting for the common clinical variables and other genomic signatures. These results show that credentialed murine models can predict the efficacy of would-be anti-cancer compounds in humans, and that GEMMs can be used to develop new biomarkers of therapeutic responsiveness in humans. control X treatment

2014-01-01 | E-GEOD-37915 | biostudies-arrayexpress

Next-generation sequencing to define the impact of metastatic prostate cancer on neutrophils

Project description:Purpose: Prostate cancer most frequently metastasizes to bone and is incurable. Metastatic prostate cancer cells thrive in bone through molecular regulation of surrounding bone stroma; however, it is unclear how non-metastatic vs. metastatic cancer differentially alter the bone cells. Since neutrophils are the most abundant stromal cell in bone, the goal of this study was to identify prostate cancer-induced transcriptomic changes in bone marrow neutrophils for comparison to non-metastatic prostate cancer cells.

2022-08-03 | GSE193468 | GEO

GEMM CRC collection analysis

2014-07-01 | GSE50794 | GEO