Prostate Cancer Treatment and Research

Androgen receptor activity inversely correlates with immune cell infiltration and immunotherapy response across multiple cancer lineages

The paper examines the relationship between androgen receptor activity and immune cell infiltration, showing that lower AR activity correlates with increased immune activity and better immunotherapy response across multiple cancers.

TP63-TRIM29 axis regulate enhancer methylation and chromosomal instability in prostate cancer

The paper identifies TP63 and TRIM29 as regulators of enhancer methylation and chromosomal instability in prostate cancer by integrating multi-omics data from The Cancer Genome Atlas.

Agent-based modeling of the prostate tumor microenvironment uncovers spatial tumor growth constraints and immunomodulatory properties

This study uses an agent-based model to simulate prostate cancer growth and ADT effects, revealing CRPC development and immunomodulatory interactions in the tumor microenvironment.

Neuroendocrine Prostate Cancer Drivers SOX2 and BRN2 Confer Differential Responses to Imipridones ONC201, ONC206, and ONC212 in Prostate Cancer Cell Lines

This study investigates whether neuroendocrine differentiation (NED) affects sensitivity to imipridones ONC201 and ONC206 in prostate cancer cell lines, finding differential responses based on SOX2 and BRN2 overexpression.

Synergistic combination therapy with ONC201 or ONC206, Enzalutamide and Darolutamide in preclinical studies of castration-resistant prostate cancer

This study shows that combining ONC201 with enzalutamide or darolutamide synergistically reduces mCRPC cell viability and PSA levels, with in vivo anti-tumor effects.

Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in AR-altered lethal prostate cancer

Chromatin Accessibility and Pioneer Factor FOXA1 Shape Glucocorticoid Receptor Action in Prostate Cancer

The paper identifies chromatin pre-accessibility and FOXA1-mediated repression as key regulators of GR action in prostate cancer, offering new strategies to combat antiandrogen resistance.

5-hydroxymethylcytosine sequencing in plasma cell-free DNA identifies unique epigenomic features in prostate cancer patients resistant to androgen deprivation therapy

This study identifies 5hmC-based gene set activity scores in cfDNA as biomarkers for early detection of ADT resistance in prostate cancer.

Molecular analysis of archival diagnostic prostate cancer biopsies identifies genomic similarities in cases with progression post-radiotherapy, and those with de novo metastatic disease.

Heterogeneity and genomic evolution of metastatic prostate cancer

The paper identifies 14 metastasis-related mutated genes and develops a Mscore to predict metastatic risk in primary prostate tumors using xgboost.

curatedPCaData: Integration of clinical, genomic, and signature features in a curated and harmonized prostate cancer data resource

curatedPCaData harmonizes prostate cancer datasets to enable meta-analysis and clinical insights across multiple cohorts.

Intermediate basal cell population in prostate homeostasis and cancer initiation

The paper identifies an intermediate basal cell population (Basal-B) in the prostate that shows lineage plasticity and contributes to both homeostasis and cancer initiation.

BAZ2A-RNA mediated association with TOP2A and KDM1A represses gene expression in prostate cancer

The paper identifies a novel RNA-based mechanism in prostate cancer where BAZ2A interacts with TOP2A and KDM1A to repress gene expression, distinct from its role in rRNA gene silencing.

The CDK7 inhibitor CT7001 (Samuraciclib) targets proliferation pathways to inhibit advanced prostate cancer

This study investigates the antitumour activity of CT7001, a CDK7 inhibitor, in castration-resistant prostate cancer models, showing it inhibits proliferation and enhances enzalutamide efficacy.

Identification of Biomarkers and Trajectories of Prostate Cancer Progression: A Bioinformatics Fusion of Weighted Correlation Network Analysis and Machine Learning

This study identifies biomarkers and trajectories of prostate cancer progression using bioinformatics fusion of weighted correlation network analysis and machine learning, finding the EZH2-TROAP axis as a key trajectory and 58 validated biomarkers.

Gene Expression Analysis of Patients with Prostate Cancer vs Benign Prostate Hyperplasia

This study identifies differentially expressed genes in prostate epithelial stem and transit amplifying cells from prostate cancer and benign prostate hyperplasia patients, finding USP10 and SOCS3 associated with prostate cancer.

Targeting the BAG-1 family of co-chaperones in lethal prostate cancer.

This study investigates Thio-2's mechanism of action in inhibiting AR signaling in CRPC, showing it acts independently of BAG-1 isoforms and with potential AR NTD binding.

Multi-omics biomarkers aid prostate cancer prognostication

This study identifies multi-omics prognostic signatures for prostate cancer using transcriptomics and metabolomics data, showing their ability to stratify patients into distinct risk groups.

Patterns of Structural Variation Define Prostate Cancer Across Disease States

This study identifies distinct structural variation patterns in prostate cancer across disease states, defining clinically actionable subgroups based on whole genome profiling.

Integrating pharmacogenomics data-driven prediction with bulk and single-cell RNAseq to demonstrate the efficacy of an NAMPT inhibitor against aggressive, taxane-resistant, and stem-like cells in lethal prostate cancer

The paper uses scRNAseq and pharmacogenomics to identify FK866 as a potential drug for aggressive prostate cancer, showing its efficacy against drug-resistant and stem-like cells.

The genes controlling normal function of citrate and spermine secretion is lost in aggressive prostate cancer and prostate model systems

The paper identifies a gene signature associated with citrate and spermine secretion in prostate epithelial cells and shows its expression decreases in aggressive prostate cancer.

MYC drives aggressive prostate cancer by disrupting transcriptional pause release at androgen receptor targets

This study shows MYC overexpression disrupts AR transcriptional pause release, promoting aggressive prostate cancer progression.

Identification of transcriptional network disruptions in drug-resistant prostate cancer with TraRe

The paper identifies transcriptional network disruptions in drug-resistant prostate cancer using TraRe, uncovering key regulatory modules and transcription factors associated with resistance.

Cistrome and transcriptome analysis identifies unique androgen receptor (AR) and AR- V7 splice variant chromatin binding and transcriptional activities

The paper compares the chromatin binding and transcriptional activities of AR and AR-V7 in prostate cancer cells, finding distinct cistromes and transcriptomes.

Genomic analyses identify key molecules and significant signaling pathways in AZIN1 regulated prostate cancer cells

The paper identifies key molecules and signaling pathways in AZIN1-regulated prostate cancer using RNA-seq data from the GSE189379 dataset.

Genomic Analyses of the Metastasis-derived LNCaP, VCaP, and PC3-AR Prostate Cancer Cell Lines

The paper reports genomic analyses of prostate cancer cell lines, identifying mutations and chromothripsis events associated with TP53 inactivation.

Biologically informed deep neural network for prostate cancer classification and discovery

This paper introduces a biologically informed deep learning model for prostate cancer classification and identifies molecular drivers of treatment resistance.

BAZ2A association with H3K14ac is required for the transition of prostate cancer cells into a cancer stem-like state

This study shows BAZ2A's role in prostate cancer stem-like state transition through its interaction with H3K14ac and repression of tumor suppressor genes.

PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts

PCaDB provides a database for analyzing transcriptomes from prostate cancer cohorts and includes scRNA-seq data and prognostic signatures to aid in diagnosis and prognosis.

In silico Computed Clusters of Prostate Luminal Progenitors Match FACS-Enriched LSCmed cells

The paper re-analyzes scRNA-seq datasets to show that luminal progenitor clusters across studies overlap and matches FACS-enriched LSCmed cells in mice and humans.