Prostate Cancer Treatment and Research

This study shows that combining a novel ERβ ligand with Enzalutamide reduces MYC signaling and growth in advanced prostate cancer.

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

This paper identifies hydroxyflutamide as an AR arrested agonist that induces DNA damage in prostate cancer cells, enabling selective radiosensitization without promoting growth.

This study shows HOXB13 promotes prostate cancer proliferation by altering chromatin accessibility through interactions with the SWI/SNF complex, particularly in AR-negative castration-resistant prostate cancer.

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

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.

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.

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.

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.

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.

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

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

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.

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.

This study identifies potential biomarkers for primary prostate cancer through meta-analysis of transcriptomic data and functional enrichment analysis.

The paper identifies patient-specific deregulated regulatory networks in prostate cancer to inform personalized therapeutic strategies.

The paper identifies SCAND1 as a tumor suppressor that negatively regulates CDC37 gene transcription by inhibiting MZF1 in prostate cancer.

The paper identifies a basal stem cell subpopulation in the prostate using lineage tracing, functional analysis, and single-cell RNA-seq, showing Zeb1+ cells are multipotent prostate basal stem cells.