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Identification of Molecular Markers Associated with Prostate Cancer Subtypes: An Integrative Bioinformatics Approach.

Ilaria Granata1, Paola Barboro2

  • 1High Performance Computing and Networking Institute (ICAR), National Council of Research (CNR), Via Pietro Castellino 111, 80131 Naples, Italy.

Biomolecules
|January 23, 2024
PubMed
Summary

This study identifies key genes for stratifying prostate cancer (PCa) risk and distinguishing castration-resistant PCa (CRPC) phenotypes. These findings support developing targeted therapies for advanced prostate cancer.

Keywords:
castration-resistant prostate cancerdata integrationessential genesmolecular profilingprecision medicineprostate cancer

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Area of Science:

  • Oncology
  • Genetics
  • Pharmacology

Background:

  • Prostate cancer (PCa) is androgen-dependent, but resistance (CRPC) emerges under treatment, leading to diverse phenotypes.
  • Castration-resistant prostate cancer (CRPC) remains incurable, highlighting the need for novel therapeutic targets.
  • Context-specific essential genes are promising candidates for targeted anti-cancer therapies.

Purpose of the Study:

  • To identify and validate gene sets for stratifying PCa patient risk and discriminating CRPC phenotypes.
  • To explore the association of identified genes with cancer dependency and clinical outcomes.
  • To discover potential drug candidates for treating lethal variants of PCa using computational repositioning.

Main Methods:

  • Integration of gene/protein annotations and transcriptomic data to identify consensus gene lists.
  • Receiver Operating Characteristic (ROC) and Kaplan-Meier survival analyses for gene set validation.
  • Evaluation of gene association with cancer dependency and drug repositioning for therapeutic targeting.

Main Results:

  • Identified gene sets effectively stratify PCa risk and differentiate CRPC phenotypes based on androgen receptor activity.
  • Deregulation of PCa-related genes correlates with survival, metastasis, and recurrence risk.
  • CRPC-related genes distinguish between adenocarcinoma and neuroendocrine phenotypes; some genes show context-specific essentiality.

Conclusions:

  • The study provides a proof-of-concept for an integrative approach to identify biomarkers for PCa progression and CRPC.
  • Identified genes and drug candidates offer potential for precision medicine in treating advanced prostate cancer.
  • This research advances the understanding of CRPC pathogenesis and supports the development of targeted therapies.