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Updated: Oct 11, 2025
Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking
Published on: November 17, 2023
Patient-matched analysis identifies deregulated networks in prostate cancer to guide personalized therapeutic
Akinchan Kumar1,2,3,4,5, Yasenya Kasikci1,2,3,4,5, Alaa Badredine1,2,3,4,5,6
1Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Department of Functional Genomics and Cancer Illkirch, France.
Abstract:
Prostate cancer (PrCa) is the second most common malignancy in men. More than 50% of advanced prostate cancers display the TMPRSS2-ERG fusion. Despite extensive cancer genome/transcriptome data, little is known about the impact of mutations and altered transcription on regulatory networks in the PrCa of individual patients. Using patient-matched normal and tumor samples, we established somatic variations and differential transcriptome profiles of primary ERG-positive prostate cancers. Integration of protein-protein interaction and gene-regulatory network databases defined highly diverse patient-specific network alterations. Different components of a given regulatory pathway were altered by novel and known mutations and/or aberrant gene expression, including deregulated ERG targets, and were validated by using a novel in silico methodology. Consequently, different sets of pathways were altered in each individual PrCa. In a given PrCa, several deregulated pathways share common factors, predicting synergistic effects on cancer progression. Our integrated analysis provides a paradigm to identify druggable key deregulated factors within regulatory networks to guide personalized therapies.
Insights
This study reveals diverse, patient-specific regulatory network alterations in prostate cancer (PrCa) by integrating mutation and gene expression data. Identifying shared deregulated factors offers a new approach for personalized PrCa therapies.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Prostate cancer (PrCa) is a leading male malignancy.
- Over 50% of advanced PrCa cases exhibit the TMPRSS2-ERG fusion.
- Understanding patient-specific regulatory network changes in PrCa remains limited.
Purpose of the Study:
- To investigate somatic variations and transcriptome profiles in primary ERG-positive prostate cancers.
- To define patient-specific gene regulatory network alterations.
- To identify potential therapeutic targets for personalized PrCa treatment.
Main Methods:
- Analysis of patient-matched normal and tumor samples.
- Integration of protein-protein interaction and gene-regulatory network databases.
- Utilized a novel in silico methodology for validation.
Main Results:
- Identified highly diverse, patient-specific network alterations in PrCa.
- Demonstrated that different regulatory pathways are altered in each patient.
- Discovered shared deregulated factors across multiple pathways within individual PrCa, suggesting synergistic effects.
Conclusions:
- Patient-specific network alterations are a hallmark of prostate cancer.
- Integrated analysis can reveal druggable targets within deregulated networks.
- This approach provides a framework for guiding personalized PrCa therapies.
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