Stromal Gene Expression is Predictive for Metastatic Primary Prostate Cancer

Area of Science:

• Oncology
• Genomics
• Biomarker Discovery

Background:

• Current prostate cancer (PCa) clinical grading systems and nomograms lack precision for treatment decisions.
• There is a critical need for novel biomarkers to accurately stratify PCa patients.
• Existing methods struggle to distinguish indolent from aggressive disease effectively.

Purpose of the Study:

• To identify a robust prognostic signature for distinguishing indolent from aggressive prostate cancer (PCa).
• To develop and validate a gene expression signature that predicts metastatic potential.
• To improve risk stratification for PCa patients.

Main Methods:

• Whole-genome and whole-transcriptome sequencing of PCa patient-derived xenograft (PDX) models.
• Development of a 93-gene stroma-derived metastasis signature (SDMS) using lasso regularization.
• Validation of the SDMS in multiple independent clinical cohorts, including intermediate-risk patients.

Main Results:

• A strong association was observed between stromal gene expression and metastatic phenotype.
• The SDMS was validated as an independent prognostic factor for metastasis in PCa.
• Higher SDMS scores correlated with worse prognosis and improved risk stratification accuracy.

Conclusions:

• The stroma-derived metastasis signature (SDMS) is a validated, independent prognostic tool for PCa.
• SDMS can predict the metastatic potential of early-stage prostate tumors.
• This signature can enhance clinical decisions regarding active surveillance versus definitive treatment.