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Isolation, Culture, and Characterization of Prostate Cancer-Associated Fibroblasts
Published on: August 1, 2025
Expression changes in the stroma of prostate cancer predict subsequent relapse
Zhenyu Jia1, Farah B Rahmatpanah, Xin Chen
1Department of Pathology and Laboratory Medicine, University of California Irvine, Irvine, California, United States of America. zjia@uci.edu
Plos One
|August 8, 2012
Summary
New biomarkers from the tumor microenvironment can predict prostate cancer relapse. This approach helps avoid overtreatment for patients unlikely to die from the disease.
Area of Science:
- Oncology
- Genomics
- Biomarker Discovery
Background:
- Overtreatment of prostate cancer is common, affecting patients who would not die from the disease.
- Tumor heterogeneity poses a challenge for identifying reliable prostate cancer biomarkers.
- The tumor microenvironment, specifically tumor-adjacent stroma, offers a potential source for consistent prognostic markers.
Purpose of the Study:
- To identify biomarkers within the tumor microenvironment for predicting prostate cancer relapse.
- To develop a prognostic classifier based on gene expression in the prostate tumor microenvironment.
Main Methods:
- Compared Affymetrix gene expression profiles in stroma near tumor.
- Identified probe sets correlated with time-to-relapse.
- Compared gene expression between rapid and slow relapsing prostate cancer patients post-prostatectomy.
- Developed and tested a PAM-based classifier using stroma samples.
Main Results:
- Identified 115 probe sets significantly correlated with time-to-relapse.
- Found 131 differentially expressed microarray probe sets between rapid and indolent relapse groups.
- Developed a classifier achieving 87% accuracy in predicting patient risk status.
- Demonstrated reproducible changes in the prostate cancer microenvironment predictive of outcomes.
Conclusions:
- The tumor microenvironment contains reproducible biomarkers for predicting prostate cancer outcomes.
- A novel prognostic classifier based on tumor-adjacent stroma gene expression shows high accuracy.
- This approach may help personalize treatment and reduce overtreatment in prostate cancer.
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