Cell type composition in bulk prostate cancer tissue is a prognostic biomarker

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Prostate cancer shows significant heterogeneity, necessitating improved molecular subtyping for patient stratification.
• Limited somatic mutations in prostate cancer highlight the value of whole-transcriptome data for molecular characterization.

Purpose of the Study:

• To characterize primary prostate cancer cell type composition using bulk tissue transcriptomes.
• To define novel molecular subtypes based on cell composition for improved patient stratification and outcome prediction.

Main Methods:

• Analysis of bulk tissue transcriptomes from four cohorts to deconvolve cell types.
• Development and validation of a machine learning model for classifying cell type composition subtypes.
• Investigation of interfocal and intrafocal heterogeneity in multifocal prostate cancer.

Main Results:

• Three distinct cell type composition subtypes were identified: T cells enriched (TCE), epithelial cells enriched (EPCE), and tumor-associated stromal cells enriched (TASCE).
• The subtyping correlated significantly with clinicopathological parameters (e.g., Gleason score).
• The TASCE subtype was significantly associated with a higher risk of biochemical recurrence, and the classifier showed predictive potential.

Conclusions:

• A novel prostate cancer subgrouping based on cell type composition was established.
• The TASCE subtype represents a molecular signature associated with increased biochemical recurrence risk.
• Understanding cell type composition offers a promising avenue for prostate cancer research and clinical management.