Unique Biological Characteristics of Patients with High Gleason Score and Localized/Locally Advanced Prostate Cancer Using an In Silico Translational Approach

TL;DR

This study explores how high Gleason scores in prostate cancer are linked to increased cell proliferation, immune cell infiltration, and high mutation rates using genomic data.

Contribution

The first report linking Gleason scores to homologous recombination deficiency and intratumor heterogeneity through in silico analysis.

Findings

High Gleason scores correlate with increased activity of cell proliferation-related genes and immune cell infiltration.

GS levels are positively associated with homologous recombination defects, intratumor heterogeneity, and high mutation rates.

These biological features may contribute to worse clinical outcomes in prostate cancer patients.

Abstract

Gleason score (GS) is one of the best predictors of prostate cancer aggressiveness. GS classifies cancer cells based on the histological patterns of prostate tissue sections and does not evaluate the nuclear grade or proliferation of the cancer cells. A small number of studies focused on the association between gene expression signatures and GS using an in silico translational approach. GS is associated with cell cycle-related genes, changes in DNA repair genes, stromal-related genes, immune-related genes, cuprotosis-related genes, and several specific genes. To our knowledge, this is the first report showing that GS was positively correlated not only with homologous recombination deficiency mutations but also with intratumor heterogeneity, fractional mutations, single nucleotide variant neoantigen, silent mutation rate, and non-silent mutation rate. Our findings emphasize that GS reflects not only morphological abnormalities but also differences in cancer cell proliferation, immune cell infiltration, and high mutation rates, which may affect prognosis.

Gleason score (GS) is one of the best predictors of prostate cancer (PCa) aggressiveness; however, its biological features need to be elucidated. This study aimed to explore the biological characteristics of localized/locally advanced PCa stratified using in silico GS analysis. Biological features were analyzed using gene set variation analysis and the xCell algorithm with mRNA expression in two independent public databases: The Cancer Genome Atlas (TCGA) (n = 493; radical prostatectomy cohort) and GSE116918 (n = 248; radiation therapy cohort). GS levels were positively correlated with the activity levels of cell proliferation-related gene sets, including E2F targets, the G2M checkpoint, the mitotic spindle, and MYC targets v1 and v2 in both cohorts. Furthermore, GS levels were positively associated with the activity levels of immune-related gene sets and infiltrating fractions of immune cells, including CD4+ memory T cells, dendritic cells, M1 macrophages, and Th2 cells, in both cohorts. Notably, GS levels were positively associated with the score levels of homologous recombination defects, intratumor heterogeneity, fraction genome alteration, neoantigens, and mutation rates in the TCGA cohort. In conclusion, PCa with high GS levels was associated with cancer cell proliferation, immune cell infiltration, and high mutation rates, which may reflect worse clinical outcomes.

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