Exploring the Molecular Mechanism and Role of Glutathione S-Transferase P in Prostate Cancer
Year: 2025
Type: article
Abstract: Aims: To investigate the effect of Glutathione metabolism in prostate cancer pathogenesis. Background: There is growing evidence that Glutathione metabolism plays an important role in prostate cancer, with genes encoding key enzymes in this pathway potentially serving as diagnostic or prognostic biomarkers. Objective: To explore whether there is a causal relationship between key enzymes in the Glutathione metabolism and prostate cancer, and to further investigate the molecular mechanisms and roles of the genes encoding their proteins in relation to prostate cancer. Method: Transcriptomic datasets from the Gene Expression Omnibus (GEO) database were analyzed to identify differentially expressed genes (DEGs) and enriched pathways in prostate cancer versus normal tissues. Two-sample bidirectional Mendelian randomization (MR) was employed to assess causal relationships between Glutathione metabolic enzymes (exposure) and prostate cancer risk (outcome). Immune infiltration analysis and LASSO regression were performed to construct a diagnostic model. Single-cell RNA sequencing (scRNA-seq) data were utilized to elucidate cell-type-specific expression patterns and functional associations of target genes. Result: The results of two-sample bidirectional MR showed that Glutathione S-transferase P (GSTP) in Glutathione metabolism could reduce the risk of prostate cancer. The Glutathione S-transferase Pi-1 (GSTP1) gene was lowly expressed in prostate cancer and was able to diagnose prostate cancer more accurately. Single-cell analysis showed that the high expression of GSTP1 in prostate cancer epithelial cells was closely associated with the upregulation of the P53 pathway and apoptosis. Conclusions: Our study reveals that GSTP in Glutathione metabolism reduces the risk of prostate cancer and further analyzes the genetic association and mechanism of action between GSTP1 and prostate cancer.
Source: Biomedicines
Authors: Shan Huang, Hang Yin
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W4409896200
