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. 2024 Sep;48(9):1313-1325.
doi: 10.1002/cbin.12195. Epub 2024 Jun 23.

Comprehensive analysis of the prognostic value of glutathione S-transferases Mu family members in breast cancer

Nazanin Gohari  1 , Elham Abbasi  2 , Hassan Akrami  3
Affiliations

Comprehensive analysis of the prognostic value of glutathione S-transferases Mu family members in breast cancer

Nazanin Gohari et al. Cell Biol Int. 2024 Sep.

Abstract

Breast cancer (BC) remains a significant public health concern globally, with a high number of reported cases and a substantial number of deaths every year. Accumulating reactive oxygen species (ROS) and oxidative stress are related to BC and the Glutathione S-transferases Mu (GSTM) family is one of the most important enzymatic detoxifiers associated with many cancers. In this study, UALCAN, Kaplan-Meier plotter, bc-GenExMiner, cBioPortal, STRING, Enrichr, and TIMER databases were employed to carry out a comprehensive bioinformatic analysis and provide new insight into the prognostic value of GSTMs in BC. GSTM2-5 genes in mRNA and protein levels were found to be expressed at lower levels in breast tumors compared to normal tissues, and reduction in mRNA levels is linked to shorter overall survival (OS) and relapse-free survival (RFS). The lower mRNA levels of GSTMs were strongly associated with the worse Scarff-Bloom-Richardson (SBR) grades (p < 0.0001). The mRNA levels of all five GSTMs were substantially higher in estrogen receptor (ER)-positive and progesterone receptor (PR)-positive compared to ER-negative and PR-negative BC patients. As well, when nodal status was compared, GSTM1, GSTM3, and GSTM5 were significantly higher in nodal-positive BC patients (p < .01). Furthermore, GSTM4 had the most gene alteration (4%) among other family members, and GSTM5 showed the strongest correlation with CD4+ T cells (Cor= .234, p = 2.22e-13). In conclusion, our results suggest that GSTM family members may be helpful as biomarkers for prognosis and as therapeutic targets in BC.

Keywords: TCGA; bioinformatic analysis; cancer genome atlas; cancer survival; mRNA expression analysis.

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