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A combined signature of glycolysis and immune landscape predicts prognosis and therapeutic response in prostate cancer

Authors :
Tao Guo
Jian Wang
Shi Yan
Xiangyu Meng
Xiaomin Zhang
Shuang Xu
Shancheng Ren
Yuhua Huang
Source :
Frontiers in Endocrinology, Vol 13 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

Prostate cancer (PCa) is a common malignancy that poses a major threat to the health of men. Prostate-specific antigen (PSA) and its derivatives, as FDA-approved detection assays, are insufficient to serve as optimal markers for patient prognosis and clinical decision-making. It is widely acknowledged that aberrant glycolytic metabolism in PCa is related to tumor progression and acidifies the tumor microenvironment (TME). Considering the non-negligible impacts of glycolysis and immune functions on PCa, we developed a combined classifier in prostate cancer. The Glycolysis Score containing 19 genes and TME Score including three immune cells were created, using the univariate and multivariate Cox proportional hazards model, log-rank test, least absolute shrinkage and selection operator (LASSO) regression analysis and the bootstrap approach. Combining the glycolysis and immunological landscape, the Glycolysis-TME Classifier was then constructed. It was observed that the classifier was more accurate in predicting the prognosis of patients than the current biomarkers. Notably, there were significant differences in metabolic activity, signaling pathways, mutational landscape, immunotherapeutic response, and drug sensitivity among the Glycolysishigh/TMElow, Mixed group and Glycolysislow/TMEhigh identified by this classifier. Overall, due to the significant prognostic value and potential therapeutic guidance of the Glycolysis-TME Classifier, we anticipate that this classifier will be clinically beneficial in the management of patients with PCa.

Details

Language :
English
ISSN :
16642392 and 81464193
Volume :
13
Database :
Directory of Open Access Journals
Journal :
Frontiers in Endocrinology
Publication Type :
Academic Journal
Accession number :
edsdoj.215783cd8c81464193892d54b7aec787
Document Type :
article
Full Text :
https://doi.org/10.3389/fendo.2022.1037099