Abstract

A thorough assessment of lactate-related genes (LRGs) in different types of human cancers is currently lacking. To elucidate the molecular landscape of LRGs, we conducted a comprehensive analysis using genomic, mRNA, and microRNA expression profiles and developed a lactate score model using the least absolute shrinkage and selection operator (LASSO) algorithm. We found that our lactate score could be a prognostic marker instead of LDHA for several cancer patients who possess high-frequency variants in LRGs. The lactate score also demonstrated an association with CD8+ T cells infiltration in multiple cancer types. Furthermore, our findings indicate that the lactate score holds promise as a potential biomarker for immunotherapy in patients with bladder cancer (BLCA) and skin cutaneous melanoma (SKCM). Among the seventeen genes of the lactate score model, PDP1 showed the strongest positive correlation with lactate score and the potential as a standalone biomarker for prognosis. In general, our study has yielded crucial insights into the potential application of the lactate score as a predictive biomarker for both survival outcomes and the response to immunotherapy. By recognizing the prognostic significance of lactate metabolism, we open avenues for further investigations aimed at harnessing the therapeutic potential of lactate.