Identifying a lactic acid metabolism-related gene signature contributes to predicting prognosis, immunotherapy efficacy, and tumor microenvironment of lung adenocarcinoma.

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However, studies about lactic acid metabolism-related genes (LRGs) in lung adenocarcinoma (LUAD) remain unclear. Two distinct molecular subtypes were identified on basis of 24 LRGs and found the significant enrichment of subtype A in metabolism-related pathways and had better overall survival (OS). Subsequently, a prognostic signature based on 5 OS-related LRGs was generated using Lasso Cox hazards regression analysis in TCGA dataset and was validated in two external cohorts. Then, a highly accurate nomogram was cosntructed to improve the clinical application of the LRG_score. By further analyzing the LRG_score, higher immune score and lower stromal score were found in the low LRG_score group, which presented a better prognosis. Patients with low LRG_score also exhibited lower somatic mutation rate, tumor mutation burden (TMB), and cancer stem cell (CSC) index. Three more independent cohorts (GSE126044: anti-PD-1, GSE135222: anti-PD-1, and IMvigor210: anti-PD-L1) were analyzed, and the results showed that patients in the low LRG_score category were more responsive to anti-PD-1/PD-L1 medication and had longer survival times. It was also determined that gefitinib, etoposide, erlotinib, and gemcitabine were more sensitive to the low LRG_score group. Finally, we validated the stability and reliability of LRG_score in cell lines, clinical tissue samples and HPA databases. Overall, the LRG_score may improve prognostic information and provide directions for current research on drug treatment strategies for LUAD patients.", "claims": [{"id": "claim-method", "statement": "Based on the expression of prognostic LRGs and survival data, the Last absolute shrinkage and selection operator (LASSO) Cox regression analysis by R package “glmnet” was performed to further select the most useful prognostic markers and the penalty regularization parameter lambda was chosen based on 10 cross-validations by R package “caret”.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36275729", "locator": "sections[6] \"Construction of the prognostic LRG_score and nomogram\" paragraph 2", "quote": "Based on the expression of prognostic LRGs and survival data, the Last absolute shrinkage and selection operator (LASSO) Cox regression analysis by R package “glmnet” was performed to further select the most useful prognostic markers and the penalty regularization parameter lambda was chosen based on 10 cross-validations by R package “caret”."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36275729", "locator": "sections[23] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . 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