Abstract 864: Pan-cancer analysis of lactic acid metabolism landscape across the Cancer Genome Atlas
Authors: Xiaolin Wei, Lei Cai, Qian He
Journal: Cancer Research (2024)

Abstract Introduction: Metabolic reprogramming plays an important role in tumor occurrence and progression. Our studies confirmed the survival state of patients with different metabolic systems was heterogeneous and glycolytic metabolism may cause tumor progression. Based on these findings, lactic acid metabolism in glycolysis aroused our interest. This study evaluated the potential association between lactate metabolism gene and tumor clinical process in hepatocellular carcinoma, and proved that it can be used as an effective tool for survival prediction and treatment guidance of 32 kinds of tumor patients by establishing lactate score prognosis model. Methods: We used the expression profile, proteomics and epigenetics of HCC lactate gene set in the Cancer Genome Atlas Database to systematically describe the changes of lactate related genes. The differentially expressed genes were then verified in 32 clinical tumor data sets. A prognostic model of tumor lactic acid infiltration was constructed to evaluate its correlation with the prognosis of patients. Finally, we analyzed the effects of lame score, immunotherapy and drug response on the clinical process of tumor. Results: Firstly, we analyzed the differential expression of lactate metabolism genes in HCC and found that the prognosis of patients with high lactate infiltration was significantly lower than that of mild infiltration. AF angiogenesis factor and EMT factor in high infiltration may be the main reason for their differential expression. We constructed a tumor lactic acid prognosis model through six significantly different lactic acid genes, and found that lame score can be used as a predictor of immunotherapy. In addition, we proved the role of lame score in Pan cancer. PGA was positively correlated with lame score in most tumors. The prognosis of 16 tumors with high lame score group was significantly lower than that of low lame score group. There were significant differences in lame score between metastatic and non metastatic cancer groups of Cesc, kirc and kirp. The high and low risk groups of some tumors showed different dryness indices and dampness. At the same time, methylation gene modification has a significant impact on the Lame score of pan cancer, and the Lame score is used to link the drug tolerance and specific pathway enrichment of pan cancer tumor cell lines, confirming the targeted effect of Lame score on tumor treatment. Finally, we used the clinical characteristics and immunohistochemical analysis of a cohort study of real patients with breast cancer endocrine therapy (Tamoxifen) and hepatocellular carcinoma targeted therapy (Lenvartinib) to verify the clinical treatment prediction ability of lame score. Conclusions: Our study provides a comprehensive analysis of lactate metabolic across cancers and highlights the potential treatment of lactate targeted therapies for cancers. Citation Format: Xiaolin Wei, Lei Cai, Qian He. Pan-cancer analysis of lactic acid metabolism landscape across the Cancer Genome Atlas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 864.