A New Genetic Signature of Lactate Metabolism-Associated Genes Predicting Clinically Distinctive Features and Tumor Microenvironment in Colorectal Cancer

Abstract

Background Colorectal cancer (CRC) is characterized by its high malignancy and challenging prognosis. A significant aspect of cancer is metabolic reprogramming, where lactate serves as a crucial metabolite that contributes to the development of cancer and the tumor microenvironment (TME). Current studies have indicated that lactate plays a significant role in the progression of CRC. However, the relationship between lactate and the tumor microenvironment remains understudied, underscoring the potential of lactate as a novel biomarker. Methods We sourced transcriptomic data for colorectal cancer (CRC) patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and the Gene Expression Omnibus (GEO) portals, along with the corresponding clinical information. Utilizing univariate Cox regression in conjunction with LASSO regression analysis, we identified genes involved in lactate metabolism that are associated with CRC prognosis. Subsequently, we developed models based on multi-factor Cox regression. To evaluate the correlation between tumor mutational burden (TMB), tumor microenvironment (TME), and lactate scores with patient survival, we conducted gene set enrichment analysis (GSEA) and immunogenic signature analyses. Results 3 lactate metabolism-related genes (LMRGs) (SLC16A8, GATA1, and PYGL) were used to construct models that categorized patients into 2 subgroups based on their lactate scores. The function of the differential genes between the 2 subgroups was mainly enriched in cell cycle and mRNA division, and the prognosis of patients in the high score subgroup was poor. Furthermore, a significant positive correlation was observed between TMB and LMRGs scores in the high-scoring group ( P = 0.003, r 2 = 0.12). Lastly, LMRGs also reflected the characteristics of TME, with differences in immune cells and immune checkpoints between the 2 subgroups. Conclusions LMRGs may serve as a promising biomarker for predicting prognostic survival in CRC patients and to assess the TME.