识别用于预测结直肠癌预后、肿瘤浸润免疫细胞和化疗反应的乳酸化相关模型

Colorectal cancer (CRC) is a leading cause of cancer-related mortality, and its molecular heterogeneity continues to impede accurate prognostic assessment and effective treatment stratification. Emerging evidence indicates that protein lactylation, a recently identified post-translational modification linked to metabolic reprogramming, plays an important role in tumor progression, immune regulation, and therapeutic response in multiple cancers.

However, its functional relevance and prognostic significance in CRC remain insufficiently characterized. In this study, we integrated lactylation-related gene expression profiles with single-cell RNA sequencing to identify novel biomarkers capable of refining CRC molecular subtyping.

Differential expression analysis revealed 89 lactylation-associated genes, among which five key genes-CALD1, S100A11, S100A6, LGALS1, and CSRP2-were significantly associated with poor survival and enriched in pathways including glycolysis and carbon metabolism. Unsupervised clustering based on these genes identified two robust CRC subgroups with distinct immune infiltration patterns and prognostic outcomes, further validated by a prognostic risk model.

Our findings highlight the potential of lactylation-related biomarkers to enhance CRC prognostic prediction and therapeutic stratification, providing new insights into immune modulation and chemoresistance.

This study underscores the importance of incorporating lactylation features into CRC molecular profiling to improve personalized treatment strategies.