Novel immune checkpoint-related gene model to predict prognosis and treatment responsiveness in low-grade gliomas

A pan-cancer multi-omics analysis of lactylation genes associated with tumor microenvironment and cancer development

Background

Lactylation is a significant post-translational modification bridging the gap between cancer epigenetics and metabolic reprogramming. However, the association between lactylation and prognosis, tumor microenvironment (TME), and response to drug therapy in various cancers remains unclear.

Methods

First, the expression, prognostic value, and genetic and epigenetic alterations of lactylation genes were systematically explored in a pan-cancer manner. Lactylation scores were derived for each tumor using the single-sample gene set enrichment analysis (ssGSEA) algorithm. The correlation of lactylation scores with clinical features, prognosis, and TME was assessed by integrating multiple computational methods. In addition, GSE135222 data was used to assess the efficacy of lactylation scores in predicting immunotherapy outcomes. The expression of lactylation genes in breast cancers and gliomas were verified by RNA-sequencing.

Results

Lactylation genes were significantly upregulated in most cancer types. CREBBP and EP300 exhibited high mutation rates in pan-cancer analysis. The prognostic impact of the lactylation score varied by tumor type, and lactylation score was a protective factor for KIRC, ACC, READ, LGG, and UVM, and a risk factor for CHOL, DLBC, LAML, and OV. In addition, a high lactylation score was associated with cold TME. The infiltration levels of CD8+ T, γδT, natural killer T cell (NKT), and NK cells were lower in tumors with higher lactylation scores. Finally, immunotherapy efficacy was worse in patients with high lactylation scores than other types.

Conclusion

Lactylation genes are involved in malignancy formation. Lactylation score serves as a promising biomarker for predicting patient prognosis and immunotherapy efficacy.