Lactylation-related gene signatures identify glioma molecular subtypes with prognostic, immunological, and therapeutic implications
Year: 2025
Type: article
Abstract: Introduction: Lactic acid is a by-product of energy metabolism and a signaling molecule that influences tumor progression by regulating immune cell function, angiogenesis, and epigenetic modifications. Methods: This study analyzed data from the TCGA database on gliomas to systematically elucidate the expression patterns, prognostic value, and functional regulatory networks of lactylation-related genes. Results: In this study, 17 lactylation-related prognostic genes were identified through the analysis of TCGA-GBM data. Using non- negative matrix factorization (NMF), two GBM subtypes based on lactylation- related genes (LRGs), termed GBM1 and GBM2, were identified. Survival analysis revealed that the overall survival (OS) of the GBM1 group was significantly lower than that of GBM2 group. Furthermore, notable differences were observed in the expression of key GBM-associated molecular markers between the two subtypes. Tumor microenvironment (TME) analysis demonstrated distinct immune landscapes and genomic characteristics between GBM1 and GBM2. The GBM1 group exhibited higher immune cell infiltration and immune function scores compared to GBM2. Drug sensitivity analysis further revealed differences in response to chemotherapy and targeted therapies between the two subtypes. In vitro data demonstrated that LCP1 knockdown suppressed cell proliferation and invasion, and promoted apoptosis in glioma cells. Conclusion: In conclusion, our study systematically uncovers the significant role of LRGs in GBM molecular subtyping, prognosis evaluation, and therapeutic guidance. These findings offer new insights and potential strategies for the personalized treatment of GBM.
Source: Frontiers in Oncology
Authors: Yanliang Tang, Xiaoli Zhang, Xiaofei Tang, Ye Yuan, Wenwen Wang
Institution: Hangzhou Hospital of Traditional Chinese Medicine
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4412463712