Digestive diseases and sciences · 2026
Development and Validation of a Crotonylation-Related Prognostic Risk Model for Cholangiocarcinoma Based on Integrative Transcriptome Analysis.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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He Xinlei, Lv Mingyue, Chen Jiamin, Zhu Qiancheng, Zhao Jianfu, Chen Wenhui
Аннотация
BACKGROUND: Cholangiocarcinoma (CCA) is a common and highly refractory malignancy; however, biomarkers and therapeutic targets associated with its progression remain incompletely understood. Crotonylation is an emerging lysine acylation modification that has been implicated in multiple diseases.
AIMS: In this study, we aimed to identify crotonylation-related prognostic genes in CCA.
METHODS: First, differentially expressed genes (DEGs) with consistent expression patterns were identified using the TCGA-CHOL and GSE26566 datasets. Key module genes associated with the expression patterns of known lysine crotonylation-related gene (LCRG) scores were subsequently identified through weighted gene co-expression network analysis (WGCNA), and candidate genes were obtained by intersection analysis.
RESULTS: Three prognostic genes, complement factor H (CFH), phosphatidylcholine N-methyltransferase (PEMT), and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein epsilon (YWHAE), were ultimately selected to construct and validate a prognostic risk model. In addition, immune infiltration analysis revealed significant differences in mast cell abundance between the high- and low-risk groups. Moreover, the expression levels of the immune checkpoints FMS-like tyrosine kinase 3 (FLT3) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) also differed between the two risk groups.
CONCLUSIONS: These findings may have important implications for CCA immunotherapy and provide a theoretical basis for improving diagnostic and prognostic assessment in CCA.
AIMS: In this study, we aimed to identify crotonylation-related prognostic genes in CCA.
METHODS: First, differentially expressed genes (DEGs) with consistent expression patterns were identified using the TCGA-CHOL and GSE26566 datasets. Key module genes associated with the expression patterns of known lysine crotonylation-related gene (LCRG) scores were subsequently identified through weighted gene co-expression network analysis (WGCNA), and candidate genes were obtained by intersection analysis.
RESULTS: Three prognostic genes, complement factor H (CFH), phosphatidylcholine N-methyltransferase (PEMT), and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein epsilon (YWHAE), were ultimately selected to construct and validate a prognostic risk model. In addition, immune infiltration analysis revealed significant differences in mast cell abundance between the high- and low-risk groups. Moreover, the expression levels of the immune checkpoints FMS-like tyrosine kinase 3 (FLT3) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) also differed between the two risk groups.
CONCLUSIONS: These findings may have important implications for CCA immunotherapy and provide a theoretical basis for improving diagnostic and prognostic assessment in CCA.