Identification of prognostic biomarkers for cholangiocarcinoma by combined analysis of molecular characteristics of clinical MVI subtypes and molecular subtypes.
Ming-Yue LiYa-Hui LiuFeng WeiPing ZhangXiao-Dong SunMeng WangXiao-Hong DuJun-Feng YeWei QiuXiao-Ju ShiBai JiYing-Chao WangChao JiangWen-Gang ChaiBo HuangXing-Kai LiuQing-Min ChenYu FuXin-Tong HuLi-Guo ChenJia-Xue HeKai-Yuan ChaiZhao-Ming GouTian YangGuang-Yi WangYan-Fang JiangZhong-Qi FanGuo-Yue LvPublished in: Genomics (2024)
Cholangiocarcinoma (CCA) is widely noted for its high degree of malignancy, rapid progression, and limited therapeutic options. This study was carried out on transcriptome data of 417 CCA samples from different anatomical locations. The effects of lipid metabolism related genes and immune related genes as CCA classifiers were compared. Key genes were derived from MVI subtypes and better molecular subtypes. Pathways such as epithelial mesenchymal transition (EMT) and cell cycle were significantly activated in MVI-positive group. CCA patients were classified into three (four) subtypes based on lipid metabolism (immune) related genes, with better prognosis observed in lipid metabolism-C1, immune-C2, and immune-C4. IPTW analysis found that the prognosis of lipid metabolism-C1 was significantly better than that of lipid metabolism-C2 + C3 before and after correction. KRT16 was finally selected as the key gene. And knockdown of KRT16 inhibited proliferation, migration and invasion of CCA cells.
Keyphrases
- cell cycle
- epithelial mesenchymal transition
- fatty acid
- genome wide
- signaling pathway
- end stage renal disease
- induced apoptosis
- ejection fraction
- cell proliferation
- newly diagnosed
- gene expression
- transforming growth factor
- cell cycle arrest
- prognostic factors
- genome wide identification
- electronic health record
- dna methylation
- single molecule
- single cell
- peritoneal dialysis
- copy number
- oxidative stress
- patient reported outcomes
- deep learning
- pi k akt