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Comprehensive analysis of cell death genes in hepatocellular carcinoma based on multi-omics data

程序性细胞死亡 小桶 生物 基因 癌症研究 福克斯M1 基因签名 自噬 癌症 肝细胞癌 赫拉 细胞凋亡 细胞周期 遗传学 转录组 基因表达 克拉斯 突变
作者
Lanlan Zhang,Xiaohong Chen,Xiangchai Guo,Huajuan Shen,Danying Qiu,Jin Wei-qun,Dongjie Hou
出处
期刊:Advances in Clinical and Experimental Medicine [Wroclaw Medical University]
卷期号:32 (2): 233-244
标识
DOI:10.17219/acem/152737
摘要

Hepatocellular carcinoma (HCC) is a common tumor of the digestive system. Cell death is an essential process in normal tissue that consists of 3 classical pathways: apoptosis, necrosis and autophagy.To perform a comprehensive analysis of the impact of cell death on liver cancer.The Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the Cancer Genome Atlas (TCGA) datasets were used to analyze the relationships between mutations in cell death-related genes and clinical variables of HCC. Then, we applied the DESeq2 package to identify aberrantly expressed genes in HCC and their related biological functions through a Pearson correlation analysis. Finally, a cell death-related signature of HCC was constructed using the single-factor Cox regression.We identified the genes involved in apoptosis, necrosis and autophagy, of which TP53 and SPTA1 had the highest frequency of mutations. The results revealed that cell death-related tumor mutational burden (TMB) was significant for the pathologic stage and had a strong relationship with the prognosis. Moreover, 53 cell death-related genes that are differentially expressed in HCC were screened, and 3 of them were correlated with HCC prognosis. Harvey rat sarcoma viral oncogene homolog (HRAS) affected the infiltration of immune cells and was closely correlated with ferroptosis. Peptidylprolyl isomerase A (PPIA) played a significant role in mitochondrial pathways. At last, we constructed a cell death-related signature of HCC using 10 prognosis-related genes and a nomogram based on 3 variables (expression, group and stage).This study provided a comprehensive analysis of cell death-related genes in HCC based on multi-omics data, identified the contribution of each variable to clinical outcome and predicted the survival probability of HCC patients more directly.

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