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Signature Construction and Molecular Subtype Identification Based on Immune-related Genes for Better Prediction of Prognosis in Hepatocellular Carcinoma by Sun, Liang (author);Wu, Zhengyi (author);Dong, Cairong (author);Yu, Shian (author);Huang, He (author);Chen, Zhendong (author);Wu, Zhipeng (author);Yin, Xiangbao (author) is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Signature Construction and Molecular Subtype Identification Based on Immune-related Genes for Better Prediction of Prognosis in Hepatocellular Carcinoma about?

## Objective Hepatocellular carcinoma (HCC) immunotherapy is a focus of current research. We established a model that can effectively predict the prognosis and efficacy of HCC immunotherapy by analyzing the immune genes of HCC. ## Methods Through the data mining of hepatocellular carcinoma in The Cancer Genome Atlas (TCGA), the immune genes with differences in tumor and normal tissues are screened, and then the univariate regression analysis is carried out to screen the immune genes with differences related to prognosis. The prognosis model of immune related genes is constructed by using the minimum absolute contraction and selection operator (lasso) Cox regression model in the TCGA training set data, The risk score of each sample was calculated, and the survival was compared with the Kaplan Meier curve and the receiver operating characteristic (ROC) curve to evaluate the predictive ability. Data sets from ICGC and TCGA were used to verify the reliability of signatures. The correlation between clinicopathological features, immune infiltration, immune escape and risk score was analyzed. ## Results Seven immune genes were finally determined as the prognostic model of liver cancer. Ac

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Author

Sun, Liang (author);Wu, Zhengyi (author);Dong, Cairong (author);Yu, Shian (author);Huang, He (author);Chen, Zhendong (author);Wu, Zhipeng (author);Yin, Xiangbao (author)

Publisher

Springer Science and Business Media LLC

Published

2023

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)