|Table of Contents|

Prognostic model construction and effect analysis of hepatocellular carcinoma patients based on immune-related genes

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2022 06
Page:
1051-1056
Research Field:
Publishing date:

Info

Title:
Prognostic model construction and effect analysis of hepatocellular carcinoma patients based on immune-related genes
Author(s):
YANG Yong1; ZHU Peiyao2; XU Tao3; 4; HAN Yong3; 4; QIAO Xuan3; 4; WANG Renhao1; 4; SONG Jun1; 4; ZHANG Bin1; YANG Jun1
1.Department of General Surgery,the Affiliated Hospital of Xuzhou Medical University,Jiangsu Xuzhou 221002,China;2.Nantong Hospital of Traditional Chinese Medicine,Jiangsu Nantong 226000,China;3.the Graduate School,Xuzhou Medical University,Jiangsu Xuzhou 221002,China;4.Institute of Digestive Diseases,Xuzhou Medical University,Jiangsu Xuzhou 221002,China.
Keywords:
hepatocellular carcinoma; survival prediction; gene expression; prognosis
PACS:
R735.7
DOI:
10.3969/j.issn.1672-4992.2022.06.020
Abstract:
Objective:To construct a survival model for predicting the prognosis of patients with hepatocellular carcinoma (HCC) based on immune-related genes.Methods:The data were downloaded from The Cancer Genome Atlas (TCGA) project.We performed differential expression analysis of all immune-related genes in 50 normal liver tissues and 373 HCC tissues in R software.For the obtained differentially expressed genes,univariate and multivariate Cox analysis was used and established a prognostic signature based on prognosis-related genes.We then plotted survival curves and receiver operating characteristic (ROC) curves to evaluate the model's prediction level.In addition,we performed univariate and multivariate Cox regression analysis on the prognostic model and multiple clinical information to determine whether the model can be used as an independent predictor for judging HCC patients' survival time.Results:Based on univariate and multivariate Cox analysis,we obtained 10 immune-related genes and constructed the prognostic model.The survival curve indicated that patients with higher risk scores had shorter survival time.The ROC curve showed that these models had an area under the curve (AUC) of 0.826.The risk score of prognostic model could independently predict the patient's prognosis.Conclusion:Our results have screened 10 significant immune-related genes.These genes can be used potential prognostic markers in patients with HCC.The prognostic model can provide personalized predictions for patients' survival time.

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Memo

Memo:
江苏省自然科学基金（编号：BK20191153）
Last Update: 1900-01-01