4.6 Article

The Construction of a Prognostic Model Based on a Peptidyl Prolyl Cis-Trans Isomerase Gene Signature in Hepatocellular Carcinoma

期刊

FRONTIERS IN GENETICS
卷 12, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.730141

关键词

peptidyl prolyl cis-trans isomerase; nomogram; hepatocellular carcinoma; TCGA; ICGC

资金

  1. Natural Science Foundation of Guangdong Province [2020A1515010048]
  2. Traditional Chinese Medicine research projects of Traditional Chinese Medicine Bureau of Guangdong Province [20201179]
  3. non-funded science and technology projects of Zhanjiang city [2019B01021]

向作者/读者索取更多资源

A prognostic model based on 3 peptidyl prolyl cis-trans isomerase gene signatures was constructed for hepatocellular carcinoma patients. The model showed that patients in the high-risk score group had a worse prognosis, and the validation results were consistent with the training set. A nomogram incorporating clinical stage and risk score was established with a well-matched calibration curve.
Objective: The aim of the present study was to construct a prognostic model based on the peptidyl prolyl cis-trans isomerase gene signature and explore the prognostic value of this model in patients with hepatocellular carcinoma.Methods: The transcriptome and clinical data of hepatocellular carcinoma patients were downloaded from The Cancer Genome Atlas and the International Cancer Genome Consortium database as the training set and validation set, respectively. Peptidyl prolyl cis-trans isomerase gene sets were obtained from the Molecular Signatures Database. The differential expression of peptidyl prolyl cis-trans isomerase genes was analyzed by R software. A prognostic model based on the peptidyl prolyl cis-trans isomerase signature was established by Cox, Lasso, and stepwise regression methods. Kaplan-Meier survival analysis was used to evaluate the prognostic value of the model and validate it with an independent external data. Finally, nomogram and calibration curves were developed in combination with clinical staging and risk score.Results: Differential gene expression analysis of hepatocellular carcinoma and adjacent tissues showed that there were 16 upregulated genes. A prognostic model of hepatocellular carcinoma was constructed based on three gene signatures by Cox, Lasso, and stepwise regression analysis. The Kaplan-Meier curve showed that hepatocellular carcinoma patients in high-risk score group had a worse prognosis (p < 0.05). The receiver operating characteristic curve revealed that the area under curve values of predicting the survival rate at 1, 2, 3, 4, and 5 years were 0.725, 0.680, 0.644, 0.630, and 0.639, respectively. In addition, the evaluation results of the model by the validation set were basically consistent with those of the training set. A nomogram incorporating clinical stage and risk score was established, and the calibration curve matched well with the diagonal.Conclusion: A prognostic model based on 3 peptidyl prolyl cis-trans isomerase gene signatures is expected to provide reference for prognostic risk stratification in patients with hepatocellular carcinoma.

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