A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression

Accurately predicting the survival prospects of patients suffering from pancreatic adenocarcinoma (PAAD) is challenging. In this study, we analyzed RNA matrices of 182 subjects with PAAD based on public datasets obtained from The Cancer Genome Atlas (TCGA) as training datasets and those of 63 subjec...

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Published inFrontiers in genetics Vol. 13; p. 804190
Main Authors Xie, Lin-Ying, Huang, Han-Ying, Fang, Tian, Liang, Jia-Ying, Hao, Yu-Lei, Zhang, Xue-Jiao, Xie, Yi-Xin, Wang, Chang, Tan, Ye-Hui, Zeng, Lei
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 18.05.2022
Subjects
gene expression
Genetics
metabolism
pancreatic adenocarcinoma
prognostic
survival model
prognostic
pancreatic adenocarcinoma
survival model
metabolism
gene expression
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Summary:Accurately predicting the survival prospects of patients suffering from pancreatic adenocarcinoma (PAAD) is challenging. In this study, we analyzed RNA matrices of 182 subjects with PAAD based on public datasets obtained from The Cancer Genome Atlas (TCGA) as training datasets and those of 63 subjects obtained from the Gene Expression Omnibus (GEO) database as the validation dataset. Genes regulating the metabolism of PAAD cells correlated with survival were identified. Furthermore, LASSO Cox regression analyses were conducted to identify six genes ( , , , , , and ) to create a metabolic risk score. The proposed scoring framework attained the robust predictive performance, with 2-year survival areas under the curve (AUCs) of 0.61 in the training cohort and 0.66 in the validation cohort. Compared with the subjects in the low-risk cohort, subjects in the high-risk training cohort presented a worse survival outcome. The metabolic risk score increased the accuracy of survival prediction in patients suffering from PAAD.
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Reviewed by: Wanyan Wang, Foundation Medicine Inc., United States
This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics
Luisa Chocarro, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Spain
These authors have contributed equally to this work
Edited by: Maite G. Fernandez-Barrena, University of Navarra, Spain
ISSN:1664-8021
1664-8021
DOI:10.3389/fgene.2022.804190