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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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-05-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.804190/full |
| _version_ | 1828365356781010944 |
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| author | Lin-ying Xie Han-ying Huang Tian Fang Jia-ying Liang Yu-lei Hao Xue-jiao Zhang Yi-xin Xie Chang Wang Ye-hui Tan Lei Zeng |
| author_facet | Lin-ying Xie Han-ying Huang Tian Fang Jia-ying Liang Yu-lei Hao Xue-jiao Zhang Yi-xin Xie Chang Wang Ye-hui Tan Lei Zeng |
| author_sort | Lin-ying Xie |
| collection | DOAJ |
| description | 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 (XDH, MBOAT2, PTGES, AK4, PAICS, and CKB) 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. |
| first_indexed | 2024-04-14T05:29:55Z |
| format | Article |
| id | doaj.art-39b2ea97769d405a8b5b37c86b78ad8e |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-14T05:29:55Z |
| publishDate | 2022-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-39b2ea97769d405a8b5b37c86b78ad8e2022-12-22T02:09:50ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-05-011310.3389/fgene.2022.804190804190A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene ExpressionLin-ying Xie0Han-ying Huang1Tian Fang2Jia-ying Liang3Yu-lei Hao4Xue-jiao Zhang5Yi-xin Xie6Chang Wang7Ye-hui Tan8Lei Zeng9Bethune Institute of Epigenetic Medicine, The First Hospital of Jilin University, Changchun, ChinaState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, ChinaCancer Center, The First Hospital of Jilin University, Changchun, ChinaCancer Center, The First Hospital of Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, ChinaDepartment of Endocrinology, China-Japan Union Hospital of Jilin University, Changchun, ChinaDepartment of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, ChinaCancer Center, The First Hospital of Jilin University, Changchun, ChinaCancer Center, The First Hospital of Jilin University, Changchun, ChinaBethune Institute of Epigenetic Medicine, The First Hospital of Jilin University, Changchun, ChinaAccurately 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 (XDH, MBOAT2, PTGES, AK4, PAICS, and CKB) 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.https://www.frontiersin.org/articles/10.3389/fgene.2022.804190/fullpancreatic adenocarcinomametabolismgene expressionprognosticsurvival model |
| spellingShingle | Lin-ying Xie Han-ying Huang Tian Fang Jia-ying Liang Yu-lei Hao Xue-jiao Zhang Yi-xin Xie Chang Wang Ye-hui Tan Lei Zeng A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression Frontiers in Genetics pancreatic adenocarcinoma metabolism gene expression prognostic survival model |
| title | A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression |
| title_full | A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression |
| title_fullStr | A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression |
| title_full_unstemmed | A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression |
| title_short | A Prognostic Survival Model of Pancreatic Adenocarcinoma Based on Metabolism-Related Gene Expression |
| title_sort | prognostic survival model of pancreatic adenocarcinoma based on metabolism related gene expression |
| topic | pancreatic adenocarcinoma metabolism gene expression prognostic survival model |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.804190/full |
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