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- Title
Five gene signatures were identified in the prediction of overall survival in resectable pancreatic cancer.
- Authors
Wu, Chao; Wu, Zuowei; Tian, Bole
- Abstract
<bold>Background: </bold>Although genes have been previously detected in pancreatic cancer (PC), aberrant genes that play roles in resectable pancreatic cancer should be further assessed.<bold>Methods: </bold>Messenger RNA samples and clinicopathological data corrected with PC were downloaded from The Cancer Genome Atlas (TCGA). Resectable PC patients were randomly divided into a primary set and a validation set. Univariable Cox regression analysis, lasso-penalized Cox regression analysis, and multivariable Cox analysis were implemented to distinguish survival-related genes (SRGs). A risk score based on the SRGs was calculated by univariable Cox regression analysis. A genomic-clinical nomogram was established by integrating the risk score and clinicopathological data to predict overall survival (OS) in resectable PC.<bold>Results: </bold>Five survival-related genes (AADAC, DEF8, HIST1H1C, MET, and CHFR) were significantly correlated with OS in resectable PC. The resectable PC patients, based on risk score, were sorted into a high-risk group that showed considerably unfavorable OS (p < 0.001) than the low-risk group, in both the primary set and the validation set. The concordance index (C-index) was calculated to evaluate the predictive performance of the nomogram were respectively in the primary set [0.696 (0.608-0.784)] and the validation set [0.682 (0.606-0.758)]. Additionally, gene set enrichment Analysis discovered several meaningful enriched pathways.<bold>Conclusion: </bold>Our study identified five prognostic gene biomarkers for OS prediction and which facilitate postoperative molecular target therapy for the resectable PC, especially the nomic-clinical nomogram which may be used as an effective model for the postoperative OS evaluation and also an optimal therapeutic tool for the resectable PC.
- Subjects
PANCREATIC cancer; FORECASTING; CLINICAL prediction rules; MESSENGER RNA; REGRESSION analysis; GENES; MOLECULAR pathology
- Publication
BMC Surgery, 2020, Vol 20, Issue 1, pN.PAG
- ISSN
1471-2482
- Publication type
journal article
- DOI
10.1186/s12893-020-00856-y