Author:
Ye Hua,Li Tiandong,Wang Hua,Wu Jinyu,Yi Chuncheng,Shi Jianxiang,Wang Peng,Song Chunhua,Dai Liping,Jiang Guozhong,Huang Yuxin,Yu Yongwei,Li Jitian
Abstract
Pancreatic cancer is a lethal malignancy with a poor prognosis. This study aims to identify pancreatic cancer-related genes and develop a robust diagnostic model to detect this disease. Weighted gene co-expression network analysis (WGCNA) was used to determine potential hub genes for pancreatic cancer. Their mRNA and protein expression levels were validated through reverse transcription PCR (RT-PCR) and immunohistochemical (IHC). Diagnostic models were developed by eight machine learning algorithms and ten-fold cross-validation. Four hub genes (TSPAN1, TMPRSS4, SDR16C5, and CTSE) were identified based on bioinformatics. RT-PCR showed that the four hub genes were expressed at medium to high levels, IHC revealed that their protein expression levels were higher in pancreatic cancer tissues. For the panel of these four genes, eight models performed with 0.87–0.92 area under the curve value (AUC), 0.91–0.94 sensitivity, and 0.84–0.86 specificity in the validation cohort. In the external validation set, these models also showed good performance (0.86–0.98 AUC, 0.84–1.00 sensitivity, and 0.86–1.00 specificity). In conclusion, this study has identified four hub genes that might be closely related to pancreatic cancer: TSPAN1, TMPRSS4, SDR16C5, and CTSE. Four-gene panels might provide a theoretical basis for the diagnosis of pancreatic cancer.
Subject
Immunology,Immunology and Allergy
Reference53 articles.
1. Pancreatic cancer;Kamisawa;Lancet.,2016
2. Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States;Rahib;Cancer Res.,2014
3. Cancer statistics, 2019;Siegel;CA Cancer J Clin.,2019
4. Changing cancer survival in China during 2003–15: a pooled analysis of 17 population-based cancer registries;Zeng;Lancet Global Health.,2018
5. A review of pancreatic cancer: epidemiology, genetics, screening, and management;Idachaba;Open Access Maced J Med Sci.,2019
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