胰腺癌
恶性肿瘤
基因
医学
生物信息学
肿瘤科
基因表达谱
内科学
免疫组织化学
癌症
生物
基因表达
病理
遗传学
作者
Yi-Jun Hua,Tiandong Li,Hua Wang,Jinyu Wu,Chuncheng Yi,Jianxiang Shi,Peng Wang,Chunhua Song,Liping Dai,Guozhong Jiang,Yuguang Huang,Yu Ye,Jitian Li
标识
DOI:10.3389/fimmu.2021.649551
摘要
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.
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