Abstract
Objective This study is aimed at identifying stemness-related genes in pancreatic ductal adenocarcinoma (PDAC). Methods The RNA-seq data of PADC patients were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The mRNA expression-based stemness index (mRNAsi) and epigenetically regulated mRNAsi (EREG-mRNAsi) of PADC patients were evaluated. The mRNAsi-related gene sets in PADC were identified by weighted gene coexpression network analysis (WGCNA). The key genes were further analyzed using functional enrichment analysis. The Kaplan-Meier survival analysis and the Cox proportional hazards model were used to evaluate the prognostic value of the key genes. Prognostic hub genes were used to establish nomograms. The receiver operating characteristic (ROC) curves, concordance index (C-index), and calibration curves were used to assess the discrimination and accuracy of the nomogram. Finally, these results were validated in the Gene Expression Omnibus (GEO) database. Results A total of 36 key genes related to mRNAsi were identified by WGCNA. A prognostic gene signature compromising seven genes (TPX2, ZWINT, UBE2C, CCNB2, CDK1, BUB1, and BIRC5) was established to predict the overall survival (OS) of PADC patients. The Cox regression analysis revealed that the risk score was an independent prognostic factor for PADC. Patients were then divided into the high-risk and low-risk groups. The ROC curves, C-index, and calibration curves indicated good performance of the prognostic signature in the TCGA and GEO datasets. Moreover, the nomogram incorporating clinical parameters showed better sensitivity and specificity for predicting the OS of PADC patients. Conclusion The stemness-related prognostic model successfully predicted the OS of PADC patients and could be used for the treatment of PADC.
Highlights
Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent type of pancreatic neoplasm, accounting for more than 90% of the total number of pancreatic tumors
Cancer stem cells (CSCs)-related RNA-seq data were obtained from the The Cancer Genome Atlas (TCGA) PADC dataset, including 142 PADC samples
The gene expression-based stemness index for PADC was extracted by one-class logistic regression (OCLR) [5]
Summary
Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent type of pancreatic neoplasm, accounting for more than 90% of the total number of pancreatic tumors. The 5-year survival rate of PDAC is less than 10%. PDAC is expected to become the second leading cause of cancerrelated death by 2030 [1, 2]. Surgical resection represents the only chance for cure and the advances in adjuvant chemotherapy have improved the long-term outcomes of PDAC patients [3]. Current treatments often cause trauma, which impairs the quality of life of patients. Molecular targeted therapy, which inhibits cancer growth, progression, and metastasis by targeting specific molecular biomarkers, has emerged as a promising treatment strategy with better efficacy and fewer trauma-related complications [4].
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