Construction of a prognostic prediction system for pancreatic ductal adenocarcinoma to investigate the key prognostic genes

Zheng,Bingli; Peng,Jie; Mollayup,Ablikim; Bakri,Ahmat; Guo,Lei; Zheng,Jianjiang; Xu,Hui

doi:10.3892/mmr.2017.7850

Construction of a prognostic prediction system for pancreatic ductal adenocarcinoma to investigate the key prognostic genes

Authors:
- Bingli Zheng
- Jie Peng
- Ablikim Mollayup
- Ahmat Bakri
- Lei Guo
- Jianjiang Zheng
- Hui Xu
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Affiliations: Department of Pancreatic Surgery, Xinjiang Uygur Autonomous Region People's Hospital, Ürümqi, Xinjiang 830002, P.R. China, Emergency Department, Traditional Chinese Medicine Hospital of Xinjiang Medical University, Ürümqi, Xinjiang 830000, P.R. China
Published online on: October 20, 2017 https://doi.org/10.3892/mmr.2017.7850
Pages: 216-224
Copyright: © Zheng et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Pancreatic cancer (PC) is associated with high mortality rates and poor prognoses. Pancreatic adenocarcinoma is the most common type of PC, and almost all cases of pancreatic adenocarcinoma are pancreatic ductal adenocarcinoma (PDAC). The aim of the current study was to reveal the genes involved in the prognosis of PDAC. Five datasets, including GSE71729 (145 PDAC samples and 46 normal samples), GSE15471 (39 PDAC samples and 39 normal samples), GSE1542 (24 PDAC samples and 25 normal samples), GSE28735 (45 PDAC samples and 45 normal samples) and GSE62452 (69 PDAC samples and 69 normal samples) were downloaded from the Gene Expression Omnibus database. Using the MetaDE.ES method in the MetaDE package, differentially expressed genes (DEGs) were identified from the five datasets. Furthermore, prognosis‑associated genes were screened using the Cox regression analysis in the survival package, and co‑expression network and module analyses were performed separately using Cytoscape software and GraphWeb tool, respectively. After a prognostic prediction system was constructed and validated, enrichment analysis of the signature genes was performed using the clusterProfiler package. A total of 480 DEGs were identified from the five datasets and 259 prognosis‑associated genes were screened from GSE28735 and GSE62452. In addition, the prognostic prediction system composed of 67 signature genes [including basic transcription factor 3 (BTF3), serine/threonine kinase 11 (STK11), thrombospondin 1 (THBS1), ribosomal protein L38 (RPL38) and secretin receptor (SCTR)] was constructed and validated. The signature genes involved in the co‑expression network were enriched in five pathways. In particular, STK11 was involved in three signaling pathways, and THBS1 was enriched in the phosphoinositide 3‑kinase‑Akt signaling pathway. Thus, BTF3, STK11, THBS1, RPL38 and SCTR may influence the prognosis of PDAC.

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