Research Paper Volume 13, Issue 9 pp 12493—12513

A novel gene signature for prognosis prediction and chemotherapy response in patients with pancreatic cancer

Hongcao Lin1,2, *, , Chonghui Hu3, *, , Shangyou Zheng3, *, , Xiang Zhang1,2, , Rufu Chen3, &, , Quanbo Zhou1,2, ,

  • 1 Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China
  • 2 Department of Pancreatobiliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong Province, China
  • 3 Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China
* Equal contribution

Received: November 16, 2020       Accepted: February 16, 2021       Published: April 26, 2021
How to Cite

Copyright: © 2021 Lin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Pancreatic cancer is a lethal disease. Chemoresistance is one of the characteristics of pancreatic cancer and leads to a poor prognosis. This study built an effective predictive model for personalized treatment and explored the molecular mechanism of chemoresistance. A four-gene signature, including serine peptidase inhibitor Kazal type 1 (SPINK1), anoctamin 1 (ANO1), desmoglein 3 (DSG3) and GTPase, IMAP family member 1 (GIMAP1) was identified and associated with prognosis and chemoresistance in the training group. An internal testing dataset and the external dataset, GSE57495, were used for validation and showed a good performance of the gene signature. The high-risk group was enriched with multiple oncological pathways related to immunosuppression and was correlated with epidermal growth factor receptor (EGFR) expression, a target molecule of Erlotinib. In conclusion, this study identified a four-gene signature and established two nomograms for predicting prognosis and chemotherapy responses in patients with pancreatic cancer. The clinical value of the nomogram was evaluated by decision curve analysis (DCA). It showed that these may be helpful for clinical treatment decision-making and the discovery of the potential molecular mechanism and therapy targets for pancreatic cancer.


RRDEGs: Resistance-related differentially expressed genes; ROC curve: receiver operating characteristic curve; C-index: Harrell’s concordance index; HR: Hazard ratios; CI: Confidence intervals; AUC: Area under the receiver operating characteristic curve; FDR: False discovery rate; NES: normalized Enrichment score. GSEA: Gene set enrichment analysis; PAAD: Pancreatic adenocarcinoma; TCGA: The Cancer Genome Atlas; GTEx: The Genotype-Tissue Expression project; GEO: The Gene Expression Omnibus; DEGs: Differential Expression Genes; PPI: protein–protein interaction; ESTIMATE: Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data.