Research Paper Volume 14, Issue 22 pp 9243—9263

System analysis based on the ER stress-related genes identifies WFS1 as a novel therapy target for colon cancer

Xianguang Yang1, *, , Chaoyang Zhang1, *, , Cheng Yan2, , Liukai Ma2, , Jiahao Ma2, , Xiaoke Meng2, ,

  • 1 School of Life Sciences, State Key Laboratory Base of Cell Differentiation and Regulation, Henan Normal University, Xinxiang 453007, China
  • 2 School of Pharmacy, Key Laboratory of Nano-carbon Modified Film Technology of Henan Province, Diagnostic Laboratory of Animal Diseases, Xinxiang University, Xinxiang, Henan 453000, China
* Equal contribution

Received: July 8, 2022       Accepted: November 14, 2022       Published: November 28, 2022
How to Cite

Copyright: © 2022 Yang 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.


Background: Colon cancer (COAD) is the third-largest common malignant tumor and the fourth major cause of cancer death in the world. Endoplasmic reticulum (ER) stress has a great influence on cell growth, migration, proliferation, invasion, angiogenesis, and chemoresistance of massive tumors. Although ER stress is known to play an important role in various types of cancer, the prognostic model based on ER stress-related genes (ERSRGs) in colon cancer has not been constructed yet. In this study, we established an ERSRGs prognostic risk model to assess the survival of COAD patients.

Methods: The COAD gene expression profile and clinical information data of the training set were obtained from the GEO database (GSE40967) and the test set COAD gene expression profile and clinical informative data were downloaded from the TCGA database. The endoplasmic reticulum stress-related genes (ERSRGs) were obtained from Gene Set Enrichment Analysis (GSEA) website. Differentially expressed ERSRGs between normal samples and COAD samples were identified by R “limma” package. Based on the univariate, lasso, and multivariate Cox regression analysis, we developed an ERSRGs prognostic risk model to predict survival in COAD patients. Finally, we verified the function of WFS1 in COAD through in vitro experiments.

Results: We built a 9-gene prognostic risk model based on the univariate, lasso, and multivariate Cox regression analysis. Kaplan-Meier survival analysis and Receiver operating characteristic (ROC) curve revealed that the prognostic risk model has good predictive performance. Subsequently, we screened 60 compounds with significant differences in the estimated half-maximal inhibitory concentration (IC50) between high-risk and low-risk groups. In addition, we found that the ERSRGs prognostic risk model was related to immune cell infiltration and the expression of immune checkpoint molecules. Finally, we determined that knockdown of the expression of WFS1 inhibits the proliferation of colon cancer cells.

Conclusions: The prognostic risk model we built may help clinicians accurately predict the survival of patients with COAD. Our findings provide valuable insights into the role of ERSRGs in COAD and may provide new targets for COAD therapy.


TCGA: The Cancer Genome Atlas; GEO: Gene Expression Omnibus; GSEA: Gene Set Enrichment Analysis; ER: Endoplasmic reticulum; ER stress: Endoplasmic reticulum stress; ERSRGs: Endoplasmic reticulum stress-related genes; UPR: Unfolded protein response; COAD: Colon cancer; ROC: Receiver operating characteristic; OS: Overall survival; IC50: The half maximal inhibitory concentration; TME: Tumor microenvironment; GDSC: Genomics of Drug Sensitivity in Cancer; PKC: phosphoinositide-protein kinase C; ROS: Reactive oxygen species; FDR: False discovery rate; PPI: Protein-protein interaction; TIL: Tumor-infiltrating lymphocytes; FC: Fold change; CCK8: Cell Counting Kit-8; DMEM: Dulbecco's Modified Eagle Medium.