Identification and Verification of Potential Biomarkers in Gastric Cancer By Integrated Bioinformatic Analysis

Chenyu Sun; Yue Chen; Na Hyun Kim; Scott Lowe; Shaodi Ma; Zhen Zhou; Rachel Bentley; Yi-Sheng Chen; Margarita Whitaker Tuason; Wenchao Gu; Chandur Bhan; John Pocholo Whitaker Tuason; Pratikshya Thapa; Ce Cheng; Qin Zhou; Yanzhe Zhu

doi:10.3389/fgene.2022.911740

Identification and Verification of Potential Biomarkers in Gastric Cancer By Integrated Bioinformatic Analysis

Front Genet. 2022 Jul 15:13:911740. doi: 10.3389/fgene.2022.911740. eCollection 2022.

Authors

Chenyu Sun¹, Yue Chen², Na Hyun Kim¹, Scott Lowe³, Shaodi Ma⁴, Zhen Zhou⁵, Rachel Bentley³, Yi-Sheng Chen⁶, Margarita Whitaker Tuason⁷, Wenchao Gu⁸, Chandur Bhan¹, John Pocholo Whitaker Tuason¹, Pratikshya Thapa¹, Ce Cheng^{9

10}, Qin Zhou¹¹, Yanzhe Zhu¹²

Affiliations

¹ AMITA Health Saint Joseph Hospital Chicago, Chicago, IL, United States.
² Department of Clinical Medicine, School of the First Clinical Medicine, Anhui Medical University, Hefei, China.
³ College of Osteopathic Medicine, Kansas City University, Kansas City, MO, United States.
⁴ Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, China.
⁵ Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia.
⁶ Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
⁷ Faculty of Medicine and Surgery, University of Santo Thomas, Metro Manila, Philippines.
⁸ Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan.
⁹ The University of Arizona College of Medicine, Tucson, AZ, United States.
¹⁰ Banner-University Medical Center South, Tucson, AZ, United States.
¹¹ Mayo Clinic, Rochester, MN, United States.
¹² Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.

Abstract

Background: Gastric cancer (GC) is a common cancer with high mortality. This study aimed to identify its differentially expressed genes (DEGs) using bioinformatics methods. Methods: DEGs were screened from four GEO (Gene Expression Omnibus) gene expression profiles. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. A protein-protein interaction (PPI) network was constructed. Expression and prognosis were assessed. Meta-analysis was conducted to further validate prognosis. The receiver operating characteristic curve (ROC) was analyzed to identify diagnostic markers, and a nomogram was developed. Exploration of drugs and immune cell infiltration analysis were conducted. Results: Nine up-regulated and three down-regulated hub genes were identified, with close relations to gastric functions, extracellular activities, and structures. Overexpressed Collagen Type VIII Alpha 1 Chain (COL8A1), Collagen Type X Alpha 1 Chain (COL10A1), Collagen Triple Helix Repeat Containing 1 (CTHRC1), and Fibroblast Activation Protein (FAP) correlated with poor prognosis. The area under the curve (AUC) of ADAM Metallopeptidase With Thrombospondin Type 1 Motif 2 (ADAMTS2), COL10A1, Collagen Type XI Alpha 1 Chain (COL11A1), and CTHRC1 was >0.9. A nomogram model based on CTHRC1 was developed. Infiltration of macrophages, neutrophils, and dendritic cells positively correlated with COL8A1, COL10A1, CTHRC1, and FAP. Meta-analysis confirmed poor prognosis of overexpressed CTHRC1. Conclusion: ADAMTS2, COL10A1, COL11A1, and CTHRC1 have diagnostic values in GC. COL8A1, COL10A1, CTHRC1, and FAP correlated with worse prognosis, showing prognostic and therapeutic values. The immune cell infiltration needs further investigations.

Keywords: ROC (receiver operating curve); bioinformatics analysis; gastric cancer; hub genes; immune infiltration; meta-analysis; prognostic value.