Identification of a Two-Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival in Diffuse-Type Gastric Cancer

• Published in: Current oncology (Toronto) Vol. 30; no. 1; pp. 171 - 183
• Main Authors: Chen, Songyao, Xu, Jiannan, Yin, Songcheng, Wang, Huabin, Liu, Guangyao, Jin, Xinghan, Zhang, Junchang, Wang, Huijin, Wang, Han, Li, Huan, Liang, Jianming, He, Yulong, Zhang, Changhua
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI 23-12-2022; MDPI AG
• Subjects: diffuse-type gastric cancer; gene signature; High-Throughput Nucleotide Sequencing; Humans; nomogram; Nomograms; Prognosis; Stomach Neoplasms - genetics; diffuse-type gastric cancer; nomogram; gene signature; prognosis
• ISSN: 1718-7729; 1198-0052; 1718-7729
• DOI: 10.3390/curroncol30010014

It is widely acknowledged that the molecular biological characteristics of diffuse-type gastric cancer are different from intestinal-type gastric cancer. Notwithstanding that significant progress in high-throughput sequencing technology has been made, there is a paucity of effective prognostic biomarkers for diffuse gastric cancer for clinical practice.
We downloaded four GEO datasets (GSE22377, GSE38749, GSE47007 and GSE62254) to establish and validate a prognostic two-gene signature for diffuse gastric cancer. The TGCA-STAD dataset was used for external validation. The optimal gene signature was established by using Cox regression analysis. Receiver operating characteristic (ROC) methodology was used to find the best prognostic model. Gene set enrichment analysis was used to analyze the possible signaling pathways of the two genes (MEF2C and TRIM15).
A total of four differently expressed genes (DEGs) (two upregulated and two downregulated) were identified. After a comprehensive analysis, two DEGs (MEF2C and TRIM15) were utilized to construct a prognostic model. A prognostic prediction model was constructed according to T stage, N stage, M stage and the expression of MEF2C and TRIM15. The area under the time-dependent receiver operator characteristic was used to evaluate the performance of the prognosis model in the GSE62254 dataset.
We demonstrated that MEF2C and TRIM15 might be key genes. We also established a prognostic nomogram based on the two-gene signature that yielded a good performance for predicting overall survival in diffuse-type gastric cancer.