Identification of 14 Differentially-Expressed Metabolism-Related Genes as Potential Targets of Gastric Cancer by Integrated Proteomics and Transcriptomics.

Yongxin Zhang,Xiaofeng Wang,Zehong Chen,Tianxiang Lei,Wu Song,Wenwei Liu,Wei Feng

doi:10.3389/fcell.2022.816249

Abstract

Although research on the metabolism related to gastric cancer (GC) is gradually gaining increasing interest, there are few studies regarding metabolism-related genes in GC. Understanding the characteristic changes of metabolism-related genes at the transcriptional and protein levels in GC will help us to identify new biomarkers and novel therapeutic targets. We harvested six pairs of samples from GC patients and evaluated the differentially expressed proteins using mass spectrometry-based proteomics. RNA sequencing was conducted simultaneously to detect the corresponding expression of mRNAs, and bioinformatics analysis was used to reveal the correlation of significant differentially expressed genes. A total of 57 genes were observed to be dysregulated both in proteomics and transcriptomics. Bioinformatics analysis showed that these differentially expressed genes were significantly associated with regulating metabolic activity. Further, 14 metabolic genes were identified as potential targets for GC patients and were related to immune cell infiltration. Moreover, we found that dysregulation of branched-chain amino acid transaminase 2 (BCAT2), one of the 14 differentially expressed metabolism-related genes, was associated with the overall survival time in GC patients. We believe that this study provides comprehensive information to better understand the mechanism underlying the progression of GC metastasis and explores the potential therapeutic and prognostic metabolism-related targets for GC.

Highlights

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide; the molecular mechanisms underlying GC remain largely unknown (Allemani et al, 2018)
The results showed that ADH1B, PHGDH, branched-chain amino acid transaminase 2 (BCAT2), ME3, PCCB, and CS were positively correlated with PD-1 (Figure 4A), and ADH1B, PHGDH, BCAT2, CKB, PCCB, and CS were positively correlated with CTLA4 (Figure 4B)
Thompson organized known cancer-associated metabolic changes into six hallmarks: 1) deregulated uptake of glucose and amino acids, 2) use of opportunistic modes of nutrient acquisition, 3) use of glycolysis/TCA cycle intermediates for biosynthesis and NADPH production, 4) increased demand for nitrogen, 5) alterations in metabolitedriven gene regulation, and 6) metabolic interactions with the microenvironment (Pavlova and Thompson, 2016)

Summary

INTRODUCTION

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide; the molecular mechanisms underlying GC remain largely unknown (Allemani et al, 2018). The combination of surgery and chemotherapy has shown great therapeutic progress, the prognosis of GC has still not significantly improved (Wei et al, 2020). The development of GC is a complex process in which a variety of molecules and signaling pathways are altered (Tan and Yeoh, 2015)

14 Differential Metabolic Genes

MATERIALS AND METHODS

RESULT

DISCUSSION

Findings

ETHICS STATEMENT