Abstract
Background
Stomach adenocarcinoma (STAD) dominates 80–90% of gastric cancer (GC). Over the years, it has been realized that the identification of the genes responsible for gastric carcinogenesis is essential to understand the biomarker discovery.
Methods
This study aims to identify candidate genes for biomarker discovery in STAD. RNA-Seq was performed on three paired tumor-normal and one unpaired tumor samples from four GC patients and investigated for differentially expressed genes (DEGs) using DESeq2. Gene set enrichment analysis were performed. The DEGs were compared with two STAD microarray datasets available on Gene Expression Omnibus (GEO) database. Survival study (OS) were performed using KM-Plotter on the common genes between all the datasets.
Results
Totally, 148 DEGs were identified, wherein 55 genes were upregulated and 93 genes were downregulated with |log2foldchange| > 1 and Benjamini-Hochberg (BH) Adjusted P value < 0.01. Cell adhesion molecule (CAM) Pathway was found to be the most significant among the upregulated genes. Gastric acid secretion and mineral absorption pathways were the most significant pathways among the downregulated genes. Comparison with two GEO datasets followed by OS analysis revealed two upregulating genes, APOC1 and SALL4 with prognostic significance.
Conclusion
Upregulation of APOC1 is associated with marginal overall survival (OS) and SALL4 over-expression was associated with the poor OS using KM-Plotter during 5 years data period. Our study suggests that SALL4 could be a promising biomarker candidate in STAD.
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Details
1 Mizoram University, Department of Biotechnology, Aizawl, India (GRID:grid.411813.e) (ISNI:0000 0000 9217 3865)
2 Zoram Medical College, Director, Falkawn, India (GRID:grid.411813.e)
3 Civil Hospital Aizawl, Department of Surgery, Aizawl, India (GRID:grid.411813.e)
4 Department of Medical Oncology, Mizoram State Cancer Institute, Aizawl, India (GRID:grid.411813.e)
5 National Institute of Biomedical Genomics, Kalyani, India (GRID:grid.410872.8) (ISNI:0000 0004 1774 5690)





