Selvan Tamizh G, Gollapalli Pavan, Kumar Santosh H S, Ghate Sudeep D
Central Research Laboratory, K S Hegde Medical Academy, Nitte (Deemed to Be University), Deralakatte, Mangalore, 575018, Karnataka, India.
Center for Bioinformatics, University Annexe, Nitte (Deemed to be University), Deralakatte, Mangalore, 575018, Karnataka, India.
J Genet Eng Biotechnol. 2023 Aug 18;21(1):86. doi: 10.1186/s43141-023-00539-0.
It is important to comprehend how the molecular mechanisms shift when gastric cancer in its early stages (GC). We employed integrative bioinformatics approaches to locate various biological signalling pathways and molecular fingerprints to comprehend the pathophysiology of the GC. To facilitate the discovery of their possible biomarkers, a rapid diagnostic may be made, which leads to an improved diagnosis and improves the patient's prognosis.
Through protein-protein interaction networks, functional differentially expressed genes (DEGs), and pathway enrichment studies, we examined the gene expression profiles of individuals with chronic atrophic gastritis and GC.
A total of 17 DEGs comprising 8 upregulated and 9 down-regulated genes were identified from the microarray dataset from biopsies with chronic atrophic gastritis and GC. These DEGs were primarily enriched for CDK regulation of DNA replication and mitotic M-M/G1 phase pathways, according to KEGG analysis (p > 0.05). We discovered two hub genes, MCM7 and CDC6, in the protein-protein interaction network we obtained for the 17 DEGs (expanded with increased maximum interaction with 110 nodes and 2103 edges). MCM7 was discovered to be up-regulated in GC tissues following confirmation using the GEPIA and Human Protein Atlas databases.
The elevated expression of MCM7 in both chronic atrophic gastritis and GC, as shown by our comprehensive investigation, suggests that this protein may serve as a promising biomarker for the early detection of GC.
了解胃癌早期(GC)时分子机制如何转变非常重要。我们采用综合生物信息学方法来定位各种生物信号通路和分子指纹,以理解GC的病理生理学。为了便于发现其可能的生物标志物,可进行快速诊断,从而改善诊断并改善患者预后。
通过蛋白质-蛋白质相互作用网络、功能差异表达基因(DEG)和通路富集研究,我们检查了慢性萎缩性胃炎和GC患者的基因表达谱。
从慢性萎缩性胃炎和GC活检的微阵列数据集中鉴定出总共17个DEG,包括8个上调基因和9个下调基因。根据KEGG分析,这些DEG主要富集于DNA复制的CDK调节和有丝分裂M-M/G1期通路(p>0.05)。在我们为17个DEG获得的蛋白质-蛋白质相互作用网络中(扩展后最大相互作用增加,有110个节点和2103条边),我们发现了两个枢纽基因,MCM7和CDC6。使用GEPIA和人类蛋白质图谱数据库确认后发现,MCM7在GC组织中上调。
我们的综合研究表明,MCM7在慢性萎缩性胃炎和GC中均表达升高,这表明该蛋白可能是早期检测GC的有前景的生物标志物。