ArticleScientific reports2022
Identification of hub pathways and drug candidates in gastric cancer through systems biology.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
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- Predicting Prognosis and Immunotherapy Response in Glioblastoma (GBM) With a 5-Gene CAF-Risk Signature.Cancer reports (Hoboken, N.J.) · 2025Article
- Targeting TLK2 inhibits the progression of gastric cancer by reprogramming amino acid metabolism through the mTOR/ASNS axis.Cancer gene therapy · 2023Article
- A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis.BMC gastroenterology · 2023Article
- A systems biology approach for discovering the cellular and molecular aspects of psychogenic non-epileptic seizure.Frontiers in psychiatry · 2023Article
- Transforming RNA-Seq gene expression to track cancer progression in the multi-stage early to advanced-stage cancer development.PloS one · 2023Article
- Genetic variations in relation to bleeding and pharmacodynamics of dabigatran in Chinese patients with nonvalvular atrial fibrillation: A nationwide multicentre prospective cohort study.Clinical and translational medicine · 2022Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer is the fourth cause of cancer death globally, and gastric adenocarcinoma is its most common type. Efforts for the treatment of gastric cancer have increased its median survival rate by only seven months. Due to the relatively low response of gastric cancer to surgery and adjuvant therapy, as well as the complex role of risk factors in its incidences, such as protein-pomp inhibitors (PPIs) and viral and bacterial infections, we aimed to study the pathological pathways involved in gastric cancer development and investigate possible medications by systems biology and bioinformatics tools. In this study, the protein-protein interaction network was analyzed based on microarray data, and possible effective compounds were discovered. Non-coding RNA versus coding RNA interaction network and gene-disease network were also reconstructed to better understand the underlying mechanisms. It was found that compounds such as amiloride, imatinib, omeprazole, troglitazone, pantoprazole, and fostamatinib might be effective in gastric cancer treatment. In a gene-disease network, it was indicated that diseases such as liver carcinoma, breast carcinoma, liver fibrosis, prostate cancer, ovarian carcinoma, and lung cancer were correlated with gastric adenocarcinoma through specific genes, including hgf, mt2a, mmp2, fbn1, col1a1, and col1a2. It was shown that signaling pathways such as cell cycle, cell division, and extracellular matrix organization were overexpressed, while digestion and ion transport pathways were underexpressed. Based on a multilevel systems biology analysis, hub genes in gastric adenocarcinoma showed participation in the pathways such as focal adhesion, platelet activation, gastric acid secretion, HPV infection, and cell cycle. PPIs are hypothesized to have a therapeutic effect on patients with gastric cancer. Fostamatinib seems a potential therapeutic drug in gastric cancer due to its inhibitory effect on two survival genes. However, these findings should be confirmed through experimental investigations.
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