SynthesisBMC systems biology2018
Differential networking meta-analysis of gastric cancer across Asian and American racial groups.
Synthesis in BMC systems biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 29 citations in OpenAlex.
- Temporal Trends in Stomach and Colorectal Cancer Mortality by Racial Groups in Brazil (2000-2023): A Longitudinal Ecological Study.International journal of environmental research and public health · 2025Article
- Aspartame carcinogenic potential revealed through network toxicology and molecular docking insights.Scientific reports · 2024Article
- Expression and Clinical Significance of IRE1-XBP1s, p62, and Caspase-3 in Colorectal Cancer Patients.Iranian journal of medical sciences · 2024Article
- Article
- The dynamic alteration of transcriptional regulation by crucial TFs during tumorigenesis of gastric cancer.Molecular medicine (Cambridge, Mass.) · 2022Article
- Concordance Rate between Clinicians and Watson for Oncology among Patients with Advanced Gastric Cancer: Early, Real-World Experience in Korea.Canadian journal of gastroenterology & hepatology · 2019Article
- Unravel the molecular mechanism of XBP1 in regulating the biology of cancer cells.Journal of Cancer · 2019Review
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGastric Carcinoma is one of the most lethal cancer around the world, and is also the most common cancers in Eastern Asia. A lot of differentially expressed genes have been detected as being associated with Gastric Carcinoma (GC) progression, however, little is known about the underlying dysfunctional regulation mechanisms. To address this problem, we previously developed a differential networking approach that is characterized by involving differential coexpression analysis (DCEA), stage-specific gene regulatory network (GRN) modelling and differential regulation networking (DRN) analysis.
resultIn order to implement differential networking meta-analysis, we developed a novel framework which integrated the following steps. Considering the complexity and diversity of gastric carcinogenesis, we first collected three datasets (GSE54129, GSE24375 and TCGA-STAD) for Chinese, Korean and American, and aimed to investigate the common dysregulation mechanisms of gastric carcinogenesis across racial groups. Then, we constructed conditional GRNs for gastric cancer corresponding to normal and carcinoma, and prioritized differentially regulated genes (DRGs) and gene links (DRLs) from three datasets separately by using our previously developed differential networking method. Based on our integrated differential regulation information from three datasets and prior knowledge (e.g., transcription factor (TF)-target regulatory relationships and known signaling pathways), we eventually generated testable hypotheses on the regulation mechanisms of two genes, XBP1 and GIF, out of 16 common cross-racial DRGs in gastric carcinogenesis.
conclusionThe current cross-racial integrative study from the viewpoint of differential regulation networking provided useful clues for understanding the common dysfunctional regulation mechanisms of gastric cancer progression and discovering new universal drug targets or biomarkers for gastric cancer.
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