ArticlePathology oncology research : POR2019
Investigating Potential Molecular Mechanisms of Carcinogenesis and Genes as Biomarkers for Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis.
Article in Pathology oncology research : POR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Competing Endogenous RNA Networks Reveal Long Non-coding RNAs as Potential Prognostic Biomarkers in Gastric Cancer: A Systematic Review and Meta-Analysis.Advanced biomedical research · 2025Review
- Integrated Bioinformatics Analysis Reveals Key Candidate Genes and Cytokine Pathways Involved in COVID-19 After Rhinovirus Infection in Asthma Patients.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- The Study of Sarcoma Microenvironment Heterogeneity Associated With Prognosis Based on an Immunogenomic Landscape Analysis.Frontiers in bioengineering and biotechnology · 2020Article
- Systematic Analysis of Competing Endogenous RNA Networks in Diffuse Large B-Cell Lymphoma and Hodgkin's Lymphoma.Frontiers in genetics · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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Abstract
Gastric cancer, as the fifth most common malignancy worldwide, is a deadly disease afflicting nearly a million people. Researchers have devoted much to study the mechanisms of carcinogenesis and progression, but the exact information of tumor initiation and progression is remained largely unknown. Here, we hypothesized several differentially expressed genes and possible pathways by employing integrated bioinformatics analysis. We fully analyzed four gastric cancer-related microarray datasets to screen differentially expressed mRNAs (DEMs), miRNAs (DEMis) and lncRNAs (DELs). The functional enrichment analysis was deeply construed, PPI network and ceRNA regulatory network were constructed to investigate potential mechanisms of tumorigenesis and progression. Furthermore, survival analysis was performed to identify critical lncRNAs that may significantly affect pathogenesis of gastric cancer. QRT-PCR was applied to verify our result. We identified two hub subnetworks that may explain the progression, metastasis and poor prognosis of gastric cancer. Meanwhile, several potential significant lncRNAs were identified. In summary, we ascertained several significantly changed KEGG pathways in the tumor initiation and progression. We also hypothesized several lncRNAs that contribute to poor prognosis of gastric cancer via integrated bioinformatics, which deserve further investigation.
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