ArticlePathology oncology research : POR2015
Exploring the Molecular Mechanism and Biomakers of Liver Cancer Based on Gene Expression Microarray.
Article in Pathology oncology research : POR, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Identification of a glycolysis-related gene signature for predicting pancreatic cancer survival.Journal of gastrointestinal oncology · 2022Article
- Prognostic gene biomarker identification in liver cancer by data mining.American journal of translational research · 2021Article
- Three-gene prognostic biomarkers for seminoma identified by weighted gene co-expression network analysis.PloS one · 2020Article
- MKP-4 suppresses hepatocarcinogenesis by targeting ERK1/2 pathway.Cancer cell international · 2019Article
- Aberrant promoter methylation profiles and association with survival in patients with hepatocellular carcinoma.OncoTargets and therapy · 2017Article
- Identification of key genes and molecular mechanisms associated with dedifferentiated liposarcoma based on bioinformatic methods.OncoTargets and therapy · 2017Article
- Identifying Potential New Gene Expression-Based Biomarkers in the Peripheral Blood Mononuclear Cells of Hepatitis B-Related Hepatocellular Carcinoma.Canadian journal of gastroenterology & hepatologyArticle
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver cancer is one of the most common cancers worldwide with high morbidity and mortality. Its molecular mechanism hasn't been fully understood though many studies have been conducted and thus further researches are still needed to improve the prognosis of liver cancer. Firstly, differentially expressed genes (DEGs) between six Mdr2-knockout (Mdr2-KO) mutant mice samples (3-month-old and 12-month-old) and six control mice samples were identified. Then, the enriched GO terms and KEGG pathways of those DEGs were obtained using the Database for Annotation, Visualization and Integrated Discovery (DAVID, http://david.abcc.ncifcrf.gov/). Finally, protein-protein interactions (PPI) network of those DEGs were constructed using STRING database ( http://www.string-db.org/) and visualized by Cytoscape software, at the same time, genes with high degree were selected out. Several novel biomarkers that might play important roles in liver cancer were identified through the analysis of gene microarray in GEO. Also, some genes such as Tyrobp, Ctss and pathways such as Pathways in cancer, ECM-receptor interaction that had been researched previously were further confirmed in this study. Through the bioinformatics analysis of the gene microarray in GEO, we found some novel biomarkers of liver cancer and further confirmed some known biomarkers.
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Registered trials
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