ArticleAnalytical cellular pathology (Amsterdam)2019
A Circulating miRNA-Based Scoring System Established by WGCNA to Predict Colon Cancer.
Article in Analytical cellular pathology (Amsterdam), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- S12micro: a machine learning-derived serum miRNA panel for high-performance pan-cancer diagnosis via liquid biopsy.International journal of surgery (London, England) · 2026Article
- The Impact of miRNA Expression on Colon Cancer Severity, Invasiveness, and Localization.Cancers · 2025Article
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- Article
- miR-23a-3p promotes the development of colon cancer by inhibiting the expression of NDRG4.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023Article
- Network analysis identifies DAPK3 as a potential biomarker for lymphatic invasion and colon adenocarcinoma prognosis.iScience · 2021Article
- Weighted miRNA co-expression networks analysis identifies circulating miRNA predicting overall survival in hepatocellular carcinoma patients.Scientific reports · 2020Article
- Weighted correlation network bioinformatics uncovers a key molecular biosignature driving the left-sided heart failure.BMC medical genomics · 2020Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
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Abstract
introductionCirculation microRNAs (miRNAs) perform as potential diagnostic biomarkers of many kinds of cancers. This study is aimed at identifying circulation miRNAs as diagnostic biomarkers in colon cancer.
methodsWe conducted a weighted gene coexpression network analysis (WGCNA) in miRNAs to find out the expression pattern among circulation miRNAs by using a "WGCNA" package in R. Correlation analysis was performed to find cancer-related modules. Differentially expressed miRNAs (DEmiRs) in colon cancer were identified by a "limma" package in R. Hub gene analysis was conducted for these DEmiRs in the cancer-related modules by the "closeness" method in cytoscape software. Then, logistic regression was performed to identify the independent risk factors, and a scoring system was constructed based on these independent risk factors. Then, we use data from the GEO database to confirm the reliability of this scoring system.
resultsA total of 9 independent coexpression modules were constructed based on the expression levels of 848 miRNAs by WGCNA. After correlation analysis, green (cor = 0.77,
conclusionWe built a scoring system based on circulation hub miRNAs found by WGCNA to predict the development of colon cancer.
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