ArticleComputational and mathematical methods in medicine2022
The Clinical Value of Blood miR-654-5p, miR-126, miR-10b, and miR-144 in the Diagnosis of Colorectal Cancer.
Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 10 citations in OpenAlex.
- Targeting GLS and LPIN2 in renal fibroblasts: potential therapeutic targets for kidney stone disease identified by integrated multi-omics analysis.Urolithiasis · 2026Article
- Translational insights into miR-126 and miR-423: biomarkers and therapeutic targets in cancer, cardiovascular, metabolic and kidney diseases.Frontiers in molecular biosciences · 2026Review
- Circulating MiR-126 as a potential biomarker in Egyptian colorectal cancer patients: A case-control study.Innate immunity · 2024Article
- Association analysis of gut microbiota with LDL-C metabolism and microbial pathogenicity in colorectal cancer patients.Lipids in health and disease · 2024Article
- Mapping alternative splicing events in colorectal cancer.Discover oncology · 2024Article
- Unique miRomics Expression Profiles inInternational journal of molecular sciences · 2023Article
- Systematic analyzing a five- miRNA panel and its diagnostic value of plasma expression in colorectal cancer.Molecular biology reports · 2023Article
- Emerging functions and clinical applications of exosomal microRNAs in diseases.Non-coding RNA research · 2023Review
- MicroRNA Biomarkers as Promising Tools for Early Colorectal Cancer Screening-A Comprehensive Review.International journal of molecular sciences · 2023Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Colorectal cancer (CRC) is the third cause of cancer-related death and the fourth most frequently diagnosed cancer across the globe. The objective of this study is to obtain novel and effective diagnostic markers to enrich CRC diagnosis methods. Herein, exosomal miRNA expression data of CRC and normal blood were subjected to XGBoost algorithm, and 5 miRNAs related to CRC diagnosis were primarily confirmed. Then multilayer perceptron (MLP) classifiers were constructed based on different subsets. Via integrated feature selection (IFS), we noticed that the MLP classifier constructed by the first four miRNAs (miR-654-5p, miR-126, miR-10b, and miR-144) had the highest Matthews correlation coefficient (MCC). Subsequently, principal component analysis (PCA) for dimensionality reduction was performed on samples based on the miR-654-5p, miR-126, miR-10b, and miR-144 expression data. The signature based on these four feature miRNAs, as the analysis indicated, could effectively distinguish CRC samples from normal samples. Further, we extracted the exosomes from clinical blood samples and applied qRT-PCR analysis, which revealed that the expression of these four feature miRNAs was in the trend of that in the test set. Collectively, these four feature miRNAs might be tumor biomarkers in the serum, and our study offers innovative thinking on early-stage CRC diagnosis.
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