ArticleScientific reports2020
Novel miRNA signature for predicting the stage of hepatocellular carcinoma.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed, 62 citations in OpenAlex.
- A novel minimally invasive diagnostic approach of various brain malignancies based on differential miRNA expression.Journal of neuro-oncology · 2026Article
- Artificial intelligence-based miRNA analysis for precision oncology: diagnostic and prognostic insights.Frontiers in molecular biosciences · 2026Review
- Non-viral HCC miRNA profiling reveals miR-1972 as a potential positive prognostic marker.Non-coding RNA research · 2025Article
- Decision tree-based machine learning methods for identifying colorectal cancer-associated microRNA signatures and their regulatory networks.Scientific reports · 2025Article
- Advancements in the therapeutic potential of sesquiterpenoids for the treatment of hepatocellular carcinoma (Review).International journal of oncology · 2025Review
- The epigenetic basis of hepatocellular carcinoma - mechanisms and potential directions for biomarkers and therapeutics.British journal of cancer · 2025Review
- Identification of novel microRNAs: Biomarkers for pathogenesis of hepatocellular carcinoma in mice model.Biochemistry and biophysics reports · 2025Article
- Machine Learning Approach and Bioinformatics Analysis Discovered Key Genomic Signatures for Hepatitis B Virus-Associated Hepatocyte Remodeling and Hepatocellular Carcinoma.Cancer informatics · 2025Review
- Exploring prognostic implications of miRNA signatures and telomere maintenance genes in kidney cancer.Molecular therapy. Oncology · 2024Article
- The ncRNA-AURKA Interaction in Hepatocellular Carcinoma: Insights into Oncogenic Pathways, Therapeutic Opportunities, and Future Challenges.Life (Basel, Switzerland) · 2024Review
- An evolutionary learning-based method for identifying a circulating miRNA signature for breast cancer diagnosis prediction.NAR genomics and bioinformatics · 2024Article
- Analysis of Circulating Plasma MicroRNA Profile in Low-Grade and High-Grade Glioma - A Cross-Sectional Study.F1000Research · 2024Article
- Article
- Role of Non-Coding RNAs in Hepatocellular Carcinoma Progression: From Classic to Novel Clinicopathogenetic Implications.Cancers · 2023Review
- Identifying Network Biomarkers in Early Diagnosis of Hepatocellular Carcinoma via miRNA-Gene Interaction Network Analysis.Current issues in molecular biology · 2023Article
- Artificial intelligence-driven pan-cancer analysis reveals miRNA signatures for cancer stage prediction.HGG advances · 2023Article
- Article
- Key therapeutic targets implicated at the early stage of hepatocellular carcinoma identified through machine-learning approaches.Scientific reports · 2023Article
- p53 and HuR combinatorially control the biphasic dynamics of microRNA-125b in response to genotoxic stress.Communications biology · 2023Article
- Current therapeutic modalities and chemopreventive role of natural products in liver cancer: Progress and promise.World journal of hepatology · 2023Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer deaths worldwide. Recently, microRNAs (miRNAs) are reported to be altered and act as potential biomarkers in various cancers. However, miRNA biomarkers for predicting the stage of HCC are limitedly discovered. Hence, we sought to identify a novel miRNA signature associated with cancer stage in HCC. We proposed a support vector machine (SVM)-based cancer stage prediction method, SVM-HCC, which uses an inheritable bi-objective combinatorial genetic algorithm for selecting a minimal set of miRNA biomarkers while maximizing the accuracy of predicting the early and advanced stages of HCC. SVM-HCC identified a 23-miRNA signature that is associated with cancer stages in patients with HCC and achieved a 10-fold cross-validation accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the receiver operating characteristic curve (AUC) of 92.59%, 0.98, 0.74, 0.80, and 0.86, respectively; and test accuracy and test AUC of 74.28% and 0.73, respectively. We prioritized the miRNAs in the signature based on their contributions to predictive performance, and validated the prognostic power of the prioritized miRNAs using Kaplan-Meier survival curves. The results showed that seven miRNAs were significantly associated with prognosis in HCC patients. Correlation analysis of the miRNA signature and its co-expressed miRNAs revealed that hsa-let-7i and its 13 co-expressed miRNAs are significantly involved in the hepatitis B pathway. In clinical practice, a prediction model using the identified 23-miRNA signature could be valuable for early-stage detection, and could also help to develop miRNA-based therapeutic strategies for HCC.
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