ArticleMolecules (Basel, Switzerland)2024
piRNA in Machine-Learning-Based Diagnostics of Colorectal Cancer.
Article in Molecules (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advanced artificial intelligence in piRNA and PIWI-like protein research: A systematic review of recurrent neural networks, long short-term memory, and emerging computational techniquesBiomedica : revista del Instituto Nacional de Salud · 2025Pooled it
- Machine learning approaches for cancer prognosis and diagnosis via non-coding RNA: a comprehensive review.Briefings in bioinformatics · 2026Review
- Research progress of machine learning applications in gastric cancer diagnosis and therapy.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- piRNA: Molecular Mechanisms from Germline Silencing to Somatic Regulation and Roles in Disease.International journal of molecular sciences · 2026Review
- Biological roles and clinical potential of piRNAs in cancer: Insights into glioblastoma.Iranian journal of basic medical sciences · 2026Review
- Development and validation of an AI-augmented deep learning model for survival prediction in de novo metastatic colorectal cancer.Discover oncology · 2025Article
- Targeting epigenetic regulators as a promising avenue to overcome cancer therapy resistance.Signal transduction and targeted therapy · 2025Review
- Targeting Regulatory Noncoding RNAs in Human Cancer: The State of the Art in Clinical Trials.Pharmaceutics · 2025Review
- Differential Expression of Small Non-Coding RNAs in Uterine Leiomyomas.International journal of molecular sciences · 2025Article
- Circulating Serum piRNAs as Diagnostic and Prognostic Tools for Clear Cell Renal Cell Carcinoma.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective biomarkers are crucial for early diagnosis to promote treatment and raise survival rates for diseases. With the smallest non-coding RNAs-piwi-RNAs (piRNAs)-and their transcripts, we sought to identify if these piRNAs could be used as biomarkers for colorectal cancer (CRC). Using previously published data from serum samples of patients with CRC, 13 differently expressed piRNAs were selected as potential biomarkers. With this data, we developed a machine learning (ML) algorithm and created 1020 different piRNA sequence descriptors. With the Naïve Bayes Multinomial classifier, we were able to isolate the 27 most influential sequence descriptors and achieve an accuracy of 96.4%. To test the validity of our model, we used data from piRBase with known associations with CRC that we did not use to train the ML model. We were able to achieve an accuracy of 85.7% with these new independent data. To further validate our model, we also tested data from unrelated diseases, including piRNAs with a correlation to breast cancer and no proven correlation to CRC. The model scored 44.4% on these piRNAs, showing that it can identify a difference between biomarkers of CRC and biomarkers of other diseases. The final results show that our model is an effective tool for diagnosing colorectal cancer. We believe that in the future, this model will prove useful for colorectal cancer and other diseases diagnostics.
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Registered trials
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