{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T14:52:10Z","timestamp":1787755930077,"version":"build-2784847793"},"reference-count":19,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T00:00:00Z","timestamp":1787702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:p>Early-onset colorectal cancer (EOCRC), defined as colorectal cancer diagnosed before age 50, is rising across high- and middle-income settings whilst organised screening stays anchored to older age thresholds. Blood-based liquid biopsy, combined with machine learning, is the most plausible route to early detection in this group because it does not depend on bowel preparation, endoscopy capacity, or adherence to stool-based testing. The gap is structural: incidence climbs fastest in the population below the age at which any guideline-endorsed modality is offered. The analytical challenge is that early-stage tumour-derived signals in plasma are low in abundance and distributed across heterogeneous molecular layers: circulating tumour DNA mutations, aberrant methylation, cfDNA fragmentomics, and small non-coding RNA. Machine learning converts these into a single calibrated probability. This review examines where artificial intelligence (AI)-driven liquid biopsy genuinely adds diagnostic value in EOCRC, distinguishes components in which learned models are decorative from those in which they are mechanistically necessary, and identifies the validation deficit separating research cohorts from deployable clinical tools. It summarises the first-generation tools used clinically for early detection and post-treatment monitoring, then considers analytes from exosome-bound microRNAs to long-read whole-genome sequencing of circulating plasma DNA, which reads cytosine modification natively, resolves methylation and fragmentation on single molecules, and characterises structural events short reads cannot anchor. Any analyte can feed a learned model, but more diverse input yields better discrimination. The central argument is that approved, guideline-included blood tests were validated in populations aged 45 and above, and their performance in younger patients cannot be assumed.<\/jats:p>","DOI":"10.3389\/fonc.2026.1916796","type":"journal-article","created":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T14:07:30Z","timestamp":1787753250000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["How advances in machine learning drive early detection and risk prediction of early-onset colorectal cancer"],"prefix":"10.3389","volume":"16","author":[{"given":"Sudha S.","family":"Murthy","sequence":"first","affiliation":[{"name":"Department of Histopathology and Molecular Oncology, Krishna Institute of Medical Sciences (KIMS)","place":["Hyderabad, India"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Schuh","sequence":"additional","affiliation":[{"name":"Department of Oncology, University of Oxford","place":["Oxford, United Kingdom"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,26]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21772","article-title":"Colorectal cancer statistics, 2023","volume":"73","author":"Siegel","year":"2023","journal-title":"CA Cancer J Clin"},{"key":"B2","volume-title":"Guardant Shield for Detection of Colorectal Cancer: Executive Summary","year":"2024"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2304714","article-title":"A cell-free DNA blood-based test for colorectal cancer screening","volume":"390","author":"Chung","year":"2024","journal-title":"N Engl J Med"},{"key":"B4","volume-title":"NCCN Clinical Practice Guidelines in Oncology: Colorectal Cancer Screening. Version 1.2025","year":"2025"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1002\/1878-0261.12942","article-title":"A novel cell-free DNA methylation-based model improves the early detection of colorectal cancer","volume":"15","author":"Wu","year":"2021","journal-title":"Mol Oncol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1136\/gutjnl-2012-304149","article-title":"Prospective evaluation of methylated SEPT9 in plasma for detection of asymptomatic colorectal cancer","volume":"63","author":"Church","year":"2014","journal-title":"Gut"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2026.1705156","article-title":"Leveraging cfDNA fragmentomic features for the early detection of colorectal cancer","volume":"17","author":"Shan","year":"2026","journal-title":"Front Immunol"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1053\/j.gastro.2025.08.013","article-title":"An exosome-based liquid biopsy for the detection of early-onset colorectal cancer: the ENCODER multicenter study","volume":"170","author":"Mannucci","year":"2026","journal-title":"Gastroenterology"},{"key":"B9","volume-title":"Liquid Biopsy for Early Detection of Colorectal Cancer Using Circular RNA (Circle; NCT07224789); Exosome-Based and Machine-Learning-Powered Liquid Biopsy for Early-Onset Colorectal Cancer Detection (Encode; NCT06342401)","year":"2025"},{"key":"B10","doi-asserted-by":"publisher","first-page":"e64506","DOI":"10.2196\/64506","article-title":"Predicting early-onset colorectal cancer in individuals below screening age using machine learning and real-world data: case-control study","volume":"11","author":"Sun","year":"2025","journal-title":"JMIR Cancer"},{"key":"B11","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1038\/s41698-025-00978-7","article-title":"Prediction of long-term recurrence-free and overall survival in early-onset colorectal cancer: the ENCORE multi-centre study","volume":"9","author":"Mannucci","year":"2025","journal-title":"NPJ Precis Oncol"},{"key":"B12","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1186\/s13073-023-01178-3","article-title":"Single-molecule methylation profiles of cell-free DNA in cancer with nanopore sequencing","volume":"15","author":"Lau","year":"2023","journal-title":"Genome Med"},{"key":"B13","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1038\/s43856-025-01278-8","article-title":"5-methylcytosine and 5-hydroxymethylcytosine are synergistic biomarkers for early detection of colorectal cancer","volume":"6","author":"Puddu","year":"2026","journal-title":"Commun Med"},{"key":"B14","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1186\/s13059-022-02710-1","article-title":"Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from nanopore sequencing","volume":"23","author":"Katsman","year":"2022","journal-title":"Genome Biol"},{"key":"B15","volume-title":"Early-Onset Colorectal Cancer Think Tank: Advancing Prevention, Detection, and Treatment","year":"2025"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1272-6","article-title":"Genome-wide cell-free DNA fragmentation in patients with cancer","volume":"570","author":"Cristiano","year":"2019","journal-title":"Nature"},{"key":"B17","doi-asserted-by":"publisher","first-page":"9015","DOI":"10.1038\/s41467-024-53017-7","article-title":"Cancer treatment monitoring using cell-free DNA fragmentomes","volume":"15","author":"Annapragada","year":"2024","journal-title":"Nat Commun"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.36518\/2689-0216.2259","article-title":"A blood-based test for colorectal cancer screening","volume":"6","author":"Cullison","year":"2025","journal-title":"HCA Healthc J Med"},{"key":"B19","doi-asserted-by":"publisher","first-page":"1562","DOI":"10.1038\/s41467-026-68414-3","article-title":"Multi-modal AI for opportunistic screening, staging and progression risk stratification of steatotic liver disease","volume":"17","author":"Gao","year":"2026","journal-title":"Nat Commun"}],"container-title":["Frontiers in Oncology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2026.1916796\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T14:07:32Z","timestamp":1787753252000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2026.1916796\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,26]]},"references-count":19,"alternative-id":["10.3389\/fonc.2026.1916796"],"URL":"https:\/\/doi.org\/10.3389\/fonc.2026.1916796","relation":{},"ISSN":["2234-943X"],"issn-type":[{"value":"2234-943X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,26]]},"article-number":"1916796"}}