Liquid biopsy and machine learning to detect early colorectal cancer, advanced adenomas, Lynch-related cancers, and residual disease
Liquid Biopsy and Machine Learning for Early Colorectal Cancer, Adenomas, Lynch Cancers, and Residual Disease Detection
This project will test a blood-based liquid biopsy that uses microRNA signals and machine learning to detect colorectal cancer, advanced adenomas, Lynch-associated cancers, and molecular residual disease in people who have a colonoscopy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 1200 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | San Raffaele University Academic / other |
| Locations | 4 sites (Milan, Lombardy and 3 other locations) |
| Trial ID | NCT07450612 on ClinicalTrials.gov |
What this trial studies
BEACON/2026 is a multicenter observational effort that collects blood at the time of colonoscopy to develop and validate two blood-based tests: a screening test for CRC and advanced adenomas and a multi-cancer early detection (MCED) test tailored to the Lynch syndrome spectrum. The approach combines cell-free microRNAs (cf-miRNAs) and exosome-bound microRNAs (exo-miRNAs) with machine-learning classifiers to improve sensitivity and specificity. Participants must have blood drawn before any curative-intent treatment and will be assigned to cohorts based on standard pathological and endoscopic diagnoses, with cases compared to controls to estimate diagnostic accuracy. A pre-planned analysis will also evaluate the test's use for molecular residual disease (MRD) monitoring following standard diagnostic and staging procedures.
Who should consider this trial
Good fit: Ideal candidates are people undergoing colonoscopy who can provide informed consent, have blood drawn before any curative-intent treatment, and do not have inflammatory bowel disease.
Not a fit: People with inflammatory bowel disease, those who cannot or will not have a colonoscopy at the time of blood sampling, or those who already received curative treatment prior to the blood draw are unlikely to benefit from this project.
Why it matters
Potential benefit: If successful, this could offer a less invasive blood test that detects both cancers and pre-cancerous adenomas earlier and enable monitoring for residual disease and Lynch-related tumors.
How similar studies have performed: Similar liquid-biopsy and machine-learning approaches have shown promise in early research for cancer detection and MRD, but blood tests sensitive for advanced adenomas and Lynch-spectrum cancers remain largely experimental.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * All individuals included in the study need to have had a colonoscopy at the time of blood sampling. * Received standard diagnostic and staging (as necessary) procedures as per local guidelines, and at least one sample was drawn before receiving any curative-intent treatment. * Received standard pathological and endoscopic diagnosis and assessment for cohort assignment Exclusion Criteria: * Lack of informed consent * Inflammatory bowel disease
Where this trial is running
Milan, Lombardy and 3 other locations
- Gastronterology and Gastrointestinal Endoscopy Unit, IRCCS San Raffaele Hospital — Milan, Lombardy, Italy (Not_yet_recruiting)
- Prof Giulia Martina Cavestro, MD PhD — Milan, Lombardy, Italy (Not_yet_recruiting)
- San Raffaele Scientific Institute, Gastroenterology and Gastrointestinal Endoscopy Unit — Milan, Lombardy, Italy (Recruiting)
- Dipartimento di Chirurgia Oncologica e Dipartimento di Oncologia Sperimentale Istituto Nazionale Tumori — Milan, Mi, Italy (Not_yet_recruiting)
Study contacts
- Principal investigator: Giulia Martina Cavestro, MD, PhD — IRCCS San Raffaele Hospital
- Study coordinator: Giulia Martina Cavestro, MD, PhD
- Email: cavestro.giuliamartina@hsr.it
- Phone: 0226437217
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.