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Liquid Biopsy and Machine Learning for Early Colorectal Cancer, Adenomas, Lynch Cancers, and Residual Disease Detection

Liquid Biopsy and Machine Learning for Early Colorectal Cancer, Adenomas, Lynch Cancers, and Residual Disease Detection

Recruiting
18 years and older
All
Phase N/A

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Overview

This is an multicenter study that will test the diagnostic accuracy of a blood test (i.e., a liquid biopsy) for the diagnosis of colorectal cancer (CRC), advanced adenomas (AAs), as well as Lynch-syndrome associated cancers. Additionally, a pre-planned analysis will evaluate the use of this liquid biopsy as a tool for molecular residual disease monitoring purposes.

Description

Colorectal cancer (CRC) remains a significant public health burden as the third-most commonly diagnosed and second-deadliest malignancy. While CRC is potentially preventable through the removal of precursor lesions known as advanced adenomas (AAs), current screening modalities have limitations. The fecal immunochemical test (FIT) exhibits reduced sensitivity for early-stage CRC and AAs, primarily lowering mortality rather than incidence. Colonoscopy, while effective, is invasive, costly, and suffers from suboptimal adherence. Additionally, individuals with Lynch syndrome (LS), who carry a pathogenic germline variant in mismatch repair (MMR) genes, lack effective and reliable methods for early-stage detection of non-CRC tumors associated with the syndrome.

The rationale of this study, BEACON/2026, is to develop and validate two blood-based tests to address these clinical gaps. The first is a screening test sensitive to both CRC and AAs to complement existing screening options; the second is a multi-cancer early detection (MCED) test tailored to the LS spectrum. The central hypothesis is that a liquid biopsy approach combining cell-free microRNAs (cf-miRNAs, which are sensitive) and exosome-bound microRNAs (exo-miRNAs, which are specific) can effectively distinguish patients with AAs, CRC, and LS-associated cancers from controls.

This study follows the Early Detection Research Network (EDRN) recommendations for biomarker development, including biomarker discovery, prioritization, training, and independent validation (Phases I through III). The experimental design complies with PROBE recommendations for prospectively collected biospecimens that are blindly evaluated. The procedure involves the collection of peripheral blood to isolate RNA from plasma or serum for reverse transcription, quantitative polymerase chain reaction (RT-qPCR) analysis and machine-learning modeling . This non-invasive approach aims to provide a cost-effective, patient-friendly alternative to improve screening participation and disease monitoring

Eligibility

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

Study details
    Colorectal Cancer
    Adenoma Colon
    Adenoma Colon Polyp
    Colon Adenoma
    Colo-rectal Cancer
    Colon Disease
    Colon Neoplasm
    Lynch Syndrome
    Lynch Syndrome I
    Lynch Syndrome II
    Lynch Syndrome I (Site-specific Colonic Cancer)
    LYN Gene Mutation
    Mismatch Repair Deficiency
    Mismatch Repair Gene Mutation
    MLH1 Gene Mutation
    MSH2 Gene Mutation
    MSH6 Gene Mutation
    PMS2 Gene Mutation
    EPCAM Gene Mutation

NCT07450612

San Raffaele University

13 May 2026

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