Minimal residual disease in colorectal cancer. Tumor-informed versus tumor-agnostic approaches: unraveling the optimal strategy.

Fecha de publicación: 01/03/2025 Fecha Ahead of Print: 13/12/2024

Autores de INCLIVA

Participantes ajenos a INCLIVA

Martín-Arana J

Grupos y Plataformas de I+D+i

Grupo de Investigación en Cáncer Colorrectal y Nuevos Desarrollos Terapéuticos en Tumores Sólidos - InDeST

Leading Researcher

Andrés Cervantes Ruiperez
Unidad de Bioestadística

Responsable de Plataforma

Juan Antonio Carbonell Asíns

Abstract

BACKGROUND: Circulating tumor DNA (ctDNA) analysis has emerged as a minimally invasive tool for detecting minimal residual disease (MRD) in colorectal cancer (CRC) patients. This enables dynamic risk stratification, earlier recurrence detection and optimized post-surgical treatment. Two primary methodologies have been developed for ctDNA-based MRD detection: tumor-informed strategies, which identify tumor-specific mutations through initial tissue sequencing to guide ctDNA monitoring, and tumor-agnostic approaches, which utilize predefined panels to detect common cancer-associated genomic or epigenomic alterations directly from plasma without prior tissue analysis. The debate over which is superior in terms of sensitivity, specificity, cost-effectiveness and clinical feasibility remains unsolved. DESIGN: This review summarizes studies published up to November 2024, exploring the utility and performance of tumor-informed and tumor-agnostic approaches for ctDNA analysis in CRC. We evaluate the strengths and limitations of each methodology, focusing on sensitivity, specificity and clinical outcomes. RESULTS: Both strategies demonstrate clinical utility in post-operative risk stratification and guiding adjuvant chemotherapy decisions in CRC patients. Tumor-informed approaches generally exhibit superior sensitivity and specificity for recurrence prediction, attributed to their personalized tumor profile designs. However, these methods are limited by the need for prior tissue sequencing and higher associated costs. In contrast, tumor-agnostic approaches offer broader applicability due to their reliance on plasma-only analysis, although with relatively lower sensitivity. Technological advancements, including fragmentomics and multi-omic integrations, are expanding the capabilities of ctDNA-based MRD detection, enhancing the performance of both approaches. CONCLUSIONS: While tumor-informed strategies currently offer higher precision in MRD detection, tumor-agnostic approaches are gaining traction due to their convenience and improving performance metrics. The integration of novel technologies in ongoing clinical trials may redefine the optimal approach for MRD detection in CRC, paving the way for more personalized and adaptive patient management strategies.

Datos de la publicación

ISSN/ISSNe:: 0923-7534, 1569-8041
Tipo:: Article
Páginas:: 263-276
DOI:: 10.1016/j.annonc.2024.12.006
PubMed:: 39675560

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Filiaciones

Martínez-Castedo B:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Camblor DG:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
Martín-Arana J:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Carbonell-Asins JA:: Instituto de Investigación. Biostatistics Unit, INCLIVA Biomedical Research Institute, University of Valencia, Spain
García-Micó B:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Gambardella V:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
Huerta M:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Roselló S:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Roda D:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Gimeno-Valiente F:: Cancer Evolution and Genome Instability Laboratory, University College London Cancer Institute, London, UK
Cervantes A:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain
Tarazona N:: Instituto de Investigación. Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain

CIBER. CIBERONC, Carlos III Health Institute, Madrid, Spain