Differentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches

Metastatic colorectal cancer (mCRC) remains a major clinical challenge; however, tumor burden significantly influences treatment outcomes. In this review, we explore the biological and clinical relevance of low tumor burden (LTB) in mCRC. The primary challenge in defining LTB mCRC lies in establishing a standardized definition that extends beyond the current focus on oligometastatic disease. Patients with LTB mCRC exhibit distinct clinical characteristics that may impact both prognosis and therapeutic response. Evidence suggests that LTB patients often respond better to systemic therapies and may derive potential benefits from targeted and immunotherapy approaches. However, establishing a clear definition is crucial for consistent patient stratification, and for guiding research and selecting the most appropriate therapeutic strategies, particularly in the context of emerging treatments such as immunotherapy. Recent studies using advanced imaging modalities, liquid biopsies, and lactate dehydrogenase (LDH) measurements offer novel approaches to evaluate tumor burden more accurately. These developments, coupled with emerging evidence that patients with LTB may benefit from immunotherapy, highlight the need for further research focused on LTB mCRC patients. Additionally, artificial intelligence (AI) could enhance tumor detection, automate three-dimensional (3D) volume quantification, extract radiomics-based prognostic information, and integrate multimodal data. These capabilities may enhance our ability to stratify patients and guide treatment decisions, potentially leading to better outcomes for mCRC patients. Future studies should focus on refining the definition of LTB, validating these new assessment techniques, and evaluating their impact on treatment outcomes in mCRC patients.

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Publication Details

Journal
ESMO Open
Published
2025-08-01
DOI
https://doi.org/10.1016/j.esmoop.2025.105520
Citations
2
Primary Topic
Colorectal Cancer Treatments and Studies
Type
article
Field-Weighted Citation Impact
2.09
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article

Differentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches

Iosune Baraibar, Josep M. Tabernero, Raquel Pérez-López, Élena Elez et al.
2 citations
ESMO Open
Colorectal Cancer Treatments and Studies
2.09
article

Differentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches

Iosune Baraibar, Josep M. Tabernero, Raquel Pérez-López, Élena Elez, Sara Lonardi, Francesc Salvà, Javier Ros, Maria Caterina De Grandis, Marta Rodríguez-Castells, Maria Balaguer‐Montero, Olivia Prior
article en
2 citations

Abstract

Metastatic colorectal cancer (mCRC) remains a major clinical challenge; however, tumor burden significantly influences treatment outcomes. In this review, we explore the biological and clinical relevance of low tumor burden (LTB) in mCRC. The primary challenge in defining LTB mCRC lies in establishing a standardized definition that extends beyond the current focus on oligometastatic disease. Patients with LTB mCRC exhibit distinct clinical characteristics that may impact both prognosis and therapeutic response. Evidence suggests that LTB patients often respond better to systemic therapies and may derive potential benefits from targeted and immunotherapy approaches. However, establishing a clear definition is crucial for consistent patient stratification, and for guiding research and selecting the most appropriate therapeutic strategies, particularly in the context of emerging treatments such as immunotherapy. Recent studies using advanced imaging modalities, liquid biopsies, and lactate dehydrogenase (LDH) measurements offer novel approaches to evaluate tumor burden more accurately. These developments, coupled with emerging evidence that patients with LTB may benefit from immunotherapy, highlight the need for further research focused on LTB mCRC patients. Additionally, artificial intelligence (AI) could enhance tumor detection, automate three-dimensional (3D) volume quantification, extract radiomics-based prognostic information, and integrate multimodal data. These capabilities may enhance our ability to stratify patients and guide treatment decisions, potentially leading to better outcomes for mCRC patients. Future studies should focus on refining the definition of LTB, validating these new assessment techniques, and evaluating their impact on treatment outcomes in mCRC patients.

ESMO OpenVol. 10(8)
Istituto Oncologico Veneto (IT), Vall d'Hebron Hospital Universitari (ES), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Vall d'Hebron Institute of Oncology (ES)
Good health and well-being
Openalex Percentile: Top 11%
Colorectal Cancer Treatments and Studies
2.09
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