区分结直肠癌低肿瘤负荷与寡转移疾病:呼吁采用个体化治疗方法。
Differentiating low tumor burden from oligometastatic disease in colorectal cancer: a call for individualized therapeutic approaches.
作者信息
de Grandis M C, Baraibar I, Prior O, Balaguer-Montero M, Salvà F, Ros J, Rodríguez-Castells M, Tabernero J, Lonardi S, Perez-Lopez R, Élez E
机构信息
Department of Oncology, Veneto Institute of Oncology IOV - IRCCS, Padova, Italy.
Department of Medical Oncology, Vall d'Hebron University Hospital, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.
出版信息
ESMO Open. 2025 Aug 12;10(8):105520. doi: 10.1016/j.esmoop.2025.105520.
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.
转移性结直肠癌(mCRC)仍然是一项重大的临床挑战;然而,肿瘤负荷对治疗结果有显著影响。在本综述中,我们探讨了低肿瘤负荷(LTB)在mCRC中的生物学和临床相关性。定义LTB mCRC的主要挑战在于建立一个标准化的定义,该定义要超越目前对寡转移疾病的关注。LTB mCRC患者表现出独特的临床特征,这些特征可能会影响预后和治疗反应。有证据表明,LTB患者通常对全身治疗反应更好,可能从靶向治疗和免疫治疗方法中获得潜在益处。然而,建立一个明确的定义对于一致的患者分层以及指导研究和选择最合适的治疗策略至关重要,特别是在免疫治疗等新兴治疗的背景下。最近使用先进成像模式、液体活检和乳酸脱氢酶(LDH)测量的研究提供了更准确评估肿瘤负荷的新方法。这些进展,再加上LTB患者可能从免疫治疗中获益的新证据,凸显了针对LTB mCRC患者进行进一步研究的必要性。此外,人工智能(AI)可以增强肿瘤检测、自动进行三维(3D)体积量化、提取基于放射组学的预后信息以及整合多模态数据。这些能力可能会增强我们对患者进行分层和指导治疗决策的能力,有可能为mCRC患者带来更好的治疗结果。未来的研究应专注于完善LTB的定义、验证这些新的评估技术,并评估它们对mCRC患者治疗结果的影响。
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