Department of Gastroenterology, Sichuan University, Chengdu, China.
Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway.
Nat Rev Clin Oncol. 2024 Jan;21(1):67-79. doi: 10.1038/s41571-023-00834-2. Epub 2023 Nov 24.
The current standard-of-care adjuvant treatment for patients with colorectal cancer (CRC) comprises a fluoropyrimidine (5-fluorouracil or capecitabine) as a single agent or in combination with oxaliplatin, for either 3 or 6 months. Selection of therapy depends on conventional histopathological staging procedures, which constitute a blunt tool for patient stratification. Given the relatively marginal survival benefits that patients can derive from adjuvant treatment, improving the safety of chemotherapy regimens and identifying patients most likely to benefit from them is an area of unmet need. Patient stratification should enable distinguishing those at low risk of recurrence and a high chance of cure by surgery from those at higher risk of recurrence who would derive greater absolute benefits from chemotherapy. To this end, genetic analyses have led to the discovery of germline determinants of toxicity from fluoropyrimidines, the identification of patients at high risk of life-threatening toxicity, and enabling dose modulation to improve safety. Thus far, results from analyses of resected tissue to identify mutational or transcriptomic signatures with value as prognostic biomarkers have been rather disappointing. In the past few years, the application of artificial intelligence-driven models to digital images of resected tissue has identified potentially useful algorithms that stratify patients into distinct prognostic groups. Similarly, liquid biopsy approaches involving measurements of circulating tumour DNA after surgery are additionally useful tools to identify patients at high and low risk of tumour recurrence. In this Perspective, we provide an overview of the current landscape of adjuvant therapy for patients with CRC and discuss how new technologies will enable better personalization of therapy in this setting.
目前,结直肠癌(CRC)患者的标准辅助治疗包括氟嘧啶(5-氟尿嘧啶或卡培他滨)单药或联合奥沙利铂治疗,持续 3 或 6 个月。治疗方案的选择取决于传统的组织病理学分期程序,这是患者分层的一种粗糙工具。鉴于患者从辅助治疗中获得的生存获益相对较小,提高化疗方案的安全性并确定最有可能从中受益的患者是一个未满足的需求领域。患者分层应能够区分手术治愈可能性高且复发风险低的患者与复发风险较高、从化疗中获得更大绝对获益的患者。为此,遗传分析导致发现了氟嘧啶毒性的种系决定因素,确定了发生危及生命毒性的高风险患者,并能够通过调整剂量来提高安全性。到目前为止,对切除组织进行分析以确定具有预后生物标志物价值的突变或转录组特征的结果相当令人失望。在过去的几年中,人工智能驱动模型在切除组织的数字图像中的应用已经确定了具有潜在用途的算法,可以将患者分层为不同的预后组。类似地,手术后测量循环肿瘤 DNA 的液体活检方法也是识别高复发风险和低复发风险患者的有用工具。在本观点中,我们概述了结直肠癌患者辅助治疗的现状,并讨论了新技术如何使该环境中的治疗更具个性化。
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