The biological and technical challenges facing utilizing circulating tumor DNA in non-metastatic breast cancer patients

IF 10.1 1区 医学 Q1 ONCOLOGY Cancer letters Pub Date : 2025-02-19 DOI:10.1016/j.canlet.2025.217574
Zihang Zeng , Zongbi Yi , Binghe Xu
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Abstract

Breast cancer is one of the most prevalent cancers and has emerged as a major global challenge. Circulating tumor DNA (ctDNA), a liquid biopsy method, overcomes the accessibility limitations of tissue-based testing and is widely used for monitoring minimal residual disease and molecular relapse, predicting prognosis, evaluating the response of neoadjuvant therapy, and optimizing treatment decisions in non-metastatic breast cancer. However, the application of ctDNA still faces many challenges. Here, we survey the clinical applications of ctDNA in non-metastatic breast cancer and discuss the significant biological and technical challenges of utilizing ctDNA. Importantly, we investigate potential avenues for addressing the challenges. In addition, emerging technologies, including fragmentomics detection, methylation sequencing, and long-read sequencing, have clinical potential and could be a future direction. Proper utilization of machine learning facilitates the identification of meaningful patterns from complex fragment and methylation profiles of ctDNA. There is still a lack of clinical trials focused on the subsets of ctDNA (e.g., circulating mitochondrial DNA), ctDNA-inferred drug-resistant clonal evolution, tumor heterogeneity, and ctDNA-guided clinical decision-making in non-metastatic breast cancer. Due to regional differences in the number of registered clinical trials, it is essential to enhance communication and foster global collaboration to advance the field.
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在非转移性乳腺癌患者中利用循环肿瘤DNA所面临的生物学和技术挑战
乳腺癌是最常见的癌症之一,已成为一项重大的全球挑战。循环肿瘤DNA (ctDNA)是一种液体活检方法,克服了基于组织的检测的可及性限制,广泛用于监测微小残留疾病和分子复发,预测预后,评估新辅助治疗的反应,优化非转移性乳腺癌的治疗决策。然而,ctDNA的应用仍面临许多挑战。在这里,我们调查了ctDNA在非转移性乳腺癌中的临床应用,并讨论了利用ctDNA的重大生物学和技术挑战。重要的是,我们研究了应对这些挑战的潜在途径。此外,包括片段组学检测、甲基化测序和长读测序在内的新兴技术具有临床潜力,可能是未来的发展方向。适当利用机器学习有助于从复杂的片段和甲基化谱中识别有意义的模式。目前仍缺乏针对ctDNA亚群(如循环线粒体DNA)、ctDNA推断的耐药克隆进化、肿瘤异质性以及ctDNA指导的非转移性乳腺癌临床决策的临床试验。由于注册临床试验数量的地区差异,必须加强沟通和促进全球合作,以推动该领域的发展。
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来源期刊
Cancer letters
Cancer letters 医学-肿瘤学
CiteScore
17.70
自引率
2.10%
发文量
427
审稿时长
15 days
期刊介绍: Cancer Letters is a reputable international journal that serves as a platform for significant and original contributions in cancer research. The journal welcomes both full-length articles and Mini Reviews in the wide-ranging field of basic and translational oncology. Furthermore, it frequently presents Special Issues that shed light on current and topical areas in cancer research. Cancer Letters is highly interested in various fundamental aspects that can cater to a diverse readership. These areas include the molecular genetics and cell biology of cancer, radiation biology, molecular pathology, hormones and cancer, viral oncology, metastasis, and chemoprevention. The journal actively focuses on experimental therapeutics, particularly the advancement of targeted therapies for personalized cancer medicine, such as metronomic chemotherapy. By publishing groundbreaking research and promoting advancements in cancer treatments, Cancer Letters aims to actively contribute to the fight against cancer and the improvement of patient outcomes.
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