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循环肿瘤DNA(ctDNA)中编码的分子特征揭示了高危侵袭性B细胞淋巴瘤的异质性并可预测其预后。

Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma.

作者信息

Meriranta Leo, Alkodsi Amjad, Pasanen Annika, Lepistö Maija, Mapar Parisa, Blaker Yngvild Nuvin, Jørgensen Judit, Karjalainen-Lindsberg Marja-Liisa, Fiskvik Idun, Mikalsen Lars Tore G, Autio Matias, Björkholm Magnus, Jerkeman Mats, Fluge Øystein, Brown Peter, Jyrkkiö Sirkku, Holte Harald, Pitkänen Esa, Ellonen Pekka, Leppä Sirpa

机构信息

Research Programs Unit, Applied Tumor Genomics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.

Department of Oncology, Helsinki University Hospital Comprehensive Cancer Center, Helsinki, Finland.

出版信息

Blood. 2022 Mar 24;139(12):1863-1877. doi: 10.1182/blood.2021012852.

Abstract

Inadequate molecular and clinical stratification of the patients with high-risk diffuse large B-cell lymphoma (DLBCL) is a clinical challenge hampering the establishment of personalized therapeutic options. We studied the translational significance of liquid biopsy in a uniformly treated trial cohort. Pretreatment circulating tumor DNA (ctDNA) revealed hidden clinical and biological heterogeneity, and high ctDNA burden determined increased risk of relapse and death independently of conventional risk factors. Genomic dissection of pretreatment ctDNA revealed translationally relevant phenotypic, molecular, and prognostic information that extended beyond diagnostic tissue biopsies. During therapy, chemorefractory lymphomas exhibited diverging ctDNA kinetics, whereas end-of-therapy negativity for minimal residual disease (MRD) characterized cured patients and resolved clinical enigmas, including false residual PET positivity. Furthermore, we discovered fragmentation disparities in the cell-free DNA that characterize lymphoma-derived ctDNA and, as a proof-of-concept for their clinical application, used machine learning to show that end-of-therapy fragmentation patterns predict outcome. Altogether, we have discovered novel molecular determinants in the liquid biopsy that can noninvasively guide treatment decisions.

摘要

高危弥漫性大B细胞淋巴瘤(DLBCL)患者的分子和临床分层不足是一项临床挑战,阻碍了个性化治疗方案的制定。我们在一个接受统一治疗的试验队列中研究了液体活检的转化意义。治疗前循环肿瘤DNA(ctDNA)揭示了隐藏的临床和生物学异质性,并且高ctDNA负荷独立于传统风险因素决定了复发和死亡风险的增加。对治疗前ctDNA的基因组剖析揭示了超出诊断组织活检范围的与转化相关的表型、分子和预后信息。在治疗期间,化疗难治性淋巴瘤表现出不同的ctDNA动力学,而治疗结束时微小残留病(MRD)呈阴性则表明患者已治愈,并解决了临床谜团,包括假阳性PET残留。此外,我们发现了游离DNA中的片段化差异,这些差异是淋巴瘤来源的ctDNA的特征,并且作为其临床应用的概念验证,我们使用机器学习表明治疗结束时的片段化模式可预测预后。总之,我们在液体活检中发现了新的分子决定因素,它们可以无创地指导治疗决策。

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