Akkari Yassmine M N, Bruyere Helene, Hagelstrom R Tanner, Kanagal-Shamanna Rashmi, Liu Jie, Luo Minjie, Mikhail Fady M, Pitel Beth A, Raca Gordana, Shago Mary, Shao Lina, Smith Lisa R, Smolarek Teresa A, Yenamandra Ashwini, Baughn Linda B
Cytogenetics and Molecular Pathology, Legacy Health, Portland, OR, United States.
Cytogenomics Laboratory, Department of Pathology and Laboratory Medicine, Vancouver General Hospital and University of British Columbia, Canada.
Cancer Genet. 2020 May;243:52-72. doi: 10.1016/j.cancergen.2020.03.001. Epub 2020 Mar 21.
Clinical management and risk stratification of B-lymphoblastic leukemia/ lymphoma (B-ALL/LBL) depend largely on identification of chromosomal abnormalities obtained using conventional cytogenetics and Fluorescence In Situ Hybridization (FISH) testing. In the last few decades, testing algorithms have been implemented to support an optimal risk-oriented therapy, leading to a large improvement in overall survival. In addition, large scale genomic studies have identified multiple aberrations of prognostic significance that are not routinely tested by existing modalities. However, as chromosomal microarray analysis (CMA) and next-generation sequencing (NGS) technologies are increasingly used in clinical management of hematologic malignancies, these abnormalities may be more readily detected. In this article, we have compiled a comprehensive, evidence-based review of the current B-ALL literature, focusing on known and published subtypes described to date. More specifically, we describe the role of various testing modalities in the diagnosis, prognosis, and therapeutic relevance. In addition, we propose a testing algorithm aimed at assisting laboratories in the most effective detection of the underlying genomic abnormalities.
B淋巴细胞母细胞白血病/淋巴瘤（B-ALL/LBL）的临床管理和风险分层在很大程度上取决于使用传统细胞遗传学和荧光原位杂交（FISH）检测所获得的染色体异常的识别。在过去几十年中，已经实施了检测算法以支持最佳的风险导向治疗，从而使总体生存率有了很大提高。此外，大规模基因组研究已经确定了多种具有预后意义的畸变，而现有检测方法并未对其进行常规检测。然而，随着染色体微阵列分析（CMA）和下一代测序（NGS）技术越来越多地用于血液系统恶性肿瘤的临床管理，这些异常可能更容易被检测到。在本文中，我们对当前B-ALL的文献进行了全面的、基于证据的综述，重点关注迄今为止已知和已发表的亚型。更具体地说，我们描述了各种检测方法在诊断、预后和治疗相关性方面的作用。此外，我们提出了一种检测算法，旨在帮助实验室最有效地检测潜在的基因组异常。
