Department of Malignant Hematology, H Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Center for Accelerating Leukemia/Lymphoma Research at Comprehensive Cancer Center, IRCCS Humanitas Research Hospital, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Milan, Italy.
Lancet Haematol. 2024 Nov;11(11):e862-e872. doi: 10.1016/S2352-3026(24)00251-5. Epub 2024 Oct 9.
The WHO and International Consensus Classification 2022 classifications of myelodysplastic syndromes enhance diagnostic precision and refine decision-making processes in these diseases. However, some discrepancies still exist and potentially cause inconsistency in their adoption in a clinical setting. We adopted a data-driven approach to provide a harmonisation between these two classification systems. We investigated the importance of genomic features and their effect on the cluster assignment process to define harmonised entity labels. A panel of expert haematologists, haematopathologists, and data scientists who are members of the International Consortium for Myelodysplastic Syndromes was formed and a modified Delphi consensus process was adopted to harmonise morphologically defined categories without a distinct genomic profile. The panel held regular online meetings and participated in a two-round survey using an online voting tool. We identified nine clusters with distinct genomic features. The cluster of highest hierarchical importance was characterised by biallelic TP53 inactivation. Cluster assignment was irrespective of blast count. Individuals with monoallelic TP53 inactivation were assigned to other clusters. Hierarchically, the second most important group included myelodysplastic syndromes with del(5q). Isolated del(5q) and less than 5% of blast cells in the bone marrow were the most relevant label-defining features. The third most important cluster included myelodysplastic syndromes with mutated SF3B1. The absence of isolated del(5q), del(7q)/-7, abn3q26.2, complex karyotype, RUNX1 mutations, or biallelic TP53 were the basis for a harmonised label of this category. Morphologically defined myelodysplastic syndrome entities showed large genomic heterogeneity that was not efficiently captured by single-lineage versus multilineage dysplasia, marrow blasts, hypocellularity, or fibrosis. We investigated the biological continuum between myelodysplastic syndromes with more than 10% bone marrow blasts and acute myeloid leukaemia, and found only a partial overlap in genetic features. After the survey, myelodysplastic syndromes with low blasts (ie, less than 5%) and myelodysplastic syndromes with increased blasts (ie, 5% or more) were recognised as disease entities. Our data-driven approach can efficiently harmonise current classifications of myelodysplastic syndromes and provide a reference for patient management in a real-world setting.
世界卫生组织和国际共识分类 2022 年版对骨髓增生异常综合征的分类提高了这些疾病的诊断精度,并完善了决策过程。然而,仍然存在一些差异,这可能导致在临床环境中采用这些分类时出现不一致。我们采用数据驱动的方法来实现这两种分类系统之间的协调。我们研究了基因组特征的重要性及其对聚类分配过程的影响,以确定协调一致的实体标签。成立了一个由国际骨髓增生异常综合征合作组的血液学家、血液病理学家和数据科学家组成的专家组,并采用改良德尔菲共识程序来协调没有明确基因组特征的形态定义类别。专家组定期举行在线会议,并使用在线投票工具参与两轮调查。我们确定了九个具有不同基因组特征的聚类。具有双等位基因 TP53 失活的聚类是最高层次的重要聚类。聚类分配与原始细胞计数无关。单等位基因 TP53 失活的个体被分配到其他聚类中。从层次结构上看,第二重要的组包括伴有 del(5q)的骨髓增生异常综合征。孤立性 del(5q)和骨髓中原始细胞少于 5%是最相关的定义标签特征。第三重要的聚类包括伴有 SF3B1 突变的骨髓增生异常综合征。无孤立性 del(5q)、del(7q)/-7、abn3q26.2、复杂核型、RUNX1 突变或双等位基因 TP53 是此类协调标签的基础。形态学定义的骨髓增生异常综合征实体具有很大的基因组异质性,这不能通过单系与多系发育不良、骨髓原始细胞、低细胞性或纤维化来有效地捕捉。我们研究了骨髓增生异常综合征中骨髓原始细胞超过 10%与急性髓系白血病之间的生物学连续性,发现仅在遗传特征上有部分重叠。调查后,骨髓增生异常综合征中的低原始细胞(即低于 5%)和骨髓增生异常综合征中的高原始细胞(即 5%或以上)被认为是疾病实体。我们的数据驱动方法可以有效地协调骨髓增生异常综合征的现行分类,并为现实环境中的患者管理提供参考。