Revised Risk Stratification Criteria for Children with Newly Diagnosed Acute Myeloid Leukemia: A Report from the Children's Oncology Group
Revised Risk Stratification Criteria for Children with Newly Diagnosed Acute Myeloid Leukemia: A Report from the Children's Oncology Group
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修订后的新诊断急性髓系白血病儿童风险分层标准：儿童肿瘤学小组的报告
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发表时间：
2017
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通讯作者：
S. Meshinchi
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作者：
T. Cooper;R. Ries;T. Alonzo;R. Gerbing;M. Loken;L. Brodersen;S. Raimondi;B. Hirsch;R. Aplenc;A. Gamis;E. Kolb;S. Meshinchi
简介：目前，大多数急性髓性白血病（AML）患儿的表型、细胞遗传学或分子标记物未用于危险分层或治疗分配。从历史上看，在儿童肿瘤组（COG）初探性研究AAML 03 P1中，核心结合融合（CBF）[t（8; 21），inv（16）]或NPM 1或CEBPA突变患者的结局更有利。具有高等位基因比率（FLT3-ITD-HAR）、单体7或-5/del（5q）的FLT3-ITD患者具有更多不良结局。在AAML 03 P1中，31%的患者被认为是低风险（LR），9%是高风险（HR），其余60%被认为是标准风险（SR），无事件生存期（EFS）约为50%（图1A）。将相同的风险分类转入后续III期COG研究AAML 0531，结局相似。为了开发一种改进的风险分层策略，我们对使用AAML 0531治疗的患者的可用核型、免疫表型和下一代测序（NGS）数据报告的潜在生物标志物进行了全面的回顾性评价。方法：AAML0531入组了1,022例患者（年龄0 - 29岁），并随机接受标准治疗（含或不含吉妥珠单抗）。本研究可获得中心审查的核型数据和FLT3、NPM1和CEBPA状态。通过NGS（全基因组、转录组或靶向捕获测序）询问另外740份个体诊断标本，以鉴定其他体细胞变异，包括隐蔽融合、单核苷酸（SNV）和拷贝数变异（CNV）。诱导后反应的多维流式细胞术（FCM），一个重要的预后模式，也进行了分析，SR患者的危险分层分配。分析来自基因组和基因组参数的信息与无事件（EFS）和无病生存期（DFS）的相关性。结果：表1显示了我们新的危险分层模型中使用的细胞遗传学、分子和免疫表型标记。通过核型检测的HR融合体包括5种不同的KMT2A（MLL）融合体类型，DEK-NUP214、NPM1-MLF1、MECOM（3q26.2）和KAT6A（8p11.21）。通过NGS检测的HR隐蔽融合体包括CBFA 2T3-GLIS2、NUP98家族融合体（NUP98-NSD 1、NUP98-KDM 5A、NUP98-HMGB3和NUP98-HOXD 13）以及ETS转录因子家族成员（ETV 6、ERG、FEV）。NGS还在10%最初报告为正常核型的患者中鉴定出HR MLL、t（6; 9）或ETS融合。通过免疫表型分析进行的HR分层包括在与FAB-M7以及CBFA 2T3-GLIS2融合重叠的年轻患者中报告的RAM表型。当对AAML 0531治疗的患者进行回顾性核型、免疫表型和NGS分析时，与AAML 03 P1相比，每个风险组中患者的分布发生了显著变化（图1A和1B）。根据修订的危险分层，HR变异占所有AML患者的34%，预后不良（EFS-26.3% ± 5.4%）。具有CBF AML、NPM 1或CEBPA突变的患者被纳入LR队列，具有RBM15-MLK1融合的患者被重新分配至LR队列，这些患者共占AML病例的33%（EFS-70.4% ± 5.6%）。在该建议的风险分层方案中，SR队列降低至33%（EFS-48.6% ± 6.2%）。在拟定的风险分类（图1C）中，SR患者考虑了首次诱导结束时根据DFS确定的微小残留病（MRD），发现其具有预后意义;因此，SR患者被分配至HR（DFS-28.5% ± 5.2%）或LR（DFS-63.7% ± 4.5%）队列。结论：对AAML 0531患者的精确核型分析和分子数据以及经验证的NGS数据的合并分析显著改变了用于预测复发和分配患者接受适当治疗的风险分层。这份报告是第一份研究大量分配到临床试验的患者，并应用新的标准进行核型分析，分子和NGS。在未来的研究中，我们计划通过NGS方法研究COG试验中的所有患者，验证其他新的生物标志物，并为未来基于精确医学的临床试验确定新的靶点。Loken：Hematologics Inc：就业，股权所有权。Brodersen：Hematologics Inc：就业。
Introduction: Currently, most phenotypic, cytogenetic or molecular markers identified in children with acute myeloid leukemia (AML) are not used for risk stratification or treatment assignment. Historically, in the Children9s Oncology Group (COG) pilot study AAML03P1, patients with core binding fusion (CBF) [t(8;21), inv(16)] or with NPM1 or CEBPA mutations had a more favorable outcome. Patients with FLT3 -ITD with high allelic ratio ( FLT3 -ITD-HAR), monosomy 7, or -5/del(5q) had more adverse outcomes. In AAML03P1, 31% of patients were deemed low risk (LR), 9% were high risk (HR) and the remaining 60% were considered standard risk (SR) with event-free survival (EFS) of approximately 50% (Figure 1A). The same risk classification was carried forward to the successor Phase III COG study AAML0531 with similar outcomes. To develop an improved risk stratification strategy, we conducted a comprehensive retrospective evaluation of potential biomarkers that have been reported using available karyotype, immunophenotype and next generation sequencing (NGS) data from patients treated on AAML0531. Methods: AAML0531 enrolled 1,022 patients (age 0-29 years) and randomized to standard therapy with or without gemtuzumab ozogamicin. Centrally reviewed data karyotype and FLT3 , NPM1 and CEBPA status were available for this study. An additional 740 individual diagnostic specimens were interrogated by NGS (whole genome, transcriptome or targeted capture sequencing) to identify additional somatic variants including cryptic fusions, single nucleotide (SNV) and copy number variants (CNVs). Post induction response by multidimensional flow cytometry (MDF), an important prognostic modality, was also analyzed for risk stratification assignment in SR patients. Information from genomic and MDF parameters were analyzed for association with event free (EFS) and disease free survival (DFS). Results: Table 1 shows the cytogenetic, molecular, and immunophenotypic markers used in our new risk stratification model. HR fusions detected by karyotype included 5 distinct KMT2A (MLL) fusion types, DEK-NUP214, NPM1 - MLF1, MECOM (3q26.2), and KAT6A (8p11.21). HR cryptic fusions detected by NGS include CBFA2T3-GLIS2 , NUP98 family fusions ( NUP98-NSD1 , NUP98-KDM5A , NUP98-HMGB3 and NUP98-HOXD13 ) as well as ETS transcription factor family members ( ETV6, ERG, FEV ). NGS also identified HR MLL , t(6;9) or ETS fusions in 10% of patients who were initially reported as having a normal karyotype. HR stratification by immunophenotype analysis includes the RAM phenotype that was reported in younger patients with overlap with FAB-M7 as well as CBFA2T3-GLIS2 fusions. When karyotype, immunophenotype, and NGS analyses were retrospectively applied to patients treated in AAML0531, the distribution of patients in each risk group changed significantly compared to AAML03P1 (Figure 1A and 1B). According to the revised risk stratification, HR variants constituted 34% of all AML patients and had poor prognosis (EFS-26.3% ± 5.4%). Patients with CBF AML, NPM1 or CEBPA mutations were included in the LR cohort and those with RBM15-MLK1 fusion were relocated to the LR cohort and these collectively constitute 33% of AML cases (EFS-70.4% ± 5.6%). The SR cohort was reduced to 33% in this proposed risk stratification schema (EFS-48.6% ± 6.2%). Minimal residual disease (MRD) by MDF at end of first induction was factored for SR patients in the proposed risk classification (Figure 1C) and found to have prognostic significance; therefore SR patients were assigned to either HR (DFS-28.5% ± 5.2%) or LR (DFS-63.7% ± 4.5%) cohorts. Conclusions: Analysis of refined karyotyping and molecular data and incorporation of validated NGS data for patients in AAML0531 significantly altered the risk stratification used to predict relapse and assign patients to appropriate therapy. This report is the first to study a large number of patients assigned to a clinical trial and apply new standards for karyotyping, molecular and NGS. In future studies, we plan to study all patients on COG trials by NGS methods, validate additional novel biomarkers, and to identify new targets for future precision medicine-based clinical trials. Disclosures Loken: Hematologics Inc: Employment, Equity Ownership. Brodersen: Hematologics Inc: Employment.