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Блау О., Долник А., Буллингер Л. ОСТРЫЙ МИЕЛОИДНЫЙ ЛЕЙКОЗ - МОЛЕКУЛЯРНАЯ ДИАГНОСТИКА В 2021 ГОДУ
Blau O., Dolnik A., Bullinger L.
Department of Hematology, Oncology, and Tumorimmunology, Campus Virchow Klinikum, Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
ACUTE MYELOID LEUKEMIA - MOLECULAR DIAGNOSTICS IN 2021
Резюме
Острый миелолейкоз (ОМЛ) развивается как клональная экспансия недифференцированных миелоидных предшественников, имеющих соматически приобретенные мутации, которые объясняют биологическую и клиническую сгетерогенность заболевания. За последние десятилетия накопилось много информации о патогенной значимости этих геномных аберраций. В последнее время мо-лекулярно-генетичечкая диагностика широко применяется в обычной клинической практике, что позволяет расширить наше понимание механизмов клональной эволюции лейкоза и динамики заболевания. Новые технологии секвенирования следующего поколения (NGS) позволяют нам выявлять множество субклонов, сосуществующих на различных этапах развития заболевания. Этот обзор содержит краткий обзор возможностей молекулярной диагностики и влияния генетических аномалий на индивидуальные особенности течения заболевания. В настоящее время информация о прогностической значимости молекулярно-генети-ческих аберраций активно используется в клинической практике и формирует современные рекомендации по диагностике ОМЛ. В соответствии с ними, наряду с хорошо изученными молекулярными маркерами NPM1, CEBpA и FLT3, обновленная версия рекомендаций European LeukemiaNet (ELN) также рекомендует скрининг на мутации RUNX1, TP53 и ASXL1. В будущем эти, а также другие аберрации, характерные для ОМЛ, будут иметь решающее значение не только для мониторинга минимальной остаточной болезни (МРБ), но и для выбора адекватных терапевтических персонализированных подходов в лечении ОМЛ.
Abstract
Acute myeloid leukemia (AML) develops as a clonal expansion of undifferentiated myeloid precursors that have somatically acquired mutations, which account for the biological and clinical complexity of the disease. Over the past decades, there has been a growing knowledge on the pathogenic relevance of these genomic aberrations. Recently, molecular genomic diagnostics have begun to be translated into the clinic, and mechanisms of clonal leukemia evolution and disease dynamics are starting to be understood, especially as novel next generation sequencing (NGS) technologies allow us to capture multiple competing clones coexisting at any disease time point. This review provides a short summary of molecular diagnostics and the impact of genomic changes on the individual patient outcome. Molecular diagnostics forms the basis for novel genomic classification schemes that are reproducible and clinically relevant. In accordance, next to the well-established molecular markers NPM1, CEBPA, and FLT3, the updated version of the European LeukemiaNet (ELN) guidelines also recommends the screening for RUNX1, TP53, and ASXL1 mutations. In the future, these as well as other AML associated aberrations will not only be crucial in determining measurable residual disease (MRD), but also in guiding targeted therapeutic approaches and novel genome-wide approaches will lead the way.
Introduction
Since the development of chromosomal banding and conventional karyotyping techniques, genomic aberrations have started to play an important role in the understanding of the pathogenesis of acute myeloid leukemia (AML), and since then have become well established diagnostic and prognostic markers[1, 2]. With the turn of the century, advances
in microarray and next-generation sequencing (NGS)-based "omics" technologies have led to an exponential growth of the knowledge about molecular aberrations underlying AML biology [3, 4], and since several years molecular diagnostics have begun to translate into refined disease classification and improved patient management [5, 6]. In this short review, a brief overview of the heterogeneous genomic landscape
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of AML and its impact on molecular diagnostics is provided, including recent advances in genomics-based AML classification and patient care.
Current State of the Art
Genomic landscape: Following comprehensive studies using microarray technologies, in the 208 AML was also the first tumor genome to be completely
sequenced using the novel NGS technology [7]. Subsequent studies led to the identification of novel recurrent somatic mutations of biologic, prognostic, and therapeutic relevance, and they identified AML as complex and dynamic disease characterized by a high inter- and intra-individual heterogeneity (Figure 1).
Figure 1. Mutational Landscape in AML. Illustration of eight functional categories of genes commonly
mutated in AML. Adopted from reference [1]
(1) mutations in signaling genes, such as the class III tyrosinekinasereceptorgeneFLT3 (ITD,internaltandem duplications; TKD, tyrosine kinase domain mutations) confer proliferative advantage through activated signaling (upper left panel in lilac); (2) mutations in myeloid transcription factors (TFs), such as RUNX1, and/ or transcription factor (TF) fusions by chromosomal rearrangements, such as t(8;21)(q22;q22) [RUNX1-RUNX1T1] lead to transcriptional deregulation and impaired hematopoietic differentiation (center panel in yellow); (3) mutations in the nucleophosmin (NPM1) gene, encoding a multifunctional nucleocytoplasmic shuttling protein, result in the aberrant cytoplasmic localization of NPM1 and NPMl-interacting proteins
(lower left panel in blue); (4) mutations of spliceosome complex genes, such as SRSF2, SF3B1, U2AF1, and ZRSR2, are involved in deregulated RNA processing (lower middle panel in lilac); (5) Cohesion complex gene mutations, such RAD21 and STAG2, might impair accurate chromosome segregation and transcriptional regulation (center panel in purple); mutations of genes involved in the epigenetic homeostasis of cells lead to either (6) deregulation of chromatin modification, such as ASXL1, EZH2, and KMT2A mutations (lower right panel in green) or (7) deregulation of DNA methylation, such as DNMT3A, IDH1, IDH2, and TET2 mutations (upper right panel in purple); and (8) mutations of tumor-suppressor genes, such as TP53, can e.g. lead
to transcriptional deregulation (upper middle panel in orange).
Genome-wide profiling of 200 de novo AML cases within the "The Cancer Genome Atlas (TCGA)" project revealed an average of 13 coding mutations [single nucleotide variations (SNVs), and insertions/ deletions (indels) per adult AML as well as a median of one somatic copy-number variant (e.g., trisomies or monosomies) and an average of less than one genefusion event [3]. While the recurrently mutated genes included known candidates (such as NPM1, FLT3, CEBPA, DNMT3A, IDH1, and IDH2) as well as genes just recently implicated in leukemogenesis (including EZH2, U2AF1, SMC1A, and SMC3), the mutational patterns are non-random of co-occurrence and mutual exclusivity. Especially NPM1, CEPBA, and RUNX1 mutations were mutually exclusive of transcription factor fusions, thereby indicating that these aberrations might be leukemia-initiating events similar to the fusion genes.
Clonal evolution: Analysis of the variant allele frequency (VAF) demonstrated that over half of the TCGA cases exhibited at least one subclone in addition to a founding leukemia clone (the clone showing the highest VAF values) [3]. Together with other studies, these data support a clonal evolution concept in which epigenetic regulator mutations (e.g. DNMT3A, TET2, and ASXL1 mutations) or splicing factor gene mutations (e.g. SF3B1, and SRSF2 mutations) occur as early founder events in pre-leukemic progenitor cells prior to transforming leukemogenic events (e.g. NPM1 or signaling molecule mutations). In accordance, recurrent
mutations in epigenetic regulators and splicing factor genes can be found in the blood of mainly elderly patients [8, 9], and the term "clonal hematopoiesis of indeterminate potential" (CHIP) was proposed to describe the presence of leukemia-associated somatic mutations in blood or bone marrow in the absence of conventional diagnostic criteria for a hematologic malignancy [10]. While the transformation rate of CHIP into a hematologic malignancy is 0.5-1% per year, in the future the role of persisting CHIP following leukemia treatment will have to be better understood by monitoring of measurable residual disease (MRD) for both pre-leukemic and leukemic markers.
Molecular diagnostics: Until today, conventional cytogenetic analysis remains mandatory for the AML workup, although molecular testing by reverse transcriptase-polymerase chain reaction (RT-PCR) for recurring rearrangements can be useful if cytogenetic analysis fails and in the future whole genome sequencing approaches might fill in (see below). Molecular genetic diagnostics, as recommended by the European LeukemiaNet (ELN) [6], should comprise at least screening for (i) disease defining mutations in NPM1, CEBPA, and RUNX1 genes; (ii) prognostic and targetable mutations in FLT3, both tyrosine kinase domain mutations (at codons D835 and I836) mutations and internal tandem duplications (ITDs) (including data on the mutant-to-wild-type allelic ratio); and (iii) mutations in TP53 and ASXL1 that have consistently been associated with poor prognosis (Table 1).
Table 1.
2017 European LeukemiaNet (ELN) risk stratification by geneticsa
Risk Categoryb Genetic Lesion
Favorable t(8;21)(q22;q22.1); RUNX1-RUNX1T1 inv(16)(p13.1q22) or t(16;16)(p13.1;q22); CBFB-MYH11 Mutated NPM1 without FLT3-ITD or with FLT3-ITDlow(c) Biallelic mutated CEBPA
Intermediate Mutated NPM1 and FLT3-ITDhigh(c) Wild type NPM1 without FLT3-ITD or with FLT3-ITDlow(c) (w/o adverse-risk gene mutations) t(9;11)(p21.3;q23.3); MLLT3-KMT2Ad Cytogenetic abnormalities not classified as favorable or adverse
Adverse t(6;9)(p23;q34.1); DEK-NUP214 t(v;11q23.3); KMT2A rearranged t(9;22)(q34.1;q11.2); BCR-ABL1 inv(3)(q21.3q26.2) or t(3;3)(q21.3;q26.2); GATA2, MECOM(EVI1) -5 or del(5q); -7; -17/abn(17p) Complex karyotyped monosomal karyotypef Wild type NPM1 and FLT3-ITDhigh(c) Mutated RUNX1g Mutated ASXL1g Mutated TP53h
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Adopted from reference (6).
a Frequencies, response rates and outcome measures should be reported by risk category, and, if sufficient
numbers are available, by specific genetic lesions indicated. b Prognostic impact of a marker is treatment-dependent and may change with new therapies. c Low, low allelic ratio (<0.5); high, high allelic ratio (>0.5); semi-quantitative assessment of FLT3-ITD allelic ratio (using DNA fragment analysis) is determined as ratio of the area under the curve (AUC) "FLT3-ITD" divided by AUC "FLT3-wild type"; recent studies indicate that AML with NPM1 mutation and FLT3-ITD low allelic ratio may also have a more favorable prognosis and patients should not routinely be assigned to allogeneic hematopoietic-cell transplantation. d The presence of t(9;11)(p21.3;q23.3) takes precedence over rare, concurrent adverse-risk gene mutations. e Three or more unrelated chromosome abnormalities in the absence of one of the WHO-designated recurring translocations or inversions, i.e., t(8;21), inv(16) or t(16;16), t(9;11), t(v;11)(v;q23.3), t(6;9), inv(3) or t(3;3); AML with BCR-ABL1.
f Defined by the presence of one single monosomy (excluding loss of X or Y) in association with at least one
additional monosomy or structural chromosome abnormality (excluding core-binding factor AML). g These markers should not be used as an adverse prognostic marker if they co-occur with favorable-risk AML subtypes.
h TP53 mutations are significantly associated with AML with complex and monosomal karyotype.
While it is time consuming and cost ineffective to capture these aberrations by conventional sequencing strategies, the list of molecular markers informing clinical practice is growing and testing has started to be replaced by NGS-based gene panel diagnostics in many laboratories, which in daily routine have become the preferred methodology [11]. In the future, it will be crucial to invest in flexible platforms and to develop diagnostic tools that can simultaneously test for both gene mutations and gene rearrangements [12, 13].
Genomic classification: Leukemia-associated chromosomal translocations and inversions opened the avenue towards the genetic AML classification reflected in the currently updated World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia [5] however, during recent years NGS studies have also been informing disease classification [3, 4, 14]. Beyond currently defined classes (such as the balanced rearrangements, AML with mutated NPM1, or biallelic mutated CEBPA), three more heterogeneous classes emerged, i.e. "AML with mutated chromatin, RNA-splicing genes, or both", "AML with TP53 mutations, chromosomal aneuploidy, or both", and "AML with IDH2R172 mutation" (without other class-defining lesions). Using this classification scheme, at least 80% of AML could ambiguously be categorized in a single group based upon the underlying genetic abnormalities [4].
Genomics informed patient care: Recent advanced proved also that novel genetic information can be successfully applied to inform clinical practice. For example, a large knowledge bank of matched genomic-clinical AML data could be devised to accurately predict likelihoods of remission, relapse and mortality with findings being validated on independent TCGA data [15]. Future models based on increased patient numbers will allow to further reduce the error rate
of such personalized treatment predictions, and European initiatives like HARMONY (Healthcare Alliance for Resourceful Medicines Offensive against Neoplasms in Hematology) are currently capturing, integrating, and harmonizing patient data from large AML cohorts to gain valuable novel insights (https://www.harmony-alliance.eu/). Similarly, genomic knowledge does now also facilitate follow-up monitoring of MRD, and highly sensitive digital PCR as well as targeted ultra-deep NGS approaches are valuable novel tools adding to quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR) and multiparameter flow cytometry (MFC) methods. The NGS-based identification of molecular markers in almost 100% of diagnostic AML cases provides a prerequisite for comprehensive and individualized MRD assessment to identify patients at high relapse risk at early time points and to detect persistent pre-leukemic hematopoiesis [16, 17]. Finally, genomics knowledge will allow us to better guide the use of novel drugs such as protein kinase inhibitors, epigenetic modulators, immune checkpoint inhibitors and cellular immunotherapies [2, 6]. However, selective inhibition may only address distinct leukemia subclones. Thus, future molecularly targeted treatment designs will have to take clonal relationships into account and treatment strategies should be adjusted based on longitudinal clonal monitoring.
Future Perspectives
Given a growing list of disease-relevant genes in AML, NGS-based gene panel diagnostics have started to enter our daily clinical routine. Today, rapid technical NGS advances allow for more accurate MRD assessment and start to offer the possibility to capture leukemia heterogeneity at the single cell level at unprecedented accuracy both at the genomic and transcriptomic level [18, 19]. While current strategies
can already be used for genome-wide unbiased tests at high quality based on which individualized treatment approaches can be further advanced [13], further development of innovative long-read sequencing approaches, such as Oxford Nanopore Technology (ONT), will offer the possibility to use affordable benchtop sequencer for genome-wide transcriptome and whole genome sequencing approaches that can provide real-world results at low consumable costs that can be scaled to individual sample input [20].
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Lars Bullinger
Augustenburger Platz 1, 13353 Berlin, Germany.
Phone: +49-30-450-553192, Fax: +49-30-450-553987,
E-mail: lars.bullinger@charite.de
