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University of Groningen the Aberrant Transcriptional Program of Myeloid University of Groningen The aberrant transcriptional program of myeloid malignancies with poor prognosis Gerritsen, Myléne DOI: 10.33612/diss.113503008 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2020 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Gerritsen, M. (2020). The aberrant transcriptional program of myeloid malignancies with poor prognosis: the effects of RUNX1 and TP53 mutations in AML. Rijksuniversiteit Groningen. https://doi.org/10.33612/diss.113503008 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 06-10-2021 5 137853-gerritsen-layout.indd 102 14/01/2020 14:13 Ring sideroblasts in AML are associated with adverse risk characteristics and have a distinct gene expression pattern G. Berger, M. Gerritsen, G. Yi, T.N. Koorenhof-Scheele, L.I. Kroeze, M. Stevens-Kroef, K. Yoshida, Y. Shiraishi, E. van den Berg, H. Schepers, G. Huls, A.B. Mulder, S. Ogawa, J.H.A. Martens, J.H. Jansen, E. Vellenga This research was originally published in Blood Advances. © the American Society of Hematology. 137853-gerritsen-layout.indd 103 14/01/2020 14:13 Chapter 5 ABSTRACT Ring sideroblasts (RS) emerge as result of aberrant erythroid differentiation leading to excessive mitochondrial iron accumulation, a characteristic feature for myelodysplastic syndromes (MDS) with mutations in the spliceosome gene SF3B1. However, RS can also be observed in patients diagnosed with acute myeloid leukemia (AML). The objective of this study was to characterize RS in AML patients. Clinically, RS-AML is enriched for ELN adverse-risk (55%). In line with this finding, 35% of all cases had complex cytogenetic aberrancies and TP53 was most recurrently mutated in this cohort (37%), followed by DNMT3A (26%), RUNX1 (25%), TET2 (20%) and ASXL1 (19%). In contrast to RS-MDS, the incidence of SF3B1 mutations was low (8%). Whole exome sequencing and SNP array analysis on a subset of patients did not uncover one single genetic defect underlying the RS phenotype. Shared genetic defects between erythroblasts and total mononuclear cell fraction indicate common ancestry for the erythroid lineage and the myeloid blast cells in RS-AML patients. RNA sequencing analysis on CD34+ AML cells revealed differential gene expression between RS-AML and non RS-AML cases, including genes involved in megakaryocyte and erythroid differentiation. Furthermore, several heme metabolism-related genes were found to be up-regulated in RS- CD34+ AML cells, as was observed in SF3B1mut MDS. These results demonstrate that although the genetic background of RS-AML differs from that of RS-MDS, certain downstream effector pathways are in common. 104 137853-gerritsen-layout.indd 104 14/01/2020 14:13 Ring sideroblasts in AML INTRODUCTION Ring sideroblasts (RS) are erythroid precursor cells that accumulate excessive mitochondrial iron and can be observed in bone marrow smears associated with multiple medical conditions1. Presence of RS is a characteristic feature in myelodysplastic syndrome (MDS) subtypes, including MDS with single lineage dysplasia (MDS-RS-SLD), multilineage dysplasia (MDS-RS-MLD) and in combination with the presence of thrombocytosis (MDS/MPN-RS-T)2. Non-malignant causes of RS include several drugs, toxins, alcohol, copper deficiency and congenital sideroblastic anemia3. This latter group comprises conditions caused by inborn defects in genes that operate in several mitochondrial pathways, including ALAS2, ABCB7, SLC25A38 and HSPA94–7. In MDS, the RS phenotype is strongly correlated with mutations in splicing factor 3B subunit 1 (SF3B1), with an incidence higher than 80%8–12. SF3B1 mutations are usually observed in low-risk MDS, which is characterized by a stable clinical course and a low risk of leukemic transformation8,13. As a core component of the U2 small nuclear ribonucleoprotein particle (snRNP), SF3B1 is essential for pre- RNA splicing14. The molecular mechanism by which SF3B1 mutations result in RS formation is 5 not yet fully understood. A proposed mechanism is that specific patterns of missplicing result in altered expression of genes that are essential for correct programming of erythropoiesis15–17. The relationship between genetic defects in SF3B1 and the RS phenotype is not one-to-one; in 10- 20% of the MDS-RS patients no mutation in the SF3B1 gene is detected8–12. Moreover, RS can also be present in a subset of AML patients, while SF3B1 mutations are infrequent in this disease10,18,19. Besides SF3B1, the only other correlation between a gene defect and the RS phenotype was described for PRPF8, for which mutations are reported in ~3% of myeloid neoplasms, including MDS, MDS/MPN and (s)AML20. In the present study we determined the prevalence of RS in various ontogenic AML subtypes and the association of the RS phenotype in AML with adverse risk characteristics. To identify the landscape of genomic defects that underlies the RS phenotype in AML, we performed whole exome sequencing, targeted sequencing and SNP-array analysis. Finally, to identify differential expression of genes associated with the RS phenotype in AML, we performed RNA sequencing on CD34+-selected AML cells. MATERIALS AND METHODS Patients and data collection For this study, we collected data from 126 AML and high-risk MDS (≥10% bone marrow blasts) patients who were diagnosed between January 2000 and April 2018 at the University Medical Center Groningen. The inclusion criterion was the presence of ring sideroblasts in the diagnostic bone-marrow smear. Patients with previously reported MDS-RS were excluded. Diagnosis and risk classification was revised based upon World Health Organization classification (2016)2 and European Leukemia Net (ELN) recommendations (2017)21. Bone marrow (BM) and/or peripheral blood (PB) from patients were biobanked after informed consent for investigational use. The 105 137853-gerritsen-layout.indd 105 14/01/2020 14:13 Chapter 5 study was conducted in accordance with the Declaration of Helsinki and institutional guidelines and regulations. Morphological and cytogenetic analyses were based on standard procedures. On iron-stained aspirate smears, 400 red blood cell precursors were counted. Ring sideroblasts were defined by ≥ 5 iron granules encircling one third or more of the nucleus. The ring sideroblasts percentage was determined as percentage of the total red blood cell precursor cells. Sorting of cell fractions The mononuclear cell (MNC) fraction from BM and/or PB was obtained by density gradient centrifugation using lymphoprep (PAA, Cölbe, Germany) according to standard procedures. Analysis and sorting of various cell fractions was performed on MoFlo XDP or Astrios (Beckman Coulter). A list of antibodies can be found in the Supplementary Methods. DNA isolation and amplification Genomic DNA from various cell fractions was extracted with the NucleoSpin Tissue kit (Macherey- Nagel, Düren, Germany) according to the manufacturer’s instructions. In case of insufficient yield, a maximum of 70 ng DNA was amplified using the Qiagen REPLI-g kit (Qiagen, Venlo, the Netherlands), according to the manufacturer’s protocol. Targeted deep sequencing using a myeloid gene panel Targeted sequencing of DNA derived from BM or PB samples obtained at diagnosis was carried out using the myeloid TruSight sequencing panel (Illumina, San Diego, CA, USA) or by in- house sequencing panel containing 27 genes (Supplementary Table 1). Library preparation was performed according to the manufacturer’s protocol (Illumina). Aligning and filtering of sequencing data was performed using NextGENe version 2.3.4.2 (SoftGenetics, Pennsylvania, US). Cartagenia Bench Lab NGS (Agilent, Santa Clara, CA, USA) was used for analysis of the resulting vcf files. Sequencing artifacts were excluded using a threshold of 5%. A minimal variant read depth of 20 reads was set as criterion. Variants that frequently occur in the general healthy population (>2% 1000 Genome Phase 1, ESP6500 and dbSNP, and >5% Genome of the Netherlands) were excluded from further analysis. Microarray-based genomic profiling Microarray-based genomic profiling on MNC and erythroblast fractions was performed on a CytoScan HD array platform (Affymetrix, Inc., Santa Clara, CA, USA) in agreement with the manufacturer’s reference. Data analysis was performed using Chromosome Analysis Suite software package (Affymetrix) using annotations of reference genome build GRCh37 (hg19). Comprehensive analysis and interpretation
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