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Cryptic Genomic Lesions in Adverse-Risk Acute Myeloid Leukemia Identified by Integrated Whole Genome and Transcriptome Sequencing

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Cryptic Genomic Lesions in Adverse-Risk Acute Myeloid Leukemia Identified by Integrated Whole Genome and Transcriptome Sequencing Leukemia (2020) 34:306–311 https://doi.org/10.1038/s41375-019-0546-1 LETTER Cytogenetics and molecular genetics Cryptic genomic lesions in adverse-risk acute myeloid leukemia identified by integrated whole genome and transcriptome sequencing 1,2,3 2 3 3,4 2 Jaeseung C. Kim ● Philip C. Zuzarte ● Tracy Murphy ● Michelle Chan-Seng-Yue ● Andrew M. K. Brown ● 2 5 1,3,4 1,3 1,2,6 Paul M. Krzyzanowski ● Adam C. Smith ● Faiyaz Notta ● Mark D. Minden ● John D. McPherson Received: 15 March 2019 / Revised: 23 April 2019 / Accepted: 17 June 2019 / Published online: 21 August 2019 © The Author(s) 2019. This article is published with open access To the Editor: treated accordingly [1]. In recent years, advancements in next-generation sequencing and efforts by large genomics Acute myeloid leukemia (AML) is a heterogeneous group studies have led to a classification of 11 AML subgroups of hematologic malignancies characterized by the pro- based on cytogenetic abnormalities as well as mutations in liferation of myeloid cells blocked in their ability to dif- genes, such as NPM1 or CEBPA [1]. 1234567890();,: 1234567890();,: ferentiate. Evaluation by G-banding and fluorescence in situ AML with a complex karyotype, defined by the presence hybridization is an essential aspect in the initial disease of three or more unrelated chromosomal aberrations and the characterization and even now is fundamental in identifying absence of favorable cytogenetic rearrangements, is asso- cytogenetic abnormalities that can inform disease diagnosis, ciated with TP53 mutations and strikingly poor outcome prognosis, and treatment decision [1, 2]. For instance, the [1, 3]. While conventional cytogenetics is still a powerful identification of t(8;21)(q22;q22) or t(15;17)(q22;q12), technique, complex chromosomal aberrations test the limits which generate RUNX1-RUNX1T1 or PML-RARA gene of cytogenetic resolution. Moreover, detection of cryptic fusions, respectively, confers favorable prognosis when genomic lesions, especially gene fusions, by orthogonal methods can lead to adjustment of treatment regimens and/or identification of biomarkers [4]. The frequency at which cryptic gene fusions are present within complex karyotypes is Supplementary information The online version of this article (https:// doi.org/10.1038/s41375-019-0546-1) contains supplementary currently unknown [5]. In this study, we investigated whether material, which is available to authorized users. whole-genome sequencing (WGS) and whole-transcriptome sequencing (RNA-seq) can resolve these complex aberrations * Mark D. Minden in a series of patients where conventional cytogenetics could [email protected] not resolve the driver event. Sequencing was performed on * John D. McPherson [email protected] nine patients with adverse-risk AML; seven cases had com- plex karyotypes and the others had unusual translocation events (Table 1 and Supplementary Table 1). The study was 1 Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada approved by the Research Ethics Board of the University Health Network (REB# 01–0573) and written informed 2 Genomics Technology Program, Ontario Institute for Cancer Research, Toronto, ON, Canada consent was obtained from all patients. WGS and RNA-seq libraries were generated using NEB- 3 Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada Next DNA Library Prep (New England Biolabs) and TruSeq Stranded Total RNA Sample Prep (Illumina), respectively, 4 PanCuRx Translational Research Initiative, Ontario Institute for Cancer Research, Toronto, ON, Canada and were sequenced on the Illumina HiSeq 2000 platform. 5 Bioinformatic tools used here are listed in Supplementary Department of Laboratory Medicine and Pathobiology, University fl of Toronto and the Laboratory Medicine Program, University Table 2. Brie y, we used BWA-MEM for WGS alignment, Health Network, Toronto, ON, Canada CREST for structural variant (SV) calling, and HMMcopy for 6 Biochemistry and Molecular Medicine, University of California, copy number variation (CNV) detection. In parallel, we used Davis, Sacramento, CA, USA STAR for RNA-seq alignment, STAR-Fusion for fusion Cryptic genomic lesions in adverse-risk acute myeloid leukemia identi Table 1 Comparison of cytogenetic and genomic findings from nine patients with adverse-risk AML Case Karyotypea Complex Composite No. of cytogenetic CNVsb Chromosomal rearrangementsb Gene fusions SNVs karyotype karyotype abnormalities Total NGS concordant 1 51, XY, +Y, +der(1;7)(q10;p10), Yes 5 5 Gains: 1q, 6, 7p, 8, 10, Y RUNX1, +6, +8, +10 [10] PTPN11, BCOR 2 45, XX, -7 [17] / 45, X, t(X;8)(p21.2; 2 2 Losses: 7, BCOR t(X;8)(p11.4;q24.13) linked to IDH2 q24.1), -7 [2] / 46, XX[1] BCOR deletion; t(3;15)(p24.3;q14) 3 43~45, X, -Y, t(1;5)(q21;p13), t(1;6) Yes Yes 31 9 Gains: 1p36.33-p35.1, 2p25.3- t(1;5)(q42.3;q12.3); t(3;12) (q26.2; ETV6-MECOM TP53 (q21;p25), -2, add(2)(p21), add(3) p22.3, 2p21-p11.2 (BCL11A), p13.2) linked to gene fusion; t(9;20) (q27), del(3)(q27), add(4)(p16), del(4) 3q26.32-q29, 8q12.1-q23.1 (q34.11;q13.12); der(Y)t(Y;3) (q33), del(5)(q31), add(6)(p25), del(6) (RUNX1T1), 11q13.4-q25 (ETS1), (q11.221;q26.32) linked to 3q gain (q21), -7, add(7)(q36), del(7)(q22), -8, 12p13.33-p13.2, 17q25.1-q25.3 and Yq loss; chr4/7 rearrangements add(8)(q24.3), del(8)(?q23), +del(8) (SRSF2), 19p13.3, 20q13.32- linked to 7q loss; chr2/3/8/11/12/16/ (q22), add(9)(p22), add(9)(q34), add q13.33 17/ 19/22/X rearrangements linked (11)(p15), add(12)(p13), -16, add(16) Losses: 2q11.2-q31.3, 7q21.3- to CNVs (p13.3), -17, der(17)t(11;17)(q13; q36.2, 11p15.5-p13 (WT1), 16q13- p13), add(18)(q23), der(19)t(11;19) q24.3 (CTCF), 17p13.3-p12 (q13;q13.3), -21, add(22)(p11.2), (TP53), 17q11.2-q24.3 (NF1), +4mar [cp20] 19q13.42-q13.43, Yq11.221-q12 4 48-49, XX, +6, +8, +9, t(12;17)(p13; Yes Yes 6 5 Gains: 6, 8, 9 t(11;12;17)(p15.4;p13.3;q11.2) NUP98-KDM5A ASXL1 q11.2), i(17)(q10), inv(18)(q11.2q21) Losses: 17p13.3-p13.1 (TP53), linked to gene fusion (Figure 1) [cp20] 18q21.2 (SMAD4) fi ed by integrated whole genome. 307 5 46, XY, del(6)(q21q23), t(10;11)(p1? Yes Yes 4 3 Losses: ARPP21, BBX, 6q16.1- t(10;11)(p12.3;q14.2) linked to gene PICALM- 2;q21), inv(12)(q15q24.1), del(15) q22.31 (FOXO3), MACC1, 8p12- fusion; t(7;18) linked to MACC1 del; MLLT10; FIP1L1- (q2?4) [cp19] / 46, XY [1] p11.21 (FGFR1), 8q11.21-q11.23, chr12 rearrangements linked to PDGFRA (only in SH2B3, TBX3, MIR5009, SETD4 SH2B3 and TBX3 deletions relapse) 6 46, XX, del(5)(q31), t(11;12)(p13; Yes 3 3 Losses: FHIT, CDH18, 5q22.2q32 chr11/12/17 rearrangements linked NUP98-BPTF WT1, ETV6 p13) [4] / 45, idem, -13 [5] / 46, XX (APC), LACE1/FOXO3, 11p13 to CNVs and gene fusion (Figure 1) [1] (WT1), 11p13-p12, 12p13.2-p12.3 (ETV6), 12p11.1, 12q12, 13, SLC47A1 7 43~48, XY, +?Y, +?Y, der(5)t(5;17) Yes Yes 8 5 Gains: 8, 13q12.11-q12.2 (FLT3) chr1 rearrangements linked to three TP53 (q1?3;q11.2), -7, +8, -12, -13, t Losses: 1p36.12-p36.11 (RPL11), segmental losses; chr2/5/8/12/13/16/ (16;18)(q24;q23), +1~2mar [cp10] 1p35.3-p35.2, 1p22.1-p21.3, 17/18 rearrangements linked to other 2p13.3-p13.1, 2p12-p11.2, 2q32.2- CNVs; inv(7)(q11.22q36.3) q37.3 (SF3B1), 5q11.2-q35.3 (APC, NPM1), 7, 12p13.2-p12.1 (ETV6), 12p12.1-p11.21, 12q12- q24.13, TCF12, 16q21-q22.2 (CTCF), 16q22.3-q24.3, 17p13.3- p11.2 (TP53), 17q11.2-q12 (NF1), 18p11.31, 18q22.3-q23 8 42-45, X, der(X)t(X;3)(q28;q21), der Yes Yes 14 6 Gains: 3q13.33-q29, 8q (MYC), chr1/5/8/9/11/12/16/17/19 TP53 (1)t(1;17)(p35;q21), -3, -5, add(8) 13, 22 rearrangements linked to CNVs (q13), -9, add(11)(q13), add(12)(q24), Losses: 3, 5q31.1, 5q31.2-q35.3 i(13)(q10), del(16)(q23), -17, -18, -19, (NPM1), SMARCA2, 9p13.2-p11.2 +idic(22)(p12), +2r, +mar1 [cp9] / (PAX5), 9q33.1-q33.3, 12p13.33- 46, XX [1] p11.23 (ETV6), 16q21-q24.3 (CTCF), 17p13.2-p11.2 (TP53), 17q11.2-q12 (NF1), 19p13.2- p13.12 (JUNB), BCOR, KDM6A 308 J. C. Kim et al. transcript detection, and GATK for SNV/indel calling from RNA-seq data. By performing low-coverage WGS (mean genome coverage of 11.3×; Supplementary Table 1) of leukemia DNA without matched germline DNA, we aimed to DNMT3A, FLT3, TET2 detect SVs and CNVs in a manner comparable to conven- tional cytogenetics. Furthermore, we compared gene fusions column. and rearrangements detected by CREST with fusion tran- ” scripts detected by STAR-Fusion to cross validate. DNA breakpoints and fusion transcripts were validated by PCR and Gene fusions SNVs RT-PCR, respectively, followed by Sanger sequencing. Analysis of the leukemia genomes concordantly identi- b fied 39 out of 74 (53%) cytogenetic abnormalities annotated NGS concordant “ by visual inspection (Table 1 and Supplementary Table 3). linked to The concordance rates for translocations/inversions, chro- mosomal gains/losses, and subchromosomal gains/losses ATP1A2 were 74%, 54%, and 37%, respectively (Supplementary Table 1).
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