Portal de Periódicos da CAPES

Clinical Validation and Diagnostic Utility of Optical Genome Mapping for Enhanced Cytogenomic Analysis of Hematological Neoplasms

2022; Elsevier BV; Volume: 24; Issue: 12 Linguagem: Inglês

10.1016/j.jmoldx.2022.09.009

1943-7811

Nikhil Sahajpal, Ashis K. Mondal, Tatiana Tvrdik, Jennifer Hauenstein, Huidong Shi, Kristin K. Deeb, Debra Saxe, Alex Hastie, Alka Chaubey, Natasha M. Savage, Vamsi Kota, Ravindra Kolhe,

Lymphoma Diagnosis and Treatment

The current standard-of-care cytogenetic techniques for the analysis of hematological malignancies include karyotyping, fluorescence in situ hybridization, and chromosomal microarray, which are labor intensive and time and cost prohibitive, and they often do not reveal the genetic complexity of the tumor, demonstrating the need for alternative technology for better characterization of these tumors. Herein, we report the results from our clinical validation study and demonstrate the utility of optical genome mapping (OGM), evaluated using 92 sample runs (including replicates) that included 69 well-characterized unique samples (59 hematological neoplasms and 10 controls). The technical performance (quality control metrics) resulted in 100% first-pass rate, with analytical performance (concordance) showing a sensitivity of 98.7%, a specificity of 100%, and an accuracy of 99.2%. OGM demonstrated robust technical, analytical performance, and interrun, intrarun, and interinstrument reproducibility. The limit of detection was determined to be at 5% allele fraction for aneuploidy, translocation, interstitial deletion, and duplication. OGM identified several additional structural variations, revealing the genomic architecture in these neoplasms that provides an opportunity for better tumor classification, prognostication, risk stratification, and therapy selection. Overall, OGM has outperformed the standard-of-care tests in this study and demonstrated its potential as a first-tier cytogenomic test for hematologic malignancies. The current standard-of-care cytogenetic techniques for the analysis of hematological malignancies include karyotyping, fluorescence in situ hybridization, and chromosomal microarray, which are labor intensive and time and cost prohibitive, and they often do not reveal the genetic complexity of the tumor, demonstrating the need for alternative technology for better characterization of these tumors. Herein, we report the results from our clinical validation study and demonstrate the utility of optical genome mapping (OGM), evaluated using 92 sample runs (including replicates) that included 69 well-characterized unique samples (59 hematological neoplasms and 10 controls). The technical performance (quality control metrics) resulted in 100% first-pass rate, with analytical performance (concordance) showing a sensitivity of 98.7%, a specificity of 100%, and an accuracy of 99.2%. OGM demonstrated robust technical, analytical performance, and interrun, intrarun, and interinstrument reproducibility. The limit of detection was determined to be at 5% allele fraction for aneuploidy, translocation, interstitial deletion, and duplication. OGM identified several additional structural variations, revealing the genomic architecture in these neoplasms that provides an opportunity for better tumor classification, prognostication, risk stratification, and therapy selection. Overall, OGM has outperformed the standard-of-care tests in this study and demonstrated its potential as a first-tier cytogenomic test for hematologic malignancies. The World Health Organization classifies hematological neoplasms into myeloid and lymphoid subtypes, several of which are defined by the presence of specific genetic abnormalities.1Hasserjian R.P. Le Beau M.M. List A.F. Thiele J. WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues.ed 4. IARC, Lyon, France2017Google Scholar The genetic diagnostic workup in routine clinical use includes both molecular and cytogenetic analysis to investigate single-nucleotide variants, small insertions and deletions, and structural variations (SVs).2Rack K.A. van den Berg E. Haferlach C. Beverloo H.B. Costa D. Espinet B. Foot N. Jeffries S. Martin K. O'Connor S. Schoumans J. Talley P. Telford N. Stioui S. Zemanova Z. Hastings R.J. European recommendations and quality assurance for cytogenomic analysis of haematological neoplasms.Leukemia. 2019; 33: 1851-1867Crossref PubMed Scopus (79) Google Scholar, 3Tallman M.S. Wang E.S. Altman J.K. Appelbaum F.R. Bhatt V.R. Bixby D. Coutre S.E. De Lima M. Fathi A.T. Fiorella M. Foran J.M. Hall A.C. Jacoby M. Lancet J. LeBlanc T.W. Mannis G. Marcucci G. Martin M.G. Mims A. O'Donnell M.R. Olin R. Peker D. Perl A. Pollyea D.A. Pratz K. Prebet T. Ravandi F. Shami P.J. Stone R.M. Strickland S.A. Wieduwilt M. Gregory K.M. .O.C.N. Hammond L. Ogba N. Acute myeloid leukemia, version 3.2019, NCCN clinical practice guidelines in oncology.J Natl Compr Canc Netw. 2019; 17: 721-749Crossref PubMed Scopus (295) Google Scholar, 4Döhner H. Estey E. Grimwade D. Amadori S. Appelbaum F.R. Büchner T. Dombret H. Ebert B.L. Fenaux P. Larson R.A. Levine R.L. Lo-Coco F. Naoe T. Niederwieser D. Ossenkoppele G.J. Sanz M. Sierra J. Tallman M.S. Tien H.F. Wei A.H. Löwenberg B. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel.Blood. 2017; 129: 424-447Crossref PubMed Scopus (3838) Google Scholar, 5Hallek M. Cheson B.D. Catovsky D. Caligaris-Cappio F. Dighiero G. Döhner H. Hillmen P. Keating M. Montserrat E. Chiorazzi N. Stilgenbauer S. Rai K.R. Byrd J.C. Eichhorst B. O'Brien S. Robak T. Seymour J.F. Kipps T.J. iwCLL guidelines for diagnosis, indications for treatment, response assessment, and supportive management of CLL.Blood. 2018; 131: 2745-2760Crossref PubMed Scopus (925) Google Scholar, 6Sonneveld P. Avet-Loiseau H. Lonial S. Usmani S. Siegel D. Anderson K.C. Chng W.J. Moreau P. Attal M. Kyle R.A. Caers J. Hillengass J. San Miguel J. van de Donk N.W. Einsele H. Bladé J. Durie B.G. Goldschmidt H. Mateos M.V. Palumbo A. Orlowski R. Treatment of multiple myeloma with high-risk cytogenetics: a consensus of the International Myeloma Working Group.Blood. 2016; 127: 2955-2962Crossref PubMed Scopus (616) Google Scholar, 7Aguilera-Diaz A. Vazquez I. Ariceta B. Mañú A. Blasco-Iturri Z. Palomino-Echeverría S. Larrayoz M.J. García-Sanz R. Prieto-Conde M.I. del Carmen Chillón M. Alfonso-Pierola A. Assessment of the clinical utility of four NGS panels in myeloid malignancies: suggestions for NGS panel choice or design.PLoS One. 2020; 15: e0227986Crossref PubMed Scopus (27) Google Scholar In the past decade, significant progress has been made in the molecular profiling of these tumors with the use of next-generation sequencing technology, which has replaced single-variant/gene analysis with gene panels and even whole-exome sequencing.8Sahajpal N.S. Mondal A.K. Ananth S. Njau A. Ahluwalia P. Jones K. Ahluwalia M. Okechukwu N. Savage N.M. Kota V. Rojiani A.M. Kolhe R. Clinical performance and utility of a comprehensive next-generation sequencing DNA panel for the simultaneous analysis of variants, TMB and MSI for myeloid neoplasms.PLoS One. 2020; 15: e0240976Crossref PubMed Scopus (7) Google Scholar,9Hansen M.C. Haferlach T. Nyvold C.G. A decade with whole exome sequencing in haematology.Br J Haematol. 2020; 188: 367-382Crossref PubMed Scopus (21) Google Scholar However, recurrent chromosomal abnormalities are used in many hematologic malignancies to assist in diagnosis, prognosis, and therapy selection, as recommended by the professional guidelines.3Tallman M.S. Wang E.S. Altman J.K. Appelbaum F.R. Bhatt V.R. Bixby D. Coutre S.E. De Lima M. Fathi A.T. Fiorella M. Foran J.M. Hall A.C. Jacoby M. Lancet J. LeBlanc T.W. Mannis G. Marcucci G. Martin M.G. Mims A. O'Donnell M.R. Olin R. Peker D. Perl A. Pollyea D.A. Pratz K. Prebet T. Ravandi F. Shami P.J. Stone R.M. Strickland S.A. Wieduwilt M. Gregory K.M. .O.C.N. Hammond L. Ogba N. Acute myeloid leukemia, version 3.2019, NCCN clinical practice guidelines in oncology.J Natl Compr Canc Netw. 2019; 17: 721-749Crossref PubMed Scopus (295) Google Scholar, 4Döhner H. Estey E. Grimwade D. Amadori S. Appelbaum F.R. Büchner T. Dombret H. Ebert B.L. Fenaux P. Larson R.A. Levine R.L. Lo-Coco F. Naoe T. Niederwieser D. Ossenkoppele G.J. Sanz M. Sierra J. Tallman M.S. Tien H.F. Wei A.H. Löwenberg B. Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel.Blood. 2017; 129: 424-447Crossref PubMed Scopus (3838) Google Scholar, 5Hallek M. Cheson B.D. Catovsky D. Caligaris-Cappio F. Dighiero G. Döhner H. Hillmen P. Keating M. Montserrat E. Chiorazzi N. Stilgenbauer S. Rai K.R. Byrd J.C. Eichhorst B. O'Brien S. Robak T. Seymour J.F. Kipps T.J. iwCLL guidelines for diagnosis, indications for treatment, response assessment, and supportive management of CLL.Blood. 2018; 131: 2745-2760Crossref PubMed Scopus (925) Google Scholar, 6Sonneveld P. Avet-Loiseau H. Lonial S. Usmani S. Siegel D. Anderson K.C. Chng W.J. Moreau P. Attal M. Kyle R.A. Caers J. Hillengass J. San Miguel J. van de Donk N.W. Einsele H. Bladé J. Durie B.G. Goldschmidt H. Mateos M.V. Palumbo A. Orlowski R. Treatment of multiple myeloma with high-risk cytogenetics: a consensus of the International Myeloma Working Group.Blood. 2016; 127: 2955-2962Crossref PubMed Scopus (616) Google Scholar, 7Aguilera-Diaz A. Vazquez I. Ariceta B. Mañú A. Blasco-Iturri Z. Palomino-Echeverría S. Larrayoz M.J. García-Sanz R. Prieto-Conde M.I. del Carmen Chillón M. Alfonso-Pierola A. Assessment of the clinical utility of four NGS panels in myeloid malignancies: suggestions for NGS panel choice or design.PLoS One. 2020; 15: e0227986Crossref PubMed Scopus (27) Google Scholar,10Mikhail F.M. Heerema N.A. Rao K.W. Burnside R.D. Cherry A.M. Cooley L.D. Section E6.1- 6.4 of the ACMG technical standards and guidelines: chromosome studies of neoplastic blood and bone marrow-acquired chromosomal abnormalities.Genet Med. 2016; 18: 635-642Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar The cytogenetic analysis currently relies on a combination of traditional techniques, which are low resolution (karyotyping), are targeted, and require prior knowledge [fluorescence in situ hybridization (FISH)], or cannot detect balanced SVs and orientation of duplicated segments of the genome (chromosomal microarrays). As a result, additional clinically relevant information remains intractable with these current standard-of-care (SOC) techniques. First, although hematologic neoplasms frequently harbor acquired balanced translocations,11Aplan P.D. Causes of oncogenic chromosomal translocation.Trends Genet. 2006; 22: 46-55Abstract Full Text Full Text PDF PubMed Scopus (147) Google Scholar,12Wang Y. Wu N. Liu D. Jin Y. Recurrent fusion genes in leukemia: an attractive target for diagnosis and treatment.Curr Genom. 2017; 18: 1087-1094Crossref Scopus (29) Google Scholar the discovery of new gene fusions has not been possible because of the lack of gene-level resolution with karyotyping. Second, the location of insertion and orientation of submicroscopic duplications remain beyond the purview of these technologies, which might result in incorrect interpretation of the observed SV. Third, these techniques are not able to resolve complex rearrangements to reveal the chromosomal structure that might add additional clinically relevant information. Considering these limitations with the current cytogenetic analysis, there has been a need for a technology that can detect all classes of SVs with a higher resolution in a single assay. The utility of whole-genome sequencing as a complete solution for genetic analysis was recently tested, but is met with complex bioinformatics and sophisticated instrumentation, and remained limited to the detection of recurrent SVs (selected translocations) and karyotype-level copy number variations (CNVs) (>5-megabase resolution); it offers limited additional benefits over the conventional cytogenetic methods.13Duncavage E.J. Schroeder M.C. O'Laughlin M. Wilson R. MacMillan S. Bohannon A. Kruchowski S. Garza J. Du F. Hughes A.E.O. Robinson J. Hughes E. Heath S.E. Baty J.D. Neidich J. Christopher M.J. Jacoby M.A. Uy G.L. Fulton R.S. Miller C.A. Payton J.E. Link D.C. Walter M.J. Westervelt P. DiPersio J.F. Ley T.J. Spencer D.H. Genome sequencing as an alternative to cytogenetic analysis in myeloid cancers.N Engl J Med. 2021; 384: 924-935Crossref PubMed Scopus (119) Google Scholar Optical genome mapping (OGM) has emerged as a next-generation cytogenomic technology that can detect all classes of SVs at a higher resolution than the SOC techniques. Recently, the technology has gained enormous traction and has been evaluated in several settings, including prenatal settings,14Sahajpal N.S. Barseghyan H. Kolhe R. Hastie A. Chaubey A. Optical genome mapping as a next-generation cytogenomic tool for detection of structural and copy number variations for prenatal genomic analyses.Genes (Basel). 2021; 12: 398Crossref PubMed Scopus (39) Google Scholar postnatal settings,15Mantere T. Neveling K. Pebrel-Richard C. Benoist M. van der Zande G. Kater-Baats E. Baatout I. van Beek R. Yammine T. Oorsprong M. Hsoumi F. Olde-Weghuis D. Majdali W. Vermeulen S. Pauper M. Lebbar A. Stevens-Kroef M. Sanlaville D. Dupont J.M. Smeets D. Hoischen A. Schluth-Bolard C. El Khattabi L. Optical genome mapping enables constitutional chromosomal aberration detection.Am J Hum Genet. 2021; 108: 1409-1422Abstract Full Text Full Text PDF PubMed Scopus (68) Google Scholar hematological neoplasms,16Neveling K. Mantere T. Vermeulen S. Oorsprong M. van Beek R. Kater-Baats E. Pauper M. van der Zande G. Smeets D. Weghuis D.O. Stevens-Kroef M.J.P.L. Hoischen A. Next-generation cytogenetics: comprehensive assessment of 52 hematological malignancy genomes by optical genome mapping.Am J Hum Genet. 2021; 108: 1423-1435Abstract Full Text Full Text PDF PubMed Scopus (52) Google Scholar and solid tumors,17Goldrich D.Y. LaBarge B. Chartrand S. Zhang L. Sadowski H.B. Zhang Y. Pham K. Way H. Lai C.J. Pang A.W.C. Clifford B. Hastie A.R. Oldakowski M. Goldenberg D. Broach J.R. Identification of somatic structural variants in solid tumors by optical genome mapping.J Pers Med. 2021; 11: 142Crossref PubMed Scopus (14) Google Scholar demonstrating 100% clinical concordance with traditional cytogenetic analysis. However, the literature lacks any clinical validation studies, which are critical for comprehensive evaluation and clinical implementation. In this study, we report the results from our clinical validation (in a Clinical Laboratory Improvement Amendments setting) of OGM for hematological neoplasms in comparison to the SOC methods (karyotyping and FISH), and report robust technical and analytical performance, as well as clinical utility of this platform for hematological malignancies. This retrospective validation study included 92 analyses (including replicates), representing 69 unique and well-characterized samples that were received in our clinical laboratory for cytogenetic analysis with karyotyping and/or FISH testing. These were composed of 59 hematological neoplasms that included adult acute myeloid leukemia (AML; n = 18), chronic lymphocytic leukemia (CLL; n = 15), myelodysplastic syndrome (MDS; n = 12), plasma cell myeloma (n = 6), lymphoma (n = 3), myeloproliferative disorders/myeloproliferative neoplasms (n = 3), and chronic myeloid leukemia (n = 2). In addition, 10 morphologically normal and cytogenetically negative samples were also analyzed to evaluate true-negative/false-positive rates and calculate performance metrics (Figure 1A). The OGM data were analyzed in a blinded manner by the analyst (N.S.S.), which was then compared for concordance with SOC methods by the board-certified laboratory director (R.K.). The SVs that were concordant were grouped under concordant calls, and all other reported SVs were considered as additional findings. These 69 samples were composed of bone marrow aspirate (n = 45), peripheral blood (n = 16), CD-138 isolated cells (n = 5), and lymph node–single-cell suspensions (n = 3), which were processed for OGM with the technologist blinded to previous SOC results (Figure 1B). Of these 69 samples, 64 were stored at –80°C within 4 days after sample collection (as recommended by the manufacturer), whereas 6 to 8 days had elapsed for 3 samples, and 18 to 20 days had elapsed for 2 samples (Figure 1C). The study was performed under Institutional Review Board A: BIOMEDICAL I (Institutional Review Board registration number 00000150), Augusta University (Institutional Review Board number 611298). On the basis of the Institutional Review Board approval, the need for consent was waived; all protected health information was removed, and all data were anonymized before accessing the clinical validation study. Ultra-high-molecular-weight DNA was isolated, labeled, and processed for analysis on the Bionano Genomics Saphyr platform following the manufacturer's protocols (Bionano Genomics Inc., San Diego, CA). Briefly, a frozen bone marrow aspirate aliquot (650 μL) was thawed, and cells were counted using HemoCue (HemoCue Holding AB, Ängelholm, Sweden). Subsequently, a bone marrow aspirate aliquot composed of approximately 1.5 million nucleated white blood cells was centrifuged, and the cells were digested with proteinase K and lysed using Lysis and Binding Buffer. DNA was precipitated on a nanobind magnetic disk using isopropanol and washed using buffers (buffers A and B). The ultra-high-molecular-weight–bound DNA was suspended in elution buffer and quantified using Qubit broad-range double-stranded DNA assay kits (ThermoFisher Scientific, San Francisco, CA). DNA was labeled following manufacturer's protocols (Bionano Genomics Inc.) in which 750 ng of purified ultra-high-molecular-weight DNA was labeled at the sequence-specific motif with direct labelling (DL)-green fluorophores using Direct Labeling Enzyme 1 reactions. Following the labeling reaction, the Direct Labeling Enzyme 1 enzyme was digested using proteinase K and the DL-green was removed in two steps using an adsorption membrane in a microtiter plate. Finally, the DNA backbone was stained blue using DNA stain and quantified using Qubit high-sensitivity double-stranded DNA assay kits. Labeled DNA was loaded onto flow cells of Saphyr chips for optical imaging. The fluorescently labeled DNA molecules were imaged on the Saphyr instrument after the labeled DNA molecules were electrophoretically linearized in the nanochannel arrays. Analytical quality control (QC) targets were set to achieve >400× effective coverage of the genome (>200× deemed analyzable), >70% mapping rate, 13 to 17 label density (labels per 100 kbp), and >230 kbp N50 (of molecules >150 kbp). Genome analysis was performed using the rare variant pipeline included in the Bionano Access version 1.6 or version 1.5/Bionano Solve version 3.6 or version 3.5 software for all the samples. Briefly, molecules of a given sample data set were directly aligned to GRCh38, reference human genome assembly, and SVs (insertions, duplications, deletions, inversions, and translocations) were detected on the basis of the differences in the alignment of labels between the sample and the reference assembly. In addition, a coverage-based algorithm enabled the detection of large CNVs and aneuploidies. SVs and CNVs generated by the rare variant pipeline were then annotated with known canonical gene sets extracted from the reference genome assembly. For data analysis, the variants were filtered using the following criteria for the following: i) The manufacturer's recommended confidence scores version 1.6 were applied: insertion, 0; deletion, 0; inversion, 0.01; duplication, –1; translocation, 0; and copy number, 0.99 (low stringency, filter set to 0). ii) The GRCh38 SV mask filter that hides any SVs in difficult-to-map regions was turned off for analysis. iii) To narrow the number of variants to be analyzed, we filtered out polymorphic variants [ie, those that appeared in >1% of an internal OGM control database (n > 300)]. iv) SVs impacting a gene/loci listed in the National Comprehensive Cancer Network/National Health Service/World Health Organization guidelines (https://www.nccn.org/guidelines/recently-published-guidelines, https://www.england.nhs.uk/publication/national-genomic-test-directories, last accessed March 17, 2022) for hematological malignancies were investigated using a customized bed file.18Arber D.A. Orazi A. Hasserjian R. Thiele J. Borowitz M.J. Le Beau M.M. Bloomfield C.D. Cazzola M. Vardiman J.W. The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia.Blood. 2016; 127: 2391-2405Crossref PubMed Scopus (6518) Google Scholar v) Translocation, inversion, or CNV >500 kb was reported as an additional finding. Five performance criteria that included positive percentage agreement, positive predictive value, negative percentage agreement, negative predictive value, and accuracy were evaluated. The clinically reported variants were compared between OGM and SOC methods for concordance evaluation. Differences in size and breakpoint are anticipated, as the resolution of OGM is higher than SOC methods, and thus, a variant was considered concordant even if the size or breakpoint was slightly different. However, balanced SVs with centromeric breakpoints, or with a variant allele frequency 150 kb) of 303 kb (±35), map rate of 87.5% (±7.5%), label density of 15.8/100 kb (±1.0), and average coverage of 391× (±89) (Supplemental Table S2). In total, 86,306 SVs were identified in the 59 samples, with an average of approximately 1462 SVs per sample. Of all the identified SVs, a total of 4226 SVs remained after the filtration criteria were applied (94.9% variants filtered out), with an average of approximately 71 SVs per sample that were further interrogated (Supplemental Table S3). OGM was concordant in identifying 162 of 164 variants, which were reported with current SOC methods (Figure 1E). The two variants that were not detected with OGM included mosaic loss of chromosome Y and an insertion, both detected at <10% allele fraction with karyotyping (4/20 and 3/20 cells). Because cultures for karyotyping might cause a bias in clonal proportion, the true variant allele frequency in the extracted bulk DNA used for OGM (preculture) may have been below the 5% LoD of OGM. The different classes of SVs included many well-known aberrations in hematological neoplasms. As such, the 60 aneuploidies included 33 monosomies, 21 trisomies, and 6 loss-of-sex chromosomes, of which the most common were monosomies 5 (n = 5), 7 (n = 5), and 13 (n = 5), trisomies 8 (n = 3), 9 (n = 3), 11 (n = 3), and 21 (n = 3), and loss of Y (n = 5) chromosome. OGM detected 59 of 60 aneuploidies, whereas one mosaic loss of chromosome Y (in a complex case of CLL) was not detected with OGM. Of these 59 aneuploidies, the software correctly called 57 aneuploidies, whereas two were manually interpreted from the visualization in the whole genome CNV viewer (the software could also detect them at a lower confidence threshold). These two aneuploidies, 12, and –13, were reported near the LoD threshold of OGM (5% allele fraction) detected in a low cell fraction (4/20 and 3/20) with karyotyping, respectively. The 34 deletions detected by SOC and compared with OGM in the study ranged from 905 kb up to the loss of entire chromosomes, which were all called by OGM data. OGM identified all 28 translocations that included balanced, unbalanced, and three-way translocations, including those that lead to reoccurring oncogenic gene fusions: RUNX1::RUNX1T1 (n = 3), KMT2A::ELL (n = 1), BCR::ABL1 (n = 1), and FGFR1::BCR (n = 1) (Figure 2). Furthermore, OGM detected duplications and was able to identify the additional material/insertions in 15 of 16 SOC calls, revealing the identity of the 12 markers and 1 ring chromosome that remained uncharacterized by karyotyping (Figure 3).Figure 3Optical genome mapping resolves a complex case of acute myeloid leukemia with higher resolution compared with karyotype and fluorescence in situ hybridization. A: The circos plot summarizing the structural variations (SVs) identified in the genome: copy number loss at 3q, t (3; 19), loss at 5q, gain of chromosome 7, loss at 13q, and complex rearrangement at chromosomes 16 and 20. B: Genome browser view of chromosome 16: maps showing complex rearrangements with fusion maps from pter to qter, revealing chromosome 16 to be the ring chromosome. C: Circos plot showing chromosomes 16 and 20: complex rearrangement with several intertranslocations and intratranslocations between the two chromosomes. D: Genome browser view of chromosome 20: maps showing complex rearrangements with interstitial gains and loss, revealing chromosome 20 to be the marker chromosome.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Of the 45 cases classified as simple, 35 had at least one clinically reported genetic aberration, whereas 10 were negative with both karyotyping and/or FISH testing. In the 35 cases with reported aberrations, OGM detected all of the previously reported variants and corrected the previously incorrect interpretations due to low resolution of karyotyping in two cases: Case 1: In a case of multiple myeloma with a negative karyotype (performed on bone marrow aspirate), the FISH testing (performed on CD-138 cells) reported a gain of one to two copies of 1q CKS1B (43/50 cells), monosomy 13 (47/50 cells), and a gain/rearrangement of one copy of 4p FGFR3 (23/50 cells). OGM (performed on CD-138 cells) confirmed 1q21.1qter (144092961_248943333)x3, (13)x1, but did not detect a copy number gain or rearrangement of the FGFR3 gene. However, OGM detected a der(4)t(4;5) (p16.3;p13.3) (1910123;32591078), with the breakpoint at 4p16.3 that overlaps the region of FGFR3 dual-fusion probes used for detecting FGFR3 gain/rearrangement. The breakpoint of the translocation did not disrupt the FGFR3 gene (Figure 4, A and B ). Case 2: In a case of CLL, karyotyping detected 46,XY,der (4)t (4; 7) (p14; q11.2),del (11) (q22q23), dic(21;21) (q22;p11.2)12Wang Y. Wu N. Liu D. Jin Y. Recurrent fusion genes in leukemia: an attractive target for diagnosis and treatment.Curr Genom. 2017; 18: 1087-1094Crossref Scopus (29) Google Scholar/46,XY,8Sahajpal N.S. Mondal A.K. Ananth S. Njau A. Ahluwalia P. Jones K. Ahluwalia M. Okechukwu N. Savage N.M. Kota V. Rojiani A.M. Kolhe R. Clinical performance and utility of a comprehensive next-generation sequencing DNA panel for the simultaneous analysis of variants, TMB and MSI for myeloid neoplasms.PLoS One. 2020; 15: e0240976Crossref PubMed Scopus (7) Google Scholar and FISH confirmed the deletion at 11q (ATM). OGM was concordant in detecting der (4)t (4; 7) (p15.1; q21.11) (2986