Challenges in the introduction of next-generation sequencing (NGS) for diagnostics of myeloid malignancies into clinical routine use

Given the vast phenotypic and genetic heterogeneity of acute and chronic myeloid malignancies, hematologists have eagerly awaited the introduction of next-generation sequencing (NGS) into the routine diagnostic armamentarium to enable a more differentiated disease classification, risk stratification, and improved therapeutic decisions. At present, an increasing number of hematologic laboratories are in the process of integrating NGS procedures into the diagnostic algorithms of patients with acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and myeloproliferative neoplasms (MPNs). Inevitably accompanying such developments, physicians and molecular biologists are facing unexpected challenges regarding the interpretation and implementation of molecular genetic results derived from NGS in myeloid malignancies. This article summarizes typical challenges that may arise in the context of NGS-based analyses at diagnosis and during follow-up of myeloid malignancies.

[1]  Christian Beisel,et al.  Clonal evolution and clinical correlates of somatic mutations in myeloproliferative neoplasms. , 2014, Blood.

[2]  A. Kohlmann,et al.  Current status and trends in the diagnostics of AML and MDS. , 2018, Blood reviews.

[3]  Shawn C. Baker,et al.  Next-Generation Sequencing Challenges , 2017 .

[4]  T. Ley,et al.  Quantifying ultra-rare pre-leukemic clones via targeted error-corrected sequencing , 2015, Leukemia.

[5]  D. Wheeler,et al.  Coexistence of gain-of-function JAK2 germ line mutations with JAK2V617F in polycythemia vera. , 2016, Blood.

[6]  Hilla Peretz,et al.  Ju n 20 03 Schrödinger ’ s Cat : The rules of engagement , 2003 .

[7]  klaguia International Network of Cancer Genome Projects , 2010 .

[8]  D. Neuberg,et al.  Clinical effect of point mutations in myelodysplastic syndromes. , 2011, The New England journal of medicine.

[9]  R. Jakesz,et al.  TP53 germline mutation may affect response to anticancer treatments: analysis of an intensively treated Li–Fraumeni family , 2015, Breast Cancer Research and Treatment.

[10]  Philip Hugenholtz,et al.  Shining a Light on Dark Sequencing: Characterising Errors in Ion Torrent PGM Data , 2013, PLoS Comput. Biol..

[11]  P. Guldberg,et al.  Persistence of DNMT3A mutations at long‐term remission in adult patients with AML , 2014, British journal of haematology.

[12]  M. Guzman,et al.  Minimal residual disease in acute myelogenous leukemia , 2017, International journal of laboratory hematology.

[13]  Mingming Jia,et al.  COSMIC: somatic cancer genetics at high-resolution , 2016, Nucleic Acids Res..

[14]  Eric Samorodnitsky,et al.  Evaluation of Hybridization Capture Versus Amplicon‐Based Methods for Whole‐Exome Sequencing , 2015, Human mutation.

[15]  Margaret C. Linak,et al.  Sequence-specific error profile of Illumina sequencers , 2011, Nucleic acids research.

[16]  E. Duncavage,et al.  The utility of next‐generation sequencing in diagnosis and monitoring of acute myeloid leukemia and myelodysplastic syndromes , 2015, International journal of laboratory hematology.

[17]  E. Wang,et al.  Predictive genomics: a cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data. , 2014, Seminars in cancer biology.

[18]  C. Bloomfield,et al.  Persistence of DNMT3A R882 mutations during remission does not adversely affect outcomes of patients with acute myeloid leukaemia , 2016, British journal of haematology.

[19]  Landscape Of Genetic Lesions In 944 Patients With Myelodysplastic Syndromes , 2013 .

[20]  Nicola D. Roberts,et al.  Genomic Classification and Prognosis in Acute Myeloid Leukemia. , 2016, The New England journal of medicine.

[21]  S. Sugano,et al.  Frequent pathway mutations of splicing machinery in myelodysplasia , 2011, Nature.

[22]  C. Ponting,et al.  Sequencing depth and coverage: key considerations in genomic analyses , 2014, Nature Reviews Genetics.

[23]  Alexis B. Carter,et al.  SPECIAL ARTICLE Standards and Guidelines for Validating Next-Generation Sequencing Bioinformatics Pipelines A Joint Recommendation of the Association for Molecular Pathology and the College of American Pathologists , 2022 .

[24]  Florian Eggenhofer,et al.  ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines , 2014, bioRxiv.

[25]  H. Meijers-Heijboer,et al.  TP53 germline mutation testing in 180 families suspected of Li–Fraumeni syndrome: mutation detection rate and relative frequency of cancers in different familial phenotypes , 2010, Journal of Medical Genetics.

[26]  M. Dolled-Filhart,et al.  Computational and Bioinformatics Frameworks for Next-Generation Whole Exome and Genome Sequencing , 2013, TheScientificWorldJournal.

[27]  D. Steensma Clinical Implications of Clonal Hematopoiesis , 2018, Mayo Clinic proceedings.

[28]  T. Barbui,et al.  The 2016 WHO classification and diagnostic criteria for myeloproliferative neoplasms: document summary and in-depth discussion , 2018, Blood Cancer Journal.

[29]  T. Haferlach,et al.  Detection of recurrent and of novel fusion transcripts in myeloid malignancies by targeted RNA sequencing , 2018, Leukemia.

[30]  Jesse J. Salk,et al.  Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations , 2018, Nature Reviews Genetics.

[31]  T. Barbui,et al.  Polycythemia vera and essential thrombocythemia: 2017 update on diagnosis, risk‐stratification, and management , 2017 .

[32]  J. Ritz,et al.  Donor-engrafted CHIP is common among stem cell transplant recipients with unexplained cytopenias. , 2017, Blood.

[33]  Michael T. Wolfinger,et al.  ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines. , 2015, F1000Research.

[34]  T. Pabst,et al.  Somatic CEBPA mutations are a frequent second event in families with germline CEBPA mutations and familial acute myeloid leukemia. , 2008, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[35]  M. Cazzola,et al.  Advances in understanding the pathogenesis of familial myeloproliferative neoplasms , 2017, British journal of haematology.

[36]  Paola Guglielmelli,et al.  Genetic variation at MECOM, TERT, JAK2 and HBS1L-MYB predisposes to myeloproliferative neoplasms , 2015, Nature Communications.

[37]  Joonhong Park,et al.  Characterization of sequence-specific errors in various next-generation sequencing systems. , 2016, Molecular bioSystems.

[38]  Ute Baumann,et al.  Sequencing error correction without a reference genome , 2013, BMC Bioinformatics.

[39]  S. Letovsky,et al.  Exploring the landscape of pathogenic genetic variation in the ExAC population database: insights of relevance to variant classification , 2015, Genetics in Medicine.

[40]  S. Gabriel,et al.  Clonal hematopoiesis and blood-cancer risk inferred from blood DNA sequence. , 2014, The New England journal of medicine.

[41]  M. Marra,et al.  Driver and passenger mutations in cancer. , 2015, Annual review of pathology.

[42]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[43]  W. Vainchenker,et al.  Genetic basis and molecular pathophysiology of classical myeloproliferative neoplasms. , 2017, Blood.

[44]  Bob Löwenberg,et al.  Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. , 2017, Blood.

[45]  T. Glenn Field guide to next‐generation DNA sequencers , 2011, Molecular ecology resources.

[46]  M. Cazzola,et al.  The number of prognostically detrimental mutations and prognosis in primary myelofibrosis: an international study of 797 patients , 2014, Leukemia.

[47]  Irina I. Abnizova,et al.  Statistical Comparison of Methods to Estimate the Error Probability in Short-Read Illumina Sequencing , 2010, J. Bioinform. Comput. Biol..

[48]  M. Cazzola,et al.  Mutations and prognosis in primary myelofibrosis , 2013, Leukemia.

[49]  Jing Zhang,et al.  Identifying driver mutations from sequencing data of heterogeneous tumors in the era of personalized genome sequencing , 2014, Briefings Bioinform..

[50]  Joshua F. McMichael,et al.  Age-related cancer mutations associated with clonal hematopoietic expansion , 2014, Nature Medicine.

[51]  R. Durbin,et al.  Evaluation of GRCh38 and de novo haploid genome assemblies demonstrates the enduring quality of the reference assembly , 2016, bioRxiv.

[52]  P. Stenson,et al.  The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies , 2017, Human Genetics.

[53]  Sushant A. Patil,et al.  Prognostic tumor sequencing panels frequently identify germ line variants associated with hereditary hematopoietic malignancies. , 2018, Blood advances.

[54]  C. Férec,et al.  RUNX1-MTG16 fusion gene in acute myeloblastic leukemia with t(16;21)(q24;q22): case report and review of the literature. , 2008, Cancer genetics and cytogenetics.

[55]  J. Geigl,et al.  Acute myeloid leukemia with TP53 germ line mutations. , 2016, Blood.

[56]  L. Godley,et al.  Genetic predisposition to leukemia and other hematologic malignancies. , 2016, Seminars in oncology.

[57]  P. Jordan,et al.  PCR amplification introduces errors into mononucleotide and dinucleotide repeat sequences , 2001, Molecular pathology : MP.

[58]  Xiaobo Zhou,et al.  A novel missense-mutation-related feature extraction scheme for 'driver' mutation identification , 2012, Bioinform..

[59]  Yiping Shen,et al.  Next-generation sequencing strategies enable routine detection of balanced chromosome rearrangements for clinical diagnostics and genetic research. , 2011, American journal of human genetics.

[60]  Mario Cazzola,et al.  The 2016 revision to the World Health Organization classification of myeloid neoplasms and acute leukemia. , 2016, Blood.

[61]  A. Kohlmann,et al.  Mutational profiling in patients with MDS: ready for every-day use in the clinic? , 2015, Best practice & research. Clinical haematology.

[62]  James Y. Zou Analysis of protein-coding genetic variation in 60,706 humans , 2015, Nature.

[63]  M. Cazzola,et al.  The genetic basis of myelodysplasia and its clinical relevance. , 2013, Blood.

[64]  Ken Chen,et al.  Use of whole-genome sequencing to diagnose a cryptic fusion oncogene. , 2011, JAMA.

[65]  Zhanjiang Liu DNA Sequencing Technologies , 2007 .

[66]  J. Sanz,et al.  Pitfalls in the molecular follow up of NPM1 mutant acute myeloid leukemia , 2018, Haematologica.

[67]  A. Tefferi,et al.  Primary myelofibrosis: 2017 update on diagnosis, risk‐stratification, and management , 2016 .

[68]  J. Uhm Comprehensive genomic characterization defines human glioblastoma genes and core pathways , 2009 .

[69]  M. Stratton,et al.  The cancer genome , 2009, Nature.

[70]  D. Hanahan,et al.  Hallmarks of Cancer: The Next Generation , 2011, Cell.

[71]  Hans B Ommen,et al.  Monitoring minimal residual disease in acute myeloid leukaemia: a review of the current evolving strategies , 2016, Therapeutic advances in hematology.

[72]  T. Barbui,et al.  Long-term survival and blast transformation in molecularly annotated essential thrombocythemia, polycythemia vera, and myelofibrosis. , 2014, Blood.

[73]  Leyla Isik,et al.  Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations. , 2009, Cancer research.

[74]  Christopher A. Miller,et al.  Genomic analysis of germ line and somatic variants in familial myelodysplasia/acute myeloid leukemia. , 2015, Blood.

[75]  N. Speck,et al.  RUNX1 Mutations in Inherited and Sporadic Leukemia , 2017, Front. Cell Dev. Biol..

[76]  Jean-Baptiste Cazier,et al.  Choice of transcripts and software has a large effect on variant annotation , 2014, Genome Medicine.

[77]  Hannah Carter,et al.  CHASM and SNVBox: toolkit for detecting biologically important single nucleotide mutations in cancer , 2011, Bioinform..

[78]  Joshua M. Korn,et al.  Comprehensive genomic characterization defines human glioblastoma genes and core pathways , 2008, Nature.

[79]  C Haferlach,et al.  Landscape of genetic lesions in 944 patients with myelodysplastic syndromes , 2013, Leukemia.

[80]  R. Bejar CHIP, ICUS, CCUS and other four-letter words , 2017, Leukemia.

[81]  B. Johansson,et al.  The emerging complexity of gene fusions in cancer , 2015, Nature Reviews Cancer.

[82]  Alexis B. Carter,et al.  Standards and Guidelines for Validating Next-Generation Sequencing Bioinformatics Pipelines: A Joint Recommendation of the Association for Molecular Pathology and the College of American Pathologists. , 2018, The Journal of molecular diagnostics : JMD.

[83]  Tony Z. Jia,et al.  Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes , 2012, Proceedings of the National Academy of Sciences.

[84]  P. Guglielmelli,et al.  Targeted deep sequencing in polycythemia vera and essential thrombocythemia. , 2016, Blood advances.

[85]  Markus G. Manz,et al.  Molecular Minimal Residual Disease in Acute Myeloid Leukemia , 2018, The New England journal of medicine.

[86]  J. McPherson,et al.  Coming of age: ten years of next-generation sequencing technologies , 2016, Nature Reviews Genetics.

[87]  M. Emond,et al.  Accuracy of Next Generation Sequencing Platforms. , 2014, Next generation, sequencing & applications.

[88]  Paola Guglielmelli,et al.  Effect of mutation order on myeloproliferative neoplasms. , 2015, The New England journal of medicine.

[89]  E. Mardis DNA sequencing technologies: 2006–2016 , 2017, Nature Protocols.

[90]  J. Gribben,et al.  Disease evolution and outcomes in familial AML with germline CEBPA mutations. , 2015, Blood.

[91]  Erdogan Taskesen,et al.  Prognostic impact, concurrent genetic mutations, and gene expression features of AML with CEBPA mutations in a cohort of 1182 cytogenetically normal AML patients: further evidence for CEBPA double mutant AML as a distinctive disease entity. , 2011, Blood.

[92]  S. Bojesen,et al.  Diagnostic value of JAK2 V617F somatic mutation for myeloproliferative cancer in 49 488 individuals from the general population , 2013, British journal of haematology.

[93]  Nuno A. Fonseca,et al.  Comparison of GENCODE and RefSeq gene annotation and the impact of reference geneset on variant effect prediction , 2015, BMC Genomics.

[94]  C. Pecquet,et al.  Cooperation of germ line JAK2 mutations E846D and R1063H in hereditary erythrocytosis with megakaryocytic atypia. , 2016, Blood.

[95]  M. Stratton,et al.  Clinical and biological implications of driver mutations in myelodysplastic syndromes. , 2013, Blood.

[96]  T. Hubbard,et al.  A census of human cancer genes , 2004, Nature Reviews Cancer.

[97]  Steven M. Chan,et al.  Clinical Utility of Next-generation Sequencing in the Management of Myeloproliferative Neoplasms: A Single-Center Experience , 2018, HemaSphere.

[98]  A. Tefferi,et al.  Targeted deep sequencing in primary myelofibrosis. , 2016, Blood advances.

[99]  Benjamin J. Raphael,et al.  Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. , 2013, The New England journal of medicine.

[100]  Gary D Bader,et al.  International network of cancer genome projects , 2010, Nature.

[101]  Nicholas Eriksson,et al.  Germ line variants predispose to both JAK2 V617F clonal hematopoiesis and myeloproliferative neoplasms. , 2016, Blood.

[102]  M. McCarthy,et al.  Age-related clonal hematopoiesis associated with adverse outcomes. , 2014, The New England journal of medicine.

[103]  J. Witte,et al.  MDS-associated somatic mutations and clonal hematopoiesis are common in idiopathic cytopenias of undetermined significance. , 2015, Blood.