Genomic profiling in myelodysplastic syndromes

<p class="article-intro">Genomic analysis of neoplastic cells assists in diagnosis, disease evaluation, prediction of prognosis and responsiveness to therapy. Recent developments in genomic technologies have contributed to a better understanding of the molecular landscape of myelodysplastic syndromes (MDS). Furthermore, it has facilitated the identification of genomic alterations in MDS patients and incorporating molecular data has the potential to improve their clinical management in the near future.</p> <p class="article-content"><div id="keypoints"> <h2>Keypoints</h2> <ul> <li>Molecular genetic markers should be added to the current existing prognostic classification and scoring systems for MDS for a more refined prediction of prognosis.</li> <li>In the vast majority of MDS patients, molecular karyotyping using SNP-array provides a similar IPSS/-R prognostic score as results based on conventional karyotyping. Therefore, molecular karyotyping can be used to determine the cytogenetic score.</li> <li>Genomic profiling in MDS patients using high density whole genome SNP-array and NGS gene panels overcomes the limitations of conventional cytogenetics, increases the yield of detected genetic lesions, which potentially can be used as MRD markers to monitor disease progression.</li> <li>Non-invasive MRD from peripheral blood in MDS patients offers future perspective for earlier identification of treatment failure.</li> </ul> </div> <h2>Genomic analysis in hematological malignancies</h2> <p>The identification of losses, gains, amplifications, mutations, copy neutral loss of heterozygosity and chromosomal rearrangements are crucial to establish diagnosis and evaluate prognosis, but most importantly enable to make therapeutic decisions. Since decades conventional chromosome analysis often supplemented by targeted analysis such as fluorescence in situ hybridization (FISH) and real-time quantitative RT-PCR (RQ-PCR) was used in the clinical management of hematologic malignancies. The current genomic era makes it possible to add screening for molecular markers into the diagnostic work up of patients diagnosed with leukemia. Nevertheless, when applying new technologies in a diagnostic laboratory, the generated results need to be sensitive, reproducible and most importantly reliable (avoiding false positive and false negative results). Moreover, knowledge about the limitations of the test is crucial for adequate interpretation of the obtained results. At present, many commercially technological platforms, software packages and reagents are available for genomic profiling, but many of those products may not have been clinically validated. It can therefore be challenging for diagnostic laboratories lacking resources to perform the required validations or lacking the sample volumes to build up a solid experience in particular with interpreting the obtained large amount of genomic data in a clinical context. Acquired genomic variants need to be distinguished from germline variants that are present in the general population and which do not contribute to the disease. Furthermore, clinical trials with accumulating data from large patient cohorts are needed to be able to correlate genomic markers to patient outcome. As a consequence, clinicians are still in an early stage of using genetic markers to make treatment decisions for cancer patients. Nonetheless, the rapidly evolving genomic information in myelodysplastic syndromes (MDS) has the potential to provide clinicians in the near future with better risk stratification tools to allow comprehensive therapeutic decision making.</p> <h2>Cytogenetics in MDS</h2> <p>Myelodysplastic syndromes (MDS) are a group of heterogeneous clonal stem cell disorders characterized by ineffective hematopoiesis, morphological dysplasia and peripheral blood cytopenia with a risk of transformation to acute myeloid leukemia. MDS is believed to arise from the clonal acquisition of mutations in multipotent hematopoietic stem cells. At present, conventional chromosome analysis is still an important part in the diagnostic evaluation of MDS which relies on morphologic assessment of the bone marrow and the presence of specific cytogenetic abnormalities. Cytogenetic risk categorization remains an important factor in the risk assessment as it is one of the major components of the International Prognostic Scoring System (IPSS) and IPSS-R.¹ Yet, metaphase cytogenetics and FISH lack resolution, and are informative in only around 50 % of the novo MDS due to the limitation in achieving results when cells are unable to grow or in case of non-informative karyotypes.<br /> In contrast, whole genome microarray analysis (so called molecular karyotyping) has the advantage of using genomic DNA from tumour cells instead of metaphases and permits to interrogate the genome at much higher resolution. It does not depend on mitotically dividing cells within the tissue of investigation to visualize the chromosomes in metaphases using a microscope as is the case in conventional karyotyping. In case the array contains both polymorphic and non-polymorphic probes it allow simultaneous analysis of copy number by measuring the signal intensity of each probe compared to normal signals as well as determining a homozygous or heterozygous state for each probe. So called high density SNP-arrays are most suitable for detection of small genomic changes in a mixed cell population with a sensitivity of around 10 % . It has the capability to unravel complex genetic anomalies and segmental regions of homozygosity, also known as regions of copy number neutral loss of heterozygosity (CNLOH). CNLOH can lead to the homozygosity of a pre-existing pathogenic mutation, providing a growth advantage to an, already mutant, clone. The array detects all cytogenetic recurrent anomalies in MDS that are integrated into the IPSS/IPRR-R scoring system apart from the balanced rearrangements involving MECOM, which can be assessed by targeted FISH. The disadvantage of microarray analysis is the inability to identify balanced translocations and its limitation when unraveling the clonal architecture.²<br /> One subtype of MDS is characterised by the presence of an isolated 5q-deletion and it is important to identify the patients with 5q-syndrome, because they respond well to the immune-modulating agent lenalidomide. However, the 5q-deletions are highly variable in size and include two different genomic regions, namely deletions of chromosome band 5q31, encompassing the EGR1 gene, and deletions of bands 5q32 and 5q33 involving haplo-insufficiency of RPS14. Molecular karyotyping enables accurate identification of all loci of the 5q deletions, which can escape detection when applying only traditional metaphase karyotyping and FISH. A recent study proved that the same IPSS/IPSS-R cytogenetic score in low and intermediate risk MDS was obtained at a rate of 96 % and 95 % respectively, when counting the number of anomalies &gt;5Mb: Furthermore, the study showed that true balanced translocations were a rare finding in non-complex karyotypes in MDS.³ In addition to the large recurrent cytogenetic anomalies, array analysis revealed small focal deletion and duplications of genes reported to be frequently mutated in MDS such as DNMT3A, ETV6, TET2, RUNX1 and MLL-PTD. Microarray genomic profiling is now becoming part of routine work up in MDS and it has been reported to reveal genomic aberrations in up to around 80 % of the cases. Moreover, cryptic anomalies and regions of acquired CNLOH harbouring point mutations have been found in up to 27 % of low to intermediate risk MDS.</p> <h2>Mutation profiling using next generation sequencing (NGS)</h2> <p>Although high resolution microarray genomic profiling can detect focal deletions and duplication sizes ranging of 20&ndash;30 kb, it is not suitable for identification of point mutations and indels (very small insertions and deletions of 10&ndash;100bp). To pick up point mutations and indels, multiplex targeted NGS using gene panels are the most common type of NGS-assays offered by clinical laboratories. It allows for the selective enrichment of particular genes or regions of interest with a much more rapid turn-around time compared to conventional sequencing methods such as Sanger or Pyrosequencing. The major advantage is the sequencing coverage depths, permitting the detection of variant allele fractions as low as 1&ndash;2 % , compared to ~20 % with conventional sequencing.<br /> Using NGS, a large number of recurrent mutations have been reported in MDS patients and mutations in some specific genes have been clearly associated with shorter survival.⁴ The mutated genes can be organized into categories corresponding to important biologic pathways involved in the pathogenesis of MDS such as DNA methylation (DNMT3A, TET2, IDH1/2), histone modification (EZH2, ASXL1), transcriptional regulation (TP53, RUNX1, GATA2), RNA splicing factors (SF3B1, U2AF1, SRSF2 and ZRSR2), signal transduction (JAK2, KRAS, CBL, PTPN11, KIT, FLT3) and cohesin components (STAG2, RAD21, SMS1A, SMC3). All genomic aberrations detected can serve as molecular markers to monitor disease evolution as they permit sensitive detection of clonal evolution and response to treatment (Fig. 1). In addition, molecular markers identified in peripheral blood in MDS patients have the potential to decrease invasive bone marrow aspiration, facilitate regular testing for MRD assessment and identify treatment failure.⁵</p> <p><img src="/custom/img/files/files_datafiles_data_Zeitungen_2017_Leading Opinions_Onko_1706_Weblinks_s6_fig1.jpg" alt="" width="1419" height="945" /></p></p> <p class="article-footer"> <a class="literatur" data-toggle="collapse" href="#collapseLiteratur" aria-expanded="false" aria-controls="collapseLiteratur" >Literatur</a> <div class="collapse" id="collapseLiteratur"> <p><strong>1</strong> Greenberg PL et al.: Revised international prognostic scoring system for myelodysplastic syndromes. Blood 2012; 120(12): 2454-65 <strong>2</strong> Schoumans J et al.: Guidelines for genomic array analysis in acquired haematological neoplastic disorders. Genes Chromosomes Cancer 2016; 55(5): 480-91 <strong>3</strong> Stevens-Kroef MJ et al.: Genomic array as compared to karyotyping in myelodysplastic syndromes in a prospective clinical trial. Genes Chromosomes Cancer 2017; 56(7): 524-34 <strong>4</strong> Bejar R: Implications of molecular genetic diversity in myelodysplastic syndromes. Curr Opin Hematol 2017; 24(2): 73-8 <strong>5</strong> Yeh P et al.: Molecular disease monitoring using circulating tumor DNA in myelodysplastic syndromes. Blood 2017; 129(12): 1685-90</p> </div> </p>