Myeloid malignancies are complex clonal diseases arising in haematopoietic stem or progenitor cells. These heterogenous disorders comprise many different subtypes such as myeloproliferative neoplasms (MPN), myelodysplastic syndrome (MDS), myelodysplastic/myeloproliferative neoplasms (MDS/MPN) and acute myeloid leukaemia (AML).
There is a growing need for molecular profiling of these blood and bone marrow disorders to provide better definition and classification to inform diagnosis, prognosis and the development of novel therapies.
Next generation sequencing (NGS) offers the promise of being able to detect rare and subclonal mutations, profiling the cancer genomics, enabling the high-throughput determination of DNA mutations, facilitating precision medicine and more.1 High-throughput, massively parallel sequencing makes it possible to detect somatic and germline mutations – even though these typically present at only a low level. NGS is different from traditional sequencing methodologies with respect to its precision and scale: case in point, NGS can detect multiple mutations in 19,000 genes – simultaneously.2
NGS: An abbreviated history
The story of NGS can be traced back to 1977 with the debut of the Sanger Sequencing method. Around a decade later, the $3B Human Genome Project began and the first draft sequence assembly was eventually published in 2001 as a result of a yeoman’s effort by hundreds of scientists and terrific advances in sequencing technology. Along the way, George Church spurred the development of multi-plexing.3 Fast-forward to today and the exciting era of NGS-enabled $1K whole genome sequencing capabilities that can be executed by an individual in only one day.4
NGS provides coverage of up to 98% of the targeted sequence regions2 and hence has the enormous potential to accelerate the discovery of genetic disorders and pharmacogenetic markers for personalised medicine treatments. The application of NGS testing of clonal myeloid malignancies is expanding with broad utility across major clinical utility categories including diagnostics and prognostics. There are numerous factors to consider before deciding which NGS strategy will best meet your research and/or clinical diagnostic needs.
Variants have high utility across multiple applications
NGS provides clinicians with a powerful diagnostic tool when patients present with unusual clinical outcomes and/or complex phenotypes. Until recently, NGS was an expensive, time-consuming and daunting approach. The resultant data volumes alone were troublesome and spawned a whole new field of science – bioinformatics.
NGS was adopted quickly by the scientific community largely because of its highly parallel approach to sequencing. However, the adoption rate was also driven in part by its inherent synergy with more conventional molecular technologies such as qPCR. In balancing time-to-results, multi-target testing and standardization, both are complementary. Specifically, qPCR is highly standardised, offers fast results, is commonly utilised in all labs but is limited with respect to target-plexing. Comparatively, NGS has high target-plexing, the data interpretation is more complicated and standardisation is in progress but not yet fully defined. That said, NGS has forever altered how clinicians and researchers alike approach the discovery and application of new treatments. And, NGS could potentially relieve some of the healthcare deficit, protect millions of people from adverse drug reactions and identify health issues if applied in the screening of the five most common health disorders in the USA (cardiovascular, stroke, cancer, COPD and diabetes).3
There are multiple clonal disorders of haematopoietic stem cells including AML, myelodysplastic syndrome (MDS), chronic myelomonocytic leukaemia (CMML), among others that can also be screened for using NGS. There is a growing need for molecular characterisation of these heterogenous blood and bone marrow disorders. The massively parallel nature of NGS affords clinical researchers with unprecedented insights into the genetic drivers of myeloid malignancies.
A number of key genes have been identified as oncogenic and many can now be readily detected and used to classify these disorders via NGS.5 For example, targeted gene sequencing with a focus on the most critical mutations (for example, SF3B1, TET2, SRSF2, ASXL1, DNMT3A, RUNX1, U2AF1, TP53, and EZH2) can detect gene abnormalities in nearly 90% of MDS patients. Numerous molecular markers have been identified which enable the stratification of AML patients which, in turn, informs treatment decisions through a prognostic utility.6 The WHO classification of myeloid neoplasms and acute leukaemia was heavily revised in 2016 in response to the multitude of biomarkers and other molecular markers that have been identified since the guidelines were first institutionalised in 2008.7 Diagnosis (which myeloid malignancy) and prognosis (risk ranges from low and favorable to high and adverse) are affected by which variants are expressed.
Therapeutic utility is also afforded via NGS and the identification of genes and/or groups of genes which have been targeted in the development of treatments. The target specificity of such treatments, which includes approved drugs as well as those currently involved in clinical trials, allows for a precision medicine approach where the therapeutic treatment is tailored to the genetic variant(s) identified.8 Despite the large number of variants, a well-designed NGS assay can effectively capture all the variants in a single experiment and an integrated data analytics solution can greatly aid interpretation.