From Driver Mutations to Genomic Classification: Current & Future Perspectives on Myeloproliferative Neoplasms

@#Myeloproliferative neoplasms (MPNs) encompass a heterogeneous group of chronic, clonal haematopoietic stem cell neoplasms that harbor the propensity to undergo leukaemic transformation. Epidemiological data on MPNs especially pertaining to non-Caucasian populations is limited, and the molecular pathogenesis of MPN remains unclear. Although the discovery of MPN driver mutations in JAK2, MPL and CALR in the last decade has revolutionised disease management, the mutations are not specific for any MPN subtype. The management of MPNs is further challenged by substantial genetic and phenotypic heterogeneity that exist between and within MPN subtypes as well as other myeloid diseases. In this review, we focus on the classical Philadelphia chromosome (Ph)-negative MPNs – polycythaemia vera (PV), essential thrombocythaemia (ET), and primary myelofibrosis (PMF); providing an overview on the current understanding of the disease at a clinical and molecular standpoint while discussing the present challenges and future opportunities in the management of MPNs.

Development and Validation of High Resolution Melting Assays for High-Throughput Screening of BDNF rs6265 and DAT1 rs40184

@#Introduction: One of the commonly used techniques for mutation screening is High Resolution Melting (HRM) analysis. HRM is a post PCR method that relies on the detection of the fluorescent signals acquired due to the release of DNA intercalated dyes upon the melting of dsDNA to ssDNA. The method is simple, inexpensive and does not require post PCR-handling, making it suitable for high throughput screening. Methods: This study aimed to develop and validate HRM technique for the screening of two disease-associated single nucleotide polymorphisms (SNPs) namely BDNF rs6265 and DAT1 rs40184 using a total of 30 gDNA samples. The obtained results were confirmed and validated by sequencing. Results: HRM analysis showed that the predicted genotypes of BDNF rs6265 and DAT1 rs40184 among all the gDNA samples were in 100% concordance with the sequencing results, making it an accurate and sensitive method for the detection of SNPs. Conclusions: The application of HRM can accurately determine the genotype of BDNF rs6265 and DAT1 rs40184 SNPs, making it a promising tool for rapid and high-throughput screening of targeted SNPs in a large population study.