Clinical characterization of the mutational landscape of 24,639 real-world samples from patients with myeloid malignancies.

Myeloid neoplasms represent a broad spectrum of hematological disorders for which somatic mutation status in key driver genes is important for diagnosis, prognosis and treatment. Here we summarize the findings of a targeted, next generation sequencing laboratory developed test in 24,639 clinical myeloid samples. Data were analyzed comprehensively and as part of individual cohorts specific to acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasms (MPN). Overall, 48,015 variants were detected, and variants were found in all 50 genes in the panel. The mean number of mutations per patient was 1.95. Mutation number increased with age (Spearman's rank correlation coefficient, ρ = 0.29, P < 0.0001) and was higher in patients with AML than MDS or MPN (Student's t-test, P < 0.0001). TET2 was the most common mutation detected (19.1% of samples; 4,695/24,639) including 7.7% (1,908/24,639) with multi-hit TET2 mutations. Mutation frequency was correlated between patients with cytopenias and MDS (Spearman's, ρ = 0.97, P < 2.2×10-16) with the MDS diagnostic gene SF3B1 being the only notable outlier. This large retrospective study shows the utility of NGS testing to inform clinical decisions during routine clinical care and highlights the mutational landscape of a broad population of myeloid patients.

A customized scaffolds approach for the detection and phasing of complex variants by next-generation sequencing.

Next-generation sequencing (NGS) is widely used in genetic testing for the highly sensitive detection of single nucleotide changes and small insertions or deletions. However, detection and phasing of structural variants, especially in repetitive or homologous regions, can be problematic due to uneven read coverage or genome reference bias, resulting in false calls. To circumvent this challenge, a computational approach utilizing customized scaffolds as supplementary reference sequences for read alignment was developed, and its effectiveness demonstrated with two CBS gene variants: NM_000071.2:c.833T>C and NM_000071.2:c.[833T>C; 844_845ins68]. Variant c.833T>C is a known causative mutation for homocystinuria, but is not pathogenic when in cis with the insertion, c.844_845ins68, because of alternative splicing. Using simulated reads, the custom scaffolds method resolved all possible combinations with 100% accuracy and, based on > 60,000 clinical specimens, exceeded the performance of current approaches that only align reads to GRCh37/hg19 for the detection of c.833T>C alone or in cis with c.844_845ins68. Furthermore, analysis of two 1000 Genomes Project trios revealed that the c.[833T>C; 844_845ins68] complex variant had previously been undetected in these datasets, likely due to the alignment method used. This approach can be configured for existing workflows to detect other challenging and potentially underrepresented variants, thereby augmenting accurate variant calling in clinical NGS testing.