Screening Gene Mutations in Myeloid Cancers by Next Generation Sequencing to Improve Treatment Results

Summary

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Description

Genetic mutations have closely linked to the pathogenesis and prognostication of myeloid cancers (including acute myeloid leukemia, myelodysplastic syndromes, and myeloproliferative neoplasms). In recent years, a number of novel therapeutic agents targeting various genetic mutations have been develo...

Genetic mutations have closely linked to the pathogenesis and prognostication of myeloid cancers (including acute myeloid leukemia, myelodysplastic syndromes, and myeloproliferative neoplasms). In recent years, a number of novel therapeutic agents targeting various genetic mutations have been developed. For instance, patients with FLT3-ITD and IDH2 mutations have been shown to derive benefits from midostaurin and enasidenib, respectively. Furthermore, the TP53-mutated patients once categorized in the very high risk group, have been found to respond favorably to the hypomethylating agent, decitabine. Detecting a wide array of cancer mutations nowadays by the traditional Sanger method has become not only time-consuming but also not as cost-effective. With the advent of next generation sequencing (NGS), we now are able to detect a panel gene mutations more rapidly, accurately, and economically. In this study, the investigators will screen and analyze myeloid-associated gene mutations in participants with myeloid cancers, with an in-house designed targeted NGS panel. The total nucleic acid from patients' blood or bone marrow specimens will be extracted, and then subjected to the library preparation procedure based on multiplex PCR amplification. Sequencing will be performed on Illumina MiSeq sequencer, and the results will be analyzed using our in-house developed bioinformatic workflow. Briefly, the sequenced reads will be aligned to human reference genome hg19 with BWA-mem, and somatic mutations called with Mutect2. The variants will be annotated via SnpEff with RefSeq, dbSNP, 1000 Genome Project, COSMIC and ClinVar databases. The investigators aim to build up the mutational landscapes of the above mentioned myeloid cancers, and investigate how these mutations are linked to clinical outcome.

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