4.4 Article

Genomic analysis in myeloid sarcoma and comparison with paired acute myeloid leukemia

期刊

HUMAN PATHOLOGY
卷 108, 期 -, 页码 76-83

出版社

W B SAUNDERS CO-ELSEVIER INC
DOI: 10.1016/j.humpath.2020.11.005

关键词

Myeloid sarcoma; Acute myeloid leukemia; Next-generation sequencing; Single-nucleotide variants

资金

  1. Department of Pathology, University of California San Francisco

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Myeloid sarcoma is a rare manifestation of acute myeloid leukemia characterized by extramedullary proliferation of myeloid blasts. Studies have shown that the genetic profiles observed in myeloid sarcoma are generally similar to paired acute myeloid leukemia samples, suggesting a common precursor origin for these tumors rather than de novo tumors. Additionally, myeloid sarcoma cases with a higher number of single-nucleotide variants tend to have worse clinical outcomes. The identification of these abnormalities may contribute to improved prognostic classification and the discovery of new therapeutic targets for myeloid sarcoma.
Myeloid sarcoma (MS) is a rare manifestation of acute myeloid leukemia (AML) characterized by extramedullary proliferation of myeloid blasts. Owing to the rarity of MS, the clonal evolution of cell populations giving rise to MS is not well understood. To study the genomic signature of MS, we used a capture-based next-generation sequencing panel targeting 479 cancer genes to interrogate the genetic variants present in MS samples and compared their genetic profiles with their paired AML samples from a cohort of seven individuals. We identified a spectrum of single-nucleotide variants (SNVs) and a spectrum of copy number alterations in MS. Our study found that variant profiles observed in MS were generally similar to AML from the same individual, supporting the notion that these tumors are derived from a common precursor, rather than de novo tumors in a susceptible host. In addition, MS cases with a higher number of SNVs show worse clinical outcomes than MS with a lower number of SNVs. Identification of these abnormalities could potentially contribute to improved prognostic classification and identify new therapeutic targets for MS. (C) 2020 Elsevier Inc. All rights reserved.

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