Genomic analysis of cellular hierarchy in acute myeloid leukemia using ultrasensitive LC-FACSeq

利用超灵敏LC-FACSeq技术对急性髓系白血病细胞层级进行基因组分析

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作者:Caner Saygin ,Eileen Hu ,Pu Zhang ,Steven Sher ,Arletta Lozanski ,Tzyy-Jye Doong ,Deedra Nicolet ,Shelley Orwick ,Jadwiga Labanowska ,Jordan N Skinner ,Casey Cempre ,Tierney Kauffman ,Virginia M Goettl ,Nyla A Heerema ,Lynne Abruzzo ,Cecelia Miller ,Rosa Lapalombella ,Gregory Behbehani ,Alice S Mims ,Karilyn Larkin ,Nicole Grieselhuber ,Alison Walker ,Bhavana Bhatnagar ,Clara D Bloomfield ,John C Byrd ,Gerard Lozanski # ,James S Blachly #

Abstract

Hematopoiesis is hierarchical, and it has been postulated that acute myeloid leukemia (AML) is organized similarly with leukemia stem cells (LSCs) residing at the apex. Limited cells acquired by fluorescence activated cell sorting in tandem with targeted amplicon-based sequencing (LC-FACSeq) enables identification of mutations in small subpopulations of cells, such as LSCs. Leveraging this, we studied clonal compositions of immunophenotypically-defined compartments in AML through genomic and functional analyses at diagnosis, remission and relapse in 88 AML patients. Mutations involving DNA methylation pathways, transcription factors and spliceosomal machinery did not differ across compartments, while signaling pathway mutations were less frequent in putative LSCs. We also provide insights into TP53-mutated AML by demonstrating stepwise acquisition of mutations beginning from the preleukemic hematopoietic stem cell stage. In 10 analyzed cases, acquisition of additional mutations and del(17p) led to genetic and functional heterogeneity within the LSC pool with subclones harboring varying degrees of clonogenic potential. Finally, we use LC-FACSeq to track clonal evolution in serial samples, which can also be a powerful tool to direct targeted therapy against measurable residual disease. Therefore, studying clinically significant small subpopulations of cells can improve our understanding of AML biology and offers advantages over bulk sequencing to monitor the evolution of disease.

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