Proteogenomic characterization of highly enriched viable leukemic blasts in acute myeloid leukemia: A SWOG report

EJHaem Pub Date : 2024-10-25 DOI:10.1002/jha2.1041
Jasmine Naru, Megan Othus, ChenWei Lin, Melinda A. Biernacki, Marie Bleakley, Thomas R. Chauncey, Harry P. Erba, Min Fang, Matthew P. Fitzgibbon, Phillip R. Gafken, Richard G. Ivey, Jacob J. Kennedy, Travis D. Lorentzen, Soheil Meshinchi, Anna Moseley, Era L. Pogosova-Agadjanyan, Vivian M. Liu, Jerald P. Radich, Uliana J. Voytovich, Pei Wang, Jeffrey R. Whiteaker, Cheryl L. Willman, Feinan Wu, Amanda G. Paulovich, Derek L. Stirewalt
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Abstract

Introduction

Acute myeloid leukemia (AML) remains one of the deadliest hematopoietic malignancies. A better understanding of the molecular biology governing AML may lead to improved risk stratification and facilitate the development of novel therapies. Proteins are responsible for much of the biology of cells. Several studies have examined the global proteome in bulk mononuclear cells (MNCs) from AML specimens, which are comprised a heterogenous population of cells at various stages of differentiation.

Methods

Given the potential impact of the nonleukemic cells on protein expression profiles, we applied an integrative proteogenomic approach utilizing next-generation sequencing and mass spectrometry-based proteomics to identify novel protein biomarkers in unsorted MNCs and viable leukemic blasts (VLBs) isolated from blood and bone marrow specimens obtained at the time of AML diagnosis.

Results

We identified significant differences in protein expression between VLBs and MNCs. Subsequent studies (N = 27) focused on proteomic profiling of VLBs that identified novel candidate biomarkers associated with mutational genotypes and clinical outcome, some of which were recapitulated in an independent cohort of patients. Using mass spectrometry, we also detected mutated protein products, some of which were predicted via in silico analyses to be potential neoantigens amenable to adoptive immunotherapy. As previously described, analyses comparing transcript and protein expression showed an overall modest correlation between mRNA and protein dataset, but enriching for genes associated with mutations significantly improved the protein–RNA correlation.

Conclusion

Together, the results provide insight into the biology of VLBs and demonstrate the gains derived from examining the proteome in addition to genome and transcriptome.

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