Recognition of recurrent protein expression patterns in pediatric acute myeloid leukemia suggests new therapeutic targets

• Published in: Molecular cancer research Vol. 16; no. 8; pp. 1275 - 1286
• Main Authors: Hoff, FW, Hu, CW, Qiu, Y, Ligeralde, A, Yoo, SY, Mahmud, H, de Bont, ESJM, Qutub, AA, Horton, TM, Kornblau, SM
• Format: Journal Article
• Language: English
• Published: 18.04.2018
• ISSN: 1541-7786; 1557-3125
• DOI: 10.1158/1541-7786.MCR-17-0731

Heterogeneity in the genetic landscape of pediatric acute myeloid leukemia (AML) makes personalized medicine challenging. As genetic events are mediated by the expression and function of proteins, recognition of recurrent protein patterns could enable classification of pediatric AML patients and could reveal crucial protein dependencies. This could help to rationally select combinations of therapeutic targets. To determine if protein expression levels could be clustered into functionally relevant groups, custom Reverse Phase Protein Arrays (RPPA) were performed for 95 pediatric AML and 10 CD34+ normal bone marrow samples probed with 194 validated antibodies. To analyze proteins in the context of other proteins, all proteins were assembled into 31 Protein Functional Groups (PFG). For each PFG an optimal number of protein clusters was defined that represented distinct transition states. Block clustering analysis revealed strong correlations between various protein clusters and identified the existence of 12 protein constellations stratifying patients into 8 protein signatures. Signatures were correlated with therapeutic outcome, as well as certain laboratory and demographic characteristics. Comparison of acute lymphoblastic leukemia (ALL) samples from the same array and AML pediatric patient samples demonstrated disease specific signatures, but also identified the existence of shared constellations, suggesting joint protein deregulation between the diseases.