Histone Modification Patterns Using RPPA-Based Profiling Predict Outcome in Acute Myeloid Leukemia Patients

Background: Prognostic factors based on cytogenetic and molecular abnormalities combined with clinical features like age, performance status, or history of an antecedent hematological disorder, are currently used to predict clinical outcome in acute myeloid leukemia (AML). (Döhner H. et al. 2010) Although, sequencing of AML has identified many driver mutations in genes associated with epigenetic regulation, e.g. post-translational histone tail modifications. Altered activity of post-translational histone tail modifications has been shown to contribute to AML leukemogenesis via regulation of gene transcription. (Fong C.Y. et al. 2014) The functions and effects of modulating histone-modifying proteins (HMP) are already typically studied by altering an individual protein of interest. However in AML, it is the net consequence of the combined influences of all the HMP, rather than a single protein, that determines the net effect on the cell. A global analysis of the level and patterns of expression of multiple HMP and the effect of different patterns of expression on outcome and prognosis has not been investigated in AML patients.

Methods: We analyzed 20 HMP by reverse phase protein array (RPPA) in a cohort of 205 newly diagnosed AML patients evaluated at the University of Texas M.D. Anderson Cancer Center. (Kornblau S.M. et al. 2009) Protein levels were correlated with patient and disease characteristics, including survival and mutational state.

Results: Different protein clusters were identified and characterized by higher (more on) or lower (more off) expression of HMP, relative to normal CD34+ cells (figure 1A). We found that the more on state of HMP was associated with poorer overall survival (P= 0.007, figure 1B) and more chemo resistance (P < 0.001) compared to normal -like and a more off state. Furthermore, FLT3 mutated AML patients were significantly overrepresented in the more on state (P= 0.025). Identification of the markedly upregulated proteins: KDM1A, hnRNPK, NCL, SIRT1, ASH2L, WTAP in all, and BRD4 and NPM1 in some on state patients suggest targets to develop drugs against that may be the most efficacious when used individually or in combination.

Conclusions: These findings showed for the first time that multiple HMP form recurrent patterns of expression and that these significantly correlate with prognosis, chemo resistance, and FLT3 mutational state in newly diagnosed AML patients.

F igure legend 1:

(A) RPPA-based heatmap containing 20 histone modification related proteins showing only 205 fresh AML patient samples. Clusters were determined by a progeny clustering based algorithm coupled with k-means, which computationally calculated the optimal number of five clusters. The five cluster colors along the top bar delineate the five fresh clusters. Cluster 1 (red) was defined as a normal -like pattern by principal component analysis, whereas clusters 2, 3, 6 and 7 were only seen with leukemic samples. Expression is normalized for each protein to range from the lowest (blue) to the highest (red). Cluster 2 and 7 were defined as the more on clusters and cluster 3 and 6 as the more off clusters.

(B) Overall Survival of patients from the normal -like histone-modifying proteins (HMP) cluster (n=61), more on HMP clusters (n=131) and the more off HMP clusters (n=13) as determined in our cohort of newly diagnosed AML fresh patient samples by RPPA-based profiling. The survival of patients with the more on state of HMP was significantly reduced compared to the more off state and the normal- like HMP signatures.

Figure 1

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Figure 1

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