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. 2017 Feb 17;7(2):e529.
doi: 10.1038/bcj.2017.10.

A novel approach for the identification of efficient combination therapies in primary human acute myeloid leukemia specimens

Affiliations

A novel approach for the identification of efficient combination therapies in primary human acute myeloid leukemia specimens

I Baccelli et al. Blood Cancer J. .

Abstract

Appropriate culture methods for the interrogation of primary leukemic samples were hitherto lacking and current assays for compound screening are not adapted for large-scale investigation of synergistic combinations. In this study, we report a novel approach that efficiently distills synthetic lethal interactions between small molecules active on primary human acute myeloid leukemia (AML) specimens. In single-dose experiments and under culture conditions preserving leukemia stem cell activity, our strategy considerably reduces the number of tests needed for the identification of promising compound combinations. Initially conducted with a selected library of 5000 small molecules and 20 primary AML specimens, it reveals 5 broad classes of sensitized therapeutic target pathways along with their synergistic patient-specific fingerprints. This novel method opens new avenues for the development of AML personalized therapeutics and may be generalized to other tumor types, for which in vitro cancer stem cell cultures have been developed.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Primary screen overview. (a) Overview of the primary screen workflow. (b) Pie-chart representation of hit compounds (drugs achieving >50% inhibition compared with DMSO-treated controls in at least one sample of the cohort) versus non-hit compounds. (c) Frequencies of selective (effective in 1–19 samples) versus non-selective (effective in all 20 specimens) hits. AML, acute myeloid leukemia; LSC, leukemic stem cells.
Figure 2
Figure 2
Primary screen results. (a) Overview of the genetic diversity of the 20 AML specimens included in the primary screen and the number and frequencies of hits per patient. (b) Number of hits with regards to genetic risk classes. P-values were assessed by Mann–Whitney test and data are presented as mean±s.d. Bi, bi-allelic; ITD, internal tandem duplication; PTD, partial tandem duplication.
Figure 3
Figure 3
Identification of CCCs. (a) Scheme summarizing the concept of CCCs. (b) Icicle representation of selective hit compounds of the primary screen highlighting five peaks of strongly correlating compounds (CCCs) with σ⩾0.9. (c) Each CCC is composed of compounds belonging to several chemotypes (series of chemical entities that share a similar scaffold), which are specific to a given CCC. CCC, Compound Correlation Cluster.
Figure 4
Figure 4
CCC inhibitory patterns. (a) Example of correlation matrixes between compounds belonging to CCC2. (b) Inhibitory patterns of the five CCCs in the primary screen cohort and corresponding genetic sample main characteristics (only genes mutated in ⩾2 samples are shown). CCC representative compounds are highlighted in red. AML, acute myeloid leukemia; Bi, bi-allelic; CCC, Compound Correlation Cluster; ITD, internal tandem duplication; Max: maximum; Min, minimum; PTD, partial tandem duplication; VEGF, vascular endothelial growth factor.
Figure 5
Figure 5
CCC synergistic fingerprints. (a) Synergy screen workflow overview. (b) CCC synergistic fingerprints of AML samples (left panel) and normal CD34-positive, mobilized peripheral blood samples (right panel). Cumulative synergistic effects were obtained as described in Dietlein et al., 2015. Red indicates synergism (positive cumulative effect) and blue antagonism (negative cumulative effects). Recurrent synergistic interactions are highlighted with thicker red boxes. Raw data are available in Supplementary Table 6. (c) Cumulative synergistic effects of CCC3 and CCC5 representative compound combinations in AML specimens (n=9) and in normal controls (n=2). Significance was probed by Mann–Whitney test. AML, acute myeloid leukemia; CCC, Compound Correlation Cluster; LSC, leukemia stem cell, PB, peripheral blood.
Figure 6
Figure 6
Inhibitory patterns and synergistic fingerprints of two distinct compounds of a same CCC. (a) Chemical structures of two members of CCC3: Deguelin and Mubritinib. (b) Correlation between EC50 values of Deguelin and Mubritinib in AML cells. (c) Comparison of the synergistic patterns of Deguelin and Mubritinib. AML, acute myeloid leukemia; CCC, Compound Correlation Cluster.

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