A transcriptomic based deconvolution framework for assessing differentiation stages and drug responses of AML

npj Precision Oncology, vol. 8, pp. 105

Abstract

The diagnostic spectrum for AML patients is increasingly based on genetic abnormalities due to their prognostic and predictive value. However, information on the AML blast phenotype regarding their maturational arrest has started to regain importance due to its predictive power for drug responses. Here, we deconvolute 1350 bulk RNA-seq samples from five independent AML cohorts on a single-cell healthy BM reference and demonstrate that the morphological differentiation stages (FAB) could be faithfully reconstituted using estimated cell compositions (ECCs). Moreover, we show that the ECCs reliably predict ex-vivo drug resistances as demonstrated for Venetoclax, a BCL-2 inhibitor, resistance specifically in AML with CD14+ monocyte phenotype. We validate these predictions using LUMC proteomics data by showing that BCL-2 protein abundance is split into two distinct clusters for NPM1-mutated AML at the extremes of CD14+ monocyte percentages, which could be crucial for the Venetoclax dosing patients. Our results suggest that Venetoclax resistance predictions can also be extended to AML without recurrent genetic abnormalities and possibly to MDS-related and secondary AML. Lastly, we show that CD14+ monocytic dominated Ven/Aza treated patients have significantly lower overall survival. Collectively, we propose a framework for allowing a joint mutation and maturation stage modeling that could be used as a blueprint for testing sensitivity for new agents across the various subtypes of AML.

Authors 13

1. Emin Onur Karakaslar Aachen Department of Biomedical Data Sciences Leiden Center for Computational Oncology

   Leiden University Medical Center · Delft University of Technology

   Affiliation as printed

   Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands

   Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands

   Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, The Netherlands

2. Jeppe F. Severens Aachen Department of Biomedical Data Sciences Leiden Center for Computational Oncology

   Leiden University Medical Center · Delft University of Technology

   Affiliation as printed

   Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands

   Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands

   Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, The Netherlands

3. Elena Sánchez‐López Aachen Center for Proteomics and Metabolomics Leiden Center for Computational Oncology

   Leiden University Medical Center

   Affiliation as printed

   Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands

   Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands

4. Peter A. van Veelen Aachen Center for Proteomics and Metabolomics

   Leiden University Medical Center

   Affiliation as printed

   Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands

5. Mihaela Zlei Aachen Department of Immunology, Leiden University Medical Center

   Leiden University Medical Center · Institutul Regional de Oncologie

   Affiliation as printed

   Department of Flow Cytometry, Medical Laboratory, Regional Institute of Oncology, Iasi, Romania

   Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands

6. Jacques J. M. van Dongen Aachen Department of Immunology, Leiden University Medical Center

   Consejo Superior de Investigaciones Científicas · Universidad de Salamanca · Leiden University Medical Center · Centro de Investigación del Cáncer · Instituto de Biología Molecular y Celular del Cáncer de Salamanca

   Affiliation as printed

   Centro de Investigación del Cáncer-Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC, USAL-CSIC-FICUS) and Department of Medicine, University of Salamanca, Salamanca, Spain

   Department of Immunology, Leiden University Medical Center, Leiden, The Netherlands

7. Annemarie M. Otte Aachen Center for Proteomics and Metabolomics

   Leiden University Medical Center

   Affiliation as printed

   Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands

8. Constantijn J.M. Halkes Aachen Department of Hematology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Hematology, Leiden University Medical Center, Leiden, The Netherlands

9. Peter van Balen Aachen Department of Hematology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Hematology, Leiden University Medical Center, Leiden, The Netherlands

10. Hendrik Veelken Aachen Department of Hematology, Leiden University Medical Center Leiden Center for Computational Oncology

    Leiden University Medical Center

    Affiliation as printed

    Department of Hematology, Leiden University Medical Center, Leiden, The Netherlands

    Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands

11. Marcel J. T. Reinders Aachen Department of Biomedical Data Sciences Leiden Center for Computational Oncology

    Leiden University Medical Center · Delft University of Technology

    Affiliation as printed

    Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands

    Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands

    Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, The Netherlands

12. Marieke Griffioen Aachen Department of Hematology, Leiden University Medical Center

    Leiden University Medical Center

    Affiliation as printed

    Department of Hematology, Leiden University Medical Center, Leiden, The Netherlands

13. Erik B. van den Akker corresponding Aachen Department of Biomedical Data Sciences Leiden Center for Computational Oncology

    Leiden University Medical Center · Delft University of Technology

    Affiliation as printed

    Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands. e.b.van_den_akker@lumc.nl

    Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands. e.b.van_den_akker@lumc.nl

    Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, The Netherlands. e.b.van_den_akker@lumc.nl

    Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, The Netherlands