Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL

Abstract

The Bruton tyrosine kinase (BTK) inhibitor ibrutinib has substantially improved therapeutic options for chronic lymphocytic leukemia (CLL). Although ibrutinib is not curative, it has a profound effect on CLL cells and may create new pharmacologically exploitable vulnerabilities. To identify such vulnerabilities, we developed a systematic approach that combines epigenome profiling (charting the gene-regulatory basis of cell state) with single-cell chemosensitivity profiling (quantifying cell-type-specific drug response) and bioinformatic data integration. By applying our method to a cohort of matched patient samples collected before and during ibrutinib therapy, we identified characteristic ibrutinib-induced changes that provide a starting point for the rational design of ibrutinib combination therapies. Specifically, we observed and validated preferential sensitivity to proteasome, PLK1, and mTOR inhibitors during ibrutinib treatment. More generally, our study establishes a broadly applicable method for investigating treatment-specific vulnerabilities by integrating the complementary perspectives of epigenetic cell states and phenotypic drug responses in primary patient samples.

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Fig. 1: Integrative analysis of epigenetic cell state and cell-selective chemosensitivity in ibrutinib-treated CLL patients.
Fig. 2: Chromatin accessibility mapping for matched CLL patient samples collected before and during ibrutinib treatment.
Fig. 3: Differential analysis of ibrutinib-induced changes in chromatin accessibility for matched CLL patient samples.
Fig. 4: Single-cell chemosensitivity profiling for matched CLL patient sample pairs collected before and during ibrutinib treatment.
Fig. 5: Prioritization and validation of ibrutinib-based drug combinations based on combined chemosensitivity and chromatin profiling.

Data availability

The ATAC-seq and pharmacoscopy data are available from http://cll-combinations.computational-epigenetics.org. The ATAC-seq data are also available from NCBI GEO under accession number GSE100672. The source code for ATAC-seq data processing is available from a Github repository linked on the above website.

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Acknowledgements

We thank all patients who have donated their samples for this study. We also thank the Biomedical Sequencing Facility at CeMM for assistance with next generation sequencing and J. Bigenzahn, M. Rebsamen as well as the G.S.-F. and C.B. labs for help and advice. This work was performed in the context of the following grants and fellowships: WWTF LS16-034 to G.S.-F. and U.J.; FWF SFB F 4711-B20 to G.S.-F.; EMBO Long-Term Fellowship 1543-2012 to G.I.V. and 733-2016 to T.P.; Swiss National Science Foundation Fellowship P300P3_147897 and PP00P3_163961 to B.S.; Marie-Sklodowska Curie Action Fellowship 703668 to N.K.; Feodor Lynen Fellowship of the Alexander von Humboldt Foundation to C. Schmidl; Marie Curie Action International Outgoing Fellowship (PIOF-2013-624924) to M.G.; Initiative Krebsforschung (UE71104017, UE71104005, UE71504001, and UE711043037), Austrian Society of Hematology and Oncology (ÖGHO AP00359OFF), and Anniversary Fund of the Austrian National Bank (OeNB AP130120ONB) to M.S.; Austrian Academy of Sciences New Frontiers Group Award and ERC Starting Grant (European Union’s Horizon 2020 research and innovation programme) 679146 to C.B.

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Contributions

C. Schmidl and T.K. performed ATAC-seq experiments; G.I.V., C.T., A.R., and K.R. performed image-based chemosensitivity experiments; C. Schmidl, G.I.V., A.F.R., N.K., B.S., O.L.d.l.F., and S.K. analyzed the ATAC-seq and image-based chemosensitivity data; S.S., C.T., T.P., M.A., R.H., D.D., M.H., and M.S. handled patient samples and performed validation experiments; M.S. and U.J. were responsible for study ethics; C. Skrabs, E.P., M.G., G.H., P.B.S., M.S., and U.J. provided and analyzed clinical data or oversaw patient care and ethics; C. Schmidl, G.I.V., A.F.R., T.P., M.S., G.S.-F., U.J., and C.B. wrote the manuscript; M.S., G.S.-F., U.J., and C.B. oversaw the project.

Corresponding author

Correspondence to Christoph Bock.

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Competing interests

G.I.V., N.K., B.S., G.S.-F. are co-founders of Allcyte GmbH, which has licensed the pharmacoscopy technology, and they are listed as inventors on patent applications for the pharmacoscopy / single-cell imaging methodology. G.I.V. and N.K. have become employees of Allcyte GmbH during the course of this study. U.J. received research grants and honoraria from Janssen Cilag, Abbvie, Novartis, and Roche Austria.

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Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7

Reporting Summary

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Source data for figures

Supplementary Table 1

Overview and clinical annotation of patient samples included in this study

Supplementary Table 2

Sample-specific sequencing statistics for the ATAC-seq experiments

Supplementary Table 3

List of all chromatin accessible regions detected in the ATAC-seq dataset

Supplementary Table 4

List of genomic regions with differential chromatin accessibility upon ibrutinib treatment

Supplementary Table 5

List of drugs and small molecules for the pharmacoscopy experiments

Supplementary Table 6

Selectivity scores before and during ibrutinib treatment for 131 drugs

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Schmidl, C., Vladimer, G.I., Rendeiro, A.F. et al. Combined chemosensitivity and chromatin profiling prioritizes drug combinations in CLL. Nat Chem Biol 15, 232–240 (2019). https://doi.org/10.1038/s41589-018-0205-2

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