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CHRONIC MYELOGENOUS LEUKEMIA

Identification of key microRNAs as predictive biomarkers of Nilotinib response in chronic myeloid leukemia: a sub-analysis of the ENESTxtnd clinical trial

Leukemia volume 36, pages 2443–2452 (2022)Cite this article

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Abstract

Despite the effectiveness of tyrosine kinase inhibitors (TKIs) against chronic myeloid leukemia (CML), they are not usually curative as some patients develop drug-resistance or are at risk of disease relapse when treatment is discontinued. Studies have demonstrated that primitive CML cells display unique miRNA profiles in response to TKI treatment. However, the utility of miRNAs in predicting treatment response is not yet conclusive. Here, we analyzed differentially expressed miRNAs in CD34+ CML cells pre- and post-nilotinib (NL) therapy from 58 patients enrolled in the Canadian sub-analysis of the ENESTxtnd phase IIIb clinical trial which correlated with sensitivity of CD34+ cells to NL treatment in in vitro colony-forming cell (CFC) assays. We performed Cox Proportional Hazard (CoxPH) analysis and applied machine learning algorithms to generate multivariate miRNA panels which can predict NL response at treatment-naïve or post-treatment time points. We demonstrated that a combination of miR-145 and miR-708 are effective predictors of NL response in treatment-naïve patients whereas miR-150 and miR-185 were significant classifiers at 1-month and 3-month post-NL therapy. Interestingly, incorporation of NL-CFC output in these panels enhanced predictive performance. Thus, this novel predictive model may be developed into a prognostic tool for use in the clinic.

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Fig. 1: Comparison of the effect of TKIs in vitro on CD34+ cells from NL-responders and nonresponders.
Fig. 2: Study design and univariate analysis of 47 differentially expressed miRNAs between NL-responders and nonresponders.
Fig. 3: Multivariate analysis of miRNAs associated with NL-nonresponse in treatment naïve patients (BL).
Fig. 4: Multivariate analysis of miRNAs associated with NL-nonresponse in 1-Month post-treatment patients (M1).
Fig. 5: Multivariate analysis of miRNAs associated with NL-nonresponse in 3-month post-treatment patients (M3).

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Acknowledgements

We thank the Stem Cell Assay Laboratory staff for processing patient samples, Josephine Leung and Kyi Min Saw for excellent technical assistance, members of the Leukemia/Bone Marrow Transplant Program of British Columbia and the Hematology Cell Bank of British Columbia for patient samples, the Terry Fox Laboratory FACS Facility for cell sorting and STEMCELL Technologies for culture reagents.

Funding

This work was supported by the Canadian Cancer Society, the Leukemia & Lymphoma Society of Canada, the Canadian Institutes of Health Research (CIHR) and the Collings Stevens Chronic Leukemia Research Fund (XJ). RY received a Four-Year Fellowship from UBC and a CIHR Frederick Banting and Charles Best Canada Graduate Scholarship; SG is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation—project 446251518), Michael Smith Health Research BC and the Lotte & John Hecht Memorial Foundation (project RT-2020-0578); AW and JS received MITACS Accelerate Fellowships; KR was a MITACS Elevate Postdoctoral Fellow.

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Authors and Affiliations

  1. Terry Fox Laboratory, British Columbia Cancer Research Institute, Vancouver, BC, Canada

    Ryan Yen, Andrew Wu, Hanyang Lin, Jiechuang Su, Katharina Rothe, Helen Nakamoto, Connie J. Eaves & Xiaoyan Jiang

  2. Department of Medicine, University of British Columbia, Vancouver, BC, Canada

    Ryan Yen, Andrew Wu, Donna L. Forrest, Connie J. Eaves & Xiaoyan Jiang

  3. Michael Smith Laboratories, Dept of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada

    Sarah Grasedieck

  4. Leukemia/Bone Marrow Transplant Program of British Columbia, Vancouver, BC, Canada

    Donna L. Forrest

  5. Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada

    Connie J. Eaves & Xiaoyan Jiang

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Contributions

DLF, CE and XJ developed the concept and designed the experiments; RY performed data analyses and statistical and bioinformatics analyses; SG provided expertise in complex statistical and data analyses and insightful discussions; HL, HN, JS, KR, AW performed q-RT-PCR, CFC experiments and data analyses; DLF provided the clinical data and insightful discussions; AW, RY, SG, JS, and XJ wrote the manuscript and all authors commented on it.

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Correspondence to Xiaoyan Jiang.

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Research funding: Novartis Canada (DLF, CE, and XJ). Other authors declare no conflicts of interests.

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Yen, R., Grasedieck, S., Wu, A. et al. Identification of key microRNAs as predictive biomarkers of Nilotinib response in chronic myeloid leukemia: a sub-analysis of the ENESTxtnd clinical trial. Leukemia 36, 2443–2452 (2022). https://doi.org/10.1038/s41375-022-01680-4

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