Cellular Composition and 5hmC Signature Predict the Treatment Response of AML Patients to Azacitidine Combined with Chemotherapy

Author:

Liang Guanghao12ORCID,Wang Linchen12,You Qiancheng34,Cahill Kirk5,Chen Chuanyuan12,Zhang Wei67,Fulton Noreen58,Stock Wendy58,Odenike Olatoyosi58,He Chuan349,Han Dali1210ORCID

Affiliation:

1. Key Laboratory of Genomic and Precision Medicine Beijing Institute of Genomics Chinese Academy of Sciences and China National Center for Bioinformation Beijing 100101 China

2. College of Future Technology Sino‐Danish College University of Chinese Academy of Sciences Beijing 100049 China

3. Department of Chemistry and Institute for Biophysical Dynamics The University of Chicago Chicago IL 60637 USA

4. Howard Hughes Medical Institute Chicago IL 60637 USA

5. Section of Hematology/Oncology Department of Medicine University of Chicago Medicine Chicago IL 60637 USA

6. Department of Medicine University of California, San Diego La Jolla CA 92093 USA

7. Bristol‐Myers Squibb San Diego CA 92121 USA

8. Comprehensive Cancer Center University of Chicago Medicine Chicago IL 60637 USA

9. Department of Biochemistry and Molecular Biology The University of Chicago Chicago IL 60637 USA

10. Institute for Stem Cell and Regeneration Chinese Academy of Sciences Beijing 100101 China

Abstract

AbstractAzacitidine (AZA) is a DNA methyltransferase inhibitor and epigenetic modulator that can be an effective agent in combination with chemotherapy for patients with high‐risk acute myeloid leukemia (AML). However, biological factors driving the therapeutic response of such hypomethylating agent (HMA)‐based therapies remain unknown. Herein, the transcriptome and/or genome‐wide 5‐hydroxymethylcytosine (5hmC) is characterized for 41 patients with high‐risk AML from a phase 1 clinical trial treated with AZA epigenetic priming followed by high‐dose cytarabine and mitoxantrone (AZA‐HiDAC‐Mito). Digital cytometry reveals that responders have elevated Granulocyte‐macrophage‐progenitor‐like (GMP‐like) malignant cells displaying an active cell cycle program. Moreover, the enrichment of natural killer (NK) cells predicts a favorable outcome in patients receiving AZA‐HiDAC‐Mito therapy or other AZA‐based therapies. Comparing 5hmC profiles before and after five‐day treatment of AZA shows that AZA exposure induces dose‐dependent 5hmC changes, in which the magnitude correlates with overall survival (p= 0.015). An extreme gradient boosting (XGBoost) machine learning model is developed to predict the treatment response based on 5hmC levels of 11 genes, achieving an area under the curve (AUC) of 0.860. These results suggest that cellular composition markedly impacts the treatment response, and showcase the prospect of 5hmC signatures in predicting the outcomes of HMA‐based therapies in AML.

Funder

National Natural Science Foundation of China

K. C. Wong Education Foundation

Howard Hughes Medical Institute

National Cancer Institute

Publisher

Wiley

Subject

General Physics and Astronomy,General Engineering,Biochemistry, Genetics and Molecular Biology (miscellaneous),General Materials Science,General Chemical Engineering,Medicine (miscellaneous)

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