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Eide CA, Kurtz SE, Kaempf A, Long N, Joshi SK, Nechiporuk T, Huang A, Dibb CA, Taylor A, Bottomly D, McWeeney SK, Minnier J, Lachowiez CA, Saultz JN, Swords RT, Agarwal A, Chang BH, Druker BJ, Tyner JW. Clinical Correlates of Venetoclax-Based Combination Sensitivities to Augment Acute Myeloid Leukemia Therapy. Blood Cancer Discov 2023; 4:452-467. [PMID: 37698624 PMCID: PMC10618724 DOI: 10.1158/2643-3230.bcd-23-0014] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/17/2023] [Accepted: 09/06/2023] [Indexed: 09/13/2023] Open
Abstract
The BCL2 inhibitor venetoclax combined with the hypomethylating agent azacytidine shows significant clinical benefit in a subset of patients with acute myeloid leukemia (AML); however, resistance limits response and durability. We prospectively profiled the ex vivo activity of 25 venetoclax-inclusive combinations on primary AML patient samples to identify those with improved potency and synergy compared with venetoclax + azacytidine (Ven + azacytidine). Combination sensitivities correlated with tumor cell state to discern three patterns: primitive selectivity resembling Ven + azacytidine, monocytic selectivity, and broad efficacy independent of cell state. Incorporation of immunophenotype, mutation, and cytogenetic features further stratified combination sensitivity for distinct patient subtypes. We dissect the biology underlying the broad, cell state-independent efficacy for the combination of venetoclax plus the JAK1/2 inhibitor ruxolitinib. Together, these findings support opportunities for expanding the impact of venetoclax-based drug combinations in AML by leveraging clinical and molecular biomarkers associated with ex vivo responses. SIGNIFICANCE By mapping drug sensitivity data to clinical features and tumor cell state, we identify novel venetoclax combinations targeting patient subtypes who lack sensitivity to Ven + azacytidine. This provides a framework for a taxonomy of AML informed by readily available sets of clinical and genetic features obtained as part of standard care. See related commentary by Becker, p. 437 . This article is featured in Selected Articles from This Issue, p. 419.
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Affiliation(s)
- Christopher A. Eide
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Stephen E. Kurtz
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
- Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Andy Kaempf
- Biostatistics Shared Resource, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Nicola Long
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Sunil Kumar Joshi
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Tamilla Nechiporuk
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Ariane Huang
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Charles A. Dibb
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Akosha Taylor
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Daniel Bottomly
- Division of Bioinformatics and Computational Biomedicine, Department of Medical Informatics and Clinical Epidemiology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Shannon K. McWeeney
- Division of Bioinformatics and Computational Biomedicine, Department of Medical Informatics and Clinical Epidemiology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Jessica Minnier
- Biostatistics Shared Resource, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Curtis A. Lachowiez
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Jennifer N. Saultz
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Ronan T. Swords
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Anupriya Agarwal
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Bill H. Chang
- Division of Pediatric Hematology and Oncology, Knight Cancer Institute, Doernbecher Children's Hospital, Oregon Health and Science University, Portland, Oregon
| | - Brian J. Druker
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
- Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
| | - Jeffrey W. Tyner
- Division of Hematology and Medical Oncology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
- Department of Cell, Developmental, and Cancer Biology, Knight Cancer Institute, Oregon Health and Science University, Portland, Oregon
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