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Guarducci C, Nardone A, Russo D, Nagy Z, Heraud C, Grinshpun A, Zhang Q, Freelander A, Leventhal MJ, Feit A, Cohen Feit G, Feiglin A, Liu W, Hermida-Prado F, Kesten N, Ma W, De Angelis C, Morlando A, O'Donnell M, Naumenko S, Huang S, Nguyen QD, Huang Y, Malorni L, Bergholz JS, Zhao JJ, Fraenkel E, Lim E, Schiff R, Shapiro GI, Jeselsohn R. Selective CDK7 Inhibition Suppresses Cell Cycle Progression and MYC Signaling While Enhancing Apoptosis in Therapy-resistant Estrogen Receptor-positive Breast Cancer. Clin Cancer Res 2024; 30:1889-1905. [PMID: 38381406 PMCID: PMC11061603 DOI: 10.1158/1078-0432.ccr-23-2975] [Citation(s) in RCA: 0] [Impact Index Per Article: 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: 09/28/2023] [Revised: 01/09/2024] [Accepted: 02/16/2024] [Indexed: 02/22/2024]
Abstract
PURPOSE Resistance to endocrine therapy (ET) and CDK4/6 inhibitors (CDK4/6i) is a clinical challenge in estrogen receptor (ER)-positive (ER+) breast cancer. Cyclin-dependent kinase 7 (CDK7) is a candidate target in endocrine-resistant ER+ breast cancer models and selective CDK7 inhibitors (CDK7i) are in clinical development for the treatment of ER+ breast cancer. Nonetheless, the precise mechanisms responsible for the activity of CDK7i in ER+ breast cancer remain elusive. Herein, we sought to unravel these mechanisms. EXPERIMENTAL DESIGN We conducted multi-omic analyses in ER+ breast cancer models in vitro and in vivo, including models with different genetic backgrounds. We also performed genome-wide CRISPR/Cas9 knockout screens to identify potential therapeutic vulnerabilities in CDK4/6i-resistant models. RESULTS We found that the on-target antitumor effects of CDK7 inhibition in ER+ breast cancer are in part p53 dependent, and involve cell cycle inhibition and suppression of c-Myc. Moreover, CDK7 inhibition exhibited cytotoxic effects, distinctive from the cytostatic nature of ET and CDK4/6i. CDK7 inhibition resulted in suppression of ER phosphorylation at S118; however, long-term CDK7 inhibition resulted in increased ER signaling, supporting the combination of ET with a CDK7i. Finally, genome-wide CRISPR/Cas9 knockout screens identified CDK7 and MYC signaling as putative vulnerabilities in CDK4/6i resistance, and CDK7 inhibition effectively inhibited CDK4/6i-resistant models. CONCLUSIONS Taken together, these findings support the clinical investigation of selective CDK7 inhibition combined with ET to overcome treatment resistance in ER+ breast cancer. In addition, our study highlights the potential of increased c-Myc activity and intact p53 as predictors of sensitivity to CDK7i-based treatments.
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Affiliation(s)
- Cristina Guarducci
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Agostina Nardone
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Douglas Russo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Zsuzsanna Nagy
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Capucine Heraud
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Albert Grinshpun
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Qi Zhang
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Allegra Freelander
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Mathew Joseph Leventhal
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
- Computational and Systems Biology PhD program, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Avery Feit
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Gabriella Cohen Feit
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ariel Feiglin
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts
| | - Weihan Liu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Francisco Hermida-Prado
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Nikolas Kesten
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Wen Ma
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Carmine De Angelis
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Department of Clinical Medicine and Surgery, University of Naples “Federico II”, Naples, Italy
| | - Antonio Morlando
- Bioinformatics Unit, Department of Oncology, Hospital of Prato, Azienda USL Toscana Centro, Prato, Italy
| | - Madison O'Donnell
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Sergey Naumenko
- Department of Biostatistics, Harvard Chan School of Public Health, Boston, Massachusetts
| | - Shixia Huang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, Texas
| | - Quang-Dé Nguyen
- Lurie Family Imaging Center, Center for Biomedical Imaging in Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Ying Huang
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Luca Malorni
- Translational Research Unit, Department of Oncology, Hospital of Prato, Azienda USL Toscana Centro, Prato, Italy
| | - Johann S. Bergholz
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Jean J. Zhao
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts
| | - Ernest Fraenkel
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Elgene Lim
- Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Rachel Schiff
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, Texas
| | - Geoffrey I. Shapiro
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Rinath Jeselsohn
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
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Guarducci C, Cristea S, Feit A, Naumenko S, Nardone A, Ma W, Russo D, Feit GC, Feiglin A, Hermida-Prado F, Sherman S, Brown M, Michor F, Jeselsohn R. Abstract GS3-07: GS3-07 Clonal evolution and mechanisms of acquired resistance to CDK4/6 inhibitors in ER-wild type and ER-mutant breast cancer. Cancer Res 2023. [DOI: 10.1158/1538-7445.sabcs22-gs3-07] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Abstract
Background Despite the remarkable activity of CDK4/6 inhibitors (CDK4/6i) in the treatment of estrogen receptor positive (ER+) metastatic breast cancer (BC), most patients eventually develop resistance to these drugs. The ctDNA analysis of the PALOMA-3 trial showed that the estrogen receptor (ER) mutation Y537S is a potential mechanism of acquired resistance to the combination of endocrine therapy (ET) with CDK4/6i. To date, the role of the ER mutations in the clonal evolution and the mechanisms of acquired resistance to CDK4/6i is unknown. Moreover, it is not known if the development of resistance to CDK4/6i in the presence or absence of ER mutations is due to the expansion of pre-existing resistant clones or to the de novo acquisition of resistance mechanisms. Methods To explore the clonal evolution and the mechanisms of resistance to CDK4/6i in ER-wild type (ER-WT) and ER-mutant (ER-Mut) BC, we transduced doxycycline (DOX)-inducible Y537S ER-Mut MCF7 cells with the ClonTracer library, a high-complexity DNA barcode library, and cultured the barcoded cells without DOX (MCF7), or with DOX to induce the expression of the Y537S ER mutation (MCF7-YS). To develop Palbociclib (Palbo)-resistant (PDR) and Abemaciclib (Abema)-resistant (ABR) cell models, the barcoded MCF7 and MCF7-YS cells were passaged in culture with increasing concentrations of Palbo and Abema until the acquisition of resistance. The clonal dynamics and the molecular characteristics of the PDR and ABR models were investigated by barcode sequencing, whole-exome sequencing (WES), bulk and single cell RNA sequencing (RNAseq) and protein analyses. Finally, using an ER-Mut barcoded mice model, we compared the in vitro clonal evolution of ER-Mut CDK4/6i-resistant cells with the in vivo clonal evolution of ER-Mut metastases. Results The analysis of the barcodes revealed that during the acquisition of resistance to either Palbo or Abema there is a strong clonal selection of pre-existing resistant clones. The PDR clones were different in the presence of the Y537S mutation versus WT-ER. In contrast, the clones enriched in the ABR cells were comparable between WT and mutant ER. Furthermore, the ER mutations led to decreased diversity of the enriched clones in the PDR but not in the ABR cells. Interestingly, the barcodes enriched in the PDR and ABR models did not overlap. Unsupervised analyses showed that the samples clustering based on the barcodes fractions and the mutations were similar, suggesting that the clonal selection was driven by cellular populations with specific mutational landscapes. All the ER-WT and ER-Mut resistant models had different transcriptional profiles and by single-cell RNAseq showed various degrees of intra-sample heterogeneity. At the protein level, the PDR and the ABR cells displayed downregulation of ER, Rb and p27 and upregulation of p21. In the ER-Mut conditions Cyclin D1 was upregulated in the PDR cells, while Cyclin E was upregulated in the ABR cells. Finally, the barcode sequencing of the mice metastases revealed that the clonal selection in ER-Mut metastases and in ER-Mut CDK4/6i-resistant cells is different. Conclusion Our study suggests that the development of resistance to CDK4/6i is due to the selection of pre-existing resistant clones. We also demonstrate that the expression of the Y537S ER mutation impacts the clonal evolution and the mechanisms of acquired resistance to Palbo but not to Abema. Finally, we show that the clonal evolution and mechanisms are disparate in Palbo and Abema resistance. These results support the addition of a third drug to CDK4/6i and ET, early in treatment, to delay the selection of pre-existing resistant clones and prolong the response to treatment and highlight differences between Palbo and Abema.
Citation Format: Cristina Guarducci, Simona Cristea, Avery Feit, Sergey Naumenko, Agostina Nardone, Wen Ma, Douglas Russo, Gabriella Cohen Feit, Ariel Feiglin, Francisco Hermida-Prado, Shira Sherman, Myles Brown, Franziska Michor, Rinath Jeselsohn. GS3-07 Clonal evolution and mechanisms of acquired resistance to CDK4/6 inhibitors in ER-wild type and ER-mutant breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS3-07.
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Affiliation(s)
- Cristina Guarducci
- 1Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Simona Cristea
- 2Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Biostatistics, Harvard Chan School of Public Health, Boston, MA, USA
| | - Avery Feit
- 3Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Sergey Naumenko
- 4Department of Biostatistics, Harvard Chan School of Public Health, Boston, MA, USA
| | - Agostina Nardone
- 5Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Wen Ma
- 6Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Douglas Russo
- 7Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Gabriella Cohen Feit
- 8Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Ariel Feiglin
- 9Department of Biomedical Informatics, Harvard Medical School, Boston, MA
| | - Francisco Hermida-Prado
- 10Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Shira Sherman
- 11Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Myles Brown
- 12Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA; Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA
| | - Franziska Michor
- 13Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA; Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA, USA
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