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Comparative oncogenomics identifies combinations of driver genes and drug targets in BRCA1-mutated breast cancer
Stefano Annunziato1,2,3, Julian R de Ruiter1,2,3,4, Linda Henneman1,5
1Division of Molecular Pathology, The Netherlands Cancer Institute, 1066 CX, Amsterdam, The Netherlands.
Abstract:
BRCA1-mutated breast cancer is primarily driven by DNA copy-number alterations (CNAs) containing large numbers of candidate driver genes. Validation of these candidates requires novel approaches for high-throughput in vivo perturbation of gene function. Here we develop genetically engineered mouse models (GEMMs) of BRCA1-deficient breast cancer that permit rapid introduction of putative drivers by either retargeting of GEMM-derived embryonic stem cells, lentivirus-mediated somatic overexpression or in situ CRISPR/Cas9-mediated gene disruption. We use these approaches to validate Myc, Met, Pten and Rb1 as bona fide drivers in BRCA1-associated mammary tumorigenesis. Iterative mouse modeling and comparative oncogenomics analysis show that MYC-overexpression strongly reshapes the CNA landscape of BRCA1-deficient mammary tumors and identify MCL1 as a collaborating driver in these tumors. Moreover, MCL1 inhibition potentiates the in vivo efficacy of PARP inhibition (PARPi), underscoring the therapeutic potential of this combination for treatment of BRCA1-mutated cancer patients with poor response to PARPi monotherapy.
Insights
Researchers developed new mouse models to study BRCA1-mutated breast cancer, identifying Myc, Met, Pten, and Rb1 as drivers. They also found MCL1 as a collaborating driver, suggesting a combination therapy with PARP inhibitors for better patient outcomes.
Area of Science:
- Oncology
- Genetics
- Cancer Biology
Background:
- BRCA1-mutated breast cancer is driven by DNA copy-number alterations (CNAs) with numerous candidate driver genes.
- Validating these drivers necessitates high-throughput in vivo methods for gene function perturbation.
Purpose of the Study:
- To develop and utilize genetically engineered mouse models (GEMMs) for rapid functional validation of driver genes in BRCA1-deficient breast cancer.
- To identify novel collaborating drivers and therapeutic targets in this cancer subtype.
Main Methods:
- Development of GEMMs for BRCA1-deficient breast cancer.
- Introduction of putative drivers via embryonic stem cell retargeting, lentiviral somatic overexpression, and CRISPR/Cas9 gene disruption.
- Comparative oncogenomics analysis and iterative mouse modeling.
Main Results:
- Validated Myc, Met, Pten, and Rb1 as bona fide drivers in BRCA1-associated mammary tumorigenesis.
- Demonstrated that MYC overexpression significantly alters the CNA landscape in BRCA1-deficient tumors.
- Identified MCL1 as a collaborating driver and showed MCL1 inhibition enhances PARP inhibitor (PARPi) efficacy in vivo.
Conclusions:
- Novel GEMMs enable efficient validation of driver genes in BRCA1-mutated breast cancer.
- MYC and MCL1 are key players in BRCA1-deficient mammary tumorigenesis.
- Combination therapy of MCL1 inhibition with PARPi shows therapeutic promise for patients with BRCA1-mutated cancer refractory to PARPi monotherapy.
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