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Updated: Jul 11, 2025

Identifying the Effects of BRCA1 Mutations on Homologous Recombination using Cells that Express Endogenous Wild-type BRCA1
Published on: February 17, 2011
Multi-scale characterisation of homologous recombination deficiency in breast cancer
Daniel H Jacobson1,2, Shi Pan1, Jasmin Fisher2
1UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, Gower Street, London, WC1E 6BT, UK.
Background:
Homologous recombination is a robust, broadly error-free mechanism of double-strand break repair, and deficiencies lead to PARP inhibitor sensitivity. Patients displaying homologous recombination deficiency can be identified using 'mutational signatures'. However, these patterns are difficult to reliably infer from exome sequencing. Additionally, as mutational signatures are a historical record of mutagenic processes, this limits their utility in describing the current status of a tumour.
Methods:
We apply two methods for characterising homologous recombination deficiency in breast cancer to explore the features and heterogeneity associated with this phenotype. We develop a likelihood-based method which leverages small insertions and deletions for high-confidence classification of homologous recombination deficiency for exome-sequenced breast cancers. We then use multinomial elastic net regression modelling to develop a transcriptional signature of heterogeneous homologous recombination deficiency. This signature is then applied to single-cell RNA-sequenced breast cancer cohorts enabling analysis of homologous recombination deficiency heterogeneity and differential patterns of tumour microenvironment interactivity.
Results:
We demonstrate that the inclusion of indel events, even at low levels, improves homologous recombination deficiency classification. Whilst BRCA-positive homologous recombination deficient samples display strong similarities to those harbouring BRCA1/2 defects, they appear to deviate in microenvironmental features such as hypoxic signalling. We then present a 228-gene transcriptional signature which simultaneously characterises homologous recombination deficiency and BRCA1/2-defect status, and is associated with PARP inhibitor response. Finally, we show that this signature is applicable to single-cell transcriptomics data and predict that these cells present a distinct milieu of interactions with their microenvironment compared to their homologous recombination proficient counterparts, typified by a decreased cancer cell response to TNFα signalling.
Conclusions:
We apply multi-scale approaches to characterise homologous recombination deficiency in breast cancer through the development of mutational and transcriptional signatures. We demonstrate how indels can improve homologous recombination deficiency classification in exome-sequenced breast cancers. Additionally, we demonstrate the heterogeneity of homologous recombination deficiency, especially in relation to BRCA1/2-defect status, and show that indications of this feature can be captured at a single-cell level, enabling further investigations into interactions between DNA repair deficient cells and their tumour microenvironment.
Insights
Homologous recombination deficiency (HRD) in breast cancer can be better classified using small insertion/deletion events. A new transcriptional signature reveals HRD heterogeneity and its impact on the tumor microenvironment, aiding PARP inhibitor response prediction.
Area of Science:
- Genomics and Molecular Biology
- Cancer Research
- Bioinformatics
Background:
- Homologous recombination (HR) is a critical DNA repair pathway; deficiencies (HRD) are linked to PARP inhibitor sensitivity.
- Current methods for identifying HRD using mutational signatures from exome sequencing have limitations in accuracy and temporal relevance.
- Understanding HRD heterogeneity is crucial for effective cancer treatment strategies.
Purpose of the Study:
- To develop and validate novel methods for characterizing homologous recombination deficiency (HRD) in breast cancer.
- To explore the heterogeneity of HRD and its association with tumor microenvironment interactions.
- To identify a transcriptional signature predictive of HRD status and PARP inhibitor response.
Main Methods:
- Development of a likelihood-based classification method utilizing small insertion and deletion (indel) events from exome sequencing data.
- Application of multinomial elastic net regression to create a transcriptional signature for heterogeneous HRD.
- Validation of the transcriptional signature on single-cell RNA sequencing data for analyzing HRD heterogeneity and tumor microenvironment interactivity.
Main Results:
- Inclusion of indel events significantly improved HRD classification accuracy in exome-sequenced breast cancers.
- A 228-gene transcriptional signature was developed, capable of characterizing HRD and BRCA1/2 defect status, and predicting PARP inhibitor response.
- The signature applied to single-cell data revealed distinct tumor microenvironment interactions in HRD cells, including altered responses to TNFα signaling.
Conclusions:
- Multi-scale approaches combining mutational and transcriptional signatures provide robust characterization of HRD in breast cancer.
- Indels are valuable for improving HRD classification from exome sequencing, and transcriptional signatures capture HRD heterogeneity at a single-cell level.
- These findings enable deeper investigation into the interplay between DNA repair deficiencies and the tumor microenvironment, with implications for targeted therapies.
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