Fig. 1

Evaluating HRD in exome-sequenced breast cancers. a Workflow for HRD classification of an exome-sequenced breast cancer sample. Each sample contains a profile of mutations, each of which has a probabilistic association with each of the 20 signature phenotypes, defined by a representative signature profile inferred from WGS data. The mutational profile is collated to calculate the probability of assignment of the respective sample to each of the 20 clusters. b Simulation analysis of SBS3-enrichment classification of ICGC samples downsampled to 50 mutational events constrained to varying indel proportions. Adding a small percentage of indels is sufficient to improve classification. AUC = area under the ROC curve for SBS3 enrichment classification. The dotted red line represents the mean proportion of indel events in the TCGA-BRCA cohort. c Classification of 968 exome-sequenced breast cancer samples from TCGA. The heat map indicates the probability of each sample (column) being assigned to each signature phenotype (rows). Samples are annotated by ER status and HR gene defects. The value p(HRD) is the sum of probabilities of assignment across the seven HRD-associated phenotypes. The label ‘Phenotype assigned’ refers to the phenotype to which the respective sample has the highest probability of assignment. d Summary of HRD cluster assignment probabilities across the TCGA-BRCA cohort. Samples with a total probability of HRD assignment greater than 0.79 (as shown by the dotted red line) would be assigned as HRD, whereas the rest would be deemed HR-proficient. e HRD classification of HR gene-defective and -positive samples in the TCGA-BRCA cohort. ‘HRD’ refers to samples with a probability of HRD assignment greater than 0.79. f F-score comparisons of HRD classifiers for exomes. ‘HRDi + ’ refers to the classifier developed in this study. The HRD index is presented using cutoffs of 42 and 63