Fig 1.
Two-dimensional representation of somatic-mutation signatures using multidimensional scaling.
We summarized each tumor based on their somatic-mutation signatures, which represent overall mutational patterns in a trinucleotide context. We used multidimensional scaling (MDS) to reduce the data to two dimensions. Each point represents a single tumor, overlaid with colors that represent the tumor’s primary somatic-mutation signature. Mutational Signature 1A (A) was the most prevalent; these tumors were widely dispersed across the signature landscape. Signatures 1B (B), 2 (C), and 3 (D) were relatively small and formed cohesive clusters. The remaining 23 clusters were rare individually and were dispersed broadly.
Fig 2.
Two-dimensional representation of gene-expression levels using multidimensional scaling.
We used multidimensional scaling (MDS) to reduce the gene-expression profiles to two dimensions. Each point represents a single tumor, overlaid with colors that represent the tumor’s primary PAM50 subtype. Generally, the PAM50 subtypes clustered cohesively, but there were exceptions. For example, some Basal-like tumors (A) exhbited expression patterns that differed considerably from the remaining Basal-like tumors. The normal-like tumors (E) showed the most variability in expression. This graph represents patients for whom we could identify a PAM50 subtype.
Fig 3.
Molecular aberrations in BRCA1 and BRCA2 across all breast-cancer patients.
A) Germline mutations, B) Somatic mutations, C) Copy-number variations, D) DNA methylation levels. SNV = single nucleotide variation.
Table 1.
Results of similarity comparisons among BRCA aberration groups.
We compared somatic-mutation signatures or gene-expression profiles between groups of patients who harbored aberrations in BRCA1 or BRCA2. We evaluated whether patients in one group (e.g., those who harbored a BRCA1 germline mutation) were more similar to patients in a second group (e.g., those with BRCA2 germline mutation) than random patient subsets of the same sizes. The numbers in this table represent empirical p-values from our resampling approach. In cases where an individual harbored an aberration in both comparison groups, we excluded that patient from the comparison. We used Holm’s method to correct for testing multiple hypotheses.
Fig 4.
Non-BRCA germline mutations on the somatic-mutation signature landscape using multidimensional scaling.
Using the same two-dimensional representation of mutational signatures shown in Fig 1, this plot indicates which patients had germline mutations in non-BRCA cancer-predisposition genes. Diamond shapes indicate patients for whom no loss-of-heterozygosity was observed.
Fig 5.
Non-BRCA somatic mutations on the somatic-mutation signature landscape using multidimensional scaling.
Using the same two-dimensional representation of mutational signatures shown in Fig 1, this plot indicates which patients had somatic mutations in non-BRCA cancer-predisposition genes. Diamond shapes indicate patients for whom no loss-of-heterozygosity was observed.
Fig 6.
Non-BRCA homozygous deletions on the somatic-mutation signature landscape using multidimensional scaling.
Using the same two-dimensional representation of mutational signatures shown in Fig 1, this plot indicates which patients had homozygous deletions in non-BRCA cancer-predisposition genes. Diamond shapes indicate patients for whom no loss-of-heterozygosity was observed.
Fig 7.
Non-BRCA hypermethylation events on the somatic-mutation signature landscape using multidimensional scaling.
Using the same two-dimensional representation of mutational signatures shown in Fig 1, this plot indicates which patients had hypermethylation events in non-BRCA cancer-predisposition genes. Diamond shapes indicate patients for whom no loss-of-heterozygosity was observed.
Table 2.
Summary of comparisons between the BRCA-like reference group and groups of patients who harbored a specific type of aberration in a candidate BRCA-like gene.
We evaluated whether somatic-mutation signatures from patients who harbored a given type of aberration (e.g., BARD1 germline mutation) were more similar to the BRCA-like reference group than expected by random chance. The numbers in this table represent empirical p-values from our resampling approach. In cases where no patient had a given type of aberration in a given gene, we list “N/A”. The “Any” group represents individuals who harbored any type of aberration in a given gene. We used Holm’s method to correct for testing multiple hypotheses.