Effects of germline and somatic events in candidate BRCA-like genes on breast-tumor signatures

Abstract

Mutations in BRCA1 and BRCA2 cause deficiencies in homologous recombination repair (HR), resulting in repair of DNA double-strand breaks by the alternative non-homologous end-joining pathway, which is more error prone. HR deficiency of breast tumors is important because it is associated with better responses to platinum salt therapies and PARP inhibitors. Among other consequences of HR deficiency are characteristic somatic-mutation signatures and gene-expression patterns. The term "BRCA-like" (or "BRCAness") describes tumors that harbor an HR defect but have no detectable germline mutation in BRCA1 or BRCA2. A better understanding of the genes and molecular events associated with tumors being BRCA-like could provide mechanistic insights and guide development of targeted treatments. Using data from The Cancer Genome Atlas (TCGA) for 1101 breast-cancer patients, we identified individuals with a germline mutation, somatic mutation, homozygous deletion, and/or hypermethylation event in BRCA1, BRCA2, and 59 other cancer-predisposition genes. Based on the assumption that BRCA-like events would have similar downstream effects on tumor biology as BRCA1/BRCA2 germline mutations, we quantified these effects based on somatic-mutation signatures and gene-expression profiles. We reduced the dimensionality of the somatic-mutation signatures and expression data and used a statistical resampling approach to quantify similarities among patients who had a BRCA1/BRCA2 germline mutation, another type of aberration in BRCA1 or BRCA2, or any type of aberration in one of the other genes. Somatic-mutation signatures of tumors having a non-germline aberration in BRCA1/BRCA2 (n = 80) were generally similar to each other and to tumors from BRCA1/BRCA2 germline carriers (n = 44). Additionally, somatic-mutation signatures of tumors with germline or somatic events in ATR (n = 16) and BARD1 (n = 8) showed high similarity to tumors from BRCA1/BRCA2 carriers. Other genes (CDKN2A, CTNNA1, PALB2, PALLD, PRSS1, SDHC) also showed high similarity but only for a small number of events or for a single event type. Tumors with germline mutations or hypermethylation of BRCA1 had relatively similar gene-expression profiles and overlapped considerably with the Basal-like subtype; but the transcriptional effects of the other events lacked consistency. Our findings confirm previously known relationships between molecular signatures and germline or somatic events in BRCA1/BRCA2. Our methodology represents an objective way to identify genes that have similar downstream effects on molecular signatures when mutated, deleted, or hypermethylated.

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.

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.