| Literature DB >> 29177190 |
Divyansh Agarwal1,2, Christoph Nowak3,4, Nancy R Zhang1,2, Lajos Pusztai5, Christos Hatzis5.
Abstract
Germline variants that affect the expression or function of proteins contribute to phenotypic variation in humans and likely determine individual characteristics and susceptibility to diseases including cancer. A number of high penetrance germline variants that increase cancer risk have been identified and studied, but germline functional polymorphisms are not typically considered in the context of cancer biology, where the focus is primarily on somatic mutations. Yet, there is evidence from familial cancers indicating that specific cancer subtypes tend to arise in carriers of high-risk germline variants (e.g., triple negative breast cancers in mutated BRCA carriers), which suggests that pre-existing germline variants may determine which complementary somatic driver mutations are needed to drive tumorigenesis. Recent genome sequencing studies of large breast cancer cohorts reported only a handful of highly recurrent driver mutations, suggesting that different oncogenic events drive individual cancers. Here, we propose that germline polymorphisms can function as oncogenic modifiers, or co-oncogenes, and these determine what complementary subsequent somatic events are required for full malignant transformation. Therefore, we propose that germline aberrations should be considered together with somatic mutations to determine what genes drive cancer and how they may be targeted.Entities:
Year: 2017 PMID: 29177190 PMCID: PMC5700137 DOI: 10.1038/s41523-017-0051-5
Source DB: PubMed Journal: NPJ Breast Cancer ISSN: 2374-4677
Fig. 1Germline variants may act as co-oncogenes in the dysregulation of biological processes that are the “hallmarks of cancer”
Significant associations between germline variants and somatic mutations detected in the TCGA breast cancer data at a false discovery rate ≤12%
| Somatic gene | Germline variant | Two-sided Fisher exact test | Direction | ||||
|---|---|---|---|---|---|---|---|
| rsID | Gene | SNP type | VAF 1000 genomes | VAF TCGA | |||
| Luminal A ( | |||||||
| SSPO | rs45551636 | PALB2 | Missense | 0.008 | 0.028 | 4 × 10–6 | Co-mutation |
| MACF1 | rs3923647 | TLR1 | Missense | 0.029 | 0.025 | 4 × 10–6 | Co-mutation |
| Luminal B ( | |||||||
| USH2A | rs8140287 | ISX | Missense | 0.031 | 0.045 | 9 × 10–5 | Co-mutation |
| ATP10B | rs2273137 | NOP56 | Missense | 0.118 | 0.084 | 8 × 10–5 | Co-mutation |
| PIK3CA | rs12099177 | MMP27 | Missense | 0.168 | 0.081 | 8 × 10–5 | Co-exclusion |
| SYNE1 | rs34605667 | MPDZ | Missense | 0.014 | 0.037 | 5 × 10–5 | Co-mutation |
| Basal ( | |||||||
| USH2A | rs17848337 | SREBF2 | Synonymous | 0.051 | 0.051 | 1 × 10–4 | Co-mutation |
| TP53 | rs55695858 | OBP2A | Missense | 0.173 | 0.224 | 1 × 10–4 | Co-mutation |
| HER2-enriched ( | |||||||
| EYS | rs2066518 | SMARCAL1 | Missense | 0.073 | 0.026 | 2 × 10–4 | Co-mutation |
| PIK3CA | rs3774372 | ULK4 | Missense | 0.173 | 0.176 | 1 × 10–4 | Co-mutation |
The germline variants included in this analysis were the 8598 CADD* predicted-deleterious SNPs (C-score ≥ 20). Only somatic mutations in canonical cancer genes listed in COSMIC and OMIM that had mutations in ≥2% of breast cancer cases were included (1649 mutations in 71 genes). Somatic mutations were aggregated at gene level for statistical comparison with individual SNPs. Molecular subtype annotation was available through the TCGA
(*) Combined annotation-dependent depletion[36]