A knowledge-based framework for the discovery of cancer-predisposing variants using large-scale sequencing breast cancer data

Giorgio E.M. Melloni, Luca Mazzarella, Loris Bernard, Margherita Bodini, Anna Russo, Lucilla Luzi, Pier Giuseppe Pelicci, Laura Riva

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: The landscape of cancer-predisposing genes has been extensively investigated in the last 30 years with various methodologies ranging from candidate gene to genome-wide association studies. However, sequencing data are still poorly exploited in cancer predisposition studies due to the lack of statistical power when comparing millions of variants at once. Method: To overcome these power limitations, we propose a knowledge-based framework founded on the characteristics of known cancer-predisposing variants and genes. Under our framework, we took advantage of a combination of previously generated datasets of sequencing experiments to identify novel breast cancer-predisposing variants, comparing the normal genomes of 673 breast cancer patients of European origin against 27,173 controls matched by ethnicity. Results: We detected several expected variants on known breast cancer-predisposing genes, like BRCA1 and BRCA2, and 11 variants on genes associated with other cancer types, like RET and AKT1. Furthermore, we detected 183 variants that overlap with somatic mutations in cancer and 41 variants associated with 38 possible loss-of-function genes, including PIK3CB and KMT2C. Finally, we found a set of 19 variants that are potentially pathogenic, negatively correlate with age at onset, and have never been associated with breast cancer. Conclusions: In this study, we demonstrate the usefulness of a genomic-driven approach nested in a classic case-control study to prioritize cancer-predisposing variants. In addition, we provide a resource containing variants that may affect susceptibility to breast cancer.

Original languageEnglish
Article number63
JournalBreast Cancer Research
Volume19
Issue number1
DOIs
Publication statusPublished - May 31 2017

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Breast Neoplasms
Neoplasm Genes
Neoplasms
Genes
Genome-Wide Association Study
Age of Onset
Case-Control Studies
Genome
Mutation

Keywords

  • Breast cancer
  • Germline mutations
  • Predisposition
  • Somatic mutations

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

A knowledge-based framework for the discovery of cancer-predisposing variants using large-scale sequencing breast cancer data. / Melloni, Giorgio E.M.; Mazzarella, Luca; Bernard, Loris; Bodini, Margherita; Russo, Anna; Luzi, Lucilla; Pelicci, Pier Giuseppe; Riva, Laura.

In: Breast Cancer Research, Vol. 19, No. 1, 63, 31.05.2017.

Research output: Contribution to journalArticle

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