Investigation of discordant sibling pairs from hereditary breast cancer families and analysis of a rare PMS1 variant

K. K. Landry, D. J. Seward, J. A. Dragon, M. Slavik, K. Xu, W. C. McKinnon, L. Colello, J. Sweasy, S. S. Wallace, M. Cuke, M. E. Wood

Research output: Contribution to journalArticlepeer-review


Background: It is likely that additional genes for hereditary breast cancer can be identified using a discordant sib pair design. Using this design we identified individuals harboring a rare PMS1 c.605G>A variant previously predicted to result in loss of function. Objectives: A family-based design and predictive algorithms were used to prioritize candidate variants possibly associated with an increased risk of hereditary breast cancer. Functional analyses were performed for one of the candidate variants, PMS1 c.605G>A. Methods: 1) 14 discordant sister-pairs from hereditary breast cancer families were identified. 2) Whole exome sequencing was performed and candidate risk variants identified. 3) A rare PMS variant was identified in 2 unrelated affected sisters but no unaffected siblings. 4) Functional analysis of this variant was carried out using targeted mRNA sequencing. Results: Genotype-phenotype correlation did not demonstrate tracking of the variant with cancer in the family. Functional analysis revealed no difference in exon 6 incorporation, which was validated by analyzing PMS1 allele specific expression. Conclusions: The PMS1 c.605G>A variant did not segregate with disease, and there was no variant-dependent impact on PMS1 exon 6 splicing, supporting this variant is likely benign. Functional analyses are imperative to understanding the clinical significance of predictive algorithms.

Original languageEnglish (US)
Pages (from-to)30-36
Number of pages7
JournalCancer Genetics
StatePublished - Jan 2022


  • Cancer genetics
  • Cancer prevention
  • Family-based design
  • Genotype-phenotype correlation
  • Hereditary breast cancer
  • Molecular epidemiology

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Cancer Research


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