In silico systems biology analysis of variants of uncertain significance in lynch syndrome supports the prioritization of functional molecular validation

Ester Borras, Kyle Chang, Mala Pande, Amanda Cuddy, Jennifer L. Bosch, Sarah A. Bannon, Maureen E. Mork, Miguel A. Rodriguez-Bigas, Melissa W. Taggart, Patrick M. Lynch, Y. Nancy You, Eduardo Vilar

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Lynch syndrome (LS) is a genetic condition secondary to germline alterations in the DNA mismatch repair (MMR) genes with 30% of changes being variants of uncertain significance (VUS). Our aim was to perform an in silico reclassification of VUS from a large single institutional cohort that will help prioritizing functional validation. A total of 54 VUS were detected with 33 (61%) novel variants. We integrated family history, pathology, and genetic information along with supporting evidence from eight different in silico tools at the RNA and protein level. Our assessment allowed us to reclassify 54% (29/54) of the VUS as probably damaging, 13% (7/54) as possibly damaging, and 28% (15/54) as probably neutral. There are more than 1,000 VUS reported in MMR genes and our approach facilitates the rioritization of further functional efforts to assess the athogenicity to those classified as probably damaging.

Original languageEnglish (US)
Pages (from-to)580-587
Number of pages8
JournalCancer Prevention Research
Volume10
Issue number10
DOIs
StatePublished - Oct 2017

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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