Advertisement

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

      Highlights

      • 14 discordant sibling pairs from high-risk breast cancer families were identified.
      • Whole exome sequencing of germline DNA was performed.
      • Rare variants, present only in affected siblings, were identified.
      • Functional assessment of a rare PMS1 variant was performed.
      • The PMS1 p.R202K (c.605G>A) variant is likely benign.

      Abstract

      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.

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Cancer Genetics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Tung N.
        • Lin N.U.
        • Kidd J.
        • et al.
        Frequency of Germline Mutations in 25 Cancer Susceptibility Genes in a Sequential Series of Patients With Breast Cancer.
        J Clin Oncol. 2016; 34: 1460-1468
        • American Cancer Society
        Breast cancer facts and figures 2019-2020.
        GACS, Atlanta2019
        • Hu C.
        • Hart S.N.
        • Gnanaolivu R.
        • et al.
        A population-based study of genes previously implicated in breast cancer.
        N Engl J Med. 2021; 384: 440-451
        • Mavaddat N.
        • Antoniou A.C.
        • Easton D.F.
        • Garcia-Closas M.
        Genetic susceptibility to breast cancer.
        Mol Oncol. 2010; 4: 174-191
        • Shiovitz S.
        • Korde L.A.
        Genetics of breast cancer: a topic in evolution.
        Ann Oncol. 2015; 26: 1291-1299
        • Turnbull C.
        • Rahman N.
        Genetic predisposition to breast cancer: past, present, and future.
        Annu Rev Genomics Hum Genet. 2008; 9: 321-345
        • Dorling L.
        • Carvalho S.
        • et al.
        Breast cancer risk genes - association analysis in more than 113,000 women.
        N Engl J Med. 2021; 384 (Breast Cancer Association C): 428-439
        • Couch F.J.
        • Shimelis H.
        • Hu C.
        • et al.
        Associations between cancer predisposition testing panel genes and breast cancer.
        JAMA Oncol. 2017; 3: 1190-1196
        • Tung N.
        • Battelli C.
        • Allen B.
        • et al.
        Frequency of mutations in individuals with breast cancer referred for BRCA1 and BRCA2 testing using next-generation sequencing with a 25-gene panel.
        Cancer. 2015; 121: 25-33
        • Kurian A.W.
        • Hare E.E.
        • Mills M.A.
        • et al.
        Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment.
        J Clin Oncol. 2014; 32: 2001-2009
        • Lincoln S.E.
        • Kobayashi Y.
        • Anderson M.J.
        • et al.
        A systematic comparison of traditional and multigene panel testing for hereditary breast and ovarian cancer genes in more than 1000 patients.
        J Mol Diagn. 2015; 17: 533-544
        • Maxwell K.N.
        • Wubbenhorst B.
        • D'Andrea K.
        • et al.
        Prevalence of mutations in a panel of breast cancer susceptibility genes in BRCA1/2-negative patients with early-onset breast cancer.
        Genet Med. 2015; 17: 630-638
        • Beitsch P.D.
        • Whitworth P.W.
        • Hughes K.
        • et al.
        Underdiagnosis of hereditary breast cancer: are genetic testing guidelines a tool or an obstacle?.
        J Clin Oncol. 2019; 37: 453-460
        • Wen H.
        • Kim Y.C.
        • Snyder C.
        • et al.
        Family-specific, novel, deleterious germline variants provide a rich resource to identify genetic predispositions for BRCAx familial breast cancer.
        BMC Cancer. 2014; 14: 470
        • Varela I.
        • Tarpey P.
        • Raine K.
        • et al.
        Exome sequencing identifies frequent mutation of the SWI/SNF complex gene PBRM1 in renal carcinoma.
        Nature. 2011; 469: 539-542
        • Wei X.
        • Walia V.
        • Lin J.C.
        • et al.
        Exome sequencing identifies GRIN2A as frequently mutated in melanoma.
        Nat Genet. 2011; 43: 442-446
        • Bentley D.R.
        • Balasubramanian S.
        • Swerdlow H.P.
        • et al.
        Accurate whole human genome sequencing using reversible terminator chemistry.
        Nature. 2008; 456: 53-59
        • Benjamin E.J.
        • Blaha M.J.
        • Chiuve S.E.
        • et al.
        Heart disease and stroke statistics-2017 update: a report from the American Heart Association.
        Circulation. 2017; 135: e146-e603
        • Tavtigian S.V.
        • Greenblatt M.S.
        • Harrison S.M.
        • et al.
        Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.
        Genet Med. 2018; 20: 1054-1060
        • Kerber R.A.
        • Amos C.I.
        • Yeap B.Y.
        • Finkelstein D.M.
        • Thomas D.C.
        Design considerations in a sib-pair study of linkage for susceptibility loci in cancer.
        BMC Med Genet. 2008; 9: 64
        • Hamdi Y.
        • Boujemaa M.
        • Ben Rekaya M.
        • et al.
        Family specific genetic predisposition to breast cancer: results from Tunisian whole exome sequenced breast cancer cases.
        J Transl Med. 2018; 16: 158
        • Gracia-Aznarez F.J.
        • Fernandez V.
        • Pita G.
        • et al.
        Whole exome sequencing suggests much of non-BRCA1/BRCA2 familial breast cancer is due to moderate and low penetrance susceptibility alleles.
        PLoS ONE. 2013; 8: e55681
        • Maatta K.
        • Rantapero T.
        • Lindstrom A.
        • et al.
        Whole-exome sequencing of Finnish hereditary breast cancer families.
        Eur J Hum Genet. 2016; 25: 85-93
        • Allison D.B.
        The use of discordant sibling pairs for finding genetic loci linked to obesity: practical considerations.
        Int J Obes Relat Metab Disord. 1996; 20: 553-560
        • Risch N.
        • Merikangas K.
        The future of genetic studies of complex human diseases.
        Science. 1996; 273: 1516-1517
        • Hirschhorn J.N.
        • Daly M.J.
        Genome-wide association studies for common diseases and complex traits.
        Nat Rev Genet. 2005; 6: 95-108
        • Bodmer W.
        • Bonilla C.
        Common and rare variants in multifactorial susceptibility to common diseases.
        Nat Genet. 2008; 40: 695-701
        • Auton A.
        • Brooks L.D.
        • et al.
        A global reference for human genetic variation.
        Nature. 2015; 526 (Genomes Project C): 68-74
        • Landrum M.J.
        • Lee J.M.
        • Benson M.
        • et al.
        ClinVar: improving access to variant interpretations and supporting evidence.
        Nucleic Acids Res. 2018; 46 (D1062-D7)
        • Bodian D.L.
        • McCutcheon J.N.
        • Kothiyal P.
        • et al.
        Germline variation in cancer-susceptibility genes in a healthy, ancestrally diverse cohort: implications for individual genome sequencing.
        PLoS ONE. 2014; 9: e94554
        • Doss C.G.
        • Sethumadhavan R.
        Investigation on the role of nsSNPs in HNPCC genes–a bioinformatics approach.
        J Biomed Sci. 2009; 16: 42
        • Taniguchi I.
        • Masuyama K.
        • Ohno M.
        Role of purine-rich exonic splicing enhancers in nuclear retention of pre-mRNAs.
        Proc Natl Acad Sci U S A. 2007; 104: 13684-13689
        • Cartegni L.
        • Chew S.L.
        • Krainer A.R.
        Listening to silence and understanding nonsense: exonic mutations that affect splicing.
        Nat Rev Genet. 2002; 3: 285-298
        • Tate J.G.
        • Bamford S.
        • Jubb H.C.
        • et al.
        COSMIC: the catalogue of somatic mutations in cancer.
        Nucleic Acids Res. 2019; 47 (D941-D7)
        • Borts R.H.
        • Leung W.Y.
        • Kramer W.
        • et al.
        Mismatch repair-induced meiotic recombination requires the pms1 gene product.
        Genetics. 1990; 124: 573-584
        • Tutt A.
        • Ashworth A.
        The relationship between the roles of BRCA genes in DNA repair and cancer predisposition.
        Trends Mol Med. 2002; 8: 571-576
        • Li M.M.
        • Datto M.
        • Duncavage E.J.
        • et al.
        Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the association for molecular pathology, American Society of Clinical Oncology, and College of American pathologists.
        J Mol Diagn. 2017; 19: 4-23
        • Pabinger S.
        • Dander A.
        • Fischer M.
        • et al.
        A survey of tools for variant analysis of next-generation genome sequencing data.
        Brief Bioinform. 2014; 15: 256-278
        • Tang H.
        • Thomas P.D.
        Tools for predicting the functional impact of nonsynonymous genetic variation.
        Genetics. 2016; 203: 635-647
        • Itan Y.
        • Casanova J.L.
        Can the impact of human genetic variations be predicted?.
        Proc Natl Acad Sci U S A. 2015; 112: 11426-11427
        • Miosge L.A.
        • Field M.A.
        • Sontani Y.
        • et al.
        Comparison of predicted and actual consequences of missense mutations.
        Proc Natl Acad Sci U S A. 2015; 112: E5189-E5198