Literature DB >> 33594121

Splicing profile by capture RNA-seq identifies pathogenic germline variants in tumor suppressor genes.

Tyler Landrith1, Bing Li1, Ashley A Cass1, Blair R Conner1, Holly LaDuca1, Danielle B McKenna2, Kara N Maxwell2, Susan Domchek2, Nichole A Morman3, Christopher Heinlen3, Deborah Wham4, Cathryn Koptiuch5, Jennie Vagher5, Ragene Rivera6, Ann Bunnell6, Gayle Patel6, Jennifer L Geurts7, Morgan M Depas7, Shraddha Gaonkar8, Sara Pirzadeh-Miller9, Rebekah Krukenberg10, Meredith Seidel11, Robert Pilarski12, Meagan Farmer13, Khateriaa Pyrtel14, Kara Milliron15, John Lee16, Elizabeth Hoodfar17, Deepika Nathan18, Amanda C Ganzak19, Sitao Wu1, Huy Vuong1, Dong Xu1, Aarani Arulmoli1, Melissa Parra1, Lily Hoang1, Bhuvan Molparia1, Michele Fennessy1, Susanne Fox1, Sinead Charpentier1, Julia Burdette1, Tina Pesaran1, Jessica Profato1, Brandon Smith1, Ginger Haynes1, Emily Dalton1, Joy Rae-Radecki Crandall1, Ruth Baxter1, Hsiao-Mei Lu1, Brigette Tippin-Davis1, Aaron Elliott1, Elizabeth Chao1,18, Rachid Karam20.   

Abstract

Germline variants in tumor suppressor genes (TSGs) can result in RNA mis-splicing and predisposition to cancer. However, identification of variants that impact splicing remains a challenge, contributing to a substantial proportion of patients with suspected hereditary cancer syndromes remaining without a molecular diagnosis. To address this, we used capture RNA-sequencing (RNA-seq) to generate a splicing profile of 18 TSGs (APC, ATM, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MSH2, MSH6, MUTYH, NF1, PALB2, PMS2, PTEN, RAD51C, RAD51D, and TP53) in 345 whole-blood samples from healthy donors. We subsequently demonstrated that this approach can detect mis-splicing by comparing splicing profiles from the control dataset to profiles generated from whole blood of individuals previously identified with pathogenic germline splicing variants in these genes. To assess the utility of our TSG splicing profile to prospectively identify pathogenic splicing variants, we performed concurrent capture DNA and RNA-seq in a cohort of 1000 patients with suspected hereditary cancer syndromes. This approach improved the diagnostic yield in this cohort, resulting in a 9.1% relative increase in the detection of pathogenic variants, demonstrating the utility of performing simultaneous DNA and RNA genetic testing in a clinical context.

Year:  2020        PMID: 33594121     DOI: 10.1038/s41698-020-0109-y

Source DB:  PubMed          Journal:  NPJ Precis Oncol        ISSN: 2397-768X


  4 in total

1.  A nonsense mutation in MLH1 causes exon skipping in three unrelated HNPCC families.

Authors:  A Stella; A Wagner; K Shito; S M Lipkin; P Watson; G Guanti; H T Lynch; R Fodde; B Liu
Journal:  Cancer Res       Date:  2001-10-01       Impact factor: 12.701

2.  Alternative Splicing Signatures in RNA-seq Data: Percent Spliced in (PSI).

Authors:  Sebastian Schafer; Kui Miao; Craig C Benson; Matthias Heinig; Stuart A Cook; Norbert Hubner
Journal:  Curr Protoc Hum Genet       Date:  2015-10-06

3.  Differential expression of two types of the neurofibromatosis type 1 (NF1) gene transcripts related to neuronal differentiation.

Authors:  T Nishi; P S Lee; K Oka; V A Levin; S Tanase; Y Morino; H Saya
Journal:  Oncogene       Date:  1991-09       Impact factor: 9.867

4.  Assessment of Diagnostic Outcomes of RNA Genetic Testing for Hereditary Cancer.

Authors:  Rachid Karam; Blair Conner; Holly LaDuca; Kelly McGoldrick; Kate Krempely; Marcy E Richardson; Heather Zimmermann; Stephanie Gutierrez; Patrick Reineke; Lily Hoang; Kyle Allen; Amal Yussuf; Suzette Farber-Katz; Huma Q Rana; Samantha Culver; John Lee; Sarah Nashed; Deborah Toppmeyer; Debra Collins; Ginger Haynes; Tina Pesaran; Jill S Dolinsky; Brigette Tippin Davis; Aaron Elliott; Elizabeth Chao
Journal:  JAMA Netw Open       Date:  2019-10-02
  4 in total

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