Comparison of mRNA Splicing Assay Protocols across Multiple Laboratories: Recommendations for Best Practice in Standardized Clinical Testing

Author:

Whiley Phillip J12,de la Hoya Miguel3,Thomassen Mads4,Becker Alexandra56,Brandão Rita7,Pedersen Inge Sokilde8,Montagna Marco9,Menéndez Mireia10,Quiles Francisco10,Gutiérrez-Enríquez Sara11,De Leeneer Kim12,Tenés Anna11,Montalban Gemma11,Tserpelis Demis7,Yoshimatsu Toshio13,Tirapo Carole14,Raponi Michela15,Caldes Trinidad3,Blanco Ana16,Santamariña Marta17,Guidugli Lucia18,de Garibay Gorka Ruiz3,Wong Ming19,Tancredi Mariella20,Fachal Laura16,Ding Yuan Chun21,Kruse Torben4,Lattimore Vanessa22,Kwong Ava23,Chan Tsun Leung23,Colombo Mara24,De Vecchi Giovanni24,Caligo Maria19,Baralle Diana15,Lázaro Conxi10,Couch Fergus17,Radice Paolo24,Southey Melissa C18,Neuhausen Susan21,Houdayer Claude14,Fackenthal Jim13,Hansen Thomas Van Overeem25,Vega Ana16,Diez Orland11,Blok Rien7,Claes Kathleen12,Wappenschmidt Barbara56,Walker Logan22,Spurdle Amanda B1,Brown Melissa A2

Affiliation:

1. Genetics & Computational Biology Division, Queensland Institute of Medical Research, Brisbane, Queensland, Australia

2. School of Chemistry and Molecular Biosciences, the University of Queensland, Queensland, Australia

3. Laboratorio de Oncología Molecular, Instituto de Investigación Sanitaria San Carlos (IdISSC), Madrid, Spain

4. Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark

5. Center for Familial Breast and Ovarian Cancer, University Hospital of Cologne, Cologne, Germany

6. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany

7. Department of Clinical Genetics, Maastricht University Medical Centre, Maastricht, the Netherlands

8. Section of Molecular Diagnostics, Department of Clinical Biochemistry, Aalborg University Hospital, Aalborg, Denmark

9. Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV—IRCCS, Padua, Italy

10. Genetic Diagnosis Unit, Hereditary Cancer Program, Institut Català d'Oncologia, Barcelona, Spain

11. Oncogenetics Laboratory, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron Institut de Recerca, University Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain

12. Center for Medical Genetics, Ghent University Hospital, De Pintelaan, Ghent, Belgium

13. Department of Medicine, the University of Chicago Medical Center, Chicago, IL

14. Service de Génétique et U830, Institut Curie, et Université Paris Descartes, Sorbonne Paris Cité, Paris, France

15. Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK

16. Fundación Pública Galega de Medicina Xenómica-SERGAS, Grupo de Medicina Xenómica-USC, CIBERER, IDIS, Santiago de Compostela, Spain

17. Grupo de Medicina Xenómica—USC, University of Santiago de Compostela, CIBERER, IDIS, Santiago de Compostela, Spain

18. Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, NY

19. Department of Pathology, University of Melbourne, Melbourne, Victoria, Australia

20. Istituto di Anatomia Patologica, Università di Pisa, Pisa, Italy

21. Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA

22. Department of Pathology, University of Otago, Christchurch, New Zealand

23. Division of Molecular Pathology, Department of Pathology, Hong Kong Sanatorium & Hospital, Hong Kong, China

24. Department of Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy

25. Center for Genomic Medicine, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark

Abstract

Abstract BACKGROUND Accurate evaluation of unclassified sequence variants in cancer predisposition genes is essential for clinical management and depends on a multifactorial analysis of clinical, genetic, pathologic, and bioinformatic variables and assays of transcript length and abundance. The integrity of assay data in turn relies on appropriate assay design, interpretation, and reporting. METHODS We conducted a multicenter investigation to compare mRNA splicing assay protocols used by members of the ENIGMA (Evidence-Based Network for the Interpretation of Germline Mutant Alleles) consortium. We compared similarities and differences in results derived from analysis of a panel of breast cancer 1, early onset (BRCA1) and breast cancer 2, early onset (BRCA2) gene variants known to alter splicing (BRCA1: c.135-1G>T, c.591C>T, c.594-2A>C, c.671-2A>G, and c.5467+5G>C and BRCA2: c.426-12_8delGTTTT, c.7988A>T, c.8632+1G>A, and c.9501+3A>T). Differences in protocols were then assessed to determine which elements were critical in reliable assay design. RESULTS PCR primer design strategies, PCR conditions, and product detection methods, combined with a prior knowledge of expected alternative transcripts, were the key factors for accurate splicing assay results. For example, because of the position of primers and PCR extension times, several isoforms associated with BRCA1, c.594-2A>C and c.671-2A>G, were not detected by many sites. Variation was most evident for the detection of low-abundance transcripts (e.g., BRCA2 c.8632+1G>A Δ19,20 and BRCA1 c.135-1G>T Δ5q and Δ3). Detection of low-abundance transcripts was sometimes addressed by using more analytically sensitive detection methods (e.g., BRCA2 c.426-12_8delGTTTT ins18bp). CONCLUSIONS We provide recommendations for best practice and raise key issues to consider when designing mRNA assays for evaluation of unclassified sequence variants.

Funder

NHMRC

National Breast Cancer Foundation

Cancer Australia

National Cancer Institute

Xunta de Galicia

Publisher

Oxford University Press (OUP)

Subject

Biochemistry (medical),Clinical Biochemistry

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