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Screening of CNVs using NGS data improves mutation detection yield and decreases costs in genetic testing for hereditary cancer
  1. José Marcos Moreno-Cabrera1,2,3,
  2. Jesús del Valle1,2,
  3. Lidia Feliubadaló1,2,
  4. Marta Pineda1,2,
  5. Sara González1,2,
  6. Olga Campos1,2,
  7. Raquel Cuesta1,2,
  8. Joan Brunet1,2,4,
  9. Eduard Serra2,3,
  10. Gabriel Capellà1,2,
  11. Bernat Gel3,
  12. Conxi Lázaro1,2
  1. 1 Hereditary Cancer Program, Joint Program on Hereditary Cancer, Catalan Institute of Oncology, Institut d’Investigació Biomèdica de Bellvitge - IDIBELL-ONCOBELL, L'Hospitalet de Llobregat, Spain
  2. 2 Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
  3. 3 Hereditary Cancer Group, Program for Predictive and Personalized Medicine of Cancer - Germans Trias i Pujol Research Institute (PMPPC-IGTP), Campus Can Ruti, Badalona, Spain
  4. 4 Hereditary Cancer Program, Catalan Institute of Oncology, IDIBGi, Girona, Spain
  1. Correspondence to Dr Conxi Lázaro, Hereditary Cancer Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, 08908 Catalunya, Spain; clazaro{at}; Dr Bernat Gel; bgel{at}


Introduction Germline CNVs are important contributors to hereditary cancer. In genetic diagnostics, multiplex ligation-dependent probe amplification (MLPA) is commonly used to identify them. However, MLPA is time-consuming and expensive if applied to many genes, hence many routine laboratories test only a subset of genes of interest.

Methods and results We evaluated a next-generation sequencing (NGS)-based CNV detection tool (DECoN) as first-tier screening to decrease costs and turnaround time and expand CNV analysis to all genes of clinical interest in our diagnostics routine. We used DECoN in a retrospective cohort of 1860 patients where a limited number of genes were previously analysed by MLPA, and in a prospective cohort of 2041 patients, without MLPA analysis. In the retrospective cohort, 6 new CNVs were identified and confirmed by MLPA. In the prospective cohort, 19 CNVs were identified and confirmed by MLPA, 8 of these would have been lost in our previous MLPA-restricted detection strategy. Also, the number of genes tested by MLPA across all samples decreased by 93.0% in the prospective cohort.

Conclusion Including an in silico germline NGS CNV detection tool improved our genetic diagnostics strategy in hereditary cancer, both increasing the number of CNVs detected and reducing turnaround time and costs.

  • genetic testing
  • germ-line mutation
  • molecular diagnostic techniques

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  • Contributors JMM-C, JdV, LF, MP, SG, CLG performed the CNV analysis. OC, RC performed genetic tests. JMM-C, BG, ES, GC, JB contributed to analysis and presentation of the results. JMM-C, JdV, BG and CLG wrote the manuscript. All authors reviewed and accepted the manuscript.

  • Funding Contract grant sponsor: supported by the Carlos III National Health Institute funded by FEDER funds—a way to build Europe—(PI19/00553; PI16/00563, PI15/00854 and CIBERONC); the Government of Catalonia (Pla estratègic de recerca i innovació en salut (PERIS_MedPerCan and URDCat projects), 2017SGR1282 and 2017SGR496) the Spanish Association Against Cancer (AECC) and Fundació La Marató de TV3.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.