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  • Perspective
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Facilitating a culture of responsible and effective sharing of cancer genome data

Abstract

Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.

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Figure 1: Data-sharing vision as facilitated by GA4GH through its working groups, each of which focuses on particular data-sharing challenges: for example, Clinical Working Group, establish common data elements; Data Working Group, establish universal API standardization; Regulatory and Ethics Working Group, harmonize ethics processes; Security Working Group, establish data-access procedures.

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References

  1. McCarthy, M. US president endorses “moonshot” effort to cure cancer. Br. Med. J. 352, i213 (2016).

    Google Scholar 

  2. Collins, F.S. & Varmus, H. A new initiative on precision medicine. N. Engl. J. Med. 372, 793–795 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Siva, N. UK gears up to decode 100,000 genomes from NHS patients. Lancet 385, 103–104 (2015).

    PubMed  Google Scholar 

  4. Meric-Bernstam, F. et al. Feasibility of large-scale genomic testing to facilitate enrollment onto genomically matched clinical trials. J. Clin. Oncol. 33, 2753–2762 (2015).

    PubMed  PubMed Central  Google Scholar 

  5. André, F. et al. Comparative genomic hybridisation array and DNA sequencing to direct treatment of metastatic breast cancer: a multicentre, prospective trial (SAFIR01/UNICANCER). Lancet Oncol. 15, 267–274 (2014).

    PubMed  Google Scholar 

  6. Walport, M. & Brest, P. Sharing research data to improve public health. Lancet 377, 537–539 (2011).

    PubMed  Google Scholar 

  7. Joly, Y., Dove, E.S., Knoppers, B.M., Bobrow, M. & Chalmers, D. Data sharing in the post-genomic world: the experience of the International Cancer Genome Consortium (ICGC) Data Access Compliance Office (DACO). PLoS Comput. Biol. 8, e1002549 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Rehm, H.L. et al. & ClinGen—the Clinical Genome Resource. N. Engl. J. Med. 372, 2235–2242 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. US National Institutes of Health. National Institutes of Health genomic data sharing policy https://gds.nih.gov/PDF/NIH_GDS_Policy.pdf (27 August 2014).

  10. Cancer Genome Atlas Research Network. et al. The Cancer Genome Atlas Pan-Cancer analysis project. Nat. Genet. 45, 1113–1120 (2013).

  11. International Cancer Genome Consortium. et al. International network of cancer genome projects. Nature 464, 993–998 (2010).

  12. Aparicio, S. & Caldas, C. The implications of clonal genome evolution for cancer medicine. N. Engl. J. Med. 368, 842–851 (2013).

    CAS  PubMed  Google Scholar 

  13. Alizadeh, A.A. et al. Toward understanding and exploiting tumor heterogeneity. Nat. Med. 21, 846–853 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Köhler, S. et al. The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res. 42, D966–D974 (2014).

    PubMed  Google Scholar 

  15. Groza, T. et al. The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease. Am. J. Hum. Genet. 97, 111–124 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Girdea, M. et al. PhenoTips: patient phenotyping software for clinical and research use. Hum. Mutat. 34, 1057–1065 (2013).

    PubMed  Google Scholar 

  17. Hamosh, A. et al. PhenoDB: a new web-based tool for the collection, storage, and analysis of phenotypic features. Hum. Mutat. 34, 566–571 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Denny, J.C. et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotechnol. 31, 1102–1111 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. McCarty, C.A. et al. The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies. BMC Med. Genomics 4, 13 (2011).

    PubMed  PubMed Central  Google Scholar 

  20. Schilsky, R.L., Michels, D.L., Kearbey, A.H., Yu, P.P. & Hudis, C.A. Building a rapid learning health care system for oncology: the regulatory framework of CancerLinQ. J. Clin. Oncol. 32, 2373–2379 (2014).

    PubMed  Google Scholar 

  21. Sioutos, N. et al. NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information. J. Biomed. Inform. 40, 30–43 (2007).

    CAS  Google Scholar 

  22. Stein, L.D., Knoppers, B.M., Campbell, P., Getz, G. & Korbel, J.O. Data analysis: Create a cloud commons. Nature 523, 149–151 (2015).

    CAS  PubMed  Google Scholar 

  23. Van Allen, E.M. et al. Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine. Nat. Med. 20, 682–688 (2014).

    CAS  PubMed  Google Scholar 

  24. Andre, F. et al. Prioritizing targets for precision cancer medicine. Ann. Oncol. 25, 2295–2303 (2014).

    CAS  PubMed  Google Scholar 

  25. Kosseim, P. et al. Building a data sharing model for global genomic research. Genome Biol. 15, 430 (2014).

    PubMed  PubMed Central  Google Scholar 

  26. Paten, B. et al. The NIH BD2K center for big data in translational genomics. J. Am. Med. Inform. Assoc. 22, 1143–1147 (2015).

    PubMed  PubMed Central  Google Scholar 

  27. Boutros, P.C. et al. Global optimization of somatic variant identification in cancer genomes with a global community challenge. Nat. Genet. 46, 318–319 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Ewing, A.D. et al. & ICGC–TCGA DREAM Somatic Mutation Calling Challenge participants. Combining tumor genome simulation with crowdsourcing to benchmark somatic single-nucleotide-variant detection. Nat. Methods 12, 623–630 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Gargis, A.S. et al. Good laboratory practice for clinical next-generation sequencing informatics pipelines. Nat. Biotechnol. 33, 689–693 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Lawler, M. et al. & Clinical Working Group of the Global Alliance for Genomics and Health (GA4GH). All the world's a stage: facilitating discovery science and improved cancer care through the global alliance for genomics and health. Cancer Discov. 5, 1133–1136 (2015).

    PubMed  Google Scholar 

  31. Tryka, K.A. et al. NCBI's Database of Genotypes and Phenotypes: dbGaP. Nucleic Acids Res. 42, D975–D979 (2014).

    CAS  PubMed  Google Scholar 

  32. Global Alliance for Genomics and Health. White Paper: creating a global alliance to enable responsible sharing of genomic and clinical data https://genomicsandhealth.org/about-the-global-alliance/key-documents/white-paper-creating-global-alliance-enable-responsible-shar (3 June 2013).

  33. Kaye, J. The tension between data sharing and the protection of privacy in genomics research. in Ethics, Law and Governance of Biobanking, Vol. 14 (ed. Mascalzoni, D.) 101–120 (Springer, the Netherlands, 2015).

    Google Scholar 

  34. Haga, S.B. & Beskow, L.M. Ethical, legal, and social implications of biobanks for genetics research. Adv. Genet. 60, 505–544 (2008).

    PubMed  Google Scholar 

  35. Wolf, L.E. & Lo, B. Untapped potential: IRB guidance for the ethical research use of stored biological materials. IRB 26, 1–8 (2004).

    PubMed  Google Scholar 

  36. Lunshof, J.E., Chadwick, R., Vorhaus, D.B. & Church, G.M. From genetic privacy to open consent. Nat. Rev. Genet. 9, 406–411 (2008).

    CAS  PubMed  Google Scholar 

  37. Lolkema, M.P. et al. Ethical, legal, and counseling challenges surrounding the return of genetic results in oncology. J. Clin. Oncol. 31, 1842–1848 (2013).

    PubMed  Google Scholar 

  38. O'Doherty, K.C. et al. From consent to institutions: designing adaptive governance for genomic biobanks. Soc. Sci. Med. 73, 367–374 (2011).

    PubMed  Google Scholar 

  39. Zika, E., Schulte In den Bäumen, T., Kaye, J., Brand, A. & Ibarreta, D. Sample, data use and protection in biobanking in Europe: legal issues. Pharmacogenomics 9, 773–781 (2008).

    PubMed  Google Scholar 

  40. Homer, N. et al. Resolving individuals contributing trace amounts of DNA to highly complex mixtures using high-density SNP genotyping microarrays. PLoS Genet. 4, e1000167 (2008).

    PubMed  PubMed Central  Google Scholar 

  41. Lin, Z., Owen, A.B. & Altman, R.B. Genetics. Genomic research and human subject privacy. Science 305, 183 (2004).

    CAS  PubMed  Google Scholar 

  42. Gymrek, M., McGuire, A.L., Golan, D., Halperin, E. & Erlich, Y. Identifying personal genomes by surname inference. Science 339, 321–324 (2013).

    CAS  PubMed  Google Scholar 

  43. Erlich, Y. & Narayanan, A. Routes for breaching and protecting genetic privacy. Nat. Rev. Genet. 15, 409–421 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Knoppers, B.M. International ethics harmonization and the global alliance for genomics and health. Genome Med. 6, 13 (2014).

    PubMed  PubMed Central  Google Scholar 

  45. Knoppers, B.M., Harris, J.R., Budin-Ljøsne, I. & Dove, E.S. A human rights approach to an international code of conduct for genomic and clinical data sharing. Hum. Genet. 133, 895–903 (2014).

    PubMed  PubMed Central  Google Scholar 

  46. Global Alliance for Genomics and Health. Framework for responsible sharing of genomic and health-related data https://genomicsandhealth.org/node/6611 (10 September 2014).

  47. Global Alliance for Genomics and Health. Consent policy https://genomicsandhealth.org/consent-policy-pdf-27-may-2015 (27 May 2015).

  48. Global Alliance for Genomics and Health. GA P3G–IPAC consent tools https://genomicsandhealth.org/ga-p3g-ipac-consent-tools (6 August 2014).

  49. Global Alliance for Genomics and Health. Privacy and security policy https://genomicsandhealth.org/privacy-and-security-policy-pdf-26-may-2015 (26 May 2015).

  50. Global Alliance for Genomics and Health. Data sharing lexicon. https://genomicsandhealth.org/files/public/GA4GH_DataSharingLexicon_Mar15.pdf (15 March 2016).

  51. Global Alliance for Genomics and Health. Security infrastructure: standards and implementation practices for protecting the privacy and security of shared genomic and clinical data https://genomicsandhealth.org/security-infrastructure-version-11 (12 March 2015).

  52. Global Alliance for Genomics and Health. Accountability policy https://genomicsandhealth.org/ga4gh-accountability-policy (10 February 2016).

  53. Christensen, K.D. et al. & MedSeq Project Team. Are physicians prepared for whole genome sequencing? a qualitative analysis. Clin. Genet. 89, 228–234 (2016).

    CAS  PubMed  Google Scholar 

  54. Pillai, U. et al. Factors that may influence the willingness of cancer patients to consent for biobanking. Biopreserv. Biobank. 12, 409–414 (2014).

    PubMed  Google Scholar 

  55. Mancini, J. et al. Consent for biobanking: assessing the understanding and views of cancer patients. J. Natl. Cancer Inst. 103, 154–157 (2011).

    PubMed  Google Scholar 

  56. Tejpar, S. et al. Awareness and understanding of stratified/personalized medicine in patients treated for cancer: a multi-national survey (37th European Society for Medical Oncology Congress) 1382P (Oxford University Press, 2012).

  57. Rogith, D. et al. Attitudes regarding privacy of genomic information in personalized cancer therapy. J. Am. Med. Inform. Assoc. 21, e2, e320–e325 (2014).

    Google Scholar 

  58. Lawler, M. et al. & European Cancer Concord (ECC). A Bill of Rights for patients with cancer in Europe. Lancet Oncol. 15, 258–260 (2014).

    PubMed  Google Scholar 

  59. Lawler, M. et al. A catalyst for change: the European cancer Patient's Bill of Rights. Oncologist 19, 217–224 (2014).

    PubMed  PubMed Central  Google Scholar 

  60. European Commission. Proposal for a regulation of the European Parliament and of the council on the protection of individuals with regard to processing of personal data and on the free movement of such data (general data protection regulation) http://ec.europa.eu/justice/data-protection/document/review2012/com_2012_11_en.pdf, (25 January 2012).

  61. Husedzinovic, A., Ose, D., Schickhardt, C., Fröhling, S. & Winkler, E.C. Stakeholders' perspectives on biobank-based genomic research: systematic review of the literature. Eur. J. Hum. Genet. 23, 1607–1614 (2015).

    PubMed  PubMed Central  Google Scholar 

  62. McGuire, A.L. et al. To share or not to share: a randomized trial of consent for data sharing in genome research. Genet. Med. 13, 948–955 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Green, R.C., Lautenbach, D. & McGuire, A.L. GINA, genetic discrimination, and genomic medicine. N. Engl. J. Med. 372, 397–399 (2015).

    CAS  PubMed  Google Scholar 

  64. Lacombe, D. et al. European perspective for effective cancer drug development. Nat. Rev. Clin. Oncol. 11, 492–498 (2014).

    PubMed  Google Scholar 

  65. Conley, B.A. & Doroshow, J.H. Molecular analysis for therapy choice: NCI MATCH. Semin. Oncol. 41, 297–299 (2014).

    PubMed  Google Scholar 

  66. Schilsky, R.L. Implementing personalized cancer care. Nat. Rev. Clin. Oncol. 11, 432–438 (2014).

    PubMed  Google Scholar 

  67. Eggermont, A.M. et al. Cancer Core Europe: a consortium to address the cancer care-cancer research continuum challenge. Eur. J. Cancer 50, 2745–2746 (2014).

    PubMed  Google Scholar 

  68. American Association for Cancer Research. Project GENIE (Genomics Evidence Neoplasia Information Exchange) http://www.aacr.org/Documents/GENIE_InfoGraph.pdf.

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Acknowledgements

This manuscript is written on behalf of the GA4GH Clinical Working Group (WG). We thank the Data WG, Regulatory and Ethics WG and Security WG for their important contributions. L.L.S. is supported by the Cancer Care Ontario Research Chair and Applied Cancer Research Units Grant; M.L., C.C. and R.C.F. are supported by Cancer Research UK; D.H. is funded by the US National Institutes of Health (award #U54HG007990). B.M.K. is supported by the Quebec Breast Cancer Foundation; C.L.S. is supported by the Howard Hughes Medical Institute and US National Cancer Institute (Grant #CA008748); E.E.V. is supported by the Barcode for Life Foundation and the Hartwig Medical Foundation.

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Correspondence to Mark Lawler.

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J.C.B. is employed by AstraZeneca and is a stock owner of AstraZeneca. W.P. is employed by Roche, is a shareholder of Roche, has rights to EGFR T790M mutation testing (licensed to MolecularMD) and is a co-founder of MyCancerGenome. W.R.S. is employed by the Novartis Institute for Biomedical Research and is a shareholder of Novartis Pharma. C.L.S. serves on the Board of Novartis Pharma. All other authors declare no competing financial interests.

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Siu, L., Lawler, M., Haussler, D. et al. Facilitating a culture of responsible and effective sharing of cancer genome data. Nat Med 22, 464–471 (2016). https://doi.org/10.1038/nm.4089

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