Rachel Liao, PhD Coordinator of the Clinical Working Group and the BRCA Challenge demonstration project for the Global Alliance for Genomics and Health Project manager for the Global Alliance for Genomics and Health and the Broad Institute of MIT and Harvard July 7, 2015

The Challenge 2 Unparalleled generation of human genetic data How do we unlock its potential? In a way that allows data to be shared on a global level Thus empowering new knowledge, new diagnostics and new therapeutics for patients and populations

The Challenge Data from millions of samples may be needed to achieve results and progress - showing patterns that would otherwise remain obscure. That will take new methods and organizational models. Right now: Data is typically in silos: by type, by disease, by country, by institution Analysis methods are non-standardized, few at scale Approaches to regulation, consent and data sharing limit interoperability If we don’t act: risk an overwhelming mass of fragmented data, such as electronic medical records in many countries 3

What can we do? Work together internationally to ensure interoperability of data and of methods, to harmonize approaches to ethics and regulation, and to promote participant autonomy Support pilot projects that responsibly and effectively harmonize, analyze and share genomic and clinical data Engage professional communities and the public; build trust and encourage appropriate sharing and learning 4

GA4GH Mission To accelerate progress in human health by helping to establish a common framework of harmonized approaches to enable effective and responsible sharing of genomic and clinical data, and by catalyzing data sharing projects that drive and demonstrate the value of data sharing 5

Role Convene stakeholders Catalyze sharing of data Create harmonized approaches Act as a clearinghouse Foster innovation Commit to responsible data sharing 6

The Global Alliance will NOT directly: Generate or store data Perform research or care for patients Interpret genomes Be exclusive to entities that have and share data 7

Organizational Members Global Alliance members include: 1.Universities and research institutes 2.Academic medical centers and health systems 3.Disease advocacy organizations and patient groups 4.Consortia and professional societies 5.Funders and agencies 6.Life science and information technology companies Last Update: Jul 4 th

Co-chairs: Sir John Burn, Newcastle University, UK Stephen Chanock, National Cancer Institute, USA T HE BRCA CHALLENGE

BRCA1 and BRCA2: Cancer predisposition genes Involved in DNA repair and other pathways Large, semi-conserved genes (BRCA1 1863aa, BRCA2 3418aa) Some variants predispose to breast and ovarian cancer Certain biallelic mutations cause Fanconi anemia + childhood cancer Most testing performed in individuals with br/ov cancer history Little population-level data until >2010

Ford D, Easton E et al, Am.J.Hum.Genet 1998, Antoniou A, Pharoah PD et al, Am.J.Hum.Genet 2003 Familial BC Unselected BC ??Population risk Risk of cancer is highly variable

Data capture and curation for variants has been highly variable Result: Many Variants of Uncertain Significance (VUS) BRCA1 Circos, BIC Database

The moment in time for the BRCA Challenge Then: Data collection and curation not standardized across institutions Data not able to be shared across institutions Regulatory limits hindered access Now High-throughput genomic analysis generates semi-standardized data Regulatory roadblocks have been dismantled APIs are in development to enable standardized, secure data sharing between databases Shared data increases statistical significance and leads to better interpretations of pathogenicity for VUS, more informed treatment decisions for at-risk patients, and peace of mind

Goals of the Challenge MISSION: To improve the care of patients at risk of monogenic disease using, as an exemplar, global data sharing and collaboration in the analysis of BRCA1 and BRCA2 1. Share BRCA1 and BRCA2 variants publically 2. Create an environment for collaborative variant curation with access to evidence (e.g. phenotypes, family history, genetic data, and functional studies) 3. Create a curated list of variants, interpreted by expert consensus, to enable, without dictating, accurate clinical care 4. Address the social, ethical, and legal challenges to global data sharing 5. Create a model for all genes

Thank you! Questions?