1. InSiGHT, the CFR & Human Variome Project Finlay Macrae Secretary, InSiGHT American College of Medical Genetics, March 2010

2. Outline of presentation InSiGHT and the Human Variome Project InSiGHT and the Human Variome Project From Clinic to NCBI and EBI From Clinic to NCBI and EBI InSiGHT and NIH Colon Family Register InSiGHT and NIH Colon Family Register Measures of efficacy Measures of efficacy

3. InSiGHT and the Human Variome Project Pilot Study Aims To pilot systems to register all variants in genes predisposing to GI cancer commencing with the MMR genes (hMLH1, hMSH2, hMSH6, PMS2) To pilot systems to register all variants in genes predisposing to GI cancer commencing with the MMR genes (hMLH1, hMSH2, hMSH6, PMS2) Other genes: APC, MUYTH, E Cadherin Other genes: APC, MUYTH, E Cadherin To be scalable to (all) other genes across the genome To be scalable to (all) other genes across the genome To develop country specific data nodes which To develop country specific data nodes which Integrate with other systems i.e.: HVP LSDBs, and then NCBI, EBI, Integrate with other systems i.e.: HVP LSDBs, and then NCBI, EBI, Has ease of access Has ease of access Adaptable to all countries Adaptable to all countries

4. InSiGHT and the HVP Objectives To enhance the capabilities of the InSiGHT MMR database (www.insight-group.org) To enhance the capabilities of the InSiGHT MMR database (www.insight-group.org)www.insight-group.org To develop governance, and policies on data security/privacy To develop governance, and policies on data security/privacy To merge existing MMR databases with the InSiGHT database To merge existing MMR databases with the InSiGHT database To develop country specific nodes for variant collection To develop country specific nodes for variant collection To facilitate uploading of national including diagnostic data to the InSiGHT database To facilitate uploading of national including diagnostic data to the InSiGHT database To develop systems of annotation around the variants on the LOVD platform for phenotype, histology, functional assays and computational biology. To develop systems of annotation around the variants on the LOVD platform for phenotype, histology, functional assays and computational biology. To facilitate/lead an international committee for interpretation of unclassified variants To facilitate/lead an international committee for interpretation of unclassified variants To develop communication with NCBI and the EBI To develop communication with NCBI and the EBI

5. InSiGHT/HVP Initiative How are we going? How are we going?

6. InSiGHT and the Human Variome Project InSiGHT formed a collaboration with HVP at its meeting in Yokohama, March 2007. InSiGHT formed a collaboration with HVP at its meeting in Yokohama, March 2007. Approved by InSiGHT Council Approved by InSiGHT Council InSiGHT MMR variant database approved by the Human Variome Project Planning Committee as a pilot for the HVP InSiGHT MMR variant database approved by the Human Variome Project Planning Committee as a pilot for the HVP

7. Progress of the InSiGHT/HVP collaboration Governance of the InSiGHT MMR gene database established, terms of reference agreed. Governance of the InSiGHT MMR gene database established, terms of reference agreed. Three related databases have merged and interacted through the InSiGHT database: The InSiGHT, Newfoundland, and the Dutch MMR missense database Three related databases have merged and interacted through the InSiGHT database: The InSiGHT, Newfoundland, and the Dutch MMR missense database Curation of database (M Woods, A Dowty, Jan 09) Curation of database (M Woods, A Dowty, Jan 09) LOVD (Leiden Open Variant Database) selected LOVD (Leiden Open Variant Database) selected www.insight-group.org www.med.mun/ca/MMRvariants/ www.mmruv.info

8. Deposition of national data from diagnostic and research laboratories German HNPCC consortium: variants submitted German HNPCC consortium: variants submitted NIH CFR MMR variant data with MSI and IHC data from tumours, and family history NIH CFR MMR variant data with MSI and IHC data from tumours, and family history China (Ming Qi): independent LOVD database China (Ming Qi): independent LOVD database Canada – Toronto – (Bapat Bharati) Canada – Toronto – (Bapat Bharati) Australian HVP node MMR data (D DuSart) Australian HVP node MMR data (D DuSart) UK diagnostic labs (A Devereau – MTA developed) UK diagnostic labs (A Devereau – MTA developed) Holland, Denmark, Sweden, Finland, S Africa agreements Holland, Denmark, Sweden, Finland, S Africa agreements South America (?Mev Dominguez) South America (?Mev Dominguez)

9. Automated Text Searching Lawrence Cavedon, Tim Smith, NICTA Algorithms being developed to automatically search the literature for MMR gene references Algorithms being developed to automatically search the literature for MMR gene references To populate the InSiGHT database with annotations relating to particular variants To populate the InSiGHT database with annotations relating to particular variants Text searching easy; table searching more difficult Text searching easy; table searching more difficult Validated against manual searching by Mike Woods Validated against manual searching by Mike Woods

10. Functional mismatch repair assays N de Winds, R Sijmons, R Hofstra, M Nystrom EU Framework meeting, Dusseldorf June 23 rd discussed “state of art” functional MMR assays EU Framework meeting, Dusseldorf June 23 rd discussed “state of art” functional MMR assays Selection of missense variants endorsed as pathogenic or non pathogenic – as calibration set for functional assays (>40) Selection of missense variants endorsed as pathogenic or non pathogenic – as calibration set for functional assays (>40) Annotation of functional assays to VUS in the InSiGHT database Annotation of functional assays to VUS in the InSiGHT database

11. Phenotype Description InSiGHT meetings: InSiGHT meetings: September 2007 (Newcastle), December 2008 (London), September 2007 (Newcastle), December 2008 (London), Endorsement of the Danish HNPCC for promotion for data collection Endorsement of the Danish HNPCC for promotion for data collection February 2009 (Lyon), February 2009 (Lyon), Five tier system according to comfort of submitters Five tier system according to comfort of submitters June 2009 (Dusseldorf) June 2009 (Dusseldorf) Endorsement of phenotype dataset Endorsement of phenotype dataset

12. InSiGHT MMR Variant Database Phenotype Annotation Five optional levels of data entry associated with variants selected by submitter: No phenotype data FHx +/- Amsterdam +/- Summary family history based on Barnetson + Chao Pedigree (for Segregation)

13. Algorithms to predict presence of mutation in a family Barnetson et al algorithm Barnetson et al algorithm https://hnpccpredict.hgu.mrc.ac.uk https://hnpccpredict.hgu.mrc.ac.uk https://hnpccpredict.hgu.mrc.ac.uk Pr/(1-Pr)=1.39 *0.89Age *2.57Gender *4.45location *9.53 sync/met tumours *46.26 CRCFH( 50) *59.36ECFH Pr/(1-Pr)=1.39 *0.89Age *2.57Gender *4.45location *9.53 sync/met tumours *46.26 CRCFH( 50) *59.36ECFH

14. InSiGHT minimum phenotype dataset Stage 1 Individual ’ s Information Proband or Relative of proband (Index Case) Age is expressed in years at time of diagnosis Gender Location: Proximal/ Distal Synchronous and/or Metachronous tumours Family History There are three possible colorectal cancer family history categories CRCFH( =50): 1 and 0 if the youngest affected first degree relative was aged =50yrs 0 and 0 if there were no affected first degree relatives; Family history of endometrial cancer: ECFH = 1 if there are any first degree relatives with endometrial cancer ECFH = 0 if none. Stage 2 Additional Mutation Analysis Immunohistochemical analysis of tumour (MLH1, MSH2, MSH6 and PMS2) MSI testing of tumour Stage 3 Additional Familial data: Number of HNPCC affected persons in the family Co-Segregation: PEDIGREEs Comment: Modified from Barnetson R et al NEJM 2006; 354:2751-63

15. Algorithm to assign pathogenicity S Tavtigian, IARC/InSiGHT Lyon, Feb 2009 Principally for unclassified variants Principally for unclassified variants Based on Bayesian Likelihood Ratios Based on Bayesian Likelihood Ratios Layering of probabilities, prior to,with data from different dimensions captured on the InSiGHT database Layering of probabilities, prior to,with data from different dimensions captured on the InSiGHT database Co-segregation, co-occurrence, Grantham difference, cross species conservation, functional assays, tumour characteristics (histopathology, IHC and MMR (in relatives), phenotype (eg summary family history) Co-segregation, co-occurrence, Grantham difference, cross species conservation, functional assays, tumour characteristics (histopathology, IHC and MMR (in relatives), phenotype (eg summary family history)

16. Privacy and Confidentiality Published versus unpublished data Published versus unpublished data Tiered system of access managed by LOVD database Tiered system of access managed by LOVD database Governance Committee to manage processes and guidelines Governance Committee to manage processes and guidelines Informed by Human Variome Project (S Povey, R Cotton) Informed by Human Variome Project (S Povey, R Cotton)

17. Current Plans Incorporation of InSiGHT and registration as a charity (Jan 2010) Incorporation of InSiGHT and registration as a charity (Jan 2010) MTA and MOU with UK DMuDB to upload all UK diagnostic lab variants MTA and MOU with UK DMuDB to upload all UK diagnostic lab variants Testing of phenotype data extraction at clinic level (Australia, Denmark, Sweden, Germany, Israel, others welcome) Testing of phenotype data extraction at clinic level (Australia, Denmark, Sweden, Germany, Israel, others welcome) Assignment of pathogenicity derived from IARC/InSIGHT Bayesian analysis (S Tavtigian; M Greenblatt; S Lipkin) Assignment of pathogenicity derived from IARC/InSIGHT Bayesian analysis (S Tavtigian; M Greenblatt; S Lipkin) Mature operations of the Interpretation Committee (Paris, 2010) Mature operations of the Interpretation Committee (Paris, 2010) Software development for integration of disparate strands of data (Australian BioGrid, grant application to NCI (M Greenblatt, March 2009) Software development for integration of disparate strands of data (Australian BioGrid, grant application to NCI (M Greenblatt, March 2009) National node connectivity development (NeAT grant, Australia, 2009-12) National node connectivity development (NeAT grant, Australia, 2009-12) Communication strategies with NCBI and EBI (D Maglott, P Flicek: to do) Communication strategies with NCBI and EBI (D Maglott, P Flicek: to do) Upload more national MMR data to the InSiGHT database Upload more national MMR data to the InSiGHT database Fund raising to support curation, and governance and, interpretation committees (“Adopt-a-gene”; New York fun run) Fund raising to support curation, and governance and, interpretation committees (“Adopt-a-gene”; New York fun run)

18. InSiGHT Flow Pathway A (commencing with phenotype) Ascertainment of clinical phenotype (see attached) (Clinicians) IHC &/or MSI data added (Histopathology) Interpretation of genotype (Clinicians & Lab) Virtual pathology added (Histopathology) Functional data added (Research Labs) Identified dataset stored locally (Family Cancer Clinic) De-identified data stored InSiGHT DB Interpretation (InSiGHT) DbGaP (NCBI) UCSC EBI Data from other centres can be submitted to update information DNA Mutational Analysis (DNA Lab)

19. InSiGHT Flow Plan B (commencing with genotype) MMR mutation Identified (DNA Lab) IHC &/or MSI data added (Histopathology) Interpretation of genotype (Clinicians & Lab) Virtual pathology added (Histopathology) Functional data added (Research Labs) Clinical phenotype added (Clinicians) Identified dataset stored locally (Family Cancer Clinic) De-identified data stored with InSiGHT Interpretation (InSiGHT) DbGaP (NCBI) UCSC EBI Data from other centres can be submitted to update information

20. Countries represented in the InSiGHT/HVP Europe: Finland, Sweden, Germany, UK, Italy, Holland, Denmark, France, Spain, Portugal, Poland Middle East: Israel Africa: South Africa. America: USA, Canada, Brazil Oceania and Asia: Australia, Japan, New Zealand, Hong Kong, China, Korea

21. The US National Institutes of Health Colon Family Register (CFR) http://epi.grants.cancer.gov/CFR/about_colon.html

23. InSiGHT, NIH Colon Family Register and the Human Variome Project: A collaboration US NIH CFR Steering Committee Meeting April 2008 Meets June 24 th 2009 in Dusseldorf

24. InSiGHT/HVP/NIH Colon Family Register collaboration InSiGHT/HVP/NIH Colon Family Register collaboration Opportunity to integrate the strengths of the NIH CFR data (eg population based, and epidemiology) with the detail and clinical utility of the InSiGHT databases Opportunity to integrate the strengths of the NIH CFR data (eg population based, and epidemiology) with the detail and clinical utility of the InSiGHT databases Formation of International consortium of MMR investigators – April 2010, Washington Formation of International consortium of MMR investigators – April 2010, Washington

25. Measurement of success of InSiGHT/HVP initiative Variant submission rate Variant submission rate Annotations submitted, including phenotype Annotations submitted, including phenotype Automated text searching implemented Automated text searching implemented Interpretation processes completed and implemented on database Interpretation processes completed and implemented on database Hits Hits User time and motion study User time and motion study Extrapolation to other genes Extrapolation to other genes Funding Funding

26. InSiGHT/HVP acknowledgements: Databases and curation DNA Variant Curators and Governance: M Woods, P Peltomaaki, R Sijmons, H Vasen, J den Dunnen DNA Variant Curators and Governance: M Woods, P Peltomaaki, R Sijmons, H Vasen, J den Dunnen Phenotype: F Macrae, (Chair), R Scott, S Clarke, C Burke, T Weber, P Watson, A Lindblom, P Rozen, G Moeslein, I Bernstein Phenotype: F Macrae, (Chair), R Scott, S Clarke, C Burke, T Weber, P Watson, A Lindblom, P Rozen, G Moeslein, I Bernstein Virtual Histology: H Morreau, E Brazowski Virtual Histology: H Morreau, E Brazowski Missense And Functional Assays: R Sijmons (Chair), R Hofstra, M Lahti, N Winds Missense And Functional Assays: R Sijmons (Chair), R Hofstra, M Lahti, N Winds Interpretation: M Genuardi (Chair), J Utsunomiya, R Ramesar, J Burn, M Greenblatt, P Peltomaaki, R Hofstra, R Sijmons, R Scott, M Corish, D Golgar, M Woods, P Peltomaaki, B Bapat, S Tavtigian, A Spurdle, S Lipkin, M Dunlop Interpretation: M Genuardi (Chair), J Utsunomiya, R Ramesar, J Burn, M Greenblatt, P Peltomaaki, R Hofstra, R Sijmons, R Scott, M Corish, D Golgar, M Woods, P Peltomaaki, B Bapat, S Tavtigian, A Spurdle, S Lipkin, M Dunlop

27. Human Variome Project Richard Cotton Richard Cotton Lauren Hardiman, Renai Horaitis, Heather Howard, Tim Smith, S Forster Lauren Hardiman, Renai Horaitis, Heather Howard, Tim Smith, S Forster Human Variome Project Planning Committee Human Variome Project Planning Committee

28. Comments and Questions? Phenotype annotation to InSiGHT database? Phenotype annotation to InSiGHT database? Uploading to InSiGHT database? Uploading to InSiGHT database? Other? Other? Finlay.macrae@mh.org.au Finlay.macrae@mh.org.au