1. Establishing a Clinical Genomics Program at an Academic Medical Center Jason Merker, M.D., Ph.D. Co-director, Stanford Clinical Genomics Service Regional APC/PDAS Meeting, Kauai 10/23/2014

2. Introduction to Clinical Genomics (in 5 Slides)

3. Wellcome Collection – Medicine Now 3.4 billion units of DNA code: 127 volumes 1,000 pages per volume

4. Size of targeted regions in assays Genome – 127 volumesExome – 2.5 volumes500 gene panel – 40 pages50 gene panel – 4 pagesSingle gene – <1/10 of a page

5. Tumor/Normal or Trio Genome Sequencing Data

6. Limit of detection - % allele burden Assay type Average limit of detection (% allele burden) Genome sequencing~20 – 30% Exome sequencing~20 – 30% NGS-based gene panels5 – 10% Sanger sequencing20% Single mutation assay<10%

7. Some mutation types are difficult to detect by genome or exome sequencing technologies Mutation typeDifficulty Single nucleotide variant Small indels (<10-20 bp) Copy-number variants Structural variants Larger indels

8. Introduction to Clinical Genomics at Stanford

9. Clinical Genomics Efforts at Stanford Clinical Genomics Service GenePool Biobank Basic, Translational, and Clinical Research

10. Advisory Committee for Clinical Genomics NameOrganization/DepartmentDirector’s Role C. DawesStanford Children’s HealthCEO L. MinorSchool of MedicineDean A. RubinStanford Health CarePresident and CEO T. Quertermous*CV MedGenePool Biobank J. Ford*OncologyCancer Institute Genomics Programs Chief Cancer Genetics E. AshleyCV MedCo-director Clinical Genomics Service Institute for Inherited CV Disease L. BoxerHematologyVice Dean A. ButtePediatricsChief Division of Systems Medicine M. ChoPediatricsCenter for Biomedical Ethics L. HudginsPediatricsChief Medical Genetics J. MerkerPathologyCo-director Clinical Genomics Service K. OrmondGeneticsGenetics and Genomics Counseling Program I. SchrijverPathologyMolecular Pathology Laboratory M. SnyderGeneticsChair Genetics Director Center for Genomics & PM

11. Stanford Clinical Genomics Service Directors – Jason Merker (Path), Euan Ashley (CV Med) Department – Pathology Goal – Build a clinical laboratory service at Stanford University Medical Center that uses genome sequencing to evaluate adult and pediatric patients with unexplained genetic diseases. Pilot – Develop analysis/curation pipeline and perform genome sequencing on 4 patient populations (100 cases total): – Heritable cancer predisposition – Heritable cardiovascular disorders – Pediatric syndromes – Familial adverse drug reactions or sensitivity

12. Workflow – 1 Test Request Patient and physician request genome sequencing for heritable disease through EMR Review by Genetic Test Consultation Service Genetic Counselor Molecular Pathologist Medical Geneticist Analysis Team MP/MGBiocurator Genetic Counselor Treating Team Outside Faculty Expert (prn) Establish questions being posed by patient and treating team Genetic? Candidate variants and analysis approach Clinical use

13. Workflow – 2 Insurance authorization Patient meets with genetic counselor Clinical counseling & consent *Options for return of secondary findings 2-step consent process for non-actionable findings Biobanking and data-sharing counseling & consent Blood draw 1 tube for genome sequencing 1 tube for confirmatory studies and specimen ID 1 tube for biobanking (with appropriate consent)

14. Workflow – 3 Illumina genome sequencing Data analysis (open source, commercial, and Stanford developed): Alignment Variant calling Quality management ID and gender checks to confirm specimen identity Variant filtering/prioritization Phenotype Inheritance pattern Predicted deleterious Secondary findings

15. Workflow – 4 Variant verification by orthogonal method Segregation analysis Curation meeting and draft report Genomics Review Boards Pediatrics Cardiovascular Oncology Pharmacogenomics Genomics Review Groups Genomics Service Treating Team Content expert

16. Workflow – 5 Final report generated and uploaded to EMR Patient meets with genetic counselor and relevant members of treatment team Yearly re-analysis upon request Improved analysis Improved sequencing Increased medical knowledge

17. Case 1 – 30 YOM w/ DCM TTN A-band truncating variant that segregates with disease in large family – likely pathogenic RYR1 variant (malignant hyperthermia) – likely pathogenic vs. variant of uncertain significance

18. Case 2

19. Clinical Genetic Test Consultation Service

20. Clinical Genetic Test Consultation Service Rationale #1 – The number of clinical genetic tests is becoming unmanageable The CDC estimates that genetic tests for use in the clinical setting have been developed for approximately 2,000 diseases

21. Clinical Genetic Test Consultation Service Rationale #2 – The number of misorders for complex genetic testing is high Miller CE et al. 2014. Am J Med Genet Part A 164A:1094–1101. “Approximately 25% of all requests for complex genetic tests assessing germ line mutations were changed following review.”

22. Clinical Genetic Test Consultation Service – Summary of rationales The number, indications, and complexity of genetic tests offered have been increasing, and will continue to do so for the foreseeable future. It is therefore not surprising that mistakes often occur in the ordering of complex genetic tests. Incorrect ordering of genetic tests results in unnecessary costs to the healthcare system, but more importantly adversely affects the care of our patients – Failure or delays in getting the needed test results – Communication of results from the incorrect test – Providing genetic information that was neither requested nor desired by the patient

23. Clinical Genetic Test Consultation Service – Personnel Molecular Pathologist Genetic Counselor Medical Geneticist

24. Clinical Genetic Test Consultation Service 1.Provide consultation to SUMC healthcare providers needing further information on available genetic testing. 2.Review all quests for send-out genetic testing from Stanford Clinical Laboratories to identify and help correct genetic test misorders. 3.Work with Genetic Test Utilization Committee develop innovative, provider-friendly ways to educate our physicians about genetic test utilization (e.g., pop-up windows in EMR offering test consultation or other educational information). 4.Assist departments and divisions with educational activities related to genetic test utilization (e.g., seminars, presentation to new residents) and with establishing protocols for genetic test ordering for common use cases

25. Clinical genomics educational efforts

26. Open Didactic Core Curriculum in Genomic Medicine 1.Experimental methods for measuring and manipulating DNA/RNA 2.Fundamentals of human genetic variation 3.Microarrays and analysis of hybridization data 4.Sequencing methods 5.Heritable genetic disorders 6.Acquired mutations in human cancers I: solid tumors 7.Acquired mutations in human cancers II: hematopoietic malignancies 8.Pharmacogenomics 9.HLA genetics 10.Ethical, legal, and economic implications of clinical genomic testing Schrijver I et al. J Mol Diagn. 2013;15:141.

27. Elective Course in Advanced Genomic Medicine 1.Next-generation sequencing methods 2.0 2.Human genetic variation 2.0 3.DNA sequence analysis methods I: sequence databases and files 4.DNA sequence analysis methods II: sequence alignment algorithms 5.DNA sequence analysis methods III: genome assembly and analysis 6.Introduction to scripting programming languages 7.Statistical tools for sequence analysis and genomics Schrijver I et al. J Mol Diagn. 2013;15:141.

28. Elective Course in Advanced Genomic Medicine 1.Next-generation sequencing methods 2.0 2.Human genetic variation 2.0 3.DNA sequence analysis methods I: sequence databases and files 4.DNA sequence analysis methods II: sequence alignment algorithms 5.DNA sequence analysis methods III: genome assembly and analysis 6.Introduction to scripting programming languages 7.Statistical tools for sequence analysis and genomics Schrijver I et al. J Mol Diagn. 2013;15:141.

29. New Elective Course in Advanced Genomic Medicine Genome and exome analysis for heritable disease Tumor/normal sequencing analysis RNA sequencing analysis Unix commands and basic scripting

30. End