The NCI Office of Cancer Centers Learning Series :

1. The NCI Office of Cancer Centers Learning Series: The Cancer Genome Atlas Program: Comprehensive Cancer Genomics Data on 5,000 + Cases Across 24 Cancer Subtypes Dial In: 888-323-2720 Passcode: CANCER CENTERSFor Technical Support, call 800-857-8777 and choose option 3.

2. The NCI Office of Cancer Centers Learning SeriesThe Cancer Genome Atlas Program: Comprehensive Cancer Genomics Data on 5,000 + Cases Across 24 Cancer Subtypes Tuesday, November 1, 2011 2:00 to 3:30 pm EDT Moderator Shannon L. Silkensen, PhD Program Director Office of Cancer Centers National Cancer Institute National Institutes of Health Bethesda, MD Featured Presenters Kenna Shaw, PhD Deputy Director, The Cancer Genome Atlas Program Office National Cancer InstituteBethesda, MD Jill Barnholtz-Sloan, PhD Associate ProfessorCase Western Reserve University/University Hospitals Cleveland, OH

3. A Quick Guide to Your Screen Please submit your question via the Q & A box on the right hand side of your screen. If you do not see the Q&A box, you can expand it by clicking the Q&A on the top navigation panel and dragging it to the right side of your screen.

4. The Cancer Genome Atlas November 1, 2011 Kenna M. Shaw, Ph.D. Deputy Director The Cancer Genome Atlas Program

5. TCGA: Core Objectives Launched in 2006 as a pilot and expanded in 2009, the goals of TCGA are to: • Establish the needed infrastructure, environment, community where the big fish swim together • Develop a scalable “pipeline” beginning with highest quality samples • Determine the feasibility of a large-scale, high throughput, systematic approach to identifying all of the relevant genetic alterations in cancer • Systematically evaluate two cancers using a statistically-robust sample set (500 cancers and matched controls) • Make the data publicly and broadly available to the cancer communities in a manner that protected patient privacy

6. TCGA: “No Platform Left Behind” 25 forms of cancer glioblastomamultiforme(brain) squamous carcinoma(lung) serouscystadenocarcinoma(ovarian) Etc. Etc. Etc. Biospecimen CoreResource with more than 150 Tissue Source Sites 6 Cancer GenomicCharacterization Centers 3 GenomeSequencingCenters 7 Genome Data Analysis Centers Data Coordinating Center • Multiple data types • Clinical diagnosis • Treatment history • Histologic diagnosis • Pathologic report/images • Tissue anatomic site • Surgical history • Gene expression/RNA sequence • Chromosomal copy number • Loss of heterozygosity • Methylation patterns • miRNA expression • DNA sequence • RPPA (protein) • Subset for Mass Spec

7. TCGA: “No Platform Left Behind” 25 forms of cancer glioblastomamultiforme(brain) squamous carcinoma(lung) serouscystadenocarcinoma(ovarian) Etc. Etc. Etc. Biospecimen CoreResource with more than 150 Tissue Source Sites 6 Cancer GenomicCharacterization Centers 3 GenomeSequencingCenters 7 Genome Data Analysis Centers Data Coordinating Center • Multiple data types • Clinical diagnosis • Treatment history • Histologic diagnosis • Pathologic report/images • Tissue anatomic site • Surgical history • Gene expression/RNA sequence • Chromosomal copy number • Loss of heterozygosity • Methylation patterns • miRNA expression • DNA sequence • RPPA (protein) • Subset for Mass Spec

8. TCGA: The Pipeline for Comprehensive Characterization Tissue Sample GDAC Analysis Pathology QC Sequencing Data and Results Storage & QC Integrative Analysis DNA & RNAIsolation, QC Expression,CNA & LOH,Epigenetics Comprehensive Characterization of a Cancer Genome Analysis = Process = Data = Results = BCR = GSCs = CGCCs = DCC = GDACs

9. TCGA: Lessons Learned from the Pilot #1: It’s About Pathways and Integrated Analyses

10. TCGA: Lessons Learned from the Pilot I #2: Generating the comprehensive parts list will require many tumor types.

11. TCGA: Lessons Learned from the Pilot II #3: Publicly accessible, high-quality data helps build a community of users.

12. Making an Exhaustible Resource Inexhaustible

13. TCGA: Lessons Learned from the Pilot III #4: Comprehensive analysis is difficult and challenging to scale.

14. TCGA Dataset: Replete with Unanswered Questions Pilot Funding Continuation 2012 - 2014 Beyond 2014? 2007 2008 2009 2010 2011 GBM Report Ovarian Report Complete Data on 3000 New Cases • Pilot Projects: GBM and Ovarian carcinoma • Expansion: 10,000 more cases across 25 tumor types • Phase III: • More clinically relevant samples? • Smaller, more biologically relevant samples? • More of the same via array and sequencing? • Some combination of all the above? • None of it?

15. TCGA: Platforms- Then and Now *- Not all samples currently receiving low pass sequencing for Copy Number/Rearrangement assays More information on platforms and data available at: TCGA data portal Platform Design

16. Quality Data Requires Quality Biospecimens …Garbage out Diamonds in…… Garbage in… Modified from Jerry Thomas/Carolyn Compton

17. Sample Criteria Limit ‘Askable’ Questions • Primary,adult tumor only (except for melanoma) • Malignant (no in situ cases) • Snap frozen, <60min from clamp to LN2 • ~ 50 mg (aka no biopsies) • Pathology review of tissue sent to TCGA • No more than 20% necrosis ; ≥ 60% tumor cells • No prior treatment • Source of germline: Blood (buffy coat/white cells)/saliva or skin for liquid tumors • Clinical annotation; but not pre-analytic variables • IRB approval for use in TCGA • MTA w/out retention of IP 10,000 10

18. Biospecimen Core Resource Review Whole Genome Amplification (Qiagen) BCR Characterization Centers Collection of Clinical Data Elements Tissue Source Sites (TSS) Preliminary Pathology Review Qualified • Tumor Pathology QC • % Tumor Nuclei • % Necrosis • Dx Confirmation via histology and pathology report Data Coordinating Center • Molecular Analyte QC • Spectrophotometery • RNA Bioanalyzer • Electrophoresis • Genotyping Sequencing Centers Diagram courtesy R. Penny, International Genomics Consortium

19. Sample Loss, Time Loss, Money Loss

20. Consistent SOPs Reduce Batch Effects

21. Where to Begin- TCGA Tumor Types ~25 Tumor Types: What Questions do We Want to Ask? • AML • Breast Ductal* • Breast Lobular/Breast Other • Bladder (pap and non-pap) • Cervical adeno & squamous • Colorectal* • Clear cell kidney* • DLBCL • Endometrial carcinoma • Esophageal adeno & squamous • Gastric adenocarcinoma • GBM* • Head and Neck Squamous • Hepatocellular • Lower Grade Glioma • Lung adenocarcinoma • Lung squamous carcinoma • Melanoma (metastatic acceptable) • Ovarian serous cystadenocarcinoma • Papillary kidney • Pancreas • Prostate • Sarcoma (dedifflipo, UPS, leiomyosarcoma) • Papillary Thyroid Red- Pilot tumors; *- Reached 500

22. Progress toward 2011 goal(3,000 cases by Sept.)

23. Tumor Project Progress

24. Sample Acquisition over Time 80% Retrospective 60% pass rate ~80% pass rate 50% pass rate 80% Prospective

25. Qualification Rates by Tumor Type Pass Rate of the Future? 60%: $4,800,000 70%: $3,400,000 80%: $2.570,000

26. TCGA: Two Phase Acquisition • Retrospective • Generally ready to go and include longer term clinical follow up • Sites rarely have what they think they have and rigorous inclusion criteria mean that many existing samples are excluded • Prospective • Lag time to develop or expand networks averages 6-8 months • Sites rarely have what they think they have and rigorous inclusion criteria mean that many patients/samples are not eligible • Samples specifically acquired following TCGA protocols and generally have more consistent, higher “pass” rates • Samples lack initial follow up/clinical data

27. Minimum Clinical Data Set • TSS name/identifier/patient #  • Primary site of disease • Histological type • Tumor grade • Gender • Date of birth (month/year)  • Prior diagnosis of prior neoplasm (if yes, another form required) • Date of initial pathologic diagnosis (month/year) • Neoadjuvant therapy • Tumor stage • Date of last contact (month/year) • Vital status (month/year) • Date of death, if applicable (month/year) • Tumor-type specific elements developed by Tumor Project Group

28. Examples of Tumor Specific Questions • Smoking status (lung/bladder) • ER/PR/Her2+ (breast) • Biochemical recurrence (prostate) • Residual tumor after surgery (ovarian/sarcoma) • Prior malignancy details (melanoma) • International Prognostic Index (lymphoma)

29. Clinical Data Collection (Supplemental) • Pharmaceutical Treatment Form • Drugs, doses, days, regimens, dates, etc. • Simultaneously tracks chemotherapy, immunotherapy, molecularly targeted, hormone therapy • Radiation Treatment From • Type, location, dose, dates, etc.

30. Clinical Data Collection (Follow-Up) • Follow up Data Form • Type of treatment incurred • Measure of success to treatment • Recurrences, progression since last form completed • New tumor events • Additional surgeries • Last follow-up and vital status

31. TCGA-Cancer Center Collaborations • TCGA actively collaborates with investigators at 27 cancer centers • Room for significant growth for collaborations at other CCs for almost all tumor types • Funding opportunity to support sample acquisition to be announced later this year or early 2012 • Interested groups should contact shawk@mail.nih.gov for clinical data collection forms, sample inclusion criteria, etc. • Disease working groups engage investigators from all over the world in the first phase of analysis and collaborators are welcome

32. Acknowledgements • Barbara Wold (Center for Cancer Genomics Director) • Brad Ozenberger (NHGRI) • TCGA Project Team/Staff/Research Network Kenna Shaw: shawk@mail.nih.gov First Annual TCGA Scientific Symposium: TCGA 1st Annual Scientific Symposium

33. The NCI Office of Cancer Centers Learning SeriesThe Cancer Genome Atlas Program: Comprehensive Cancer Genomics Data on 5,000 + Cases Across 24 Cancer Subtypes Questions? Please submit your question via the Q & A box on the right hand side of your screen. If you do not see the Q&A box, you can expand it by clicking the Q&A on the top navigation panel and dragging it to the right side of your screen. Kenna Shaw, PhD Deputy Director, The Cancer Genome Atlas Program Office National Cancer InstituteBethesda, MD

34. Involvement in TCGA from the Comprehensive Cancer Center PerspectiveJill Barnholtz-Sloan, PhDjsb42@case.edu

35. Mechanisms for Cancer Center Involvement in TCGA • Individual accrual site for TCGA or member of an accrual network • Member of TCGA working groups • dbGAP controlled TCGA data access • Bioinformatics analysis for multiple cancers

36. Benefits of being a TCGA accrual site • “omics” data very expensive to generate • Limited “clinical” data in TCGA • Extensive data at individual cancer centers on these patients • In depth inquiry into your own patient samples to answer novel questions • Correlate with other “omic” data types

37. Introduction • Brain tumors account for ~1-2% of all cancers • Majority of malignant BTs are GLIOMAS • Majority of benign BTs are MENINGIOMAS • Incidence and survival vary greatly by histological type • Adult Incidence: 16.2/100,000 for benign 8.9/100,000 for malignant (CBTRUS 2011) • Adult Survival: 12-15 months for GBMs >5-10 years for low grade glioma >20 years for benign tumors

38. Known Prognostic Factors for BTs • Karnofsky Performance Score (KPS) • Age at diagnosis • Extent of surgical resection • Histological Type of Tumor • Quality of life and other cognitive/depression/etc measurements?? • Methylated at MGMT • Responsive to chemo and radiation • LaCroix et al, J Neurosurg, 2001 • GBM only • 13 months versus 8.8 months – p<0.0001

39. Ohio Brain Tumor Study (OBTS) • State of Ohio collaborative: • CWRU/UHCMC (Barnholtz-Sloan (PI), Gerson, Sloan, Selman) – Lead coordinating site • CCF (Barnett) • OSU (Chiocca) • U Cincinnati (Warnick, McPherson) • OBJECTIVE: To assess the association between “omics”, environmental factors and clinical outcomes for brain tumors • TCGA Network for accrual of brain tumors (PI: Barnholtz-Sloan)– also now includes St. Josephs hospital in Phoenix, AZ

40. Ohio Brain Tumor Study (OBTS)

41. Uniqueness and Strengths of OBTS 4 major academic centers in Ohio Standardized operating procedures for clinical annotation and biospecimen collection & processing Signed and executed research/MTAs Multi-disciplinary teams: neurosurgeons, oncologists, neuro-pathologists, nurses, basic scientists, research management

42. The Ohio Brain Tumor Study is: Brain Tumor and Neuro-Oncology Center at Case Western Reserve University / University Hospitals Case Medical Center: Jill Barnholtz-Sloan, PhD, Andrew Sloan, MD, Warren Selman, MD, Stanton Gerson, MD, Nicholas Bambakidis, MD, Clifford Megerian, MD, Mark Cohen, MD, Karen Devine, RN, BSN, CNRN, Henry Krzemien, RN, Wendi Barrett, Anita Merriam, Ashokkumar Patel, MD, Rajnish Gupta, Yingli Wolinsky, PhD, MBA Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center at the Cleveland Clinic:Gene H Barnett, MD, Manmeet Ahluwalia, MD, Michael Vogelbaum, MD, PhD, Susan Staugaitis, MD, PhD, Cathy Brewer, RN, Cathy Schilero, RN, BSN, Kathy Smolenski, RN, Barbara Denk, RN, Mary McGraw, Theresa Naska The Dardinger Neuro-oncology Center and The Department of Neurosurgery at the James Cancer Hospital and Ohio State University Medical Center: E Antontio Chiocca, MD, PhD, Abhik Ray Chaudhury, MD, Susan Bell, CNP, BSN, MSN, Laurie Johnson, Kelly Senecal, Phillip Knorr, Dina Aziz Brain Tumor Center at the University of Cincinnati:Ronald Warnick, MD, Christopher McPherson, MD, Ady Kendler, MD, Dale Greene, RN, Frances Laube, RN, Ruth Steele, BS, EMT-P, CCRC, Ashley Fehrenbach, Alison Kastl, BS, CCRC

43. Benefits of being a GBM and LGG Working Group Member • Involved in defining and prioritizing the questions to address with these datasets • Networking and further collaborations established

44. Benefits of having dbGAP TCGA controlled data access • Many investigators at Cancer Centers are interested in these data • bioinformatics/biostatistics expertise needed • Hypothesis generating and validation • Generating preliminary data for grants • Validation sets for publications

45. CWRU Barnholtz-Sloan Team

46. The NCI Office of Cancer Centers Learning SeriesThe Cancer Genome Atlas Program: Comprehensive Cancer Genomics Data on 5,000 + Cases Across 24 Cancer Subtypes Questions? Please submit your question via the Q & A box on the right hand side of your screen. If you do not see the Q&A box, you can expand it by clicking the Q&A on the top navigation panel and dragging it to the right side of your screen. Jill Barnholtz-Sloan, PhD Associate Professor Case Western Reserve University/University Hospitals Cleveland, OH

47. Disclosures • Kenna Shaw: No relevant financial relationships with commercial interest • Jill Barnholtz-Sloan: No relevant financial relationships with commercial interest

48. The NCI Office of Cancer Centers Learning SeriesThe Cancer Genome Atlas Program: Comprehensive Cancer Genomics Data on 5,000 + Cases Across 24 Cancer Subtypes If you have further questions, please contact: Kenna Shaw shawk@mail.nih.gov This webinar was created by the Office of Cancer Centers in the National Cancer Institute http://cancercenters.cancer.gov/ For information about the TCGA program through the National Cancer Institute, please visit http://cancergenome.nih.gov/