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The Cancer Genome Atlas and The Future of Personalized Medicine

A National and International Imperative to Eliminate the Cancer Burden . Canada138,000 / 66,000. United States of America1.4M / 566,000. Australia86,000 / 37,000. China2.2M / 1.6M. Austria37,000 / 19,000. France269,000 / 149,000. Germany408,000 / 218,000. . . Switzerland35,000 / 17,000. . .

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The Cancer Genome Atlas and The Future of Personalized Medicine

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    1. The Cancer Genome Atlas and The Future of Personalized Medicine BIO IT Coalition Conference May 4, 2006 Anna D. Barker, Ph.D. Deputy Director, National Cancer Institute

    3. The Human and Economic Burden of Cancer 570,280 Americans will die of cancer this year 1,372,910 Americans will hear the words you have cancer this year $189 billion per year on healthcare costs for cancer alone Reference note: Top two bullets are from ACS 2005 Cancer Facts and Figures Chart is from 2003 National Center for Health StatisticsReference note: Top two bullets are from ACS 2005 Cancer Facts and Figures Chart is from 2003 National Center for Health Statistics

    4. Cancers Reach Men have an almost 1 in 2 lifetime risk of developing cancer.

    5. Current Healthcare System: Reactive Focus on treatment, at the expense of prevention, results in: Significant unnecessary cost for expensive, acute care Significant burden on healthcare system especially in low-income communities Significant pain, suffering, and death for patients and their families Individual and national wealth and healthcare spending do not reduce these problems Rates of diabetes, hypertension, heart disease, myocardial infarction, stroke, lung disease, and cancer are higher in United States than other nation, even among wealthiest populations JAMA Journal of the American Medical Association; 2006;295:2037-2045 May 3, 2006

    6. The Shift to 21st Century Personalized Medicine

    7. Convergence: Molecular Biology, Advanced Technologies, Bioinformatics/Broadband

    8. What is a Genomic Alteration?

    10. Data Generation: Unprecedented Scale

    11. Bioinformatics: The Cancer Bioinformatics Grid (CaBIG) Piloted in cancer centers System, common software and systems Standards based Open source plug and play common language (e.g, clinical trials; biospecimens; genomic and clinical data ) Capability to integrate genomics, proteomics, animal models, etc. with clinical data Broad capability to connect all sectors Can provide support for electronic medical record Integrated with FDAs clinical trials reporting systems

    12. Standards

    13. Proof of Concept: Setting the Stage for The Cancer Genome Atlas

    14. The Human Genome Project Changed Everything HGP Resulted In: Understanding of genomic alteration and disease Sequencing of many genes Development of advanced genomics analysis technologies

    15. Gleevec: 50 Years From Discovery to Delivery Unfortunately, Gleevec took 50 years to develop. We hope that what we learn from TCGA will speed development of other cancer therapeutics.Unfortunately, Gleevec took 50 years to develop. We hope that what we learn from TCGA will speed development of other cancer therapeutics.

    16. 1st Generation Personalized Medicine Is Underway Clinical applications now include: Selection of breast cancer patients for optimal therapy Prevention of drug toxicity in the treatment of colorectal cancer and acute lymphoblastic leukemia Identification of individuals with high risk of breast cancer or melanoma for increased surveillance and preventive treatment FDA is committed to advancing molecular medicine The Critical Path Over 100 IND submissions to FDA contain pharmacogenomic data Pharmacogenomic data is being used to rescue drugs in clinical trials Major insurers (e.g., Blue Cross/Blue Shield and United Healthcare) are conducting cost-benefit studies for specific pharmacogenomic tests

    17. TCGA Pilot Project

    18. Critical Importance of the TCGA? TCGA is among the firstefforts to systematically use data generated by theHuman Genome Projectto better understand a specific disease cancer. An atlas of genomic alterations associated with major types of cancer could enable new scientific discoveries. Scientific discoveries arising from TCGA data may translate into: New targets for cancer therapeutics Ability to more specifically assign patients within clinical trials Assessment of risk for specific cancers

    19. What is TCGA? The Cancer Genome Atlas (TCGA) is a 3-year, $100 million pilot project of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI). TCGA Mission: Increase scientific understanding of the molecular basis of cancer and apply this information to improve our ability to diagnose, treat, and prevent cancer. TCGA Purpose: Determine the feasibility of a full-scale project to develop a complete atlas of all genomic alterations involved in cancer.

    20. Project Development History

    21. Broad Interest and Support Positive response from scientific community, business community, and the public. The National Cancer Institute and the National Human Genome Research Institute launched The Cancer Genome Atlas pilot project in December 2005. The idea met with a great deal of interest from the public and the media, as well as the scientific community and those who are focusing on finding better cancer diagnostics and treatments.The National Cancer Institute and the National Human Genome Research Institute launched The Cancer Genome Atlas pilot project in December 2005. The idea met with a great deal of interest from the public and the media, as well as the scientific community and those who are focusing on finding better cancer diagnostics and treatments.

    22. How TCGA Will Function

    23. Verify authenticity and perform the pathologic QC of qualified tumors from existing collections Perform central processing of specimens Develop and monitor the standard operating procedures for prospective specimen collection Track all specimen-related operations (consent, acquisition, transport, processing, QC, distribution) through caBIG Provide samples for technology platform comparisons Distribute materials Biospecimen Core Resource

    24. Genome characterization Expression profiling Copy number changes Epigenomics Improve existing technologies Epigenomics to meet required throughput rate Copy number detection and expression profiling for characterizing small amounts of biological samples Real-time data release into public database CGCCs RFA: Mechanism: U24 (cooperative agreement) Cancer Genome Characterization Centers (CGCCs)

    25. High-throughput Genome Sequencing Centers (NHGRI) Sequence large number of targets from at least 2 tumor types Develop and integrate sequencing technologies Genome Sequencing Centers RFA: Mechanism: U54 (cooperative agreement) Genome Sequencing Centers

    26. caBIG principles: open source, open access, open development Common, widely distributed infrastructure allows research community to focus on discovery Infrastructure: Data management Database development Specific analytic tools Inter-program communication caBIG-Based Bioinformatics Core Community driven Information was gathered from members of the cancer community across the country, spanning Discovery to Development to Delivery Hundreds of potential users at academic institutions and NCI Cancer Centers (researchers and clinicians) identified priorities and set the framework Open development All participants can develop tools, as long as they are shared Existing resources are applied and advanced whenever possible, rather than inventing tools de novo in every case Open access ALL caBIG resources are freely obtainable by the cancer community to ensure the full access and to maximize collaboration Community driven Information was gathered from members of the cancer community across the country, spanning Discovery to Development to Delivery Hundreds of potential users at academic institutions and NCI Cancer Centers (researchers and clinicians) identified priorities and set the framework Open development All participants can develop tools, as long as they are shared Existing resources are applied and advanced whenever possible, rather than inventing tools de novo in every case Open access ALL caBIG resources are freely obtainable by the cancer community to ensure the full access and to maximize collaboration

    27. Technology Development Opportunities For Technology Development Genomic rearrangement, epigenetic assays Highly parallel single molecule assays Method for selecting/enriching defined regions of genome Magnitude improvement in cost, throughput, accuracy, and precision Technology Development RFA Mechanisms: SBIR/STTR; R21 (exploratory/development)

    28. TCGA: Next Steps

    29. TCGA Milestones for 2006

    30. TCGA Pilot Project Milestones

    31. How Will TCGA Decide Which Tumors to Study First? Criteria: The tumor samples are derived from patients entered in a clinical trial with: Uniform entry criteria Consistent treatment Clinical data that has undergone regular audits Samples represent a single type of tumor and/or (if a solid tumor) derived from a single cancer site (e.g. brain, breast, lung, etc.) Tumors are from a primary tumor site Samples are properly consented for use in this project

    32. How Will TCGA Decide Which Tumors to Study First? Criteria continued: There must be a sufficient amount of each tumor sample to conduct the necessary analysis Tumor samples have been obtained and stored in a manner that meets the technical requirements of TCGA At least 500 individual samples from unique cancer cases are available All tumors samples have matched normal samples Individual tumor samples should contain at least 80% tumor cells

    33. Success Factors for TCGA By end of the 3-year pilot project, we hope to have: Completion of genomic analysis of two tumors, leading to identification of new genes involved in cancer Ability to find specific genomic alterations in the genes associated with cancer Ability to differentiate tumor subtypes based on genomic alterations Establishment of a genomics database that scientists can access Ability to translate genomic information into positive clinical outcomes

    35. Vision: 21st Century Personalized Medicine Lottery v certainty This is our new model and there are major trends shaping it Instead of relying on a description of a disease we will have certainty about the molecular characteristics of the disease Instead of empirical intervention well have rationale intervention directed by the better understanding of the disease Instead of treating all people as uniform well begin to treat as individuals Instead of practising reactive medicine, well practise pro-active disease management based on risk assessment, in short information based targeted care The days of exploratory operations have gone; the days of the average medicine being prescribed to everyone is no longer going to be acceptable This is a long journey and let me touch on how Amersham started on this journey 14 years ago Lottery v certainty This is our new model and there are major trends shaping it Instead of relying on a description of a disease we will have certainty about the molecular characteristics of the disease Instead of empirical intervention well have rationale intervention directed by the better understanding of the disease Instead of treating all people as uniform well begin to treat as individuals Instead of practising reactive medicine, well practise pro-active disease management based on risk assessment, in short information based targeted care The days of exploratory operations have gone; the days of the average medicine being prescribed to everyone is no longer going to be acceptable This is a long journey and let me touch on how Amersham started on this journey 14 years ago

    36. TCGA is an Important Step Toward Personalized Medicine But Barriers remain Lack of technology standards (genomics, informatics, emerging technologies) Lack of common technology platforms to enable the sharing of information and transfer to clinical application Lack of common reagents and highly qualified public data sets Inability to manage and interpret large quantities of pre-processed data Disconnect in developing tools needed for assessing the science in the development process Led to the FDAs Critical Path Lack of a coordinated, integrated system Lack of common vocabularies Need for new funding mechanisms to facilitate data sharing and collaboration Need for new clinical trials design models Existence of cultural barriers No sector can meet all of these challenges

    37. Personalized Medicine Is Transforming Discovery/Development/Delivery

    38. How To Stay Involved in TCGA Updates on TCGA website: http://cancergenome.nih.gov Updates in the NCI Cancer Bulletin: www.cancer.gov Coming Soon: Sign up at the TCGA website to receive automatic email updates

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