Converged IT Summit - NCI Data Sharing
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The document discusses the Cancer Moonshot initiative and its goal to enhance cancer research through the genomic data commons, focusing on precision medicine and the sharing of genomic data. Estimates from 2015 indicated 1.7 million new cancer cases in the U.S., highlighting the need for improved research frameworks that integrate data for better outcomes in prevention and treatment. The genomic data commons aims to facilitate data interoperability, accessibility, and discovery to support a national cancer learning health system.
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Precision Oncology
Trials Launched
2014:
MPACT
Lung MAP
ALCHEMIST
Exceptional Responders
2015:
NCI-MATCH
2017:
Pediatric-MATCH
NCI-MATCH: Features
[Molecular Analysis for Therapy Choice]
Foundational treatment/discovery trial;
assigns therapy based on molecular
abnormalities, not site of tumor origin for
patients without available standard
therapy
Regulatory umbrella for phase II
drugs/studies from > 20 companies;
single agents or combinations
Available nationwide (2400 sites)
Accrual began mid-August 2015
Latest match-rate is 25% with 24 open
arms
Biopsy results in 13 days, average from
June-Sept 2016](https://image.slidesharecdn.com/ncigdcfairconvergeditsummitkibbe-161103214049/85/Converged-IT-Summit-NCI-Data-Sharing-16-320.jpg)
Converged IT Summit - NCI Data Sharing
- 1. Cancer Moonshot, Data Sharing, Genomic Data Commons October 26th, 2016 Warren Kibbe, PhD Warren.kibbe@nih.gov @wakibbe
- 2. 2 To develop the knowledge base that will lessen the burden of cancer in the United States and around the world. NCI Mission
- 3. 3 Cancer Statistics In 2015 there will be an estimated 1,700,000 new cancer cases and 600,000 cancer deaths - American Cancer Society 2015 Cancer remains the second most common cause of death in the U.S. - Centers for Disease Control and Prevention 2015
- 4. 4 Understanding Cancer Precision medicine will lead to fundamental understanding of the complex interplay between genetics, epigenetics, nutrition, environment and clinical presentation and direct effective, evidence-based prevention and treatment.
- 5. Cancer Moonshot: Genomic Data Commons, Data sharing, Ecosystem The era of precision oncology is predicated on the integration of research, care, and molecular medicine and the availability of data for modeling, risk analysis, and optimal care The Genomic Data Commons is a completely new way of making scientific data available to the cancer research community
- 6. 6 Cancer Data Sharing & Data Commons • Making data available for discovery, validation, new therapies • Working toward a National Learning Health System for Cancer • Maximizing the impact, reuse, and reproducibility of cancer research • We need to change the incentives for data sharing Reduce the risk, improve early detection, outcomes and survivorship in cancer
- 7. 7 FAIR – Making data Findable, Accessible, Attributable, Interoperable, Reusable, and provide Recognition Force11 white paper https://www.force11.org/group/fairgroup/fairprinciples
- 8. 8 NIH Genomic Data Sharing Policy https://gds.nih.gov/ Went into effect January 25, 2015 NCI guidance: http://www.cancer.gov/grants-training/grants- management/nci-policies/genomic-data Requires public sharing of genomic data sets
- 9. 9 Changing the conversation around data sharing How do we find data, software, standards? How can we make data, annotations, software, metadata accessible? How do we reuse data standards How do we make more data machine readable? NIH Data Commons NCI Genomic Data Commons Data commons co-locate data, storage and computing infrastructure, and commonly used tools for analyzing and sharing data to create an interoperable resource for the research community. *Robert L. Grossman, Allison Heath, Mark Murphy, Maria Patterson, A Case for Data Commons Towards Data Science as a Service, to appear. Source of image: Interior of one of Google’s Data Center, www.google.com/about/datacenters/.
- 10. Cancer Research Data Ecosystem – Cancer Moonshot BRP Well characterized research data sets Cancer cohorts Patient data EHR, Lab Data, Imaging, PROs, Smart Devices, Decision Support Learning from every cancer patient Active research participation Research information donor Clinical Research Observational studies Proteogenomics Imaging data Clinical trials Discovery Patient engaged Research Surveillance Big Data Implementation research SEERGDC
- 11. 11 Cancer Research Data Commons Ecosystem Genomic Data Commons Data Standards Validation and Harmonization Imaging Data Commons Proteomics Data Commons Clinical Data Commons (Cohorts / Indiv.) SEER (Populations) Data Contributors and Consumers Researchers PatientsClinician s Institutions
- 12. 12 (10,000+ patient tumors and increasing) Courtesy of P. Kuhn (USC) 2006-2015: A Decade of Illuminating the Underlying Causes of Primary Untreated Tumors Omics Characterization
- 13. 13 1997 20152001 20051998 20142002 20061999 2003 20112000 2004 2007 20122008 20132009 2010 10/23/2001 (~5 yrs old) 4/21/1997 1/9/2007 (~10 yrs old) iPod (10GB max) WinAMP(mp3) iPhone (EDGE, 16 GB max) 9/16/1999 (~3 yrs old) 802.11b WiFi 4/3/2010 (~13 yrs old) iPad (EDGE, 64 GB max) 4/23/2005 (~8 yrs old) 9/26/2006 (~9 yrs old) 7/15/2006 2/7/2007 Google Drive 4/24/2012 (~15 yrs old)7/11/2008 (~11 yrs old) iPhone 3G (16 GB max) 9/12/2012 (~15 yrs old) iPhone5 (LTE, 128 GB max) Google Baseline 7/14/2014 (~17 yrs old) 3/9/2015 (~18 yrs old) Digital technology is changing rapidly
- 14. 14 $640M (FY74) $5.21 B (FY16) Cancer therapy is changing
- 15. 1518 Application of Cancer Genomics is changing
- 16. 16 Precision Oncology Trials Launched 2014: MPACT Lung MAP ALCHEMIST Exceptional Responders 2015: NCI-MATCH 2017: Pediatric-MATCH NCI-MATCH: Features [Molecular Analysis for Therapy Choice] Foundational treatment/discovery trial; assigns therapy based on molecular abnormalities, not site of tumor origin for patients without available standard therapy Regulatory umbrella for phase II drugs/studies from > 20 companies; single agents or combinations Available nationwide (2400 sites) Accrual began mid-August 2015 Latest match-rate is 25% with 24 open arms Biopsy results in 13 days, average from June-Sept 2016
- 17. 17 Vice President’s Cancer Moonshot How do we enable meaningful, patient-centered and patient-level data sharing for cancer and promote access to clinical trials for all Americans?
- 18. 18 Cancer Moonshot Outline • Genomic Data Commons June 6, 2016 • Vice President’s Cancer Moonshot Summit – June 29, 2016 • Rethinking Clinical Trial Search - Development of Application Programming Interface (API) to NCI’s Clinical Trials Reporting Program, for use by: - NCI’s Cancer.gov website - Third party innovators providing clinical trial content to their communities • Blue Ribbon Panel recommendations – accepted by the National Cancer Advisory Board on September 7th, 2016 • Cancer Moonshot Task Force and BRP recommendations sent to President on October 17th, 2016 https://www.cancer.gov/research/key-initiatives/moonshot-cancer- initiative/milestones • https://cancer.gov/brp
- 20. Blue Ribbon Panel Recommendations Network for Direct Patient Engagement Cancer Immunotherapy Translational Science Network Therapeutic Target Identification to Overcome Drug Resistance A National Cancer Data Ecosystem for Sharing and Analysis Fusion Oncoproteins in Childhood Cancers Symptom Management Research Prevention and Early Detection – Implementation of Evidence-based Approaches Retrospective Analysis of Biospecimens from Patients Treated with Standard of Care Generation of 4D Human Tumor Atlas Development of New Enabling Cancer Technologies
- 21. 21 The Cancer Genomic Data Commons (GDC) is an existing effort to standardize and simplify submission of genomic data to NCI and follow the principles of FAIR – Findable, Accessible, Attributable, Interoperable, Reusable, and Provide Recognition. The GDC is part of the NIH Big Data to Knowledge (BD2K) initiative and an example of the NIH Commons Genomic Data Commons Microattribution, nanopublications, tracking the use of data, annotation of data, use of algorithms, supports the data /software /metadata life cycle to provide credit and analyze impact of data, software, analytics, algorithm, curation and knowledge sharing Force11 white paper https://www.force11.org/group/fairgroup/fairprinciples
- 22. NCI Genomic Data Commons The GDC went live on June 6, 2016 with approximately 4.1 PB of data. This includes: 2.6 PB of legacy data; and 1.5 PB of “harmonized” data. 577,878 files about 14194 cases (patients), in 42 cancer types, across 29 primary sites. 10 major data types, ranging from Raw Sequencing Data, Raw Microarray Data, to Copy Number Variation, Simple Nucleotide Variation and Gene Expression. Data are derived from 17 different experimental strategies, with the major ones being RNA-Seq, WXS, WGS, miRNA-Seq, Genotyping Array and Expression Array. Foundation Medicine announced the release of 18,000 genomic profiles to the GDC at the Cancer Moonshot Summit.
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- 26. Genomic Data Commons Data Portal https://gdc.cancer.gov
- 27. The NCI Genomic Data Commons User Interface Home Page
- 28. The NCI Genomic Data Commons User Interface Sample Browser
- 29. 29 Clinical data Biospecimen data Molecular data Files uploaded The NCI Genomic Data Commons User Interface Data Submission Dashboard
- 30. Development of the NCI Genomic Data Commons (GDC) To Foster the Molecular Diagnosis and Treatment of Cancer GDC Bob Grossman PI Univ. of Chicago Ontario Inst. Cancer Res. Leidos Institute of Medicine Towards Precision Medicine 2011
- 31. The Mutational Burden of Human Cancer Mike Lawrence and Gaddy Getz, Broad Institute: Nature 2014 Increasing genomic complexity Childhood cancers Known Carcinogens
- 35. Discovery of Cancer Drivers With 2% Prevalence Lung adeno. + 2,900 Colorectal + 1,200 Ovarian + 500 Lawrence et al, Nature 2014 Power Calculation for Cancer Driver Discovery Need to resequence >100,000 tumors to identify all cancer drivers at >2% prevalence
- 36. GDC Infrastructure and Functionality Data Submitters Open Access Users Controlled Access Users eRA Commons & dbGaP Open Access Data Metadata+Data Storage Reporting System Harmonization GDC Users GDC System Components Data Submission Data Security System APIsDigital ID System Controlled Access Data
- 37. Exome-seq Whole genome-seq RNA-seq Copy number Genome alignment Genome alignment Genome alignment Data segmentation 1° processing Mutations Mutations + structural variants Digital gene expression Copy number calls 2° processing Oncogene vs. Tumor suppressor Translocations Relative RNA levels Alternative splicing Gene amplification/ deletion 3° processing GDC Data Harmonization Multiple data types and levels of processing
- 38. Mutect2 pipeline GDC Data Harmonization Open Source, Dockerized Pipelines
- 39. Recovery rate (% true positives) A0F0 SomaticSniper 81.1% 76.5% VarScan 93.9% 84.3% MuSE 93.1% 87.3% All Three 96.4% 91.2% GDC variant calling pipelines Wash U Baylor Broad GDC Data Harmonization Multiple pipelines needed to recover all variants
- 40. GDC Content TCGA 11,353 cases TARGET 3,178 cases Current Foundation Medicine 18,000 cases Cancer studies in dbGAP ~4,000 cases Coming soon NCI-MATCH ~5,000 cases Clinical Trial Sequencing Program ~3,000 cases Planned (1-3 years) Cancer Driver Discovery Program ~5,000 cases Human Cancer Model Initiative ~1,000 cases APOLLO – VA-DoD ~8,000 cases ~58,000 cases
- 41. Towards a Cancer Knowledge System Continue genomic investigations of cancer • Need > 100,000 cases analyzed • Embrace all genomic platforms • Relationship of relapse and primary biopsies Incorporate associated clinical annotations • Clinical trial data • Observational, longitudinal standard-of-care data • N-of-1 clinical data Promote and curate biological investigations of cancer genetic variants • Driver vs. passenger mutations • Multiple phenotypic assays • Alterations in regulatory pathways – proteomics • Mechanisms of therapeutic resistance • Functional genomic investigations Integrative models for high-dimensional data Genomic Data Commons
- 42. GDC Utility of a Cancer Knowledge System Identify low-frequency cancer drivers Define genomic determinants of response to therapy Compose clinical trial cohorts sharing targeted genetic lesions Cancer information donors Genomic Data Commons
- 43. 43 Support the Precision Medicine Initiative • Expand data model to include other data (e.g. imaging and proteomics) • Allow easy publication of persistent links to data, annotations, algorithms, tools, workflows • Measure usage and impact • Change incentives for public contributions The Genomic Data Commons and Cloud Pilots
- 44. 44 PMI – Oncology, the GDC and the Cloud Pilots Goals Support precision medicine-focused clinical research Enable researchers to deposit well-annotated (Interoperable) genomic data sets with the GDC Provide a single source (and single dbGaP access request!) to Find and Access these data Enable effective analysis and meta-analysis of these data without requiring local downloads – data Reuse Understand Contributions, Assess value through usage, and give Attribution to all users
- 45. 45 PMI – Oncology, the GDC and the Cloud Pilots Goals Provide a data integration platform to allow multiple data types, multi-scalar data, temporal data from cancer models and patients through open APIs Work with the Global Alliance for Genomics and Health (GA4GH) to define the next generation of secure, flexible, meaningful, interoperable, lightweight interfaces – open APIs Engage the cancer research community in evaluating the open APIs for ease of use and effectiveness
- 46. Cancer Research Data Ecosystem – Cancer Moonshot BRP Well characterized research data sets Cancer cohorts Patient data EHR, Lab Data, Imaging, PROs, Smart Devices, Decision Support Learning from every cancer patient Active research participation Research information donor Clinical Research Observational studies Proteogenomics Imaging data Clinical trials Discovery Patient engaged Research Surveillance Big Data Implementation research SEERGDC
- 47. GDC Acknowledgements NCI Center for Cancer Genomics Univ. of Chicago Bob Grossman Allison Heath Mike Ford Zhenyu Zhang Ontario Institute for Cancer Research Lou Staudt Zhining Wang Martin Ferguson JC Zenklusen Daniela Gerhard Deb Steverson Vincent Ferretti 'Francois Gerthoffert JunJun Zhang Leidos Biomedical Research Mark Jensen Sharon Gaheen Himanso Sahni NCI NCI CBIIT Tony Kerlavage Tanya Davidsen
- 48. CGC Pilot Team Principal Investigators • Gad Getz, Ph.D - Broad Institute - http://firecloud.org • Ilya Shmulevich, Ph.D - ISB - http://cgc.systemsbiology.net/ • Deniz Kural, Ph.D - Seven Bridges – http://www.cancergenomicscloud.org NCI Project Officer & CORs • Anthony Kerlavage, Ph.D –Project Officer • Juli Klemm, Ph.D – COR, Broad Institute • Tanja Davidsen, Ph.D – COR, Institute for Systems Biology • Ishwar Chandramouliswaran, MS, MBA – COR, Seven Bridges Genomics GDC Principal Investigator • Robert Grossman, Ph.D - University of Chicago • Allison Heath, Ph.D - University of Chicago • Vincent Ferretti, Ph.D - Ontario Institute for Cancer Research Cancer Genomics Project Teams NCI Leadership Team • Doug Lowy, M.D. • Lou Staudt, M.D., Ph.D. • Stephen Chanock, M.D. • George Komatsoulis, Ph.D. • Warren Kibbe, Ph.D. Center for Cancer Genomics Partners • JC Zenklusen, Ph.D. • Daniela Gerhard, Ph.D. • Zhining Wang, Ph.D. • Liming Yang, Ph.D. • Martin Ferguson, Ph.D.
- 49. 49 Rethinking Clinical Trials Search Thanks to: PIFs, various NCI teams (CBIIT, CCCT, OCPL)
- 50. 50 Improving Cancer Clinical Trials Search Engage Presidential Innovation Fellows Create an Application Programming Interface (API) for clinical trials Engage with third-party innovators to guide the API development process Utilize the API on NCI’s website, cancer.gov *An API is a set of protocols that provides communication between a software application and a computer operating system or between applications
- 51. 51 The API (https://clinicaltrialsapi.cancer.gov/v1/) makes publicly available trial registration information from NCI’s clinical trial data base (Clinical Trial Reporting Program, CTRP) available to third-party innovators Enables innovators to build new tools tailored to the clinical trial search need of their users Expands opportunities for patients and doctors to locate cancer trials Cancer.gov now utilizes the API (http://trials.cancer.gov) , enhancing clinical trial searching on the NCI website The API source code is publicly available on GitHub (https://github.com/presidential-innovation-fellows/clinical-trials-search) Cancer Clinical Trials API
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