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Consortia: A Tool for Interdisciplinary Research
in Cancer Genetic Epidemiology
Daniela Seminara, Ph.D., MPHEGRP
Desirable Characteristics of Interdisciplinary Consortia in Cancer
Genetic Epidemiology
• Large studies with interdisciplinary teams working at solving complex scientific problems and responding to an obvious opportunity to advance scientific discovery and its applications
• Intensely collaborative• Common Protocol and Methods• Coordinated Parallel and Pooled Analyses
• Development of a resource for testing hypotheses from entire research community
• Exchange of concepts, approaches and intellectual discourse produces results beyond these possible with single-discipline approaches
Why Consortia in Cancer Genetic Epidemiology?
A Consortium can support the study of:• Interactions with environmental exposures• Complex multigenic effects• Gene discovery• Etiologic heterogeneity for tumor subgroups• Prognostic factors
A Consortium can facilitate:• Rapid replication of findings.• Pooling of data to increase sample size.• New large-scale efforts.
Where are Epidemiologic Consortia on the NIH Roadmap?
Interdisciplinary Research Implementation Group▪ Interdisciplinary Research (IR) Centers. Planning grants will be awarded to begin IR programs that will address significant and complex biomedical problems, particularly those that have been resistant to more traditional approaches. Planning activities will include approaches to overcoming traditional institutional barriers to IR, which are intended to lay the foundation and prepare investigators for submitting a subsequent application for support through an IR Consortium. (NIH website)
EGRP $ In Consortia (in Millions)
$225
$740
N on-C onsortiaC onsortia
EGRP- Supported Epidemiology Consortia: Flexibility of Design
CohortsConsortium
Breast and Colon CFRs
(hybrid design)
Familial Consortia
Case-ControlConsortia
Gene discoveryGene characterizationGxG and GxE
Translational Clinical GeneticsScreening/prevention/treatment
Design-Based Consortia
• Cohorts: • multiple outcomes • converging mechanisms
• Case-control: • less common tumors• specialized components
• Family-based: • high and intermediate penetrance genes • environmental modifiers
Existing or Developing Consortia by Cancer Site
(1996-2005) Prostate Lung Melanoma Breast Colon Chronic Lymphocytic
Leukemia Multiple Myeloma
Brain Lymphoma Bladder Esophagus Head and Neck Pancreas Ovarian Endometrial Others…
Characteristics of Consortia in Cancer Genetic
Epidemiology Retrospective and/or prospective data Based on cancer site or research theme Initially formed by investigators or
solicited by funded agency Support for infrastructure and/or for
research project (s) Different levels of data and biospecimen
sharing Centralized or de-centralized molecular
technologies
How does the Epidemiology and Genetics Research Program (EGRP)
Foster Consortia?
Identify research prioritiesAssess needsProvide resources, coordination and communication among participating groups and with other consortia (website, portal, meetings)Facilitate and expedite research implementation and translational processPerformance evaluation: in cooperation with investigators, develops milestones and “best practices”Involvement in planning and liaison with other agencies/institutions
Emerging Consortia: Criteria for Evaluation (EGRP-CWG)
Emerging consortium: a group of three or more groups of investigators from different institutions planning to launch a joint initiative by combining resources from case-control, familial or cohort studies.
Criteria: Scientific rationale and justification of need : what are the scientific
questions that only the consortium can address Preliminary rationale that large numbers are needed to address
questions outlined in #1 Outline of proposed internal leadership and organizational structure Outline of guidelines for sharing of data and specimen resources
and publication policies Tabulation of similarities and differences in design, data variables,
and specimen acquisition and storage (if applicable) across studies Proposed plan to address informed consent issues
Consortia Challenges and Possible Solutions (CWG)
CHALLENGES POSSIBLE SOLUTIONS
Communication and coordination
Informed consent and IRBs’ variable behaviors
Website, portals, teleconferences and in-person meetings
Prospective consortia, re-consent, IRBs’education
Informatics and analytic support for collection, management and analysis of extremely large and complex datasets
Central informatics units, standardization of informatics platform (caBIG), “think tank for analytic challenges”
Rapid and continuous integration of cutting-edge genomic and other technologies
Centralized technology platforms, public-private partnership
Biorepositories: centralized versus local, large scale retrieval of tissue
Work toward maximizing bioresources (transformed cell lines,WGA, pooling, tissue microdissection, multiplex microarrays)
Integration of disciplines Interdisciplinary training, integration of new knowledge and concepts as they arise, shift in academic culture triggered by multiple outcome funding approaches
CHALLENGES POSSIBLE SOLUTIONSIntellectual property rights Carefully crafted agreements, involving all
partners
Authorship and principal investigatorship (especially for young investigators)
Change in structure of funding mechanisms, tenure criteria, publication credits.
Access for the scientific community at large (Data sharing)
Development of clear process and policies (I.E. CFRs), NIH may help with cost of sharing data
Review Process Appropriate IRG, education of peer scientists Interdisciplinary science requires interdisciplinary peer-review
Interdisciplinary research teams take time to assemble and require unique resources
Appropriate criteria for evaluation and measure of productivity taking in account planning and time to establish Infrastructure. Evaluate core activities and tools developed
…and More
The Breast and ColonCancer Family Registry
A Hypothesis-Driven Research Infrastructure Sponsored
by the National Cancer Institute
http://epi.grants.cancer.gov/CFR/
BC-CFR Objectives
To establish a comprehensive research resource infrastructure to assist with the implementation of collaborative, interdisciplinary research protocols in the genetic epidemiology of breast, ovarian, colon and related cancers
To identify, characterize, and follow-up a cohort of individuals and their family members, spanning the spectrum of cancer risk
To identify diverse genetically susceptible populations that could benefit from enrollment in preventive and therapeutic interventions
To develop an adaptive and evolving informatics model to support ongoing and future research consortia
BC-CFRs Components Funding
B-CFR Phase I B-CFR Phase II B-CFR Phase III
C-CFR Phase I C-CFR Phase II
Informatics Center Informatics Center’95 ’96 ’97 ’98 ’99 ’00 ’01 ’02 ’03 ’04 ’05 ’06 ’07 ’08 ’09 ’10 ‘11
Fiscal Year
(Phase I, Phase II, Proposed Phase III)
BC-CFR Funding Support
BC-CFR SitesColon CFR: Australia Consortium, University of
Melbourne John Hopper
Cancer Care Ontario Steve Gallinger
Fred Hutchinson Cancer Research Center, Seattle John Potter
Mayo Clinic Noralane Lindor
Cancer Research Center of Hawaii Loic Le Marchand
USC (LA) Consortium Robert Haile
Affiliated Sites – Galicia, Spain; Newfoundland, Canada; Northern California Cancer Center
Breast CFR: Australia Consortium, University of
Melbourne John Hopper
Fox Chase Cancer Center, Philadelphia Mary Daly
Metropolitan New York Ruby T. Senie
Northern California Cancer Center Esther M. John
Cancer Care Ontario Irene Andrulis
University of Utah, Huntsman Cancer Institute Saundra Buys
BC-CFR Organizational
StructureNCI Program
Officer
Core Working Groups
Research Working Groups
Steering Committee
Advisory Committee
Informatics Center
Six Awarded Sites (and Affiliates)
Adapted John et al. Breast Cancer Res 2004
Design of the BC-CFR
COLLABORATIVE
FAMILIES
PopulationBased
Clinic-based
Participating Sites (U01s)
CentralRegistry
DataBase
CentralRegistry
DataBase
Informatics Center (Contract)Biospecimen Repositories
Molecular Genetics Laboratories
Family History
Risk Factors Qs
Clinical/Pathology
Biospecimen Tracking
Follow-up
Molecular Characterization
Informatics Units
Pilot Studies
S T U D I E S
BC-CFR Core Activities
Core Activities Follow-up of enrolled proband/families and new families Molecular characterization (mutational/genotyping) Biospecimen repositories Virtual tissue repository Informatics Support Administrative, travel and coordination Accrual of new probands/families Minorities/ethnic projects Ashkenazi*
Additional Activities Pilot/ancillary projects Establishment of fresh frozen tissue repository
BC-CFR Core Study Designs(Genetic Epidemiology)
Adapted from Study Designs to Identify and Characterize Disease Susceptibility Genes, AS Whittemore and LM Nelson, JNCI Monograph 26, 1999
Goal DesignIdentify new disease genes
Linkage Studies Parametric Linkage
Non-parametric Linkage
Association Studies Case-unrelated Control
Case-related Control
Characterize known disease genes
Estimating Allele Frequency
Cross-sectional Studies
Estimating Penetrance
Case-unrelated Control
B-CFR Consented Participants
6916
3184
1052 934
12825
4692
1811
92
1266
0
2000
4000
6000
8000
10000
12000
14000
CaseProbands
ControlProbands
AffectedRelatives
UnaffectedRelatives
BreastAffected
Probands
OvarianAffected
Probands
UnaffectedProbands
Population-basedClinic-based
Collected (1997-2004)
C-CFR Consented Participants
5628
3939
843 748
12663
3507
785201
6061266
0
2000
4000
6000
8000
10000
12000
14000
CaseProbands
ControlProbands
AffectedRelatives
UnaffectedRelatives
SpouseControls
AffectedProbands
UnaffectedProbands
Population-basedClinic-based
Collected (1997-2004)
Strengths of BC-CFR
Dual-ascertainment Families across spectrum of risk Large sample size Quality and comprehensive collection Establishment of immortalized cell lines Interdisplinary team of experts Development of collaborative projects Flexibility in study design Prospective follow-up and data collection
Diverse sample Race/ethnicity International sites Isolated populations (Ashkenazi Jewish and Newfoundland)
Designs for Studying Association in the CFRsD. Thomas, Genetic Epidemiology
Population-based case-control studies
Family-based designs:Case-parent triadsDiscordant sibshipsKin-cohort designsCase-control family designsHigh-risk family designs
BC-CFR Review Process
Advisory Committee Review (scientific merit)
Steering Committee Review
(availability of data/biospecimen; conflict of interest)
Access to BC-CFR infrastructure granted P.I seeks funding for research project
Contact: Alysa Lesemann (Scientific Review Coordinator) lesemana@mail.nih.gov
0
20
40
60
80
100
120
140
# of applicationsB-CFR# of applicationsC-CFR
Applications for BC-CFR Collaborative Projects
Total # 122 B-CFR
Total # 98 C-CFR
Cumulative Publications from BC-CFR Peer-Approved Research Projects
0
20
40
60
80
100
120
140
Total B-CFRTotal C-CFR
Total # 117 B-CFR
Total # 41 C-CFR
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