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

We Still Have a Long Way to Go