Cohorts and consortia conference: a summary report (Banff, Canada, June 17–19, 2009)

Boffetta, Paolo; Colditz, Graham A.; Potter, John D.; Kolonel, Laurence N.; Robson, Paula J.; Malekzadeh, Reza; Seminara, Daniela; Goode, Ellen L.; Yoo, Keun Young; Demers, Paul A.; Gallagher, Richard P.; Prentice, Ross L.; Yasui, Yutaka; O’Doherty, Kieran C.; Petersen, Gloria M.; Ulrich, Cornelia M.; Csizmadi, Ilona; Amankwah, Ernest K.; Brockton, Nigel T.; Kopciuk, Karen; McGregor, S. Elizabeth; Kelemen, Linda E.

doi:10.1007/s10552-010-9717-0

Cited by 12 publications

(11 citation statements)

References 24 publications

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“…Use of consortia has become standard in SNP-oriented molecular epidemiology in order to minimize the false discoveries of smaller sample sizes, to increase precision of true risk allele effect estimates, and to evaluate generalizability (49, 50). Indeed, the large sample size of our replication set provided 80% power to detect relatively small effect sizes of 1.21 in the replication set and 1.19 in the combined set of participants (assuming MAF=0.20, α= 0.05, and dominance), minimizing the possibility of a false negative result.…”

Section: Discussionmentioning

confidence: 99%

Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Goode

Chenevix-Trench

Hartmann

et al. 2011

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Invasive ovarian cancer is a significant cause of gynecologic cancer mortality. Methods We examined whether this mortality was associated with inherited variation in ~170 candidate genes/regions (993 SNPs) in a multi-stage analysis based initially on 312 Mayo Clinic cases (172 deaths). Additional analyses used The Cancer Genome Atlas (TCGA; 127 cases, 62 deaths). For the most compelling gene, we immunostained Mayo Clinic tissue micro-arrays (TMAs, 326 cases) and conducted consortium-based SNP replication analysis (2,560 cases, 1,046 deaths). Results The strongest initial mortality association was in HGF (hepatocyte growth factor) at rs1800793 (HR 1.7, 95% CI 1.3–2.2, p=2.0×10−5) and with overall variation in HGF (gene-level test, p=3.7×10−4). Analysis of TCGA data revealed consistent associations (e.g., rs5745709 [r2=0.96 with rs1800793]: TCGA 2.4, 1.4–4.1, p=2.2×10−3; Mayo Clinic+TCGA 1.6, 1.3–1.9, p=7.0×10−5) and suggested genotype correlation with reduced HGF mRNA levels (p=0.01). In Mayo Clinic TMAs, protein levels of HGF, its receptor MET, and phospho-MET were not associated with genotype and did not serve as an intermediate phenotype; however, phospho-MET was associated with reduced mortality (p=0.01) likely due to higher expression in early-stage disease. In eight additional ovarian cancer case series, HGF rs5745709 was not associated with mortality (1.0, 0.9–1.1, p=0.87). Conclusions We conclude that although HGF signaling is critical to migration, invasion, and apoptosis, it is unlikely that genetic variation plays a major role in ovarian cancer mortality; any minor role is not related to genetically-determined expression. Impact Our study demonstrates the utility of multiple data types and multiple datasets in observational studies.

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Section: Discussionmentioning

confidence: 99%

Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Goode

Chenevix-Trench

Hartmann

et al. 2011

Cancer Epidemiology, Biomarkers &Amp; Prevention

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“…This is not surprising, since “-omic” technologies permeated cancer research in the first decade of the 21st century and cancer consortia were established at the end of the 20th century, primarily to overcome the issue of small sample sizes in cancer epidemiology. Thus, the original purpose of consortium-based research was to pool study data together to obtain the increased statistical precision afforded by a consortium’s larger sample size (14, 15) for discovery/etiological research in an era of genome-driven technologies.…”

Section: Discussionmentioning

confidence: 99%

Evolution of the "Drivers" of Translational Cancer Epidemiology: Analysis of Funded Grants and the Literature

Lam¹,

Chang²,

Rogers³

et al. 2015

American Journal of Epidemiology

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Concurrently with a workshop sponsored by the National Cancer Institute, we identified key “drivers” for accelerating cancer epidemiology across the translational research continuum in the 21st century: emerging technologies, a multilevel approach, knowledge integration, and team science. To map the evolution of these “drivers” and translational phases (T0–T4) in the past decade, we analyzed cancer epidemiology grants funded by the National Cancer Institute and published literature for 2000, 2005, and 2010. For each year, we evaluated the aims of all new/competing grants and abstracts of randomly selected PubMed articles. Compared with grants based on a single institution, consortium-based grants were more likely to incorporate contemporary technologies (P = 0.012), engage in multilevel analyses (P = 0.010), and incorporate elements of knowledge integration (P = 0.036). Approximately 74% of analyzed grants and publications involved discovery (T0) or characterization (T1) research, suggesting a need for more translational (T2–T4) research. Our evaluation indicated limited research in 1) a multilevel approach that incorporates molecular, individual, social, and environmental determinants and 2) knowledge integration that evaluates the robustness of scientific evidence. Cancer epidemiology is at the cusp of a paradigm shift, and the field will need to accelerate the pace of translating scientific discoveries in order to impart population health benefits. While multi-institutional and technology-driven collaboration is happening, concerted efforts to incorporate other key elements are warranted for the discipline to meet future challenges.

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“…While the need for collaboration appears obvious; there are technical and methodological challenges that require the collective cooperation from experts to address, including data harmonization, population heterogeneity, and imprecise measurements of exposures across studies. A forum to discuss the opportunities and challenges of consortia and large-scale cohorts was held in 2006 and summaries of the conversations have been published (16). …”

Section: Drivers Of Translational Cancer Epidemiology: Needs Opportumentioning

confidence: 99%

“Drivers” of Translational Cancer Epidemiology in the 21st Century: Needs and Opportunities

Lam

Spitz

Schully

et al. 2013

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Cancer epidemiology is at the cusp of a paradigm shift--propelled by an urgent need to accelerate the pace of translating scientific discoveries into healthcare and population health benefits. As part of a strategic planning process for cancer epidemiologic research, the Epidemiology and Genomics Research Program (EGRP) at the National Cancer Institute (NCI) is leading a “longitudinal” meeting with members of the research community to engage in an on-going dialogue to help shape and invigorate the field. Here, we review a translational framework influenced by “drivers” that we believe have begun guiding cancer epidemiology towards translation in the past few years and are most likely to drive the field further in the next decade. The drivers include: (1) collaboration and team science; (2) technology; (3) multi-level analyses and interventions; and (4) knowledge integration from basic, clinical and population sciences. Using the global prevention of cervical cancer as an example of a public health endeavor to anchor the conversation, we discuss how these drivers can guide epidemiology from discovery to population health impact, along the translational research continuum.

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Cohorts and consortia conference: a summary report (Banff, Canada, June 17–19, 2009)

Cited by 12 publications

References 24 publications

Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Assessment of Hepatocyte Growth Factor in Ovarian Cancer Mortality

Evolution of the "Drivers" of Translational Cancer Epidemiology: Analysis of Funded Grants and the Literature

“Drivers” of Translational Cancer Epidemiology in the 21st Century: Needs and Opportunities

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