Working Groups - Genetic Associations and Mechanisms in Oncology (GAME-ON) Initiative

Working Groups

The GAME-ON Initiative established working groups between the five projects in order share expertise, spread knowledge across all five projects, and streamline results between cancer types. Working groups specialize in one scientific area and include experts from each of the five projects.

Analytic and Risk Modeling Working Group

Purpose: Develop models to characterize risk factors for cancer, share analytic approaches and develop analytic tools, and determine when risk models are ready to transition to the Epidemiology and Clinical Working Group.

Epidemiology and Clinical Working Group

Purpose: Phenotypic, genotypic, survival, and pathology data harmonization and sharing; secondary phenotypes; develop ideas for cross-project collaborations involving gene – environment interactions and new projects aimed at understanding the functional consequences of single nucleotide polymorphisms by using available biomarkers.

TERT-CLPTM1L Working Group
Purpose: This sub-group of the Epidemiology and Clinical Working Group will determine which TERT-CLPTM1L SNPs are the most highly associated with a given cancer site; whether the susceptibility SNPs are similar or different across cancer sites; whether the associations vary by population; what the haplotype structures are across populations; and whether SNPs in this locus are associated with telomere length.

Epigenetics Working Group

Purpose: To investigate the relationship between epigenetic regulation and cancer risk in the GAME-ON consortium, by focusing on (a) inherited genetic variability in epigenetic regulators/pathways in relation to cancer risk, (b) stratified analysis of tumor phenotypes characterized by epigenetic dysregulation and (c) functional follow-up on GAME-ON hits with respect to epigenetic characteristic mechanisms in multiple interrelated studies.

Functional Assays Working Group

Purpose: Share approaches to the characterization of functional consequences of risk variants and identify specific gene targets (e.g., regulatory) and how they interact.

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