Article Figures & Data
Figures
- Figure 1.
Twenty risk regions analyzed as part of the GAME-ON OncoArray, including 17 pleiotropic regions conferring risks to two or more common cancers (breast, colorectal, lung, ovarian, or prostate cancers). A, Circos plot illustrating the 24 different regions ordered by chromosome and cytoband. The index SNP(s) at each locus are color coded by cancer type. B, Integration of correlated risk SNPs at each locus with regional catalogs of regulatory marks for related tissue types for common cancers to identify SNPs intersecting tissue-specific regulatory targets. Publicly available genome-wide regulatory profiling data were available for the HMECs (human mammary epithelial cells; specific to breast cancer), LNCap cancer cells (for prostate cancer), CaOV3 cancers (for ovarian cancer), SAEC cells (for lung cancer). The first column indicates a risk-associated SNP that intersects a regulatory mark, color coded by cancer type. For other columns, colored squares represent an intersection between a risk associated SNP and a regulatory mark, and in which tissue type, indicating which marks are common across tissues and which are tissue specific. White squares indicate the most strongly associated SNPs (index SNP) in a region and a dot within the square indicates an intersection between a regulatory mark and an index. The position of each regulatory mark is indicated relative to hg19 coordinates. In B, only SNPs with regulatory marks are shown, thus excluding 24 of the regional associations shown in A.
- Figure 2.
Failure rates (<95% of SNPs called) for 211,594 samples genotyped by CIDR across multiple tissue types. The overall failure rate was 2.97%. All tumor samples were prepared from formalin-fixed paraffin embedded ovarian cancers.
- Figure 3.
Correlation between replicate HapMap samples genotyped at Cambridge versus the Center for Inherited Disease Research. Samples 1–8 are of European origin while samples 9–14 are Asian or African. There are multiple replicates of samples 1, 4, 5, 6, and 8. Samples 1–8 are European, 9–10 are Chinese, sample 11 is Japanese, and samples 12–14 are Yoruban.
Tables
- Table 1.
Organization of SNP requests within consortia
Consortium Selection of SNP TRICL BCAC/DRIVE/CIMBA FOCI/OCAC ELLIPSE/PRACTICAL CORECT Fine-mapping 0.437 0.259 0.700 0.359 0.346 Significant SNPs from existing GWAS 0.032 0.465 0 0.379 0.598 Sequencing/rare variants 0.001 0.075 0 0.025 0.012 Other GWAS studies/ethnicities 0.072 0.044 0 0.128 0.005 Candidate SNP and pathways 0.156 0.012 0.105 0.056 0.027 Correlated phenotypes 0.083 0.015 0 0.051 0 GxG or GxE interactions 0.004 0.063 0.115 0 0.012 SNPs from tumor genes 0.053 0 0 0 0 Functional and eQTL 0.161 0.005 0.002 0 0 Survival 0 0.062 0.079 0 0 SNPs within consortium 32,464 88,475 42,921 67,757 37,397 Abbreviations: BCAC, Breast Cancer Association Consortium; CORECT, Colorectal Transdisciplinary Study; DRIVE, Discovery, Biology, and Risk of Inherited Variants in Breast Cancer; Ellipse, Elucidating Loci Involved in Prostate cancer Susceptibility; FOCI, Follow-up of Ovarian Cancer Genetic Association and Interaction Studies; OCAC, Ovarian Cancer Association Study; PRACTICAL, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome; TRICL, Transdisciplinary Research in Cancer of the Lung.
Supplementary Data
- Supplementary Methods and Tables - Supplementary Methods and Tables
Volume 26, Issue 1
