Abstract 2782: Risk loci for a breast-colon cancer phenotype: results from a genome-wide association study
Bibliographic record
Abstract
Abstract Purpose: Clustering of breast and colorectal cancer has been observed within families in population-based studies giving rise to speculation that there are “breast-colon” cancer susceptibility genes. We performed a genome-wide association study (GWAS) to identify genetic markers associated with a potential breast-colon cancer phenotype. Methods: Cases and controls were ascertained from the Breast and Colon Cancer Family Registries’ (CFR) GWAS subjects. “Breast-colon phenotype” definition was based on 2 or more breast and colon cancer cases diagnosed in first- or second-degree relatives within a family. Cases (n = 985) were women with a history of breast cancer and a family history of colorectal cancer, or persons with colorectal cancer with a family history of breast cancer. Unrelated controls (n = 1769) were frequency matched to cases for age and gender. Following standard quality control measures, 6,220,060 directly measured and imputed single nucleotide polymorphisms (SNPs) were included in the discovery set. SNPs associated at p<1×10−5 were analyzed in a replication dataset of cases (n = 293) and controls (n = 2103) from the Genetics and Epidemiology of Colorectal Cancer Consortium. Results: In a regression model that included gender, age, CFR center and 6 principal components, the top association in the discovery set was in the chromosome 8q22.3 region overlying the BAALC gene (top SNP rs12548629, P = 3.63×10−7). In the replication dataset, of 341 SNPs tested, the top signal was found in multiple correlated SNPs overlying the ROBO1 gene on chromosome 3p12 (rs7429100, P = 2.8×10−3), however, the signal on chromosome 8, the BAALC gene did not replicate. In the discovery set, P values for the SNPs overlaying ROBO1 gene ranged from 2.2×10−5 to 9.7×10−5 (rs7429100, P = 3.9×10−5). The combined meta-analysis showed strongest association at the ROBO1 gene (rs7429100, Pfixed effects 1.84×10−6, Pheterogeneity >0.05 for testing for heterogeneity between the overall discovery set and the replication set). ROBO1 (roundabout, axon guidance receptor, homolog 1) is a transmembrane receptor of the immunoglobulin family and is differentially expressed in human cancers, with a possible role as a tumor suppressor gene. Low ROBO1 expression has been shown to be an adverse prognostic factor for invasive ductal breast cancer and may also play a role in pathogenesis of colorectal cancer. BAALC (brain and acute leukemia, cytoplasmic) is predominantly expressed by neural and blood cells and is largely implicated in acute leukemia. Conclusion: In this exploratory analysis, to elucidate genes/regions associated with pleiotropic effect for breast and colorectal cancer risk we identified germline variation in the region of ROBO1 and BAALC. Validation in a larger dataset and functional characterization of the loci is warranted to elucidate mechanisms by which these genes/SNPs may contribute to the development of breast and colorectal cancer. Citation Format: Mala Pande, Aron Joon, Sanjay Shete, Abenaa M. Brewster, Cathy Eng, Wei V. Chen, Habibul Ahsan, Irene L. Andrulis, Esther M. John, Yi Lin, Polly A. Newcomb, Noralane M. Lindor, Christopher I. Amos, John Hopper, Patrick M. Lynch. Risk loci for a breast-colon cancer phenotype: results from a genome-wide association study. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2782. doi:10.1158/1538-7445.AM2015-2782
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".