Abstract 4850: Variation in circadian rhythm genes influence epithelial ovarian cancer risk and invasiveness.
Bibliographic record
Abstract
Abstract Background: Circadian rhythms of biological processes are regulated by endogenous clock genes and clock-controlled genes. Aberrant expression of circadian clock genes may have important consequences on the transactivation of downstream targets that control the cell cycle and cellular proliferation potentially promoting carcinogenesis. Animal models indicate that several circadian rhythm genes are expressed in the ovaries, where they influence and are influenced by estrous cycles. The goal of the current study was to examine the association of circadian gene variants and epithelial ovarian cancer (EOC) risk. Methods: Thirty-one SNPs from five circadian genes (i.e., ARNTL, CRY2, KLF10, NPAS2, PER3, TIMELESS) were genotyped in 14,736 cases and 23,448 control women of European ancestry from 43 studies in the Ovarian Cancer Association Consortium (OCAC), on a custom Illumina iSelect designed for the Collaborative Oncological Gene-Environment Study (COGS). Both invasive cancers combined and the four main histological subtypes (serous [n=8,372], endometroid [n=2,068], clear cell [n=1,025] and mucinous [n=943] were analyzed, SNP analyses were conducted using unconditional logistic regression under a log-additive model. All analyses were adjusted for study site and population substructure. Results: Eleven SNPs were found to be associated with ovarian cancer risk. The SNPs most associated with serous cancer risk were KLF10 rs2513928 (OR=.95 p=6.1x10−3), rs2513927 (OR=1.05 p=6.1x10−3), rs2511703 (OR=1.05 p=9.8x10−3), rs3191333 (OR=1.05, p=1.5x10−2) and NPAS2 rs13012930 (OR=.95, p=3.5x10−2). Endometroid cancer risk was significantly associated with ARNTL SNPs rs10732458 (OR=1.3, p=1.0x10−2) and rs7117836 (OR=1.2, p=4.6x10−2), while clear cell cancer risk was associated with ARNTL rs1562438 (OR=.88, p=1.5x10−2), rs1026071 (OR=.89, p=1.8x10−2), and rs3816360 (OR=.91, p=4.8x10−2) and KLF10 rs2388232 (OR=1.1, p=3.3x10−2). No variants were significantly associated with mucinous cancer risk. Four SNPs in KLF10 were associated with cancer invasiveness; they were rs2513928 (OR=.95, p=1.8x10−3), rs3191333 (OR=1.04, p=1.4x10−2), rs2513927 (OR=1.04, p=1.9x10−2), and rs2511703 (OR=1.03, p=2.8x10−2). Conclusions: Data from the current study suggest that polymorphisms in circadian genes ARNTL, KLF10, and NPAS2 are significantly associated with ovarian cancer histopathologic subtypes and invasiveness. These findings merit further investigation and replication. Funding: R01 CA149429 Citation Format: Heather Jim, Jonathan Tyrer, Hui-Yi Lin, Gang Han, Xiaotao Qu, Ellen L. Goode, Zhihua Chen, Ya-Yu Tsai, Julie M. Cunningham, Edward Iversen, Susan Ramus, Andrew Berchuck, Joellen Schildkraut, Alvaro Monteiro, Simon Gayther, Steven A. Narod, Thomas A. Sellers, Paul Pharoah, Catherine M. Phelan. Variation in circadian rhythm genes influence epithelial ovarian cancer risk and invasiveness. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4850. doi:10.1158/1538-7445.AM2013-4850 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".