Abstract 2562: Polymorphisms in microRNA (miRNA) pathways and survival in esophageal cancer (EC) patients.
Bibliographic record
Abstract
Abstract Introduction: Polymorphisms within miRNA and in genes regulating miRNA biogenesis can regulate a variety of cancer pathways in EC patients. Comprehensive pathway analyses of miRNA-related genes were performed on EC outcomes. Methods: 324 EC patients from Princess Margaret Hospital (Toronto, Canada) were screened for 62 single nucleotide polymorphisms (SNPs) in 21 miRNA or miRNA biogenesis pathway genes. Multivariate Cox-proportional hazard models, adjusted for key prognostic factors evaluated the association of each SNP with overall survival (OS) and progression free survival (PFS). Significant SNPs were further analysed for joint effects, and also in subgroup and pathway analyses. All results were internally validated through bootstrapping. Results: Five polymorphisms belonging to the miRNA biogenesis pathway and one in a miRNA were nominally associated with OS or PFS, where adjusted hazard ratios (aHR) were between 1.23-1.41 for each comparison; p=0.003-0.04: AGO1 (rs595961; chromosome (chr) 1), GEMIN3 (rs197412; chr1) CD86 (rs17281995; chr 3) hs-miRNA-26a1 (rs7372209; chr 3), GEMIN4 (rs7813 and rs910924; chr 17). Joint effect analysis of SNPs in the same chromosome found additive effects of these risk alleles (RA) on outcome: chr 1 (2-4 vs 0-1: aHROS=1.82 [1.21-2.75], p=0.004), chr 3 (3-4 vs 0: aHROS=4.07 [1.91-8.67], p=0.003), chr 17 (4 vs 0: aHRPFS=2.21 [1.13-4.31], p=0.02). Pathway based analysis found each additional RA conferring a strong additive effect on OS (per 2 RA: aHR=1.50 [1.25-1.81], p=1.9x10E-5). Results on PFS were similar, with aHRPFS per 2RA of 1.51 [1.26-1.82], p=1.3x10E-5. Internal validation found consistent results for all analyses. Exploratory subgroup analysis identified two SNPs that had differential effects on OS based on histology: for adenocarcinomas, the aHR for KIAA0423 (rs1053667) was 0.51 [0.28-0.96], p=0.03, while for squamous cell carcinomas, the aHR was 7.36 [2.07-26.1], p=0.002. Similarly, for DICER (rs13078), aHRadenocarcinoma=0.96 [0.72-1.28], p=0.78 vs aHRsquamous=2.51[1.21-5.21], p=0.01). In subset analyses, hsa-mir-30a (rs1358379), hsa-mir-492 (rs2289030), hsa-mir-499 (rs3746444), and DGCR8 (rs1640299) were significantly associated with different outcomes by nodal status. Conclusion: We identified the miRNA biogenesis pathway as having an important role in the prognosis of EC patients, with a 50% increase in death or disease progression when carrying two additional miRNA risk alleles. Although some of the identified polymorphisms have been previously associated with risk or prognosis in other cancer disease sites, we report for the first time, their associations with esophageal cancer prognosis. Citation Format: Lawson Eng, Olusola O. Faluyi, Xin Qiu, Dangxiao Cheng, Daniel J. Renouf, Lorin Dodbiba, Sevtap Savas, Sharon Marsh, Jennifer J. Knox, Gail E. Darling, Rebecca KS Wong, Wei Xu, Geoffrey Liu, Abul K. Azad. Polymorphisms in microRNA (miRNA) pathways and survival in esophageal cancer (EC) patients. [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 2562. doi:10.1158/1538-7445.AM2013-2562 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 | 0.000 | 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) | 0.003 | 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".