Abstract 1336: A population-based study of Transforming Growth Factor-Beta1 (TGFB1) polymorphisms and risk of breast cancer.
Bibliographic record
Abstract
Abstract Transforming growth factor-beta1 (TGFB1) is a multifunctional cytokine that may play an important role in the development and progression of cancer. The results of a number of association studies of TGFB1 polymorphisms and breast cancer risk are inconclusive. This study examined 4 single nucleotide polymorphisms (SNPs) in TGFB1 and risk of breast cancer using data previously collected from a population based case-control study (n=307 cases and 664 controls) of Caucasian women conducted in Northeastern Ontario, Canada. The SNPs (rs8179181, rs8110090, rs1800470 (L10P), rs1800469 (-509C/T)) were selected as either tag SNPs or had been identified as potentially functional in other studies, and were analysed using Taqman genotyping assays. Two of the SNPs were at the 5’ end (rs1800469 (-509C/T), rs1800470) and were in high LD (D’ 0.98); the remaining SNPs (rs8179181, rs8110090) were at the 3’ end and were also in high LD (D’ 0.99). In single-SNP analyses, the variant homozygous genotypes in rs1800470 (CC) and rs8179181 (AA) were significantly protective in the codominant model with Odds Ratios (OR) and 95% Confidence Intervals (95% CIs) of 0.63 (0.40-0.99) and 0.45 (0.21-0.96), while the AG genotype of rs8110090 was significantly associated with increased breast cancer risk with an OR of 1.78 (95% CI 1.14-2.77). Of the seven estimated haplotypes, 3 were significantly protective for breast cancer; when compared to the referent haplotype (see Table). In conclusion, our results suggest that SNPs at both the 3’ and 5’ end of TGFB1 may be associated with risk of breast cancer, and future studies examining additional polymorphisms in these regions would be valuable. Haplotype association with breast cancer risk (n = 969; Global Haplotype Association p-value 0.0021)rs8179181rs8110090rs1800470rs1800469FrequencyOR (95% CI)P-value1GATC0.40281.002GACT0.23870.73 (0.55–0.97)0.033AATC0.17280.67 (0.48–0.93)0.0174GACC0.06710.49 (0.30–0.81)0.00545AACT0.0560.55 (0.30–1.00)0.0526GGTC0.02981.00 (0.48–2.09)0.997GGCT0.02271.82 (0.82–4.06)0.14 Citation Format: Mary A. Bewick, Michael SC Conlon. A population-based study of Transforming Growth Factor-Beta1 (TGFB1) polymorphisms and risk of breast cancer. [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 1336. doi:10.1158/1538-7445.AM2013-1336
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".