Abstract 915: Xenobiotic metabolizing gene variants, occupational chemical exposures, and renal cell cancer
Bibliographic record
Abstract
Abstract The countries of Central and Eastern Europe have among the highest worldwide rates of renal cell cancer. Few studies have examined whether genetic variation in xenobiotic metabolic pathway genes may modify risk for this cancer. The Central and Eastern Europe Renal Cell Cancer study was a hospital-based case-control study conducted between 1998 and 2003 across seven centers in central and eastern Europe. The study centers were in the Czech Republic (Ceske, Prague, Olomouc, Brno), Poland (Lodz), Romania (Bucharest), and Russia (Moscow). Incident cases of primary kidney cancer were recruited and underwent an in-person interview in which detailed data were collected on demographics as well as work history and occupational exposure to chemical agents. Genes (cytochrome P-450 family, N-acetyltransferases, NAD(P)H:quinone oxidoreductase I (NQO1), microsomal epoxide hydrolase (mEH), catechol-O-methyltransferase (COMT)) were selected for the present analysis based on their putative role in xenobiotic metabolism. Genotyping (874 cases and 2396 controls) was conducted with a GoldenGate® Oligo Pool All (OPA) assay by Illumina® and the 5’ nuclease assay (Taqman, Applied Biosystems). Haplotypes were calculated using fastPhase. Odds ratios (OR) and 95% confidence intervals (CI) were estimated by unconditional logistic regression adjusted for country of residence, age, and sex. We observed an increased risk of renal cell cancer (RCC) with two NAT1 SNPs (NAT1A40T, OR=1.36, CI 1.00, 1.86; NAT1R187Q, OR=1.65, CI 1.01, 2.71) and with CYP1B1V432L (OR=1.14, CI 1.01, 1.28). The slow (NAT1*14) phenotype was associated with increased risk of RCC (OR=1.69, CI 1.00-2.86) in comparison to normal phenotype (NAT1*4, *3, *11). Among persons with NAT1*14 phenotype, occupational exposure to trichloroethylene (OR=9.94, CI 1.15, 86.1) and chlorinated solvents (OR=9.79, CI 1.13, 84.8) conferred an increased risk of RCC. Among those with the CYP1B1V432L variant, occupational exposure to trichloroethylene (OR=1.68, CI 1.21, 2.34) and chlorinated solvents (OR=1.58, CI 1.14, 2.19) also had increased risk of RCC. These results require replication, but provide evidence that the relationship between certain agents and RCC may be modified by particular variants in xenobiotic metabolism genes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 915.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".