Genetic Heterogeneity of 8q24 Region in Susceptibility to Cancer
Bibliographic record
Abstract
A region of chromosome 8q24 contains a cluster of single nucleotide polymorphism (SNP) markers that are differentially associated with cancers at a number of different sites. Various SNPs in 8q24.21 region have been reported to be associated with breast, colorectal, and prostate cancers in several studies and in many ethnic groups ( 1–3 ). Most variants were associated with a cancer at a single site; however, one SNP (rs6983267) was associated with both prostate and colon cancers ( 4 ). It is of interest to determine how many distinct susceptibility loci are present in the region, which cancer sites are associated with each locus (and to what degree), and if the basis of the susceptibility is related to the disruption or aberrant expression of any genes in the region or elsewhere in the genome. Ghoussaini et al. ( 5 ) addressed these issues by genotyping nine SNPs from the 8q24 region in prostate, breast, colorectal, and ovarian cancer subjects and controls. After examining haplotype blocks and by estimating odds ratios for different cancers, they proposed that at least five independent loci are within this region. Four loci were site specific (ie, they were associated with increased risk for a cancer at a single site), but one locus, marked by the rs6983267 SNP, was associated with increased risk of prostate, colorectal, and ovarian cancers. In previous studies, the locus was not associated with breast or endometrial cancer or chronic lymphocytic leukemia ( 5 , 6 ).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.005 | 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".