Susceptibility loci for lung cancer are associated with mRNA levels of nearby genes in the lung
Bibliographic record
Abstract
Recent studies identified three genetic loci reproducibly associated with lung cancer in populations of European ancestry, namely 15q25, 5p15 and 6p21. The goals of this study are first to confirm whether these loci are associated with lung cancer in a French Canadian population and second to identify disease-associated single nucleotide polymorphisms (SNPs) influencing messenger RNA (mRNA) expression levels of genes in the lung, that is expression quantitative trait loci (eQTLs). SNPs were genotyped in 420 patients undergoing lung cancer surgery and compared with 3151 controls of European ancestry. Genome-wide gene expression levels in non-tumor lung tissues of the same 420 patients were also measured to identify eQTLs. Significant eQTLs were then followed-up in two replication sets (n = 339 and 363). SNPs found in the three susceptibility loci were associated with lung cancer in the French Canadian population. Strong eQTLs were found on chromosome 15q25 with the expression levels of CHRNA5 (P = 2.23 × 10(-) (22) with rs12907966). The CHRNA5-rs12907966 eQTL was convincingly validated in the two replication sets (P = 3.46 × 10(-) (16) and 2.01 × 10(-) (15)). On 6p21, a trend was observed for rs3131379 to be associated with the expression of APOM (P = 3.58 × 10(-) (4)) and validated in the replication sets (P = 1.11 × 10(-) (8) and 6.84 × 10(-) (4)). On 5p15, no significant eQTLs were found. This study confirmed that chromosomes 15q25, 5p15 and 6p21 harbored susceptibility loci for lung cancer in French Canadians. Most importantly, this study suggests that the risk alleles at 15q25 and 6p21 may mediate their effect by regulating the mRNA expression levels of CHRNA5 and APOM in the lung.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".