Lung cancer susceptibility genetic variants modulate HOXB2 expression in the lung
Bibliographic record
Abstract
The HOX genes are transcription factors that are expressed in coordinated spatiotemporal patterns to ensure normal development. Ectopic expression may instead lead to the development and progression of tumors. Genetic polymorphisms in the regions of four HOX gene clusters were tested for association with lung cancer in 420 cases and 3,151 controls. The effect of these variants on lung gene expression (expression quantitative trait loci, eQTL) was tested in a discovery set of 409 non-tumor lung samples and validated in two lung eQTL replication sets (n = 287 and 342). The expression levels of HOXB2 were evaluated at the mRNA and protein levels by quantitative real-time PCR and immunohistochemistry in paired tumor and non-tumor lung tissue samples. The most significant SNP associated with lung cancer in the HOXB cluster was rs10853100 located upstream of the HOXB cluster. HOXB2 was the top eQTL-regulated gene with several polymorphisms associated with its mRNA expression levels in lung tissue. This includes the lung cancer SNP rs10853100 that was significantly associated with HOXB2 expression (P=3.39E-7). In the lung eQTL discovery and replication sets, the lung cancer risk allele (T) for rs10853100 was associated with lower HOXB2 expression levels. In paired normal-tumor samples, HOXB2 mRNA and protein levels were significantly reduced in tumors when compared to non-tumor lung tissues. Genetic variants in the HOXB cluster may confer susceptibility to lung cancer by modulating the expression of HOXB2 in the lung.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".