Decision letter: The chemokine CXCL13 in lung cancers associated with environmental polycyclic aromatic hydrocarbons pollution
Bibliographic record
Abstract
Lung cancer causes the most cancer deaths worldwide. For decades, people have known that lung cancer is associated with environmental factors, and both cigarette smoke and air pollution are known to cause cancers in humans. Smoke and air pollution both contain chemicals called polycyclic aromatic hydrocarbons (or PAHs). These chemicals cause chronic inflammation of the lung, which in turn is a major risk factor for developing lung cancer. However, it is unclear exactly how PAHs trigger inflammation and cancer. Xuanwei City in China is suited to the study of this question because until the 1970s its inhabitants used 'smoky coal' for cooking in unventilated indoor spaces; this produced high levels of small particles that contain high concentrations of PAHs. Women from this region, who traditionally do most of the cooking, have rates of lung cancer comparable to those of men. In other parts of China a woman’s chance of getting lung cancer is approximately half that of a man’s. Therefore, Xuanwei City provides a setting in which air pollution is a main contributor to lung cancer risk. Wang, Cheng et al. have now compared the levels of certain proteins (which are linked to inflammation) in lung cancer patients from Xuanwei City with those in control regions of China. The level of one such protein marker, called CXCL13, was particularly high in almost all patients from Xuanwei City, but only highly expressed in half of the patients from the control regions. Moreover, there was also a clear link between cigarette smoke and CXCL13 expression because, in control regions, smokers were much more likely to have high levels of CXCL13 than non-smokers. To test whether PAHs cause CXCL13 expression, Wang, Cheng et al. first exposed normal lung epithelial cells, cancer cells and then mice to a PAH. These experiments showed that CXCL13 levels did indeed increase and the mice developed lung tumours. However, when the genes for CXCL13 or its binding partner were deleted, the mice no longer got cancer when exposed to the PAH. This shows that CXCL13 signalling is an important mechanism by which PAHs cause lung cancer. Lastly, further experiments showed that CXCL13’s binding partner is highly expressed on some immune cells that can promote lung cancer. Importantly, the over-expression of CXCL13 occurred before the lung tumours developed. This might provide a new treatment strategy in which CXCL13 signalling could be inhibited after the exposure to PAHs. Future studies may now focus on discovering new drugs, or modifying existing drugs, to achieve this goal.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.094 | 0.045 |
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".