Mitogen-Activated Protein Kinase Activation in Lung Adenocarcinoma: A Comparative Study between Ever Smokers and Never Smokers
Bibliographic record
Abstract
PURPOSE: There are major differences affecting genes in adenocarcinomas in ever and never smokers. However, data on whether mitogen-activated protein kinase (MAPK) activation state differs according to smoking status are limited. EXPERIMENTAL DESIGN: Expression of activated extracellular signal-regulated kinases, c-Jun NH(2)-terminal kinases, and P38 enzymes (pP38) were evaluated by means of immunohistochemistry in 188 chemonaïve patients with surgically resected lung adenocarcinoma. Cell viability of the lung adenocarcinoma cell line HCC827 was studied after treatment with cisplatin or the P38 MAPK inhibitor SB 203580. RESULTS: Thirty-seven of 44 never smokers [84%; 95% confidence intervals (95% CI), 70-92%] expressed high pP38 levels compared with 45 of 104 ever smokers (43%; 95% CI, 34-53%; P < 0.0001). The proportion of never smokers expressing high c-Jun NH(2)-terminal kinase levels (72%; 95% CI, 57-83%) was greater than that of ever smokers (53%; 95% CI, 44-62%; P = 0.03). The proportion of ever smokers expressing high extracellular signal-regulated kinase levels (51%; 95% CI, 42-59%) was similar to that of never smokers (57%; 95% CI, 42-71%; P = 0.47). Never smokers were 10.5 times (95% CI, 3.5-31.5) more likely to express high pP38 levels after adjustment for variables linked to smoking status, including age, sex, and histologic subtype. None of the activated MAPKs predicted for overall survival. Cell viability of HCC827 was significantly reduced after exposure to SB203580 alone or when combined with cisplatin. CONCLUSIONS: Life-long nonsmoking is associated with high activated P38 levels in patients with lung adenocarcinoma. Activated P38 can contribute to the viability of adenocarcinoma cells in never smokers, but is not predictive for overall survival.
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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 | 0.000 |
| 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 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".