Validation of putative prognostic markers for non-small cell lung carcinoma
Bibliographic record
Abstract
Lung cancer is the second most diagnosed cancer in North America. Several microarray studies have reported gene expression signatures capable of classifying non-small cell carcinoma (NSCLC) patients according to prognosis. However, these signatures rarely overlap and most have not been independently validated using other methods. We therefore validated putative prognostic markers from previously published NSCLC microarray expression studies in a large independent patient cohort by real-time quantitative PCR. Two independent algorithms were used to select prognostic subsets, identifying a 6- and 3-gene classifier that could significantly segregate NSCLC patients. Next, preliminary experiments examined the potential biological role of the most robust prognostic gene in the classifiers, syntaxin 1A (STX1A). Loss of STX1A expression by RNAi had no effect on cell proliferation or cell cycle, but decreased the ability of H460 cells to migrate through collagen IV and form colonies in soft agar. STX1A represents a novel target for further investigation.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".