Characterisation of the Phosphatidylinositol 3-Kinase Pathway in Non-Small Cell Lung Cancer Cells Isolated from Pleural Effusions
Bibliographic record
Abstract
OBJECTIVES: We hypothesised that it was possible to quantify phosphorylation of important nodes in the phosphatidylinositol 3-kinase (PI3K) pathway in cancer cells isolated from pleural effusions of patients with non-small cell lung cancer (NSCLC) and study their correlation to somatic mutations and clinical outcomes. MATERIALS AND METHODS: Cells were immunomagnetically separated from samples of pleural effusion in patients with NSCLC. p-AKT, p-S6K and p-GSK3β levels were quantified by ELISA; targeted next-generation sequencing was used to characterise mutations in 26 genes. RESULTS: It was possible to quantify phosphoproteins in cells isolated from 38/43 pleural effusions. There was a significant correlation between p-AKT and p-S6K levels [r = 0.85 (95% confidence interval 0.73-0.92), p < 0.0001], but not p-AKT and p-GSK3β levels [r = 0.19 (95% confidence interval -0.16 to 0.5), p = 0.3]. A wide range of mutations was described and p-S6K was higher in samples that harboured at least one mutation compared to those that did not (p = 0.03). On multivariate analysis, p-S6K levels were significantly associated with poor survival (p < 0.01). CONCLUSION: Our study has shown a correlation between p-AKT levels and p-S6K, but not GSK3β, suggesting differences in regulation of the distal PI3K pathway by AKT. Higher p-S6K levels were associated with adverse survival, making it a critically important target in NSCLC.
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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 | 0.000 | 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 | 0.000 | 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".