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- Title
Characterisation of the Phosphatidylinositol 3-Kinase Pathway in Non-Small Cell Lung Cancer Cells Isolated from Pleural Effusions.
- Authors
Puglisi, Martina; Stewart, adam; Thavasu, Parames; Frow, Michael; Carreira, Suzanne; Minchom, anna; Punwani, Ravi; Bhosle, Jaishree; Popat, Sanjay; Ratoff, Jonathan; de Bono, Johann; Yap, Timothy anthony; O''Brien, Mary; Banerji, Udai
- 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 mu tation 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.
- Subjects
LUNG cancer complications; CANCER patients; CONFIDENCE intervals; ENZYME-linked immunosorbent assay; PLEURA cancer; PLEURAL effusions; RESEARCH funding; SURVIVAL analysis (Biometry); DATA analysis software; DESCRIPTIVE statistics; SEQUENCE analysis
- Publication
Oncology, 2016, Vol 90, Issue 5, p280
- ISSN
0030-2414
- Publication type
Article
- DOI
10.1159/000444928