mTOR modulates resistance to gemcitabine in lung cancer in an MTORC2 dependent mechanism
Background:Lung cancer has a poor prognosis partly due to a lack of response to treatments such as the chemotherapy drug gemcitabine. Combinations of chemotherapy drugs with signal transduction inhibitors may be more effective treatments. In this study we have investigated the impact of targeting the mTOR signalling pathway on the efficacy of gemcitabine in different cancer cell lines. Methods:Time-lapse microscopy, immuno-staining, and western blot techniques were used to evaluate the efficacy of applied treatments either in measuring phosphorylation levels of mTOR down-stream targets or in tracking down the fate of targeted cells. Reactive oxygen species and relative levels of protein phosphorylation were also quantified. For comparison between treated groups t-test and analysis of variance test were applied. Results:Our data showed that mTORC1 has no role in sensitising A549 lung cancer cells to gemcitabine. However, targeting mTORC1/2 with the pharmacological inhibitor torin1 or by over-expressing Deptor, the negative regulator of mTOR signalling, sensitised these cells to gemcitabine. Silencing mTORC2, but not mTORC1, induced apoptosis and significantly improved the apoptosis-inducing effects of gemcitabine. Results also suggest that Rictor is required to maintain cell survival through modulating p38α, ERK1/2, RSK1/2/3 and the transcription factor STAT3. Multiple cell line comparisons revealed that PANC-1 pancreatic cancer cells were also sensitive to mTOR inhibition, but MCF7 breast cancer, MCF10A breast epithelial and H727 lung cancer cell lines were more resistant to the treatment. Conclusions:Inhibition of mTORC2 may have benefits in the treatment of gemcitabine resistant cancers, and the genetic background of the cell line may determine its response to mTOR inhibition.Keywords:Cell death; Chemotherapy resistance; Gemcitabine; Lung cancer; Reactive oxygen species; Torin1; mTOR; mTORC2.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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