Project description:Comparison of gene expression of mouse lung adenocarcinoma-associated CD4 cells isolated from C57BL/6 mice injected with Kras-CL and Kras IKKa low cells
Project description:Comparison of gene expression of mouse lung adenocarcinoma-associated macrophages isolated from C57BL/6 mice injected with Kras-CL and Kras IKKa low cells
Project description:The model is based on publication:
Mathematical analysis of gefitinib resistance of lung adenocarcinoma caused by MET amplification
Abstract:
Gefitinib, one of the tyrosine kinase inhibitors of epidermal growth factor receptor (EGFR), is effective for treating lung adenocarcinoma harboring EGFR mutation; but later, most cases acquire a resistance to gefitinib. One of the mechanisms conferring gefitinib resistance to lung adenocarcinoma is the amplification of the MET gene, which is observed in 5–22% of gefitinib-resistant tumors. A previous study suggested that MET amplification could cause gefitinib resistance by driving ErbB3-dependent activation of the PI3K pathway. In this study, we built a mathematical model of gefitinib resistance caused by MET amplification using lung adenocarcinoma HCC827-GR (gefitinib resistant) cells. The molecular reactions involved in gefitinib resistance consisted of dimerization and phosphorylation of three molecules, EGFR, ErbB3, and MET were described by a series of ordinary differential equations. To perform a computer simulation, we quantified each molecule on the cell surface using flow cytometry and estimated unknown parameters by dimensional analysis. Our simulation showed that the number of active ErbB3 molecules is around a hundred-fold smaller than that of active MET molecules. Limited contribution of ErbB3 in gefitinib resistance by MET amplification is also demonstrated using HCC827-GR cells in culture experiments. Our mathematical model provides a quantitative understanding of the molecular reactions underlying drug resistance.
Project description:Understanding cellular processes underlying early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies. Here, we performed single-cell RNA sequencing (scRNA-seq) of mouse lungs from Gprc5a-/- mice during lung tumor development. We coupled scRNA-seq analysis with spatial transcriptomics of tumor-bearing lungs.
Project description:This SuperSeries is composed of the following subset Series: GSE27675: Expression data from lung tumor and stromal cells of KrasTgfbr2 -/- mouse model GSE27716: Expression data from Columbia Lung Adenocarcinoma Human Tumor Cells GSE27717: Expression data from lung tumors of KrasTgfbr2 -/- mouse model Refer to individual Series
Project description:To identify proteomic of lung adenocarcinoma, we collected five pairs of lung adenocarcinoma and normal lung tissues from the clinic for analysis