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:This SuperSeries is composed of the following subset Series: GSE32861: Genome-scale analysis of DNA methylation in lung adenocarcinoma and integration with mRNA expression GSE32863: Gene expression analysis of lung adenocarcinoma and matched adjacent non-tumor lung tissue GSE32866: Genome-scale DNA methylation profiling of lung adenocarcinoma: validation using Ontario Tumor Bank samples Refer to individual Series
Project description:Genome wide gene expression profiling of lung adenocarcinoma and non-tumor adjacent tissues. The Agilent microarray was used to obtain gene expression profiles. Samples included eight lung cancer and adjacent non-tumor tissues excised from a cohort of 8 patients with lung adenocarcinoma.
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:Gene expression profiling of 60 lung adenocarcinoma tumors and their matched histologically normal adjacent lung tissue samples were analyzed using Illumina HumanWG-6 v3.0 expression beadchip. We integrated these data with DNA methylation profiles of the same samples to identify potential DNA methylation regulated genes. Lung cancer is the leading cause of cancer death worldwide and adenocarcinoma is its most common histological subtype. Clinical and molecular evidence indicates that lung adenocarcinoma is a heterogeneous disease, which has important implications for treatment. Here we performed genome-scale DNA methylation profiling using the Illumina Infinium HumanMethylation27 platform on 59 matched lung adenocarcinoma/non-tumor lung samples, with genome-scale verification on an independent set of tissues. We identified 766 genes showing altered DNA methylation between tumors and non-tumor lung. By integrating DNA methylation and mRNA expression data, we identified 164 hypermethylated genes showing concurrent downregulation, and 57 hypomethylated genes showing increased expression. Integrated pathways analysis indicates that these genes are involved in cell differentiation, epithelial to mesenchymal transition, RAS and WNT signaling pathways and cell cycle regulation, among others. Comparison of DNA methylation profiles between lung adenocarcinomas of current and never-smokers showed modest differences, identifying only LGALS4 as significantly hypermethylated and downregulated in smokers. LGALS4, encoding a galactoside-binding protein involved in cell-cell and cell-matrix interactions, was recently shown to be a tumor-suppressor in colorectal cancer. Unsupervised analysis of the DNA methylation data identified two tumor subgroups, one of which showed increased DNA methylation and was significantly associated with KRAS mutation and to a lesser extent, with smoking. Our analysis lays the groundwork for further molecular studies of lung adenocarcinoma by providing new candidate DNA methylation biomarkers for early detection, identifying novel molecular alterations potentially involved in lung adenocarcinoma development/progression, and describing an epigenetic subgroup of lung adenocarcinoma associated with KRAS mutation. 58 lung adenocarcinoma and 58 adjacent non-tumor lung fresh frozen tissues were macrodissected, and total RNA was isolated to be analyzed using the Illumina HumanWG-6 v3.0 expression beadchip.
Project description:We used whole genome microarray expression profiling as a discovery platform to identify genes through 7 pairs lung adenocarcinoma tissues and normal tissues