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
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:RATIONALE: Diagnostic imaging procedures, such as fludeoxyglucose F 18 PET, may be effective in detecting cancer or recurrence of cancer, or premalignant polyps.
PURPOSE: This clinical trial is studying fludeoxyglucose F 18-PET imaging to see how well it works in determining protein and gene expression signatures in patients with premalignant polyps or colon cancer.
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:The World Health Organization has subclassified adenocarcinoma based upon predominant cell morphology and growth pattern such as bronchioloalveolar carcinoma (BAC), adenocarcinoma with mixed subtypes (AC-mixed), and homogenously invasive tumors with a variety of histological patterns Pure invasive adenocarcinomas are often devoid of bronchioloalveolar morphology. The clinical importance of lung adenocarcinoma invasion is supported by several recent studies indicating that the risk of death in non-mucinous BAC is significantly lower than that of pure invasive tumors and in tumors with greater than 0.6 cm of fibrosis or linear invasion (J Thorac Oncol 6:244-285) To identify human tumor cell signatures associated with lung adenocarcinoma subtype and invasion, we performed microarray gene expression profiling of microdissected tumor cells noninvasive AC and AC-Mixed invasive tumors. 17 cases of noninvasive AC tumors and 23 cases of AC-mixed subtype invasive lung adenocarcinomas resected from 2002 to 2006 were examined (Columbia Lung Adenocarcinoma dataset)