Project description:Based on the previous eVIP study (Cancer Cell, 2016), we profiled the transcriptomes of lung adenocarcinoma cell lines expressing oncogenes to compare methods and investigate the effects of these oncogenes on the cells' whole transcriptomes, differential expression, and alternative splicing
Project description:Brain metastasis developed in nearly 40% of lung adenocarcinoma (LUAD) patients diagnosed with distant metastasis. There is lack of transcriptomic data of brain lesions from human lung adenocarcinoma patients. As part of the project to understanding the tumor microenvironment in brain metastasis of LUAD patients, we performed bulk RNA analysis on brain metastases from 6 LUAD patients. In order to understand the tumor intrinsic factors that potential shape the tumor microenvironment, we compared these data with bulk RNA sequencing data from 14 early stage and 11 late stage primary LUAD tumor from TCGA database. Pathway expression analysis showed a downregulation of pro-inflammatory signals in brain metastasis and upregulation of DNA synthesis and oxidative phosphorylation pathways related to rapid proliferation in brain lesions.
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:We investigated the association between genetic variants in the histone modification regions and the prognosis of lung adenocarcinoma after curative surgery. Potentially functional SNPs were selected using integrated analysis of ChIP-seq and RNA-seq. The SNPs were analyzed in a discovery set (n=166) and a validation set (n=238). The associations of the SNPs with overall survival (OS) and disease-free survival (DFS) were analyzed. This study showed that genetic variants in the histone modification regions could predict the prognosis of lung adenocarcinoma after surgery.
Project description:We repeatedly injected FVB and C57BL/6 intraperitonealy with urethane. Mice developed lung tumours. We sacrificed the mice, harvested their lungs and cultured the tumour cells. After over 60 passages we established 3 novel mouse lung adenocarcinoma cell lines. The aim of this study os to compare their transcriptomic profile.
Project description:To identify proteomic of lung adenocarcinoma, we collected five pairs of lung adenocarcinoma and normal lung tissues from the clinic for analysis