Project description:Inevitable gefitinib resistance and relapse of the disease was the biggest hurdle to NSCLC treatment. Importantly, the role of hypoxia in solid tumor tissues in vivo in gefitinib acquired resistance and its relationship to lung cancer stem cells (LCSCs) has not been fully elucidated. Here, the PC9 cells were treated with short term gefitinib or/and hypoxia, also, PC9 gefitnib resistant (PC9-GR) cell line was established and ALDH positive PC9 cells were sorted by FACs. Transcriptome analysis among those PC9 cell groups revealed the important role of hypoxia in gefitinib acquired resistance and signaling transduction change, which may critical for NSCLC disease progression and recurrence.
Project description:In this study, we established an gefitinib resistant lung adenocarcinoma cell line (i.e. PC9/GR) from lung adenocarcinoma PC9 cell line which was sensitive to gefitinib. Then microarray was performed to elucidate the lncRNAs, cirRNAs and mRNAs involved in gefitinib resistance.
Project description:Analysis of gefitinib short-term resistance at gene expression level. The hyposthesis tested in the present study was that short-term resistance towards gefitinib in NSCLC cells influences pathways that associates with resistance towards EGFR-TKI treatment. Results provide important information of the response of EGFR mutant NSCLC cells to gefitinib and also to resistance towards gefitinib resistance, up-or down-regulated specific resistance pathways and cellular functions. Total RNA obtained from PC9 cell line (n=3), co-cultured PC9 (with MRC-5 cells)(n=3), gefitinib treated (0.5µM) PC9 (n=3), and co-cultured (MRC-5) + gefitinib treated PC9 cells (n=3) for 48h after gefitinib treatment
Project description:EGFR inhibitors (EGFRi) are effective against EGFR mutant lung cancers. The efficacy of these drugs however is mitigated by the outgrowth of resistant cells, most often driven by a secondary acquired mutation in EGFR, T790M. We recently demonstrated that T790M can arise de novo during treatment (Hata et al., Nature Medicine 2016); it follows that one potential therapeutic strategy to thwart resistance would be identifying and eliminating these cells (referred to as drug tolerant cells (DTCs)) prior to acquiring secondary mutations like T790M. We have developed DTCs to EGFRi in EGFR mutant lung cancer cell lines. Subsequent analyses of DTCs included RNA-seq, high-content microscopy, and protein translational assays. Based on these results, we tested the ability of MCL-1 BH3 mimetics to combine with EGFR inhibitors to eliminate DTCs and shrink EGFR mutant lung cancer tumors in vivo.
Project description:We established a gefitinib-resistant cell line (PC-9GR), by serial exposure of gefitinib to PC-9, an originally gefitinib-sensitive lung cancer cell line (PC-9na), for long period.We collected total RNA from both PC-9 and PC-9GR and examined mRNA expression profile, comprehensively. Gefitinib induced gene expression was measured in human lung cancer cell line was measured at 48 hours after exposure to 1uM Gefitinib.
Project description:We established a gefitinib-resistant cell line (PC-9GR), by serial exposure of gefitinib to PC-9, an originally gefitinib-sensitive lung cancer cell line (PC-9na), for long period.We collected total RNA from both PC-9 and PC-9GR and examined mRNA expression profile, comprehensively.
Project description:In order to analyze the molecular effect of the combination of Notch inhibitors and EGFR inhibitors on resistance to TKI, we performed RNA-seq gene expression profiling of PC9 resistant to Gefitinib cells treated with different combinations.
Project description:The goals of this study is to compare the whole genome transcriptome of gefitinib-resistant NSCLC cell line (PC9R) with its gefitinib-sensitive counterpart (PC9) using RNA-seq tecnology Methods: Genome-wide mRNA profiles of the PC9R and PC9 cells were generated by deep sequencing, using Illumina Hiseq2000. The sequence reads that passed quality filters were analyzed in the following steps: 1) RNA-seq reads were aligned to the hg19 genome assembly using TopHat (http://bioinformatics.oxfordjournals.org/content/25/9/1105.short) with the default parameters; 2) Expression index was generated using GFOLD V1.0.9 job count (http://bioinformatics.oxfordjournals.org/content/early/2012/08/23/bioinformatics.bts515); 3) Differential expression were calculated using GFOLD V1.0.9 job diff. Gene expression was quantified in rpkm (reads per kilobase of exon per million mapped sequence reads); 4) GFOLD, a generalized fold change, was used to rank the differentially expressed genes from the RNA-seq data. The GFOLD value can be considered as a reliable log2-fold change when only a single biological replicate is available Results: We found that hundreds of genes were either down- or up-regulated in the PC9R cells compared with the PC9 cells. Specifically, 6% of the total detected genes (1487 genes) were up-regulated in the PC9R cells, with a GFOLD value over 1, and 5% of the total detected genes (1112 genes) were down-regulated, with a GFOLD value less than -1. Conclusions: Our study reveals the differentially expressed genes in gefitinib-resistant NSCLC cells comparing with the sensitive cells in a genome-wide scale. This results help to provide the novel insight into the gefitinib-resistant mechanism.
Project description:Analysis of gene expression profiles for gefitinib-tolerant cells derived from single cells. The hypothesis tested here was that a small population of cancer cells contribute to tolerance status in a bulk of EGFR mutated lung cancer cells. Results provide important infromnation of the tolerance to the EGFR tyrosine kinase inhibitor, gefitinib, such as upregualtion of cancer-stemness related genes.