Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA278807 | ENA |
REPOSITORIES: ENA
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Project description:Non-small cell lung cancers (NSCLCs) harboring activating EGFR mutants show dramatic responses to EGFR TKIs, such as erlotinib and geffitinib. However, nearly all patients show relapse within 1 year after initial treatment. We used microarrays to detail global gene expression changes in EGFR mutant cells vs. WT cells responding to erlotinib. 4 EGFR mutant and 4 WT NSCLC cells were treated with or without erlotinib for 24 hr, followed by RNA extraction and hybridization on Affymetrix microarrays.
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Project description:Activating mutations of EGFR have been characterized as important mechanisms for carcinogenesis in a subset of EGFR-dependent non-small cell lung cancers (NSCLC). EGFR tyrosine kinase inhibitors (TKI), such as erlotinib and gefitinib, have dramatic clinical effects on EGFR-addicted lung cancers and are used as first-line therapy for EGFR-mutant tumors. However, eventually all tumors acquire secondary resistance to the drugs and progress. We established a model to better understand mechanisms of acquired resistance. NCI- HCC827 cells are EGFR-mutant and highly erlotinib-sensitive. In this study we exposed HCC827 cells to increasing concentrations of erlotinib and two highly erlotinib-resistant subclones were developed (ER3 and T15-2). In these subclones no acquired alterations of EGFR or MET were found. We hereby performed a gene expression microarray studies to understand changes that might explain mechanisms of resistance. Through these studies we demonstrated in one resistant clone (ER3) overexpression of AXL, a tyrosine kinase implicated in imatinib and lapatinib resistance. Gene expression profilings were measured in NSCLC cell line HCC827 and two erlotinib-resistant HCC827-originated sublines ER3 and T15-2.
2012-05-29 | E-GEOD-38310 | biostudies-arrayexpress
Project description:Epidermal growth factor receptor (EGFR) inhibitors, as targeted therapies for non-small-cell lung cancer (NSCLC), have significantly enhanced patient survival and quality of life. However, despite these advancements, a significant proportion of patients exhibit resistance to EGFR inhibitors, limiting their overall treatment effectiveness. This study investigates the synergistic effects of combining Paeoniae Radix (PR) with the EGFR inhibitors erlotinib and gefitinib to overcome this resistance. The transcriptomic analysis of PR treatment revealed its potential to reverse the gene signature associated with resistance to EGFR inhibitors, as identified through analysis of a cell line database in EGFR mutant NSCLC. Combination treatment experiments validated that PR increased responsiveness to erlotinib and gefitinib in H1650 and H1975 NSCLC cells. By combining molecular experiments and transcriptome analysis, we found that PR may suppress resistance by modulating the Aurora B and apoptosis pathways. Notably, the combination therapy upregulated the apoptosis pathway and downregulated the Aurora B pathway more than single drug treatments. These results may contribute to the development of natural product-based combination therapeutic strategies to inhibit drug resistance in NSCLC.
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Project description:The receptor tyrosine kinase (RTK) EGFR is overexpressed and mutated in NSCLC. These mutations can be targeted by RTK inhibitors (TKIs), such as erlotinib. Chromatin-modifying agents offer a novel therapy approach by sensitizing tumor cells to TKIs. The NSCLC cell lines HCC827 (EGFR mutant, adenocarcinoma), A549 (EGFR wt, adenocarcinoma) and NCI-H460 (EGFR wt, large cell carcinoma) were analyzed by SNP6.0 array. Changes in proliferation were quantified by WST-1 assay, apoptosis by Annexin V/7-AAD flow cytometry and histone marks (acH3, H3K4me1,-2,-3) by immunoblotting. Expectedly, the EGFR wt cell lines A549 and NCI-H460 were insensitive to the growth-inhibiting effect of single-agent erlotinib (IC50 70-100µM), compared to HCC827 (IC50 <0.02μM). Treatment with panobinostat diminished growth to <50% in both EGFR wt and <30% in HCC827 cells. The combination of both drugs significantly reduced proliferation by ≥70% in A549, >95% in HCC827, but not further in NCI-H460. Panobinostat alone induced differentiation and expression of p21WAF1/CIP1 and p53 in all three cell lines, with almost no further increase when combined with erlotinib. In contrast, combination treatment additively decreased pERK, pAKT and pEGFR in A549, and synergistically induced acH3 in both adenocarcinoma lines. Surprisingly, we also saw an induction of H3K4 methylation marks in all three cell lines. In conclusion, panobinostat synergistically sensitized lung adenocarcinoma cells to the antiproliferative effects of erlotinib. Since single-agent erlotinib has only modest clinical effects in adenocarcinoma EGFR wt patients, combination therapy with an HDACi might offer a promising therapy approach to extend this activity. Copy-number analysis of three NSCLC cell lines HCC827, A549 and NCI-H460 (in unicates) was performed according to protocol by Affymetrix Genome-Wide Human SNP-Array 6.0.
2014-12-03 | E-GEOD-63784 | biostudies-arrayexpress
Project description:Expression data from EGFR WT or EGFR mutant NSCLC with or without erlotinib
| PRJNA245807 | ENA
Project description:The non-small cell lung cancer (NSCLC) cell line HCC827 harbors an activating EGFR mutation (exon 19 deletion) that confers sensitivity to the FDA-approved EGFR inhibitor erlotinib. By applying the ClonTracer barcoding system, we were able to show the presence of pre-existing sub-populations in HCC827 that contribute to erlotinib resistance. Prior studies implicated that MET amplification confers resistance to erlotinib in this cell line. Therefore we examined the effects of the c-Met inhibitor crizotinib on the barcoded HCC827 population when treated either sequentially or simultaneously with both inhibitors. Despite the significant reduction in barcode complexity, the erlotinib/crizotinib combination treatment failed to eradicate all of the resistant clones implying the presence of an erlotinib/crizotinib dual resistant subpopulation. We performed transcriptome profiling (RNA-seq) to elucidate the potential resistance mechanisms of the dual resistant subpopulation in comparison to vehicle-treated or single agent erlotinib-resistant HCC827 cell populations as controls. mRNA profiling of the subpopulations of human NSCLC cell line HCC827 that contribute to EGFR inhibitor erlotinib and MET inhibitor crizotinib resistance
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Project description:The non-small cell lung carcinoma (NSCLC) PC9 cell line is an established preclinical model for tyrosine kinase inhibitors. Recent evidence suggests that the H3K4 demethylase KDM5A protein is required for emerging drug-resistant cell populations. To better understand the dependence of cell survival on H3K4me3 level, we treated the EGFR-mutant PC9 cells with erlotinib and performed ChIP-seq analysis using H3K4me3 antibodies. We were able to identify genomic regions that exhibit decreased H3K4me3 in drug-treated cells. The results of this study will help to address clinical usefulness of KDM5A-targeted strategies in overcoming drug resistance, particularly in NSCLC.
2020-12-19 | GSE148461 | GEO
Project description:Activating mutations of EGFR have been characterized as important mechanisms for carcinogenesis in a subset of EGFR-dependent non-small cell lung cancers (NSCLC). EGFR tyrosine kinase inhibitors (TKI), such as erlotinib and gefitinib, have dramatic clinical effects on EGFR-addicted lung cancers and are used as first-line therapy for EGFR-mutant tumors. However, eventually all tumors acquire secondary resistance to the drugs and progress. We established a model to better understand mechanisms of acquired resistance. NCI- HCC827 cells are EGFR-mutant and highly erlotinib-sensitive. In this study we exposed HCC827 cells to increasing concentrations of erlotinib and two highly erlotinib-resistant subclones were developed (ER3 and T15-2). In these subclones no acquired alterations of EGFR or MET were found. We hereby performed a gene expression microarray studies to understand changes that might explain mechanisms of resistance. Through these studies we demonstrated in one resistant clone (ER3) overexpression of AXL, a tyrosine kinase implicated in imatinib and lapatinib resistance.
2012-05-30 | GSE38310 | GEO
Project description:Bidkhori2012 - EGFR signalling in NSCLC
The paper describes and compares two models on EGFR signalling between normal and NSCLC cells. Moreover, it is shown that ERK (MAPK), STAT and Akt factor's activation pattern are different between normal and NSCLA models. This model corresponds to EGFR signalling in NSCLA cells.
Created by The MathWorks, Inc. SimBiology tool, Version 3.3
This model is described in the article:
Modeling of tumor progression in NSCLC and intrinsic resistance to TKI in loss of PTEN expression.
Bidkhori G, Moeini A, Masoudi-Nejad A
PloS one [2012, 7(10):e48004]
Abstract:
EGFR signaling plays a very important role in NSCLC. It activates Ras/ERK, PI3K/Akt and STAT activation pathways. These are the main pathways for cell proliferation and survival. We have developed two mathematical models to relate to the different EGFR signaling in NSCLC and normal cells in the presence or absence of EGFR and PTEN mutations. The dynamics of downstream signaling pathways vary in the disease state and activation of some factors can be indicative of drug resistance. Our simulation denotes the effect of EGFR mutations and increased expression of certain factors in NSCLC EGFR signaling on each of the three pathways where levels of pERK, pSTAT and pAkt are increased. Over activation of ERK, Akt and STAT3 which are the main cell proliferation and survival factors act as promoting factors for tumor progression in NSCLC. In case of loss of PTEN, Akt activity level is considerably increased. Our simulation results show that in the presence of erlotinib, downstream factors i.e. pAkt, pSTAT3 and pERK are inhibited. However, in case of loss of PTEN expression in the presence of erlotinib, pAkt level would not decrease which demonstrates that these cells are resistant to erlotinib.
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2024-09-02 | BIOMD0000000453 | BioModels