Long non-coding RNA dysregulation is a frequent event in non-small cell lung carcinoma pathogenesis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE130740 | GEO | 2019/12/09
REPOSITORIES: GEO
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Project description:PURPOSE: Non-small cell lung cancers (NSCLC) comprise multiple distinct biological groups with different prognoses. For example, patients with epithelial-like (EL) tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like (ML) tumors. Here we test the hypothesis that EL NSCLCs can be distinguished from ML NSCLCs on the basis of global DNA methylation patterns. EXPERIMENTAL DESIGN: To determine whether phenotypic subsets of NSCLC can be defined based on their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative RT-PCR and methylation specific PCR in formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. RESULTS: We show that patterns of methylation divide NSCLCs into EL and ML subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple DMRs, including ERBB2 and ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. CONCLUSIONS: Our data demonstrate that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used for predictive biomarker discovery and development. To determine whether phenotypic subsets of NSCLC can be defined based on their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative RT-PCR and methylation specific PCR in formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy.
2012-03-03 | E-GEOD-36216 | biostudies-arrayexpress
Project description:PURPOSE: Non-small cell lung cancers (NSCLC) comprise multiple distinct biological groups with different prognoses. For example, patients with epithelial-like (EL) tumors have a better prognosis and exhibit greater sensitivity to inhibitors of the epidermal growth factor receptor (EGFR) pathway than patients with mesenchymal-like (ML) tumors. Here we test the hypothesis that EL NSCLCs can be distinguished from ML NSCLCs on the basis of global DNA methylation patterns. EXPERIMENTAL DESIGN: To determine whether phenotypic subsets of NSCLC can be defined based on their DNA methylation patterns, we combined microfluidics-based gene expression analysis and genome-wide methylation profiling. We derived robust classifiers for both gene expression and methylation in cell lines and tested these classifiers in surgically resected NSCLC tumors. We validate our approach using quantitative RT-PCR and methylation specific PCR in formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. RESULTS: We show that patterns of methylation divide NSCLCs into EL and ML subsets as defined by gene expression and that these signatures are similarly correlated in NSCLC cell lines and tumors. We identify multiple DMRs, including ERBB2 and ZEB2, whose methylation status is strongly associated with an epithelial phenotype in NSCLC cell lines, surgically resected tumors, and formalin-fixed biopsies from NSCLC patients who went on to fail front-line chemotherapy. CONCLUSIONS: Our data demonstrate that patterns of DNA methylation can divide NSCLCs into two phenotypically distinct subtypes of tumors and provide proof of principle that differences in DNA methylation can be used for predictive biomarker discovery and development.
2012-03-03 | GSE36216 | GEO
Project description:Epigenetic changes largely contribute to the regulation of gene expression in cancer cells. DNA methylation is part of the epigenetic gene regulation complex which is relevant for the pathogenesis of cancer. We performed a genome-wide search for methylated CpG islands in tumors and corresponding non-malignant lung tissue samples of 101 stage I-III non-small cell lung cancer (NSCLC) patients by combining methylated DNA immunoprecipitation and microarray analysis using NimbleGenM-BM-4s 385K Human CpG Island plus Promoter arrays. By testing for differences in methylation between tumors and corresponding non-malignant lung tissues, we identified 298 tumor-specifically methylated genes. From many of these genes epigenetic regulation was unknown so far. Gene Ontology analysis revealed an over-representation of genes involved in regulation of gene expression and cell adhesion. Expression of 182 of 298 genes was found to be upregulated after 5-aza-2M-BM-4-deoxycytidine (Aza-dC) and/or trichostatin A (TSA) treatment of 3 NSCLC cell lines by Affymetrix microarray analysis. In addition, methylation of selected genes in primary NSCLCs and corresponding non-malignant lung tissue samples were analyzed by methylation-sensitive high resolution melting analysis (MS-HRM). Our results obtained by MS-HRM analysis confirmed our data obtained by MeDIP-chip analysis. Moreover, by comparing methylation results from MeDIP-chip analysis with clinico-pathological parameters of the patients we observed methylation of HOXA2 as potential parameter for shorter disease-free survival of NSCLC patients. In conclusion, using a genome-wide approach we identified a large number of tumor-specifically methylated genes in NSCLC patients. Our results stress the importance of DNA methylation for the pathogenesis of NSCLCs. Overall, samples of 3 untreated, with Aza-dC treated and with Aza-dC/TSA treated NSCLC cell lines were hybridized to Affymetrix HG-U133_plus_2.0 microarrays (18 in total).
2012-11-26 | E-GEOD-32496 | biostudies-arrayexpress
Project description:Analysis of NSCLC development at microRNA expression level. Results shows that has-miR-96 is significant up-regulated in the cancer tissue compared with the adjacent normal tissue. Illumina Human v2 MicroRNA expression beadchip Total microRNA obtained from 6 paired NSCLC cancer tissue and the adjacent normal tissue.
2012-09-16 | E-GEOD-29248 | biostudies-arrayexpress
Project description:Analysis of NSCLC development at gene expression level. Results shows that obvious activation of cell cycle pathway, and significant repression of cell-cell communication pathways. Illumina HumanHT-12 V4.0 expression beadchip Total RNA obtained from 6 paired NSCLC cancer tissue and the adjacent normal tissue.
2012-09-16 | E-GEOD-29249 | biostudies-arrayexpress
Project description:Epigenetic changes largely contribute to the regulation of gene expression in cancer cells. DNA methylation is part of the epigenetic gene regulation complex which is relevant for the pathogenesis of cancer. We performed a genome-wide search for methylated CpG islands in tumors and corresponding non-malignant lung tissue samples of 101 stage I-III non-small cell lung cancer (NSCLC) patients by combining methylated DNA immunoprecipitation and microarray analysis using NimbleGen´s 385K Human CpG Island plus Promoter arrays. By testing for differences in methylation between tumors and corresponding non-malignant lung tissues, we identified 298 tumor-specifically methylated genes. From many of these genes epigenetic regulation was unknown so far. Gene Ontology analysis revealed an over-representation of genes involved in regulation of gene expression and cell adhesion. Expression of 182 of 298 genes was found to be upregulated after 5-aza-2´-deoxycytidine (Aza-dC) and/or trichostatin A (TSA) treatment of 3 NSCLC cell lines by Affymetrix microarray analysis. In addition, methylation of selected genes in primary NSCLCs and corresponding non-malignant lung tissue samples were analyzed by methylation-sensitive high resolution melting analysis (MS-HRM). Our results obtained by MS-HRM analysis confirmed our data obtained by MeDIP-chip analysis. Moreover, by comparing methylation results from MeDIP-chip analysis with clinico-pathological parameters of the patients we observed methylation of HOXA2 as potential parameter for shorter disease-free survival of NSCLC patients. In conclusion, using a genome-wide approach we identified a large number of tumor-specifically methylated genes in NSCLC patients. Our results stress the importance of DNA methylation for the pathogenesis of NSCLCs.
2012-11-26 | GSE32496 | GEO
Project description:Illumina miRNA-seq method to uncover the expression profile of NSCLC in-vitro experimental models consisting of cell lines A549, H460 compared to healthy BEAS-2B cell line, and lung tissue (NSCLC and paired normal) from urethane treated 6-week-old FVB/NJ mice. We aimed to uncover the divergent epigenetic background of KRAS-mutant NSCLC in mouse and human cell lines, extensively used as biological models in relevant research. To that end, we have comprehensively mapped the functional miRNA and lncRNA landscape of human (A549 and H460) and mouse (experimentally developed LUAD) NSCLC models and correlated current results with LRF/ZBTB7A expression
2023-12-25 | GSE251697 | GEO
Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. Currently, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer which account for 20% and 80% of lung carcinomas, respectively. NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack of neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples. In this study, a set of 31 pairs and one non-paired sample of macroscopic tumor and non-tumor samples (10 pairs and 1 non-paired sample squamous-cell carcinoma, 19 pairs and one non-paired samples adenocarcinoma, 2 pairs adeno-squamous-cell carcinoma) was selected for bulk/macro sampling. Of these 31 pairs and 2 non-paired samples, 16 pairs plus 15 non paired samples were reanalyzed using laser capture microdissection (LCM) for sampling the cells (7 pairs and 3 non-paired samples squamous-cell carcinoma, 8 pairs and 11 non-paired samples adeno carcinomas, 1 pair and 1 non paired sample Adeno-squamous-cell carcinoma). For macroscopic samples, 50 to 80 µg of tissue was used to isolate total RNA. Gene expression profile was determined using Affymetrix Human Genome Gene 1.0 ST genechip. For the LCM samples, from representative slides histologically confirmed and mapped by a pathologist, approximately 1000 cells/sample were collected by LCM;. cDNA was amplified using Nugen WT-Ovation One-Direct amplification system. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples.
2011-08-25 | E-GEOD-31552 | biostudies-arrayexpress
Project description:The stromal microenvironment plays a vital role in cancer initiation and progression. We performed a comparative expression profiling of pulmonary MSC derived from NSCLC and corresponding normal lung tissue of 5 newly diagnosed patients. The analysis indicated variable expression of genes involved in DNA repair, apoptosis, proliferation or angiogenesis between NSCLC-MSC and NLT-MSC. MSC were derived from NSCLC and corresponding normal lung tissue of 5 patients. Paired SAM test was performed to screen for differentially expressed genes between NSCLC-MSC and NLT-MSC.
2013-02-07 | E-GEOD-23066 | biostudies-arrayexpress
Project description:There are significant differences in the lncRNA expression profiles in Chinese patients with pulmonary adenocarcinoma. LncRNAs such as AK124939 may be anti-cancer factors related to the progress of pulmonary adenocarcinoma. RNA extracted from three paired pulmonary adenocarcinoma tissue and adjacent normal lung tissue specimens was used to synthesize double-stranded complementary DNA (cDNA) after labeling and hybridization. The cDNA was labeled and hybridized to the lncRNA expression microarray, and array data were analyzed for hierarchical clustering. Gene coexpression networks were constructed to identify interactions among genes. To validate the microarray findings, we measured the relative expression levels of four random differentially expressed lncRNAs in the same tissue used for microarray using real-time quantitative polymerase chain reaction (qRT-PCR). The expression level of one lncRNA AK124939, in the paired pulmonary adenocarcinoma/adjacent normal lung tissue of another 30 patients was measured using qRT-PCR. The experimental data were further analyzed and compared with clinical features.
2014-04-17 | E-GEOD-56850 | biostudies-arrayexpress