Genome-wide DNA methylation analysis of lung carcinoma : Gene expression data
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE60644 | GEO | 2014/10/05
SECONDARY ACCESSION(S): PRJNA259181
REPOSITORIES: GEO
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Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. Experimental Design Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 12 normal lung tissues and 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas (SqCC), one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), and three small cell carcinomas (SCLC). Complimentary gene expression analyses was performed on 117 of the 124 tumors using Illumina HT12 V4 arrays (reported here). Gene expression profiling of 117 lung carcinomas using Illumina HT-12 V4 microarrays.
2014-10-05 | E-GEOD-60644 | biostudies-arrayexpress
Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer is not well studied. We performed whole-genome methylation analysis using 450K Illumina BeadArrays on 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas, one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), three small cell carcinomas (SCLC) and 12 normal lung tissues. Unsupervised class discovery was performed to identify DNA methylation subgroups with clinicopathological and molecular features. Subgroups were validated in two independent NSCLC cohorts. Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, in both discovery and validation cohorts, remaining four epitypes were associated with differences in clinicopathological and molecular features, including global hypomethylation, promoter hypermethylation, copy number alterations, expression of proliferation-associated genes, association with unsupervised and supervised gene expression phenotypes, KRAS, TP53, KEAP1, SMARCA4, and STK11 mutations, smoking history, and patient outcome. Based on a multicohort approach we conducted a comprehensive survey of genome-wide DNA methylation in lung cancer, identifying a distinct neuroendocrine epitype and four adenocarcinoma epitypes associated with molecular and clinicopathological characteristics, and patient outcome. Our results bring further understanding of the epigenetic characteristics and molecular diversity in lung cancer generally and in adenocarcinoma specifically. Genome-wide DNA methylation analysis of 124 lung carcinomas and 12 normal lung tissues using Illumina Human Methylation 450K v1.0 Beadchips.
2014-10-05 | E-GEOD-56044 | biostudies-arrayexpress
Project description:Lung cancer is the worldwide leading cause of death from cancer. DNA methylation in gene promoter regions is a major mechanism of gene expression regulation that may promote tumorigenesis. However, whether clinically relevant subgroups based on DNA methylation patterns exist in lung cancer is not well studied. We performed whole-genome methylation analysis using 450K Illumina BeadArrays on 124 tumors including 83 adenocarcinomas, 23 squamous cell carcinomas, one adenosquamous cancer, five large cell carcinomas, nine large cell neuroendocrine carcinomas (LCNEC), three small cell carcinomas (SCLC) and 12 normal lung tissues. Unsupervised class discovery was performed to identify DNA methylation subgroups with clinicopathological and molecular features. Subgroups were validated in two independent NSCLC cohorts. Unsupervised analysis identified five DNA methylation subgroups (epitypes). One epitype was distinctly associated with neuroendocrine tumors (LCNEC and SCLC). For adenocarcinoma, in both discovery and validation cohorts, remaining four epitypes were associated with differences in clinicopathological and molecular features, including global hypomethylation, promoter hypermethylation, copy number alterations, expression of proliferation-associated genes, association with unsupervised and supervised gene expression phenotypes, KRAS, TP53, KEAP1, SMARCA4, and STK11 mutations, smoking history, and patient outcome. Based on a multicohort approach we conducted a comprehensive survey of genome-wide DNA methylation in lung cancer, identifying a distinct neuroendocrine epitype and four adenocarcinoma epitypes associated with molecular and clinicopathological characteristics, and patient outcome. Our results bring further understanding of the epigenetic characteristics and molecular diversity in lung cancer generally and in adenocarcinoma specifically.
2014-10-05 | GSE56044 | GEO
Project description:Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, however, not all lung cancers can be attributable to smoking. The genetic aberrations that differ between smokers' and never-smokers’ lung carcinomas remain to a large extent unclear. We analyzed 72 early-stage primary lung carcinomas including small cell lung cancers LCNEC, adenocarcinomas and squamous cell carcinomas by Illumina HT12 gene expression microarrays.
2012-05-17 | GSE29016 | GEO
Project description:Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, however, not all lung cancers can be attributable to smoking. The genetic aberrations that differ between smokers' and never-smokersM-bM-^@M-^Y lung carcinomas remain to a large extent unclear. We analyzed 72 early-stage primary lung carcinomas including small cell lung cancers, adenocarcinomas and squamous cell carcinomas by Illumina HT12 gene expression microarrays. Gene expression profiling of 72 lung carcinomas using Illumina HT-12 V3.0 microarrays.
2012-05-16 | E-GEOD-29016 | biostudies-arrayexpress
Project description:Two prognostically significant subtypes of high-grade lung neuroendocrine tumors independent of small-cell and large-cell neuroendocrine carcinomas identified by gene expression profiles. BACKGROUND: Classification of high-grade neuroendocrine tumors (HGNT) of the lung currently recognises large-cell neuroendocrine carcinoma (LCNEC) and small-cell lung carcinoma (SCLC) as distinct groups. However, a similarity in histology for these two carcinomas and uncertain clinical course have led to suggestions that a single HGNT classification would be more appropriate. Gene expression profiling, which can reproduce histopathological classification, and often defines new subclasses with prognostic significance, can be used to resolve HGNT classification. METHODS: We used cDNA microarrays with 40386 elements to analyze the gene expression profiles of 38 surgically resected samples of lung neuroendocrine tumors and 11 SCLC cell lines. Samples of large-cell carcinoma, adenocarcinoma, and normal lung were also included to give a total of 105 samples analyzed. The data were subjected to filtering to yield informative genes before unsupervised hierarchical clustering that identified relatedness of tumor samples. FINDINGS: Distinct groups for carcinoids, large-cell carcinoma, adenocarcinoma, and normal lung were readily identified. However, we were unable to distinguish LCNEC from SCLC by gene expression profiling. Three independent rounds of unsupervised hierarchical clustering consistently divided SCLC samples into two main groups with LCNEC samples largely integrated with these groups. Furthermore, patients in one of the groups identified by clustering had a significantly better clinical outcome than the other (83% vs 12% survived for 5 years; p=0.0094. None of the highly proliferative SCLC cell lines subsequently analyzed clustered with this good-prognosis group. INTERPRETATION: Our findings show that HGNT of the lung can be classified into two groups independent of SCLC and LCNEC. To this end, we have identified many genes, some of which encode well-characterized markers of cancer that distinguish the HGNT groups. These results have implications for the diagnosis, classification, and treatment of lung neuroendocrine tumors, and provide important insights into their underlying biology. Keywords: other
2004-02-10 | E-GEOD-1037 | biostudies-arrayexpress
Project description:Two prognostically significant subtypes of high-grade lung neuroendocrine tumors independent of small-cell and large-cell neuroendocrine carcinomas identified by gene expression profiles. BACKGROUND: Classification of high-grade neuroendocrine tumors (HGNT) of the lung currently recognises large-cell neuroendocrine carcinoma (LCNEC) and small-cell lung carcinoma (SCLC) as distinct groups. However, a similarity in histology for these two carcinomas and uncertain clinical course have led to suggestions that a single HGNT classification would be more appropriate. Gene expression profiling, which can reproduce histopathological classification, and often defines new subclasses with prognostic significance, can be used to resolve HGNT classification. METHODS: We used cDNA microarrays with 40386 elements to analyze the gene expression profiles of 38 surgically resected samples of lung neuroendocrine tumors and 11 SCLC cell lines. Samples of large-cell carcinoma, adenocarcinoma, and normal lung were also included to give a total of 105 samples analyzed. The data were subjected to filtering to yield informative genes before unsupervised hierarchical clustering that identified relatedness of tumor samples. FINDINGS: Distinct groups for carcinoids, large-cell carcinoma, adenocarcinoma, and normal lung were readily identified. However, we were unable to distinguish LCNEC from SCLC by gene expression profiling. Three independent rounds of unsupervised hierarchical clustering consistently divided SCLC samples into two main groups with LCNEC samples largely integrated with these groups. Furthermore, patients in one of the groups identified by clustering had a significantly better clinical outcome than the other (83% vs 12% survived for 5 years; p=0.0094. None of the highly proliferative SCLC cell lines subsequently analyzed clustered with this good-prognosis group. INTERPRETATION: Our findings show that HGNT of the lung can be classified into two groups independent of SCLC and LCNEC. To this end, we have identified many genes, some of which encode well-characterized markers of cancer that distinguish the HGNT groups. These results have implications for the diagnosis, classification, and treatment of lung neuroendocrine tumors, and provide important insights into their underlying biology. Keywords: other
2004-02-11 | GSE1037 | GEO
Project description:Complements GSE56044 with 36 additional samples belonging to the large-cell carcinoma (LCC) and large-cell neuroendocrine (LCNEC) histologies. LCC classification is according to WHO 2004 guidelines. Genomic DNA from 36 lung cancer samples was treated with bisulfite and hybridized to Illumina methylation 450K arrays using standard protocols. Signal intensities were obtained from GenomeStudio (Illumina), converted to beta-values, filtered, and normalized to remove biases between Infinium I and II probes. Both raw intensity values, signal detection p-values and the final normalized data are included for each sample.
2020-07-27 | GSE149521 | GEO
Project description:SNP profiles from 82 lung carcinomas and 2 cell lines were analyzed to detect potential tumor suppressors in lung cancer. Homozygous deletions revealed two interesting candidates with ARID domains, which were further characterized by sequencing in the whole series. 82 lung carcinomas and 2 cell lines were analyzed with Illumina HumanCNV370-Duo v1.0 chips.
2013-01-03 | E-GEOD-31483 | biostudies-arrayexpress
Project description:There is a clear need to expand the toolkit of adequate mouse models and cell lines available for preclinical studies of high-grade neuroendocrine lung carcinoma (Small Cell Lung Carcinoma, SCLC and Large Cell Neuroendocrine Carcinoma, LCNEC), two highly aggressive tumor types with dismal prognosis and few therapeutic options. Actually, paucity is extreme in the case of LCNEC. Given the lack of murine cell lines and transplant models of LCNEC the need is imperative/unmet. In this study, we have generated and examined new models of LCNEC and SCLC transplantable cell lines derived from our previously developed primary mouse LCNEC and SCLC tumors. RNA-seq analysis demonstrated that our cell lines and syngeneic tumors maintained the transcriptome program from the original transgenic primary tumor, and display strong similarities to human SCLC or LCNEC. Importantly, the SCLC transplanted cell lines show the ability of metastasize, mimicking this characteristic of the human condition. In summary, we have generated mouse cell line tools that allow further basic and translational research, as well as preclinical testing of new treatment strategies for SCLC and LCNEC, as they retain important features of their human counterparts and address the lack of LCNEC disease models.
2023-10-29 | GSE242422 | GEO