Transcription profiling by array of human non-small cell lung cancer tissue from female non-smokers
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Lu TP
PROVIDER: S-ECPF-GEOD-19804 | biostudies-other | 2010 Oct
REPOSITORIES: biostudies-other
Similar Datasets
Project description:PURPOSE The development of reliable gene expression profiling technology is having an increasing impact on our understanding of lung cancer biology. The present study aims to determine whether the phenotypic heterogeneity and genetic diversity of lung cancer are correlated. PATIENTS AND METHODS In this study, microarray analysis was performed in a set of 91 non-small cell lung cancer (NSCLC) samples in order to: establish gene signatures in primary adenocarcinomas and squamous-cell carcinomas; determine differentially expressed gene sequences at different stages of the disease; and identify sequences with biological significance for tumor progression. After microarray analysis, the expression level of 92 selected genes was validated by qPCR in an independent set of 70 samples. RESULTS Gene sequences were differentially expressed as a function of tumor type, stage, and differentiation grade. High upregulation was observed for KRT15 and PKP1, which may be good markers to distinguish squamous cell carcinoma samples. High downregulation was observed for DSG3 in stage IA adenocarcinomas. CONCLUSION Expression signatures in NSCLC distinguish tumor type, stage, and differentiation grade. Keywords: Tumor vs control comparative genomics study 91 samples studied, 46 tumors and 45 controls. All samples are paired except three.
| S-ECPF-GEOD-18842 | biostudies-other
Project description:Affymetrix exon array data set (HuEx-1.0_st) derived from matched pairs of non-small cell lung cancer (NSCLC) and normal adjacent lung tissue (NAT). This data set includes both the adenocarcinoma (AdCa) as well as the squamous cell carcinoma (SCC) subtype of NSCLC.
| S-ECPF-MEXP-2644 | biostudies-other
Project description:This was a collaborative study to discover somatic mutations in 188 lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are likely to play a role in carcinogenesis. The observed mutational profiles correlate with clinical features, smoking status, and DNA repair defects. These results are complemented by data integration including SNP array data and gene expression array data (deposited here). Our findings shed further light on several key signaling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment. Experiment Overall Design: A subset of 75 RNAs from a corresponding set of 188 lung adenocarcinomas DNAs were resequenced across 623 genes.
| S-ECPF-GEOD-12667 | biostudies-other
Project description:Microarray gene expression analysis of genes that showed a gene copy number difference in non small cell lung cancer samples. Only data for a subset of the genes on the array chip are shown here.
| S-ECPF-TABM-270 | biostudies-other
Project description:We report the results of whole-genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and more than 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatin modification and DNA repair pathways were identified, along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never-smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions, including ROS1 and ALK, as well as novel metabolic enzymes. Cell-cycle and JAK-STAT pathways are significantly altered in lung cancer, along with perturbations in 54 genes that are potentially targetable with currently available drugs.
| S-EPMC3656590 | biostudies-literature
Project description:We identified a tumor signature of 5 genes that aggregates the 156 tumor and normal samples into the expected groups. We also identified a histology signature of 75 genes, which classifies the samples in the major histological subtypes of NSCLC. A prognostic signature of 17 genes showed the best association with post-surgery survival time. The performance of the signatures was validated using a patient cohort of similar size A genome-wide gene expression analysis was performed on a cohort of 91 patients. We used 91 tumor- and 65 adjacent normal lung tissue samples. We defined sets of predictor genes (probe sets) with the expression profiles. The power of predictor genes was evaluated using an independent cohort of 96 non-small cell lung cancer- and 6 normal lung samples
| S-ECPF-GEOD-19188 | biostudies-other
Project description:A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies. Samples were collected from eight subjects, four smokers (Sm)and four nonsmokers (NS). Each cheek was sampled creating an a and b sample for each subject which is reflected in the array name. All samples were isolated separately for total RNA. Each was hybridzed to microarrays to examine for differential gene expression between smokers and nonsmokers. There are 14 total samples in the main dataset (Set 2). One cheek sample failed in microarray analysis for two individuals, 08BCNS23 a and 08BCSm27 a, and so are not included here. A sample set (Set 1) was created which contains the four samples shown in this file. They represent repeated sampling of both cheeks for two individuals to test for reproducibility. There is a separate RMA file and metadata file (this file) for these data. These included samples 08BC11Sm a and b, a smoker, and 08BC12NSa and b a nonsmoker.
| S-ECPF-GEOD-16149 | biostudies-other
Project description:This series contain 36 samples obtained from human lung tissue and includes the following:; 7 Adenocarcinoma samples. 16 Squamous cell carcinoma samples. 1 AdenoSquamous sample. 2 Renal Metastasis. 1 Colon metastasis. 7 normal lung tissue adjacent to the tumors. 2 commercial normal lung RNA.
| S-ECPF-GEOD-1987 | biostudies-other
Project description:DNA genotype can affect gene expression, and gene expression can influence the onset and progression of diseases. Here we conducted a comprehensive study, we integrated analysis of gene expression profile and single nucleotide polymorphism (SNP) microarray data in order to scan out the critical genetic changes that participate in the onset and development of non-small cell lung cancer (NSCLC). Gene expression profile datasets were downloaded from the GEO database. Firstly, differentially expressed genes (DEGs) between NSCLC samples and adjacent normal samples were identified. Next, by STRING database, protein-protein interaction (PPI) network was constructed. At the same time, hub genes in PPI network were identified. Then, some functional SNPs in hub genes that may affect gene expression have been annotated. Finally, we carried a study to explore the relationship between functional SNPs and NSCLC risk and overall survival in Chinese female non-smokers. A total of 488 DEGs were identified in our study. There are 29 proteins with a higher degree of connectivity in the PPI network, including FOS, IL6 and MMP9. By using database annotation, we got 8 candidate functional SNPs that may affect the expression level of hub proteins. In the case-control study, we found that rs4754-T allele, rs959173-C allele and rs2239144-G allele were the protective allele of NSCLC risk. In dominant model, rs4754-CT+TT genotype were associated with a shorter survival time. In general, our study provides a novel research direction in the field of multi-omic data integration, and helps us find some critical genetic changes in disease.
| S-EPMC5386658 | biostudies-literature
Project description:Epigenetic alterations are widespread in cancer and can complement genetic alterations to influence cancer progression and treatment outcome. To determine the potential contribution of DNAmethylation alterations to tumor phenotype in non-small cell lung cancer (NSCLC) in both smoker and never-smoker patients, we performed genome-wide profiling of DNA methylation in 17 primary NSCLC tumors and 10 matched normal lung samples using the complementary assays, methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylation sensitive restriction enzyme sequencing (MRE-seq). We reported recurrent methylation changes in the promoters of several genes, many previously implicated in cancer, including FAM83A and SEPT9 (hypomethylation), as well as PCDH7, NKX2-1, and SOX17 (hypermethylation). Although many methylation changes between tumors and their paired normal samples were shared across patients, several were specific to a particular smoking status. For example, never-smokers displayed a greater proportion of hypomethylated differentially methylated regions (hypoDMRs) and a greater number of recurrently hypomethylated promoters, including those of ASPSCR1, TOP2A, DPP9, and USP39, all previously linked to cancer. Changes outside of promoters were also widespread and often recurrent, particularly methylation loss over repetitive elements, highly enriched for ERV1 subfamilies. Recurrent hypoDMRs were enriched for several transcription factor binding motifs, often for genes involved in signaling and cell proliferation. For example, 71% of recurrent promoter hypoDMRs contained a motif for NKX2-1. Finally, the majority of DMRs were located within an active chromatin state in tissues profiled using the Roadmap Epigenomics data, suggesting that methylation changes may contribute to altered regulatory programs through the adaptation of cell type-specific expression programs.
| S-EPMC10928376 | biostudies-literature