Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of human lung cancer and control samples

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

SUBMITTER: Mª Esther Farez-Vidal

PROVIDER: E-GEOD-18842 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer.

Sanchez-Palencia Abel A Gomez-Morales Mercedes M Gomez-Capilla Jose Antonio JA Pedraza Vicente V Boyero Laura L Rosell Rafael R Fárez-Vidal M Esther ME

International journal of cancer 20101128 2

The development of reliable gene expression profiling technology is having an increasing impact on our understanding of lung cancer biology. Our study aimed to determine any correlation between the phenotypic heterogeneity and genetic diversity of lung cancer. Microarray analysis was performed on a set of 46 tumor samples and 45 paired nontumor samples of nonsmall cell lung cancer (NSCLC) samples to establish gene signatures in primary adenocarcinomas and squamous-cell carcinomas, determine diff ...[more]

PMID: 20878980

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Project description:Purpose: Generate genome-wide methylation profiles of non-small cell lung carcinomas (NSCLC) and their matching lung tissues for detection of hypermethylated and hypomethylated regions present in the tumors. Methods: MethylCapture followed by next-generation sequencing (Illumina GAIIx) of 7 nsclc tumor samples and paired lung tissues in replicated, plus one cell line, 2 fully artificially methylated and 2 fully artificially unmethylated controls. Normalization of methylation reads based on CpG coupling factor–method. Relative methylation scores (rms) in 500bp non-overlapping windows. 90th percentile of rpm (reads per million) values for all 500bp genome-wide windows, with rpm <1.33 were considered. Distributions of 10bp bins rms values within each 500bp genomic region were compared using both one-sided Student’s t-test and one-sided Wilcoxon rank-sum test. Testing was done separately for hypo- and hypermethylation and p-value threshold of 10-18. Results: MethylCap-seq data revealed strong positive correlation between replicate experiments and between paired tumor/lung samples. 14472 differentially methylated regions (DMR) with non-overlapping 500 bp windows were found. 57 DMRs were present in all NSCLC tumors. 287 were unique for squamous-cell carcinomas and 26 unique for adenocarcinomas. While hypomethylated DMRs did not correlate to any particular functional category of genes, the hypermethylated DMRs were strongly associated with genes encoding transcriptional regulators. Furthermore, subtelomeric regions and satellite repeats were hypomethylated in the NSCLC samples. Conclusion: We provide a resource containing genome-wide DNA methylation maps of NSCLC and their paired lung tissues, and comprehensive lists of known and novel DMRs and associated genes in NSCLC. The DMRs can be in further studies to develop sensitive biological markers for NSCLC, which may enable non-invasive diagnosis and early detection of the disease, and potentially allow histological classification. MethylCap-seq of 7 nsclc tumor samples and paired lung tissues, plus 2 fully methylated and 2 fully unmethylated controls.

Project description:The success of targeted therapies creates a need to discriminate tumors accurately by their histological and genetic characteristics. Here, we used cDNA microarray analysis to identify gene expression profiles and single markers that recapitulate the pathological and genetic background (i.e., BRAF, EGFR, KRAS, LKB1, PIK3CA, and TP53 gene alterations) of non-small cell lung cancer (NSCLC). Gene expression profiles were determined for 6 normal lung tissues and 69 lung tumors from patients diagnosed with NSCLC. We performed an unsupervised hierarchical clustering with the most variably expressed transcript to investigate whether there was evidence for natural grouping samples based on similarity in gene expression profiles. We examined the relationship between the clusters of tumors and patient and tumor characteristics such as gender, smoking status, histological type, degree of differentiation, tumor size, lymph node involvement and genetic background. We used a supervised analysis to identify the genes that are important for distinguishing subgroups of tumors defined by histological type. Moreover, we used this supervised approach to search for markers that characterize those tumors carrying EGFR, KRAS, PIK3CA and TP53 alterations. We identify several genes with characteristic patterns of expression in each tumor histological type (adenocarcinoma and squamous cell carcinoma) and we found that the presence of EGFR mutations result in a particular expression profile. Keywords: Transciption profiling of tumors with different histological and genetic background. We analyzed 69 NSCLC tumors. All the samples were characterized by histological type and by the presence of alterations at genes that are known to be involved in lung carcinogenesis. Mutational analysis of BRAF, EGFR, KRAS, and LKB1 is provided only for adenocarcinomas and analysis of alterations at PIK3CA gene (mutational analysis or gene amplification by FISH analysis) is provided only for 47 of the tumors. We analyzed gene expression profiles to identify those genes that are differentially expressed between two subgroups by t-test: 1) adenocarcinomas vs. squamous cell carcinomas; 2) tumors with mutation at EGFR gene vs. wild type tumors; 3) tumors with mutation at KRAS gene vs. wild type tumors; 4) tumors with mutation at TP53 gene vs. wild type tumors; 5) tumors with alterations (mutation or gene amplification) at PIK3CA gene vs. wild type tumors.

Dataset Information

Transcription profiling of human lung cancer and control samples

Publications

Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer.

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