ADAM-28: A potential oncogene involved in asbestos-related lung adenocarcinomas
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE20875 | GEO | 2010/05/28
SECONDARY ACCESSION(S): PRJNA124669
REPOSITORIES: GEO
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Project description:To identify gene expression biomarkers associated with asbestos-related lung adenocarcinoma, we analyzed primary tumour gene expression for a total of 36 primary lung adenocarcinomas on 22,323 element microarrays, comparing 12 patients with lung asbestos body counts above levels associated with urban dwelling (ARLC-AC: asbestos-related lung cancer-adenocarcinoma) with 24 patients with no asbestos bodies (NARLC-AC: non-asbestos related lung cancer-adenocarcinoma). To identify gene expression biomarkers associated with asbestos-related lung tumorigenicity, we performed gene expression array analysis on tumours of 36 patients with primary lung adenocarcinoma, comparing twelve patients with lung asbestos body counts above levels associated with urban dwelling (ARLC-AC: asbestos-related lung cancer-adenocarcinoma) with twenty-four patients with no asbestos bodies (NARLC-AC: non-asbestos related lung cancer-adenocarcinoma). Synthesis of the labelled first strand cDNA was conducted using Amersham CyScribe Post-Labelling kit with starting material of 20 ug of total RNA. The amino-allyl labeled dNTP mix was added to the reaction to generate amino-allyl labelled second strand cDNA. Following the hydrolysis reaction, single-stranded cDNA probes were purified using Amersham GFX columns. Dye coupling reactions were performed by mixing the cDNA samples with Amersham Cy3 (reference) or Cy5 (tumour) and incubating in the dark. The reactions were purified with Amersham GFX columns to remove the unincorporated/quenched dyes. After the purification samples were combined for hybridization, the labeled cDNAs were co-hybridized to 22K oligo microarrays. Slides were scanned on GMS418 confocal scanner (Agilent). Genes differentially expressed between ARLC-AC and NARLC-AC were identified on fold change and P-value, and then prioritised using gene ontology.
2010-05-28 | E-GEOD-20875 | biostudies-arrayexpress
Project description:To identify gene expression biomarkers associate with asbestos-related lung squamous cell carcinoma, we analyzed gene expression profiles for a total of 56 lung squamous cell carcinomas using 44K Illumina Gene Expression microarrays. Twenty-six cases had lung asbestos body counts above levels associated with urban dwelling (ARLC-SCC: asbestos-related lung cancer-squamous cell carcinoma) and 30 cases had no lung asbestos bodies (NARLC-SCC: non-asbestos related lung cancer- squamous cell carcinoma). Genes differentially expressed between ARLC-SCC and NARLC-SCC were identified on fold change and P-value, and then prioritised using gene ontology.
2012-01-30 | GSE23822 | GEO
Project description:To identify gene expression biomarkers associate with asbestos-related lung squamous cell carcinoma, we analyzed gene expression profiles for a total of 56 lung squamous cell carcinomas using 44K Illumina Gene Expression microarrays. Twenty-six cases had lung asbestos body counts above levels associated with urban dwelling (ARLC-SCC: asbestos-related lung cancer-squamous cell carcinoma) and 30 cases had no lung asbestos bodies (NARLC-SCC: non-asbestos related lung cancer- squamous cell carcinoma). Genes differentially expressed between ARLC-SCC and NARLC-SCC were identified on fold change and P-value, and then prioritised using gene ontology. Total RNA was obtained from fresh frozen lung tumour tissue and stratified by asbestos phenotype. Gene expression profiling was performed to identify differences in the gene profiles of asbestos-related and non-asbestos related lung squamous cell carcinomas.
2012-01-30 | E-GEOD-23822 | biostudies-arrayexpress
Project description:Asbestos is the general term for a family of naturally occurring fibrous silicate minerals having commercial importance. They have been used widely for construction and for a number of industrial applications until early 70’s. It is now well known that workers exposed to asbestos are at high risk of developing many lung diseases including asbestosis, malignant mesothelioma, bronchial adenocarcinoma; squamous cell carcinoma of the respiratory epithelium and large/ small cell lung carcinoma. However, the disease causing potential and related processes associated with various asbestos/asbestiform fiber exposures are still largely unknown. In this study, we exposed C57BL6 female mice to asbestos (crocidolite, tremolite), asbestiform fibers (erionite) and a low pathogenicity mineral fiber (wollastonite) to assess pulmonary toxicity responses along with gene expression profiles in the lungs following 7 days post pharyngeal aspiration.
2018-03-01 | GSE100900 | GEO
Project description:Asbestos has been shown to cause chromosomal damage and DNA aberrations. The fiber is associated with many different lung diseases such as asbestosis, malignant mesothelioma, and lung cancer, but the disease-related processes are still largely unknown. Our aim was to identify specific gene expression profiles by using Affymetrix arrays, in human cell lines A549, Beas-2B, and MeT5A exposed to asbestos in a time-dependent manner. The hybridization data was analyzed using an algorithm specifically designed for clustering short time series expression data, a canonical correlation analysis (CCA) for identifying correlations between the cell lines, and a Gene Ontology (GO) analysis method for the identification of enriched differentially expressed biological processes. Keywords: time course, gene expression, cell line, asbestos
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Project description:This dataset encompassing the profiles of 150 lung cancer tumors was developed to serve as test dataset in the SBV IMPROVER Diagnostic Signature Challenge (sbvimprover.com). The aim of this subchallenge was to verify that it is possible to extract a robust diagnostic signature from gene expression data that can identify stages of different types of lung cancer. Participants were asked to develop and submit a classifier that can stratify lung cancer patients in one of four groups M-bM-^@M-^S Stage 1 of Adenocarcinoma (AC Stage 1), Stage 2 of Adenocarcinoma (AC Stage 2), Stage 1 of Squamous cell carcinoma (SCC Stage 1) or Stage 2 of Squamous cell carcinoma (SCC Stage 2). The classifier could be built by using any publicly available gene expression data with related histopathological information and was tested on the independent dataset described here. 150 non-small cell lung cancer tumors (adenocarcinoma, AC and squamous cell carcinoma, SCC) of stages I and II were collected by surgical resection from patients who have provided consent. Adenosquamous and large cell tumor samples were excluded. The number of smokers and non-smokers was balanced: there were 41 AC1 (adenocarcinoma stage I), 36 AC2, 34 SCC1, and 39 SCC2 samples. Study pathologists at each of the seven sites (Lebanon, Republic of Moldova, Romania, Russian Federation, Ukraine, Vietnam and United States of America) reviewed both the tumor permanent sections and the frozen sections of the samples. Clinical information was also collected about tumor staging, history of prior cancers, lymph node involvement by lymph node sampling/dissection, smoking history, age, gender.
2013-10-18 | E-GEOD-43580 | biostudies-arrayexpress
Project description:Genome-wide DNA methylation study in lung cancer and paired normal lung with well-documented asbestos exposure
2017-07-24 | GSE94785 | GEO
Project description:Asbestos disease model: Occupational lung disease comprises a wide variety of disorders caused by the inhalation or ingestion of dust particles or noxious chemical. These disorders include pneumoconiosis, asbestos-related pleural and others. Although asbestos is carcinogenic to humans, the mechanism by which it induces cancer is unknown. The study from Brody AR has shown that lung fibroblasts are activated to proliferate and produce connective tissue during the development of lung fibrosis. The 129 mouse strain does not develop asbestos-induced fibrogenesis, whereas several other inbred strains rapidly respond to inhaled fibers. David Schwartz from Duke University has bred C57B6 (high responders) to 129 (low responder) and backcrossed the F1 mice to either C57B or 129. RNA has been collected from lungs of both parental and progeny mice and we are useing microarray to generate the gene express profile. The purpose for this study is to find out the genes (either up-regulated or down-regulated) involve in the inhalation of asbestos and provide a guideline to the further study of human inhalation disease.
2007-02-14 | E-TIGR-10 | biostudies-arrayexpress
Project description:Recent in vivo studies reported that inhaled carbon nanotube distribute in the alveolar region resulting in an acute inflammation, progressive fibrotic response and particle accumulation at the bronchoalveolar junction with low clearance. With similar biopersistence and shape as asbestos, a known lung carcinogen, growing concern has arisen for elevated risk of carbon nanotube-induced lung carcinogenesis; however few studies have evaluated long-term human health risks associated with chronic pulmonary carbon nanotube exposures compared to asbestos. To address this knowledge gap, we conducted subchronic in vitro exposures of dispersed single walled carbon nanotube, multi-walled carbon nanotube and crocidolite asbestos to human small airway epithelial cells to assess their neoplastic transformation potential. Subchronic single-, multi-walled carbon nanotube and asbestos exposures caused human lung cell neoplastic transformation exhibited by increased proliferation, anchorage-independent growth, invasion and angiogenesis. Whole genome profiling and protein expression analyses showed that carbon nanotube-induced transformation mechanism(s) was largely different from asbestos-related inflammatory signaling, suggesting specific carbon nanotube-induced carcinogenic potential. This study provides novel carbon nanotube and asbestos toxicogenomic information for risk assessment and an in vitro model to evaluate transformation potential of carbon nanotubes and other nanoparticles.
2013-07-22 | GSE41178 | GEO
Project description:Background: Lung cancer has the highest mortality rate of all the cancers in the world and asbestos-related lung cancer is one of the leading occupational cancers. The identification of the asbestos-related molecular changes has been a topic of major research interest over the years. The aim of the current study was to identify novel asbestos-related molecular correlates by integrating miRNA expression profiling with previously obtained microarray data (aCGH and mRNA expression) from the same patient material. Results: Twelve novel asbestos-related miRNAs (over-expressed: miR-148b, miR-374a, miR-24-1*, Let-7d, Let-7e, miR-199b-5p, miR-331-3p and under-expressed: miR-939, miR-671-5p, miR-605, miR-1224-5p, miR-202) which inversely correlated with target genes (e.g. GADD45A, LTBP1, FOSB, NCALD, CACNA2D2, MTSS1, EPB41L3) were identified. In addition, several known and new lung cancer-associated miRNAs were identified. DNA copy number alterations were also correlated with the deregulation of four miRNAs in lung cancer. The importance of integrated analysis was highlighted by the interesting finding of linking of the over-expression of well known squamous cell carcinoma-associated miR-205 with the down-regulation of the gene DOK4. Conclusions: Novel deregulated miRNAs and inversely correlating expression of target genes associated with lung cancer etiology and histology were identified. In addition, DNA copy number alterations correlated with the deregulation of some of the miRNAs. The results of the current study could have potential diagnostic implications, but require further investigation. Methods: The patient material used in the study consisted of 26 tumour and normal lung tissue from highly asbestos-exposed (13 samples) and non-exposed (13 samples) patients. Control lung tissue samples were obtained from 7 patients without cancer as well as from a commercial lung tissue RNA. Data analysis on miRNA expression and integration of miRNA and mRNA data were performed using Chipster (http://chipster.csc.fi/). In addition, miRNA and aCGH data were integrated in a separate analysis. *** This submission represents the microRNA component of the study
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