Gene expression profiling of asbestos-related lung squamous cell carcinoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Wright Casey
PROVIDER: S-ECPF-GEOD-23822 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
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-related lung cancer accounts for 4-12% of lung cancers worldwide. We have previously identified ADAM28 as a putative oncogene involved in asbestos-related lung adenocarcinoma (ARLC-AC). We hypothesised that similarly gene expression profiling of asbestos-related lung squamous cell carcinomas (ARLC-SCC) may identify candidate oncogenes for ARLC-SCC. We undertook a microarray gene expression study in 56 subjects; 26 ARLC-SCC (defined as lung asbestos body (AB) counts >20AB/gram wet weight (gww) and 30 non-asbestos related lung squamous cell carcinoma (NARLC-SCC; no detectable lung asbestos bodies; 0AB/gww). Microarray and bioinformatics analysis identified six candidate genes differentially expressed between ARLC-SCC and NARLC-SCC based on statistical significance (p<0.001) and fold change (FC) of >2-fold. Two genes MS4A1 and CARD18, were technically replicated by qRT-PCR and showed consistent directional changes. As we also found MS4A1 to be overexpressed in ARLC-ACs, we selected this gene for biological validation in independent test sets (one internal, and one external dataset (2 primary tumor sets)). MS4A1 RNA expression dysregulation was validated in the external dataset but not in our internal dataset, likely due to the small sample size in the test set as immunohistochemical (IHC) staining for MS4A1 (CD20) showed that protein expression localized predominantly to stromal lymphocytes rather than tumor cells in ARLC-SCC. We conclude that differential expression of MS4A1 in this comparative gene expression study of ARLC-SCC versus NARLC-SCC is a stromal signal of uncertain significance, and an example of the rationale for tumor cell enrichment in preparation for gene expression studies where the aim is to identify markers of particular tumor phenotypes. Finally, our study failed to identify any strong gene candidates whose expression serves as a marker of asbestos etiology. Future research is required to determine the role of stromal lymphocyte MS4A1 dysregulation in pulmonary SCCs caused by asbestos.
| S-EPMC3325913 | biostudies-literature
Project description:Lung squamous cell carcinoma gene expression (LSCC) is highly variable. This study discovered and validated LSCC gene expression subtypes. RNA from tumors and a common reference were hybridized to Agilent two color microarrays
| S-ECPF-GEOD-17710 | biostudies-other
Project description:Gene Expression Profiling of Oral Squamous Cell Carcinoma (OSCC) was performed to delineate candidate genes clusters with potential to distinguish normal and tumor tissue from oral cavity. All tissue samples were collected after obtaining written informed consent. The RNA profile of 27 OSCC patients was compared with 4 independent controls and 1 pooled control oral cavity tissue from healthy donors. Agilent one-color experiment, Organism: Human, Agilent-014850 Whole Human Genome Microarray 4x44K G4112F
| S-ECPF-GEOD-23558 | biostudies-other
Project description:Oral squamous cell carcinoma (OSCC) is a solid neoplasm exhibiting aggressive tumor phenotypes with unpredictable biological behavior and usually a very unfavorable prognosis. The comprehension of the molecular basis of the variability within this cancer disease should lead to the development of satisfactory targeted therapies as well as to improvements in diagnosis specificity and sensitivity. Due to the lack of definite molecular concepts in OSCC, this study aimed to detail molecular characteristics possibly reflecting differences in tumor progression mechanisms through genome-wide gene expression profiles. Keywords: disease-state analysis Nine tumor samples differing in their TNM classification and their respective surgical margins were used in this study. They were obtained from individual patients during tongue and floor of the mouth tumor resection surgery. Microarray experiments were carried out using the microarray platform CodeLink (GE Healthcare). This platform utilizes bioarrays consisting of 30-base, single pre-validated oligonucleotide probe per gene target. CodeLink Whole-Genome bioarrays, containing 55,000 human transcripts, were used for all experiments. Hybridization procedures strictly followed protocols provided by the manufacturer (GE Healthcare). A total of 11 arrays were hybridized in this study. Arrays were scanned following the recommended scanning procedure and settings for use with CodeLink bioarrays (GE Healthcare) on GenePix 4000B Array Scanner/GenePix Pro 4.0 software (Axon Instruments).
| S-ECPF-GEOD-9792 | biostudies-other
Project description:OSCC is associated with substantial mortality and morbidity. To identify potential biomarkers for the early detection of invasive OSCC, we compared the gene expressions of OSCC, oral dysplasia, and normal oral tissue from patients without oral cancer or preneoplastic oral lesions (controls). Results provided models of gene expression to distinguish OSCC from controls. RNA from 167 OSCC, 17 dysplasia and 45 normal oral tissues were extracted and hybridized to Affymetrix U133 2.0 Plus GeneChip arrays. The differentially expressed genes were identified using GenePlus software and the validation was done using RT-PCR, using independent internal and external datasets.
| S-ECPF-GEOD-30784 | biostudies-other
Project description:According to epidemiological studies, a vast majority, approximately 80%~90% of male OSCC patients in Taiwan habitually drink alcohol (A), and chew betel quid (B), and use cigarette (C). To assess the impact of these dietary factors on the transcriptom, we conduct a high-throughput screen survey in an oral cancer cohort with exposure of A, B, and C. Results indicate several potential oncogenes and tumor suppressor genes are dysregulated in OSCC patients with ABC risk factors. Total RNA was collected from tumor and non-tumor pair-wise samples. These biopsies were obtained from 40 male OSCC patients who regularly drink alcohol, chew areca nut and smoking.
| S-ECPF-GEOD-37991 | biostudies-other
Project description:BackgroundLung cancer remains to be the leading cause of cancer death worldwide. Patients with similar lung cancer may experience quite different clinical outcomes. Reliable molecular prognostic markers are needed to characterize the disparity. In order to identify the genes responsible for the aggressiveness of squamous cell carcinoma of the lung, we applied DNA microarray technology to a case control study. Fifteen patients with surgically treated stage I squamous cell lung cancer were selected. Ten were one-to-one matched on tumour size and grade, age, gender, and smoking status; five died of lung cancer recurrence within 24 months (high-aggressive group), and five survived more than 54 months after surgery (low-aggressive group). Five additional tissues were included as test samples. Unsupervised and supervised approaches were used to explore the relationship among samples and identify differentially expressed genes. We also evaluated the gene markers' accuracy in segregating samples to their respective group. Functional gene networks for the significant genes were retrieved, and their association with survival was tested.ResultsUnsupervised clustering did not group tumours based on survival experience. At p < 0.05, 294 and 246 differentially expressed genes for matched and unmatched analysis respectively were identified between the low and high aggressive groups. Linear discriminant analysis was performed on all samples using the 27 top unique genes, and the results showed an overall accuracy rate of 80%. Tests on the association of 24 gene networks with study outcome showed that 7 were highly correlated with the survival time of the lung cancer patients.ConclusionThe overall gene expression pattern between the high and low aggressive squamous cell carcinomas of the lung did not differ significantly with the control of confounding factors. A small subset of genes or genes in specific pathways may be responsible for the aggressive nature of a tumour and could potentially serve as panels of prognostic markers for stage I squamous cell lung cancer.
| S-EPMC544571 | biostudies-literature
Project description:Asbestos-related lung carcinoma is one of the most devastating occupational cancers, and effective techniques for early diagnosis are still lacking. In the present study, a systematic approach was applied to detect a potential biomarker for asbestos-related lung cancer (ARLC); in particular asbestos-related squamous cell carcinoma (ARLC-SCC). Microarray data (GSE23822) were retrieved from the Gene Expression Omnibus database, including 26 ARLC-SCCs and 30 non-asbestos-related squamous cell lung carcinomas (NARLC-SCCs). Differentially expressed genes (DEGs) were identified by the limma package, and then a protein-protein interaction (PPI) network was constructed according to the BioGRID and HPRD databases. A novel scoring approach integrating an expression deviation score and network degree of the gene was then proposed to weight the DEGs. Subsequently, the important genes were uploaded to DAVID for pathway enrichment analysis. Pathway correlation analysis was carried out using Spearman's rank correlation coefficient of the pathscore. In total, 1,333 DEGs, 391 upregulated and 942 downregulated, were obtained between the ARLC-SCCs and NARLC-SCCs. A total of 524 important genes for ARLC-SCC were significantly enriched in 22 KEGG pathways. Correlation analysis of these pathways showed that the pathway of SNARE interactions in vesicular transport was significantly correlated with 12 other pathways. Additionally, obvious correlations were found between multiple pathways by sharing cross-talk genes (EGFR, PRKX, PDGFB, PIK3R3, SLK, IGF1, CDC42 and PRKCA). On the whole, our data demonstrate that 8 cross-talk genes were found to bridge multiple ARLC-SCC-specific pathways, which may be used as candidate biomarkers and potential multi-effect targets. As these genes are involved in multiple pathways, it is possible that drugs targeting these genes may thus be able to influence multiple pathways simultaneously.
| S-EPMC5360351 | biostudies-literature