Human lung squamous cell carcinoma expression profiling
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Wilkerson MD
PROVIDER: S-ECPF-GEOD-17710 | biostudies-other | 2010 Oct
REPOSITORIES: biostudies-other
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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.
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Project description:Lung squamous cell carcinoma gene expression (LSCC) is highly variable. This study discovered and validated LSCC gene expression subtypes.
2010-08-06 | GSE17710 | GEO
Project description:Emerging evidences demonstrate that circular RNAs (circRNAs) are abnormally expressed in tumors and could serve as prognostic markers for cancers. However, the expression patterns and clinical implications of circRNAs in non-small cell lung cancer (NSCLC) remain obscure. In this study, we profiled circRNA expressions in 10 pairs of lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) after ribosomal RNA-depletion and RNase R digestion to enrich circRNAs. Combining five circRNA computational programs, we found that LUAD and LUSC not only share common expression patterns, but also exhibit distinct circRNA expression signatures. Moreover, the Receiver Operating Characteristic (ROC) curve analysis indicated that hsa_circ_0077837 and hsa_circ_0001821 could serve as potential biomarkers for both LUAD and LUSC, while hsa_circ_0001073 and hsa_circ_0001495 could be diagnostic/subtyping marker for LUAD and LUSC, respectively. Therefore, our findings highlight the important diagnostic potential of circRNAs in NSCLC.
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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
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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).
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Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Experiment Overall Design: The NSCLC patient collective was composed of the histological subtype adenocarcinoma (n=40) and squamous cell carcinoma (n=18). We subjected gene expression profiles of 40 AC and 18 SCC samples into further analysis. Unsupervised hierarchical clustering of all 58 NSCLC tumors using the 500 most variably expressed transcripts revealed two different clusters, which were strongly associated with the histological subtypes AC and SCC of NSCLC. Our result indicated that the major impact on global transcriptional changes was due to the NSCLC histology.
| S-ECPF-GEOD-10245 | 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.
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Project description: Not available
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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
2010-08-06 | E-GEOD-17710 | biostudies-arrayexpress
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