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Expression data from Non small cell lung cancer cell lines

ABSTRACT: Non small cell lung cancer is the leading cause of cancer related mortality in the western world. RNA expression profiles have been demonstrated to be associated with a specific clinical course of the disease. We used microarray analysis to capture the whole transcriptome of a series of lung cancer cell lines to extract RNA profiles associated with specific genomic lesions Keywords: steady state

ORGANISM(S): Homo sapiens

PROVIDER: GSE14925 | GEO | 2009/04/15

SECONDARY ACCESSION(S): PRJNA111915

REPOSITORIES: GEO

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Expression data from Non small cell lung cancer cell lines

Project description:Non small cell lung cancer is the leading cause of cancer related mortality in the western world. RNA expression profiles have been demonstrated to be associated with a specific clinical course of the disease. We used microarray analysis to capture the whole transcriptome of a series of lung cancer cell lines to extract RNA profiles associated with specific genomic lesions Keywords: steady state Lung cancer cell lines were exponentially grown and harvested during this phase of exponential growth

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Project description:The goal of the study was to characterize gene expression profiles of lung epithelial and THP-1 monocytic cells influenzed by exposure to poultry dust extract. Gene expression profiles were determined by DNA microarrayanalysis using Illumina Human HT-12 v4 Expression bead chip, and changes in significantly induced transcripts validated by real time quantitative RT-PCR, ELISA, Western blotting and immunohistochemical staining. Significantly induced genes included IL-8, IL-6, ICAM-1, CCL2, CCL5, TLR4 and PTGS2. Pathway analysis indicated that dust extract treatment induced changes in gene expression influenced functions related to immune and inflammatory responses.

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Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions to determine prognosis II

Project description:Background: Lung carcinoma-in-situ (CIS) lesions are the pre-invasive precursor to lung squamous cell carcinoma. However, only half progress to invasive cancer in three years, while a third spontaneously regress. Whether modern molecular profiling techniques can identify those pre-invasive lesions that will subsequently progress and distinguish them from those that will regress is unknown. Methods: Progressive and regressive CIS lesions were laser-captured and their genome, epigenome and transcriptome interrogated. We analysed 83 progressive lesions, 41 regressive and 33 normal epithelial control samples. DNA methylation and gene expression profiles were further validated using publicly available lung cancer data. Results: Somatic mutation burden was higher in progressive lesions than regressive CIS lesions, across base substitutions, rearrangements, insertions and deletions. Driver mutations were present in both progressive and regressive CIS lesions, but were more numerous in progressive cases. Progressive and regressive CIS lesions had distinct epigenomic and transcriptional profiles, with a strong chromosomal instability signature. Gene expression, methylation and copy number profiles can all predict accurately which CIS lesions will progress to lung cancer. Conclusion: Pre-invasive CIS lesions that will subsequently progress to invasive lung cancer can be distinguished from those that will regress using molecular profiling. Progression is associated with a strong chromosomal instability signature. These findings inform the development of novel therapeutic targets.

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