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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

2009-04-15 | E-GEOD-14925 | biostudies-arrayexpress

Gene expression profiling of the effects of organic dust in lung epithelial and THP-1 cells reveals inductive effects on inflammatory mediators [452 expt: THP-1 vs BEAS 2B]

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.

2015-09-16 | GSE73062 | GEO

Gene expression profiling of the effects of organic dust in lung epithelial and THP-1 cells reveals inductive effects on inflammatory mediators [391 expt: A549 vs BEAS 2B]

2015-09-16 | GSE73061 | GEO

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.

2019-01-01 | GSE108082 | GEO

miRNA sequence analysis of drug-resistant small cell lung cancer

Project description:We obtained small cell lung cancer specimens and normal lung specimens from patients who died of drug-resistant SCLC. The small lung cancer specimens include primary lesions and metastatic lesions. Next generation sequencing was performed to assess the expression of miRNA in drug-resistant small cell lung cancer.

2021-06-05 | GSE176198 | GEO

Gene expression profiling of the effects of organic dust in lung epithelial and THP-1 cells reveals inductive effects on inflammatory mediators [391 expt: A549 vs BEAS 2B]

2015-09-16 | E-GEOD-73061 | biostudies-arrayexpress

Gene expression profiling of the effects of organic dust in lung epithelial and THP-1 cells reveals inductive effects on inflammatory mediators [452 expt: THP-1 vs BEAS 2B]

2015-09-16 | E-GEOD-73062 | biostudies-arrayexpress

Transcription profiling of human cohort of lymph node-negative breast cancer patients identifies a six-gene signature predicting breast cancer lung metastasis

Project description:The lungs are a frequent target of metastatic breast cancer cells, but the underlying molecular mechanisms are unclear. All existing data were obtained either using statistical association between gene expression measurements found in primary tumors and clinical outcome, or using experimentally derived signatures from mouse tumor models. Here, we describe a distinct approach that consists to utilize tissue surgically resected from lung metastatic lesions and compare their gene expression profiles with those from non-pulmonary sites, all coming from breast cancer patients. We demonstrate that the gene expression profiles of organ-specific metastatic lesions can be used to predict lung metastasis in breast cancer. We identified a set of 21 lung metastasis-associated genes. Using a cohort of 72 lymph node-negative breast cancer patients, we developed a six-gene prognostic classifier that discriminated breast primary cancers with a significantly higher risk of lung metastasis. We then validated the predictive ability of the six-gene signature in 3 independent cohorts of breast cancers consisting of a total of 721 patients. Finally, we demonstrated that the signature improves risk stratification independently of known standard clinical parameters and a previously established lung metastasis signature based on an experimental breast cancer metastasis model. Experiment Overall Design: We used microarrays to identify lung metastasis-related genes in a series of 23 patients with breast cancer metastases. No replicate, no reference sample.

2009-03-07 | E-GEOD-11078 | biostudies-arrayexpress

Single cell RNA sequencing analysis of freshly resected non-small cell lung carcinoma (NSCLC) tissues

Project description:Lung cancer is the leading cause of cancer-related deaths world-wide. ~85% of lung carcinomas are non–small cell lung carcinoma (NSCLC). Tumor cell heterogeneity is very poorly defined. However, it is known to be important for tumor response to cancer therapy and cancer agressivenes. We subjected three NSCLC tumors resected from different patients to Drop-seq in order to 1) elucidate the capability of scRNA-seq analysis in identifying different tumor cell populations; and 2) ascertain the clinical value of the genes which distinguish cancer cells from other cells in the tissue. As anticipated, the tissue composition of independently collected samples varied. Despite deficient populations in some samples, both donor and patient samples contributed to the majority of cell populations. However, cancer cells were all patient-specific. These findings emphasize the utility of single cell gene expression data in identification of tumor cell populations. The collected data might be further used for predicting of drugs specific to the biology of activated pathways and patient outcome.

2020-12-19 | GSE148466 | GEO

DNA copy number alterations in endobronchial squamous metaplastic lesions predict lung cancer

Project description:BACKGROUND Autofluorescence bronchoscopy (AFB) is a valid strategy for detecting premalignant endobronchial lesions. However, no biomarker can reliably predict lung cancer risk of subjects with AFB-visualized premalignant lesions. Our present study was set out to identify AFB-visualized squamous metaplastic lesions with malignant potential by DNA copy number profiling. METHODS Regular AFB-examinations in 474 subjects at risk of lung cancer identified 6 subjects with SqM lesions at baseline and carcinoma (in situ) at the initial SqM site at follow-up bronchoscopy. These progressive SqM lesions were compared for immunostaining pattern and arrayCGH-based chromosomal profiles to 23 SqM of subjects who remained cancer-free. Specific copy number alterations (CNAs) linked to cancer risk were identified and accuracy of CNAs to predict endobronchial cancer in this series was determined. RESULTS At baseline, p53, p63 and Ki-67 immunostaining were not predictive for a differential clinical outcome of SqM lesions. The mean number of CNAs in baseline SqM of cases was significantly higher compared to controls (p<0.01). Chromosomal regions significantly more frequently altered in SqM of cases were 3p26.3-p11.1, 3q26.2-q29, 9p13.3-p13.2, and 17p13.3-p11.2 (FWER<0.10). CNAs were specifically detected at the site of future cancer. In cases, baseline-detected CNAs persisted in subsequent biopsies taken from the initial site, and levels increased towards cancer progression. CNAs at 3p26.3-p11.1, 3q26.2-29, and 6p25.3-24.3, predicted cancer risk for AFB-visualized SqM with 97% accuracy. CONCLUSION Our data strongly suggest that the presence of specific DNA copy number alterations in endobronchial SqM lesions predict endobronchial cancer.

2011-08-02 | GSE23644 | GEO

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