Expression data regulated by hMOF in non-small cell lung cancer (NSCLC) cell lines
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Zhao Lei
PROVIDER: S-ECPF-GEOD-40424 | biostudies-other |
REPOSITORIES: biostudies-other
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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:A549 and H1299 cell lines were transfected with hMOF specific siRNA or control siRNA, and Affymetrix oligonucleotide microarray was conducted to systematically determine downstream targets regulated by hMOF.
2012-08-29 | GSE40424 | GEO
Project description:A549 and H1299 cell lines were transfected with hMOF specific siRNA or control siRNA, and Affymetrix oligonucleotide microarray was conducted to systematically determine downstream targets regulated by hMOF. Two NSCLC cell lines (four samples) transfected with hMOF specific siRNA or control siRNA
2012-08-29 | E-GEOD-40424 | biostudies-arrayexpress
Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. Currently, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer which account for 20% and 80% of lung carcinomas, respectively. NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack of neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. The methods used for sample selection and processing can have a strong influence on the expression values obtained through microarray profiling. Laser capture microdissection (LCM) provides higher specificity in the selection of target cells compared to traditional bulk tissue selection methods, but at an increased processing cost. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples. In this study, a set of 31 pairs and one non-paired sample of macroscopic tumor and non-tumor samples (10 pairs and 1 non-paired sample squamous-cell carcinoma, 19 pairs and one non-paired samples adenocarcinoma, 2 pairs adeno-squamous-cell carcinoma) was selected for bulk/macro sampling. Of these 31 pairs and 2 non-paired samples, 16 pairs plus 15 non paired samples were reanalyzed using laser capture microdissection (LCM) for sampling the cells (7 pairs and 3 non-paired samples squamous-cell carcinoma, 8 pairs and 11 non-paired samples adeno carcinomas, 1 pair and 1 non paired sample Adeno-squamous-cell carcinoma). For macroscopic samples, 50 to 80 µg of tissue was used to isolate total RNA. Gene expression profile was determined using Affymetrix Human Genome Gene 1.0 ST genechip. For the LCM samples, from representative slides histologically confirmed and mapped by a pathologist, approximately 1000 cells/sample were collected by LCM;. cDNA was amplified using Nugen WT-Ovation One-Direct amplification system. Here we describe the use of an expression microarray study on NSCLC samples and surrounding tissue, comparing macroscopic lung tumor and tissue samples (“grind and bind”), versus tumor and alveolar compartment cells laser capture microdissected (LCM) from the same macroscopic lung samples.
| S-ECPF-GEOD-31552 | biostudies-other
Project description:Snail is a zinc-finger transcription factor best known for its ability to down-regulate E-cadherin. Its established significance in embryology and organogenesis has been expanded to include a role in the tumor progression of a number of human cancers. In addition to E-cadherin, it has more recently been associated with the down-regulation and up-regulation of a number of other genes that affect important malignant phenotypes. After establishing the presence of up-regulated Snail in human non-small cell lung cancer specimens, we used microarrays to detail the global programme of gene expression in non-small cell lung cancer cell lines stably transduced to over-express Snail as compared to vector control cell lines. Non-small cell lung cancer cell lines (H441, H292, H1437) were stably transduced with a retroviral vector to over-express Snail. Elevated Snail and a corresponding down-regulation of E-cadherin was verified in the Snail over-expressing cell lines as compared to vector control cell lines by Western analysis. RNA extraction was performed and samples submitted to the UCLA Clinical Microarray Core for hybridization to Affymetrix arrays.
| S-ECPF-GEOD-16194 | biostudies-other
Project description:Azacitidine (AZA) and decitabine (DAC) are cytidine azanucleoside analogs with clinical activity in myelodysplastic syndromes (MDS) and potential activity in solid tumors. To better understand the mechanism of action of these drugs, we examined the effects of AZA and DAC in a panel of non-small cell lung cancer (NSCLC) cell lines. Of 5 NSCLC lines tested in a cell viability assay, all were sensitive to AZA (EC50 of 1.8–10.5 µM), while only H1299 cells were equally sensitive to DAC (EC50 of 5.1 µM). In the relatively DAC-insensitive cell line A549, both AZA and DAC caused DNA methyltransferase I depletion and DNA hypomethylation; however, only AZA significantly induced markers of DNA damage and apoptosis, suggesting that mechanisms in addition to, or other than, DNA hypomethylation are important for AZA-induced cell death. Cell cycle analysis indicated that AZA induced an accumulation of cells in sub-G1 phase, whereas DAC mainly caused an increase of cells in G2/M. Gene expression analysis of AZA- and DAC-treated cells revealed strikingly different profiles, with many genes distinctly regulated by each drug. In summary, while both AZA and DAC caused DNA hypomethylation, distinct effects were demonstrated on regulation of gene expression, cell cycle, DNA damage, and apoptosis. A549 and H1299 cells were treated with a dose range (0.3–3.0 μM) of AZA or DAC for 48 hours, and effects on gene expression were assessed by microarray analysis.
| S-ECPF-GEOD-29077 | biostudies-other
Project description:Purpose Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for individual non-small-cell lung cancer (NSCLC) patients. Most current molecular signatures for lung cancer are prognostic only and provide limited information with regard to the functional importance of the genes selected. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefit of ACT in NSCLC. Experimental Design An 18-hub-gene prognosis signature was developed through a systems biology approach using a large NSCLC dataset from the Director’s Challenge Consortium. The prognostic value of this signature was tested in NSCLC patients from UT Lung SPORE cohort and additional five public datasets. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefit in NSCLC. Results We showed that the 18-hub-gene set can robustly predict the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The refined 12-gene functional set was successfully validated in two independent datasets. The predicted benefit group showed significant improvement in survival after ACT (JBR.10 clinical trial data: hazard ratio=0.36, p=0.038; UT Lung SPORE data: hazard ratio=0.34, p=0.017), while the predicted non-benefit group showed no survival improvement. Conclusions This is the first study to integrate genetic aberration, genome-wide RNAi functional data, and mRNA expression data to identify a functional gene set that is predictive for ACT benefits. This 12-gene predictive signature has been validated in two independent NSCLC cohorts. Patients were eligible to enter the study if they underwent curative resection for NSCLC at MD Anderson Cancer Center between December 1996 and June 2007, and patients with radiation therapy were excluded from the study. All tissue samples were obtained by surgical resection from patients who had provided written informed consent. Tissues were stored at −140°C after being snap frozen in liquid nitrogen. Serial sectioning of each sample was used to histologically evaluate tumor and malignant cells content before RNA extraction. The primary tumor tissues from 176 patients were selected randomly from similar samples in the UT Lung SPORE tumor collection based on stringent, predefined quality control procedures before any data analysis, including the presence of ≥70% tumor tissue and ≥50% malignant cells in the frozen tissue used for RNA extraction. In this cohort, 133 patients are adenocarcinomas (ADCs) and 43 patients are squamous cell carcinomas (SCCs); 49 patients received ACT (mainly Carboplatin plus Taxanes) and 127 patients did not receive ACT.
| S-ECPF-GEOD-42127 | biostudies-other
Project description:BackgroundP2X7, a purinergic receptor, plays important roles in inflammatory diseases, but recently its expression has been found in several tumors, suggesting a potential role as a cancer cell biomarker. Moreover, the relative amount of P2X7 varies among human individuals due to numerous single nucleotide polymorphisms resulting in either a loss- or gain-of-function; the P2X7 gene is highly polymorphic, and polymorphisms in the promoter or coding region may modify its expression or function. A polymorphism in exon 13 of the P2X7 receptor gene at the +1513 position (Glu496Ala substitution, corresponding to SNP rs3751143) has been shown to eradicate the function of this receptor and has been correlated with histological variants and clinical parameters in thyroid cancer. Until now, no data regarding P2X7 expression and polymorphisms in lung cancer have been published; based on these premises, we decided to evaluate the impact of the P2X7 expression and polymorphisms in ninety-seven cases of non-small cell lung cancer (NSCLC).ResultsNo significant difference in the genotype frequency of the A1513C polymorphism was found between the two histological variants of NSCLC, adenocarcinoma and squamous cell carcinoma, and no statistically significant associations were observed between P2X7 protein expression and the main clinico-pathological characteristics of the NSCLC patients.ConclusionsBased on our results, P2X7 expression and polymorphisms seem to have no potential impact in patients with non-small cell lung cancer; however, further studies will surely provide deeper insights regarding the role of this receptor at the clinical level in NSCLC.
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Project description:Expression of the TUSC2 tumor-suppressor gene in TUSC2-deficient NSCLC cells decreased PD-L1 expression and inhibited mTOR activity. Overexpressing TUSC2 or treatment with rapamycin resulted in similar inhibition of PD-L1 expression. Both TUSC2 and rapamycin decreased p70 and SK6 phosphorylation, suggesting that TUSC2 and rapamycin share the same mTOR target. Microarray mRNA expression analysis using TUSC2-inducible H1299 showed that genes that negatively regulate the mTOR pathway were significantly upregulated by TUSC2 compared with control. The presence of IFN-γ significantly increased PD-L1 expression in lung cancer cell lines, but overexpressing TUSC2 in these cell lines prevented PD-L1 from increasing in the presence of IFN-γ. Taken together, these findings show that TUSC2 can decrease PD-L1 expression in lung cancer cells. This ability to modify the tumor microenvironment suggests that TUSC2 could be added to checkpoint inhibitors to improve the treatment of lung cancer.
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Project description:Differences in gene expression profiles regarding the expression of genes encoding for proteins with G protein-coupled receptor (GPCR) activity between SCLC and NSCLC and normal lung samples was successfully examined. In the present study, 8 SCLC, 16 NSCLC and 14 normal lung RNA samples (human) had been purchased from OriGene Technologies. Gene expression analysis was performed using Affymetrix microarrays (Human Exon 1.0 ST Array).
| S-ECPF-GEOD-40275 | biostudies-other