Expression data from Human non-small cell lung cancer
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA608646 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Expression data from chemoresistant human non-small cell lung cancer
| PRJNA645529 | ENA
Project description:Expression data from advanced non-small cell lung cancer
| PRJNA611055 | ENA
Project description:RNA profilling of non-small cell lung cancer
| PRJEB27606 | ENA
Project description:We present data of global proteomes for non-small cell lung cancer for squamous cell and adenocarcinoma, and for normal adjacent tissue.
2024-12-17 | PXD054390 | Pride
Project description:Transcriptomic heterogeneity of EGFR-mutant non-small cell lung cancer evolution towards small cell lung cancer
| PRJNA1081397 | ENA
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
Project description:This series contain 36 samples obtained from human lung tissue and includes the following: 7 Adenocarcinoma samples. 16 Squamous cell carcinoma samples. 1 AdenoSquamous sample. 2 Renal Metastasis. 1 Colon metastasis. 7 normal lung tissue adjacent to the tumors. 2 commercial normal lung RNA. Keywords = Lung Keywords = Non Small Cell Lung Cancer Keywords = Adenocarcinoma Keywords = Squamous Cell Carcinoma Keywords = Normal Lung. Keywords: other
2005-07-20 | GSE1987 | GEO
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
2009-04-15 | GSE14925 | GEO
Project description:RNA sequencing of 25 patients with non-small cell lung cancer and their matched normal lung tissue
2020-03-04 | E-MTAB-6957 | 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.
2011-08-25 | E-GEOD-31552 | biostudies-arrayexpress