RNA-sequencing of non-small cell lung cancer tissue samples
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ABSTRACT:
PROVIDER: PRJNA1148665 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Using paired tumor and non-tumor lung tissues from 47 individuals we identified common changes in DNA methylation associated with the development of non-small cell lung cancer. Pathologically normal lung tissue taken at the time of cancer resection was matched to tumorous lung tissue and together were probed for methylation status using Illumina GoldenGate arrays. For each matched pair the change in methylation at each CpG was calculated (the odds ratio), and these ratios were averaged across individuals and ranked by magnitude to identify the CpGM-bM-^@M-^Ys with the greatest change in methylation associated with tumor development. Using paired tumor and non-tumor lung tissues from 47 individuals we identified common changes in DNA methylation associated with the development of non-small cell lung cancer. Pathologically normal lung tissue taken at the time of cancer resection was matched to tumorous lung tissue and together were probed for methylation status using Illumina GoldenGate arrays. For each matched pair the change in methylation at each CpG was calculated (the odds ratio), and these ratios were averaged across individuals and ranked by magnitude to identify the CpGM-bM-^@M-^Ys with the greatest change in methylation associated with tumor development.
2012-07-02 | E-GEOD-27902 | biostudies-arrayexpress
Project description:Lung tumors, as well as normal tumor-adjacent (NTA) tissue of non-small cell lung cancer (NSCLC) patients, were collected and subjected label-free quantitation shotgun proteomics in data-independent mode to identify differences between the tumors and adjacent tissue. By employing in-depth proteomics, we identified several pathways that are up- or downregulated in the tumors of non-small cell lung cancer patients.
2023-11-27 | PXD046998 | Pride
Project description:Using paired tumor and non-tumor lung tissues from 47 individuals we identified common changes in DNA methylation associated with the development of non-small cell lung cancer. Pathologically normal lung tissue taken at the time of cancer resection was matched to tumorous lung tissue and together were probed for methylation status using Illumina GoldenGate arrays. For each matched pair the change in methylation at each CpG was calculated (the odds ratio), and these ratios were averaged across individuals and ranked by magnitude to identify the CpG’s with the greatest change in methylation associated with tumor development.
2012-07-03 | GSE27902 | GEO
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
Project description:Tissue and exosomal miRNA editing in Non-Small Cell Lung Cancer
| PRJNA472351 | ENA
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 (NSCLC) 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, an initial set of 30 pairs of macroscopic tumor and non-tumor samples (10 pairs squamous-cell carcinoma, 18 pairs adenocarcinoma, 2 pairs adeno-squamous carcinoma) and 2 unpaired samples was selected for bulk/macro sampling. Of these 30 pairs and 2 unpaired samples, 17 pairs and 9 unpaired samples were reanalyzed using laser capture microdissection (LCM) for sampling the cells (7 pairs squamous and 1 unpaired sample, 9 pairs adenocarcinomas and 7 unpaired samples, 1 pair adeno-squamous carcinoma and 1 unpaired sample). 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. In order to validate Nugen amplification bias of WT-Ovation One-Direct amplification system, the total RNA samples of 10 pairs of macroscopic tumor and non-tumor samples were amplified with this amplification system, and their cDNA was used to microarray.
2011-08-26 | GSE31552 | GEO
Project description:Lung cancer is the deadliest cancer worldwide. In this study, we obtained RNA-sequencing data from 61 lung cancer samples. We hope that this data can improve the understanding of this disease.
2024-09-12 | GSE274975 | GEO
Project description:Microarray gene expression analysis of genes that showed a gene copy number difference in non small cell lung cancer samples. Only data for a subset of the genes on the array chip are shown here.
2008-05-11 | E-TABM-270 | biostudies-arrayexpress
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