CaArray_landi-00077: EAGLE Project
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Mervi Heiskanen
PROVIDER: E-GEOD-75324 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:We have generated a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, we analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct subclasses of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients. meyer-00191 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG_U95Av2 Organism: Homo sapiens (ncbitax) Material Types: total RNA, synthetic_RNA, organism_part, whole_organism Disease States: lung cancer, Normal
2016-06-11 | E-GEOD-83227 | biostudies-arrayexpress
Project description:TCGA Analysis of RNA Expression for Non Small Cell Lung Cancer, Squamous Cell Carcinoma Using Affymetrix HT_HG-U133A EXP-592 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HT_HG-U133A Organism: Homo sapiens (ncbitax) Tissue Sites: Lung Material Types: organism_part, Primary solid_tumor Disease States: Lung Squamous Cell Carcinoma, NOT SPECIFIED
2015-05-13 | E-GEOD-68793 | biostudies-arrayexpress
Project description:Histopathology is insufficient to predict disease progression and clinical outcome in lung adenocarcinoma. Here we show that gene-expression profiles based on microarray analysis can be used to predict patient survival in early-stage lung adenocarcinomas. Genes most related to survival were identified with univariate Cox analysis. Using either two equivalent but independent training and testing sets, or 'leave-one-out' cross-validation analysis with all tumors, a risk index based on the top 50 genes identified low-risk and high-risk stage I lung adenocarcinomas, which differed significantly with respect to survival. This risk index was then validated using an independent sample of lung adenocarcinomas that predicted high- and low-risk groups. This index included genes not previously associated with survival. The identification of a set of genes that predict survival in early-stage lung adenocarcinoma allows delineation of a high-risk group that may benefit from adjuvant therapy. beer-00153 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Disease States: lung cancer, normal
2015-05-06 | E-GEOD-68571 | biostudies-arrayexpress
Project description:Tumors from 5-6 month old KrasLA mice were dissected. Gene expression analysis on U74A affy chips. 19 normal lungs from age matched controls were also includeed **NOTE: Migrated from caArray 1.x, identifier='gov.nih.nci.ncicb.caarray:Experiment:1015897590231167:1' jacks-00113 Assay Type: Gene Expression Provider: Affymetrix Array Designs: mg_u74av2 Organism: Mus musculus (ncbitax) Tissue Sites: Lung Material Types: synthetic_DNA, synthetic_RNA, organism_part Disease States: normal lung, lung cancer
2015-06-26 | E-GEOD-70271 | biostudies-arrayexpress
Project description:Here we report a large, training*testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. jacob-00182 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A Organism: Homo sapiens (ncbitax) Material Types: cell, synthetic_RNA, organism_part, whole_organism, total_RNA Disease States: Lung Adenocarcinoma
2015-05-02 | E-GEOD-68465 | biostudies-arrayexpress
Project description:Gene Expression Analysis of TCGA samples using Agilent Expression 244K microarrays. EXP-576 Assay Type: Gene Expression Provider: Agilent Array Designs: AgilentG4502A_07_3 Organism: Homo sapiens (ncbitax) Tissue Sites: Lung Material Types: Control Analyte, organism_part, Primary solid_tumor, genomic_DNA Disease States: Lung Adenocarcinoma, NOT SPECIFIED
2015-05-13 | E-GEOD-68787 | biostudies-arrayexpress
Project description:TCGA Analysis of DNA Methylation for LUSC using Illumina Infinium HumanMethylation450 platform EXP-598 Assay Type: Methylation Provider: Illumina Array Designs: jhu-usc.edu_TCGA_HumanMethylation450 Organism: Homo sapiens (ncbitax) Tissue Sites: Lung Material Types: Control Analyte, Solid normal_tissue, organism_part, Primary solid_tumor Disease States: Lung Squamous Cell Carcinoma, NOT SPECIFIED
2015-05-14 | E-GEOD-68825 | biostudies-arrayexpress
Project description:A key step in bringing gene expression data into clinical practice is the conduct of large studies to confirm preliminary models. The performance of such confirmatory studies and the transition to clinical practice requires that microarray data from different laboratories are comparable and reproducible. We designed a study to assess the comparability of data from four laboratories that will conduct a larger microarray profiling confirmation project in lung adenocarcinomas. To test the feasibility of combining data across laboratories, frozen tumor tissues, cell line pellets, and purified RNA samples were analyzed at each of the four laboratories. Samples of each type and several subsamples from each tumor and each cell line were blinded before being distributed. The laboratories followed a common protocol for all steps of tissue processing, RNA extraction, and microarray analysis using Affymetrix Human Genome U133A arrays. High within-laboratory and between-laboratory correlations were observed on the purified RNA samples, the cell lines, and the frozen tumor tissues. Intraclass correlation within laboratories was only slightly stronger than between laboratories, and the intraclass correlation tended to be weakest for genes expressed at low levels and showing small variation. Finally, hierarchical cluster analysis revealed that the repeated samples clustered together regardless of the laboratory in which the experiments were done. The findings indicate that under properly controlled conditions it is feasible to perform complete tumor microarray analysis, from tissue processing to hybridization and scanning, at multiple independent laboratories for a single study. dobbi-00100 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133A Organism: Homo sapiens (ncbitax) Tissue Sites: Kidney, Lung, Stomach, Uterus, Liver, Lymphoid tissue, Ovary, Skin, Adrenal Gland, Lymph_Node Material Types: cell, nuclear_RNA, synthetic_RNA, organism_part, total_RNA Disease States: Recurrent Renal Cell Carcinoma, Squamous Cell Carcinoma,Conventional_Clear_Cell_Renal_Cell_Carcinoma,Gastrointestinal_Stromal_Tumor, Lung_Adenocarcinoma, Leiomyoma, Non neoplastic liver with cirrosis, Stomach Adenocarcinoma, Large Cell Lymphoma, Ovarian Adenocarcinoma, Melanoma, Malignant G1 Stromal Tumor, Adrenal Cortical Adenoma, Metastatic Renal Cell Carcinoma, Malignant Melanoma
2015-05-07 | E-GEOD-68606 | biostudies-arrayexpress
Project description:In an effort to develop a genomics-based approach to the prediction of drug response, we have developed an algorithm for classification of cell line chemosensitivity based on gene expression profiles alone. Using oligonucleotide microarrays, the expression levels of 6,817 genes were measured in a panel of 60 human cancer cell lines (the NCI-60) for which the chemosensitivity profiles of thousands of chemical compounds have been determined. We sought to determine whether the gene expression signatures of untreated cells were sufficient for the prediction of chemosensitivity. Gene expression-based classifiers of sensitivity or resistance for 232 compounds were generated and then evaluated on independent sets of data. The classifiers were designed to be independent of the cells' tissue of origin. The accuracy of chemosensitivity prediction was considerably better than would be expected by chance. Eighty-eight of 232 expression-based classifiers performed accurately (with P < 0.05) on an independent test set, whereas only 12 of the 232 would be expected to do so by chance. These results suggest that at least for a subset of compounds genomic approaches to chemosensitivity prediction are feasible. golub-00299 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu6800 Organism: Homo sapiens (ncbitax) Tissue Sites: Kidney, Brain, Blood, Lung, Skin, Colon, Breast, Prostate, Ovary Material Types: cell, synthetic_RNA, whole_organism, total_RNA Disease States: Carcinoma, Glioblastoma, Lymphoma, Adenocarcinoma, Melanoma, Amelanotic Melanoma, Large Cell Carcinoma, Precursor Lymphoblastic Leukemia, Carcinosarcoma, Myeloid Leukemia, Plasma Cell Myeloma, Bronchogenic Carcinoma, Chronic Myelogenous Leukemia, Squamous Cell Carcinoma
2015-05-16 | E-GEOD-68936 | biostudies-arrayexpress
Project description:The optimal treatment of patients with cancer depends on establishing accurate diagnoses by using a complex combination of clinical and histopathological data. In some instances, this task is difficult or impossible because of atypical clinical presentation or histopathology. To determine whether the diagnosis of multiple common adult malignancies could be achieved purely by molecular classification, we subjected 218 tumor samples, spanning 14 common tumor types, and 90 normal tissue samples to oligonucleotide microarray gene expression analysis. The expression levels of 16,063 genes and expressed sequence tags were used to evaluate the accuracy of a multiclass classifier based on a support vector machine algorithm. Overall classification accuracy was 78%, far exceeding the accuracy of random classification (9%). Poorly differentiated cancers resulted in low-confidence predictions and could not be accurately classified according to their tissue of origin, indicating that they are molecularly distinct entities with dramatically different gene expression patterns compared with their well differentiated counterparts. Taken together, these results demonstrate the feasibility of accurate, multiclass molecular cancer classification and suggest a strategy for future clinical implementation of molecular cancer diagnostics. golub-00236 Assay Type: Gene Expression Provider: Affymetrix Array Designs: Hu35KsubA, Hu6800 Organism: Homo sapiens (ncbitax) Material Types: synthetic_RNA, organism_part, whole_organism, total_RNA Disease States: Colorectal Adenocarcinoma, Melanoma, Normal, pancreatic adenocarcinoma, Acute Myeloid Leukemia, Breast Adenocarcinoma, T-cell ALL, Lung Adenocarcinoma, bladder transitional cell carcinoma, Ovarian Adenocarcinoma, Mesothelioma, B-cell ALL, prostate adenocarcinoma, Medulloblastoma, Follicular Lymphoma, renal cell carcinoma, uterine adenocarcinoma, large B-cell lymphoma, Glioblastoma, bladder transitonal cell carcinoma
2015-05-16 | E-GEOD-68928 | biostudies-arrayexpress