Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA326434 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:In this study gene expression profiles for 307 cases of advanced bladder cancers were compared to molecular phenotype at the tumor cell level. TUR-B tissue for RNA extraction was macrodissected from the close vicinity of the tissue sampled for immunohistochemistry to ensure high-quality sampling and to minimize the effects of intra-tumor heterogeneity. Despite excellent agreement between gene expression values and IHC-score at the single marker level, broad differences emerge when samples are clustered at the global mRNA versus tumor cell (IHC) levels. Classification at the different levels give different results in a systematic fashion, which implicates that analysis at both levels is required for optimal subtype-classification of bladder cancer.
2017-03-13 | GSE83586 | GEO
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
Project description:Transcriptomic Landscape of Gallbladder Cancer for Molecular Classification and Tumor Microenvironment Characterization
| PRJDB10737 | ENA
Project description:Classification of carcinoma in situ lesions in human bladder cancer
| PRJNA93009 | ENA
Project description:Most epithelial ovarian cancers are thought to arise from different cells in the ovarian or fallopian tube epithelium. We hypothesized that these distinct cells-of-origin may play a role in determining ovarian tumor phenotype and also could inform the molecular classification of ovarian cancer. To test this hypothesis, we developed new methods to isolate and culture paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from multiple donors without cancer and identified a cell-of-origin gene expression signature that distinguished these cell types within the same patient. Application of the OV versus FT cell-of-origin gene signature to gene expression profiles of primary ovarian cancers permitted identification of distinct OV and FT-like subgroups among these cancers. Importantly, the normal FT-like tumor classification correlated with a significantly worse disease-free survival. This work describes a new experimental method for culture of normal human OV and FT epithelial cells from the same patient. These findings provide new evidence that cell-of-origin is an important source of ovarian tumor heterogeneity and the associated differences in tumor phenotype. We analyzed 12 samples from two donor patients and established cultures of both ovarian epithelium and fallopian tube epithelium (hTERT immortalized), each with 3 replicates (different culture passages).
2013-11-25 | E-GEOD-37648 | biostudies-arrayexpress
Project description:Most epithelial ovarian cancers are thought to arise from different cells in the ovarian or fallopian tube epithelium. We hypothesized that these distinct cells-of-origin may play a role in determining ovarian tumor phenotype and also could inform the molecular classification of ovarian cancer. To test this hypothesis, we developed new methods to isolate and culture paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from multiple donors without cancer and identified a cell-of-origin gene expression signature that distinguished these cell types within the same patient. Application of the OV versus FT cell-of-origin gene signature to gene expression profiles of primary ovarian cancers permitted identification of distinct OV and FT-like subgroups among these cancers. Importantly, the normal FT-like tumor classification correlated with a significantly worse disease-free survival. This work describes a new experimental method for culture of normal human OV and FT epithelial cells from the same patient. These findings provide new evidence that cell-of-origin is an important source of ovarian tumor heterogeneity and the associated differences in tumor phenotype.
2013-11-25 | GSE37648 | GEO
Project description:mRNA Expression data from bladder cancer and normal bladder tissue
| PRJNA306651 | ENA
Project description:Bladder tumours used to construct a tumour stage classifier Keywords = bladder cancer, disease stages, classification Keywords: other
2002-12-08 | GSE89 | GEO
Project description:Bladder cancer: analysis of miRNA-mRNA interactions
| PRJNA173681 | ENA