Ontology highlight
ABSTRACT:
PROVIDER: PRJNA219307 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Efficient identification of microRNAs for classification of tumor origin (II)
| PRJNA219311 | ENA
Project description:Efficient identification of microRNAs for classification of tumor origin (I)
| PRJNA219310 | ENA
Project description:To develop a classifier based on microRNAs for primary tumor site identification of liver core biopsies and to explore the influence of surrounding normal liver tissue on classification. Tissue samples from 333 patients, corresponding to one of the following ten assay classes, were obtained from archives of the pathology department, Copenhagen University Hospital, Rigshospitalet, Denmark: Lung cancer, breast cancer, gastric/cardia cancer, colorectal cancer, bladder cancer, pancreatic cancer, hepatocellular carcinoma, cholangiocarcinoma, squamous cell cancers of different origin, and normal liver tissue
2013-10-19 | E-GEOD-51429 | biostudies-arrayexpress
Project description:To develop a classifier based on microRNAs for primary tumor site identification of liver core biopsies and to explore the influence of surrounding normal liver tissue on classification.
2013-10-19 | GSE51429 | GEO
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: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:Carcinomas of unknown primary origin constitute 3-5% of all newly diagnosed metastatic cancers, of which the primary source is difficult to classify with current histological methods. Effective cancer treatment depends on early and accurate identification of the tumor, which is why patients with metastases of unknown origin have poor prognosis and short survival. Because microRNA expression is highly tissue specific, the microRNA profile of a metastasis may be used to identify its origin. As a first step to realize this goal, we evaluated the potential of microRNA profiling for identification of the primary tumor of known metastases. 208 formalin-fixed paraffin-embedded samples representing 15 different histologies were profiled on an LNA-enhanced microarray platform, which allows for highly sensitive and specific detection of microRNA. Based on these data, we developed and cross-validated a novel classification algorithm, LASSO (Least Absolute Shrinkage and Selection Operator), which had an overall accuracy of 85%. When the classifier was applied on an independent test set of 48 metastases, the primary site was correctly identified in 42 cases (88% accuracy). Our findings suggest that microRNA expression profiling on paraffin tissue can efficiently predict the primary origin of a tumor, and may provide pathologists with a molecular diagnostic tool that can improve their capability to correctly identify the origin of hitherto unidentifiable metastatic tumors, and eventually, enable tailored therapy. 94 samples
2013-12-01 | E-GEOD-50890 | biostudies-arrayexpress
Project description:microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrate that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors. Global transcriptomics, proteomics and target prediction resulted in the identification of several tumor suppressors involved in the G1/S transition as targets of AAGUGC-microRNAs. The clinical implications of our findings were evaluated by analysis of public domain data supporting the link between this microRNA seed-family, their tumor suppressor targets and cancer cell proliferation. In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.
2017-03-31 | MSV000080829 | MassIVE
Project description:Carcinomas of unknown primary origin constitute 3-5% of all newly diagnosed metastatic cancers, of which the primary source is difficult to classify with current histological methods. Effective cancer treatment depends on early and accurate identification of the tumor, which is why patients with metastases of unknown origin have poor prognosis and short survival. Because microRNA expression is highly tissue specific, the microRNA profile of a metastasis may be used to identify its origin. As a first step to realize this goal, we evaluated the potential of microRNA profiling for identification of the primary tumor of known metastases. 208 formalin-fixed paraffin-embedded samples representing 15 different histologies were profiled on an LNA-enhanced microarray platform, which allows for highly sensitive and specific detection of microRNA. Based on these data, we developed and cross-validated a novel classification algorithm, LASSO (Least Absolute Shrinkage and Selection Operator), which had an overall accuracy of 85%. When the classifier was applied on an independent test set of 48 metastases, the primary site was correctly identified in 42 cases (88% accuracy). Our findings suggest that microRNA expression profiling on paraffin tissue can efficiently predict the primary origin of a tumor, and may provide pathologists with a molecular diagnostic tool that can improve their capability to correctly identify the origin of hitherto unidentifiable metastatic tumors, and eventually, enable tailored therapy.
2013-12-01 | GSE50890 | GEO
Project description:microRNA dysregulation is a common feature of cancer cells, but the complex roles of microRNAs in cancer are not fully elucidated. Here we used functional genomics to identify oncogenic microRNAs in non-small cell lung cancer and to evaluate their impact on response to EGFR targeting therapy. Our data demonstrate that microRNAs with an AAGUGC-motif in their seed-sequence increase both cancer cell proliferation and sensitivity to EGFR inhibitors. Global transcriptomics, proteomics and target prediction resulted in the identification of several tumor suppressors involved in the G1/S transition as targets of AAGUGC-microRNAs. The clinical implications of our findings were evaluated by analysis of public domain data supporting the link between this microRNA seed-family, their tumor suppressor targets and cancer cell proliferation. In conclusion we propose that AAGUGC-microRNAs are an integral part of an oncogenic signaling network, and that these findings have potential therapeutic implications, especially in selecting patients for EGFR-targeting therapy.
2016-06-28 | PXD004163 | Pride