Transcription profiling of human breast tumor subtypes
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Sorlie T
PROVIDER: S-ECPF-SMDB-2227 | biostudies-other | 2003 Jul
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.
| S-ECPF-SMDB-3829 | biostudies-other
Project description:Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.
| S-ECPF-SMDB-3828 | biostudies-other
Project description:Molecular Characterization of Human Breast Tumor Microvessels Experiment Overall Design: LCM & Microarrays
| S-ECPF-GEOD-7413 | biostudies-other
Project description:BfHL's, spor zonder BfNHL's en BfHL4
| S-ECPF-NCMF-30 | biostudies-other
Project description:Gene expression for 47 human breast tumor cases (normalized by GCRMA for global expression analysis)
| S-ECPF-GEOD-3744 | biostudies-other
Project description:Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.
| S-ECPF-SMDB-3830 | biostudies-other
Project description:Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes). We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID) to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.
| S-ECPF-SMDB-3831 | biostudies-other
Project description:Experiments that were used to make the "intrinsic" gene list from.
2005-10-13 | E-SMDB-2227 | biostudies-arrayexpress
Project description:Brain metastasis is one of the most feared complications of cancer and the most common intracranial malignancy in adults. Its underlying mechanisms remain unknown. From breast cancer patients with metastatic disease we isolated cell populations that aggressively colonize the brain. Transcriptomic analysis of these cells yielded overlapping gene sets whose expression is selectively associated with brain metastasis. The expression of seventeen of these genes in primary breast tumors is associated with brain relapse in breast cancer patients. Some of these genes are also associated with metastasis to lung but not to liver, bone or lymph nodes, providing a molecular basis for the long-observed link between brain and lung metastasis. Among the functionally validated brain metastasis genes, the cyclooxigenase COX-2, the EGFR ligand HB-EGF, and the brain-specific 2-6 sialyltransferase ST6GALNAC5 mediate cancer cell passage through the blood-brain barrier. Other brain metastasis genes encode inflammatory factors and brain-specific proteolytic regulators, suggesting a multifaceted program for breast cancer colonization of the brain. Experiment Overall Design: 204 primary tumors from breast cancer patients with known site of relapse were studied, focussing on brain relapse versus other relapse. Identified genes were validated in this cohort.
| S-ECPF-GEOD-12276 | biostudies-other
Project description:To better understand the role of tumor microenvironment in breast cancer progression, we combined laser capture microdissection and microarray analysis to provide a comprehensive catalog of gene expression changes in both tumor and tumor-associated stroma. Experiment Overall Design: We used LCM to isolate the epithelial and stroma compartments separately from each of 14 fresh frozen primary breast cancer biopsies. In the epithelial compartment, we captured normal (N) and malignant (DCIS or IDC or both where available) epithelium from each tissue slide. In the stroma compartment, we captured both normal stroma away from the malignant lesion (NSS) and the DCIS-associated stroma (ISS) and/or IDC-associated stroma (INVS) whenever possible.
| S-ECPF-GEOD-14548 | biostudies-other