Transcription profiling of 47 human breast tumor cases
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Richardson AL
PROVIDER: S-ECPF-GEOD-3744 | biostudies-other | 2006 Feb
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Gene expression for 47 human breast tumor cases (normalized by GCRMA for global expression analysis)
2007-06-25 | E-GEOD-3744 | biostudies-arrayexpress
Project description:Molecular Characterization of Human Breast Tumor Microvessels Experiment Overall Design: LCM & Microarrays
| S-ECPF-GEOD-7413 | biostudies-other
Project description:Experiments that were used to make the "intrinsic" gene list from.
| S-ECPF-SMDB-2227 | biostudies-other
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
Project description:Histologically normal breast epithelium and stroma were laser capture microdissected from breast reduction specimens and from specimens of invasive ductal carcinoma. The objective of the study was to compare normal reduction tissues to tissues adjacent to I.D.C. to determine whether adjacent normal tissues contained expression profiles correlated with characteristics of the primary tumor and to identify markers of normal epithelium and stroma. Experiment Overall Design: common reference design. 66 samples replicated twice as dye swaps generating 132 arrays.
| S-ECPF-GEOD-4823 | biostudies-other
Project description:Histological grading of breast cancer defines morphological subtypes informative of metastatic potential, although not without considerable inter-observer disagreement and clinical heterogeneity particularly among the moderately differentiated grade II (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade I (G1) and grade III (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with moderately differentiated disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable to that of lymph node status and tumor size. When incorporated into the Nottingham Prognostic Index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low and high grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression. Three separate breast cancer cohorts were analyzed: 1) Uppsala (n=249), 2) Stockholm (n=58), 3) Singapore (n=40). The Uppsala and Singapore data can be accessed here. The Stockholm cohort data can be accessed at GEO Series GSE1456. Experiment Overall Design: All tumor specimens were assessed on U133 A and B arrays.
| S-ECPF-GEOD-4922 | biostudies-other
Project description:Signatures of Oncogenic Pathway Deregulation in Human Cancers. The ability to define cancer subtypes, recurrence of disease, and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies. Such data is also of substantial importance to the analysis of cellular signaling pathways central to the oncogenic process. With this focus, we have developed a series of gene expression signatures that reliably reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumors, and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumor sub-types. Clustering tumors based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Furthermore, predictions of pathway deregulation in cancer cell lines are shown to coincide with sensitivity to therapeutic agents that target components of the pathway, underscoring the potential for such pathway prediction to guide the use of targeted therapeutics. Experiment Overall Design: RNA was extracted from frozen tissue of primary breast tumors for gene array analysis.
| S-ECPF-GEOD-3143 | biostudies-other
Project description:mRNA expression data were collected from patients with brain tumor to improve diagnostic of gliomas on molecular level.
| S-ECPF-GEOD-4290 | biostudies-other
Project description:To identify genes associated with lung cancer progression, we examined gene expression profiles of tumor cells from 20 patients with primary, untreated non-small cell lung cancer (10 adenocarcinomas (AC) and 10 squamous cell carcinomas (SCC)) in comparison to lung tissue of 23 patients with stage IIIB or stage IV non-small cell lung cancer (15 AC and 8 SCC). Bronchoscopical biopsies from patient with recurrent lung tumor were taken after initial treatment. Cancer cells were isolated using laser capture microdissection in order to obtain pure samples of tumor cells. For expression analysis, microarrays covering 8793 defined genes (Human HG Focus Array, Affymetrix) were used. Array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM), respectively. Genes were considered to be up- or down-regulated when the ratio between primary and recurrent tumor samples were at least 1.5-fold differentially expressed with an estimated false discovery rate: < 5%. Based on differentially expressed genes, primary cancer samples could be separated from recurrent tumor samples. We identified 115 and 124 significantly regulates genes in AC and SCC, respectively. For example, in recurrent AC we found increased expression of genes related to the wingless (FZD6, RYK, MYC) and calcium (CALM1, ATB2B1, S100A2) signalling pathways which might play a role in metastasis of tumor cells. Other differentially expressed genes were related to cell cycle (CCND1, CDK2), transcription factors (TTF1, TAF2, YY1), nuclear mRNA splicing and mRNA processing (SFRS1, HNRPL), protein-nucleus import (NUTF2, KPNB1, NUP50) and chromatin modification (HIST1H4C, SMARCC1). In SCC, we found an increased expression of CTNNB1, an important mediator in wingless signalling pathway. Among the down-regulated genes in SCC, the utmost fraction belonged to genes coding for ubiquitin mediated proteolysis (UCHL1, PSMA3, COPS6) and ribosomal proteins (RPS26, RPL7A, RPS15). Other down regulated genes were related to transcription factors (TCEA2, TAF10), nuclear mRNA splicing and mRNA processing (SNRPD2, HNRPM). In conclusion, a distinct pattern of gene expression is found during the progression from primary carcinoma to recurrent NSCLC. Our microarray-based expression profiling revealed interesting novel candidate genes and pathways that may contribute to lung cancer progression. Experiment Overall Design: - 20 patients with primary, untreated non-small cell lung cancer (10adenocarcinomas (AC) and 10 squamous cell carcinomas (SCC)) in comparison to lung tissue of 23 patients with stage IIIB or stage IV non-small cell lung cancer (15 AC and 8 SCC) Experiment Overall Design: - Human HG Focus Array, Affymetrix) were used Experiment Overall Design: - Array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM) Experiment Overall Design: - Genes were considered to be up- or down-regulated when the ratio between primary and recurrent tumor samples were at least 1.5-fold differentially expressed with an estimated false discovery rate: < 5%
| S-ECPF-GEOD-7880 | biostudies-other