Breast Tumor's study
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE2741 | GEO | 2005/11/23
SECONDARY ACCESSION(S): PRJNA92237
REPOSITORIES: GEO
Similar Datasets
Project description:This SuperSeries is composed of the following subset Series: GSE4335: Norway/Stanford Breast Tumors GSE4336: Breast Tumors Abstract: Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities. Refer to individual Series
2006-03-07 | E-GEOD-4382 | biostudies-arrayexpress
Project description:Abstract: Characteristic patterns of gene expression measured by DNA microarrays have been used to classify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into one basal-like, one ERBB2-overexpressing, two luminal-like, and one normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. Similar cluster analyses of two published, independent data sets representing different patient cohorts from different laboratories, uncovered some of the same breast cancer subtypes. In the one data set that included information on time to development of distant metastasis, subtypes were associated with significant differences in this clinical feature. By including a group of tumors from BRCA1 carriers in the analysis, we found that this genotype predisposes to the basal tumor subtype. Our results strongly support the idea that many of these breast tumor subtypes represent biologically distinct disease entities. This SuperSeries is composed of the SubSeries listed below.
2006-03-08 | GSE4382 | GEO
Project description:Breast cancer is a profoundly heterogeneous disease with respect to biological and clinical behavior. Gene expression profiling has been used to dissect this complexity and stratify tumors into intrinsic gene expression subtypes associated with distinct biology, patient outcome and different genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. We applied global DNA copy number and gene expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy number aberrations and genomic subgroups of breast cancer. We identified 31 genomic regions that were highly amplified in >1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions (66 and 67 with DNA copy number gain and loss, respectively) revealed six genomic subtypes, termed: 17q12, basal-complex, luminal-simple, luminal-complex, amplifier and mixed subtype. Four of them had striking similarity to intrinsic gene expression subtypes and showed association to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having better prognosis while the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene expression subtypes, the former being enriched for 8p12-amplified cases while the mixed subtype included many tumors with predominantly DNA copy number losses and poor prognosis. Genomic profiling of 359 breast tumors using tiling BAC aCGH. A number of cases were hybridized as replicates or replicate as dye-swaps. Gene expression profiling of 359 breast tumors using 55K oligonucleotide microarrays.
2010-06-23 | E-GEOD-22133 | biostudies-arrayexpress
Project description:Characterization of patterns of gene expression measured by cDNA microarrays to subclassify tumors into clinically relevant subgroups. In this study, we have refined the previously defined subtypes of breast tumors that could be distinguished by their distinct patterns of gene expression. A total of 115 malignant breast tumors and 7 benign tissues were analyzed by hierarchical clustering based on patterns of expression of 534 "intrinsic" genes and shown to subdivide into a basal epithelial-like, an ERBB2-overexpressing, two luminal epithelial-like and a normal breast tissue-like subgroup. The genes used for classification were selected based on their similar expression levels between pairs of consecutive samples taken from the same tumor separated by 15 weeks of neoadjuvant treatment. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Computed
2006-03-06 | E-GEOD-4335 | biostudies-arrayexpress
Project description:A microarray targeting promoters of cancer-related genes was used to evaluate DNA methylation at 935 CpG sites in 517 invasive breast tumors from the Carolina Breast Cancer Study (CBCS), a population-based study of invasive breast cancer. Concensus clustering using methylation (β) values for the 167 most variant CpG loci defined 4 clusters differing most distinctly in hormone receptor (HR) status, intrinsic subtype (luminal versus basal-like) and p53 mutation status. Supervised analyses for HR status, subtype, and p53 status identified differentially methylated CpG loci with considerable overlap (n=266). Concensus clustering also defined a hypermethylated luminal-enriched tumor cluster 3; gene ontology analysis of cluster 3 hypermethylated loci revealed enrichment for developmental genes, including homeobox domain genes (HOXB13, PAX6, IPF1, EYA4, DLK1, IHH, ISL1, TBX1, SOX1, SOX17). The hypermethylated luminal-enriched cluster 3 independently predicted poorer survival in multivariate Cox proportional hazard analysis, and this finding was confirmed in analysis of luminal A tumors. This study demonstrates epigenetic heterogeneity among breast tumors of a single intrinsic subtype, and shows that epigenetic patterns are strongly associated with HR status, subtype, and p53 mutation status. Among HR+ tumors, a gene signature characterized by hypermethylation of developmental genes may have prognostic value. Genes differentially methylated between clinically-important tumor subsets have roles in differentiation, development, and tumor growth and may be critical to inducing and maintaining tumor phenotypes and clinical outcomes. 517 breast tumors, 9 normal breast tissues
2015-04-07 | E-GEOD-51557 | biostudies-arrayexpress
Project description:Microarrays were used to detail the global programme of gene expression underlying breast cancer cell lines. We identified two main groups of luminal-type and basal-type breast cancer cell lines by unsupervised Pearson correlation of breast cancer cell lines and intrinsic subtyping. Supervised analysis on spindle versus non-spindle breast cancer cell lines identified a spindle cell signature of 1,144 genes identifying all spindle, basal-type, E-cadherin methylated breast cancer cell lines. Breast cancer cell lines were grown to optimal cell densities for RNA extraction and hybridization on Affymetrix microarrays.
2009-07-13 | E-GEOD-16795 | biostudies-arrayexpress
Project description:Microarrays were used to detail the global programme of gene expression underlying breast cancer cell lines. We identified two main groups of luminal-type and basal-type breast cancer cell lines by unsupervised Pearson correlation of breast cancer cell lines and intrinsic subtyping. Supervised analysis on spindle versus non-spindle breast cancer cell lines identified a spindle cell signature of 1,144 genes identifying all spindle, basal-type, E-cadherin methylated breast cancer cell lines.
2009-07-13 | GSE16795 | GEO
Project description:Towards understanding breast cancer mechanisms to metastasize
| PRJNA205399 | ENA
Project description:Interactions of cancer cells with the vasculature are essential for tumor growth and likely promote metastatic progression. Endothelial cell content and lympho-vascular invasion are generally associated with tumor aggressiveness, however, these features are generally not employed in the clinic. We aimed to determine if endothelial cell gene expression signatures could be utilized to better characterize breast tumor biology, and to establish if vascular cell-derived signatures could provide information to predict tumors likely to metastasize. Here we report on the identification of a gene signature for vascular endothelial cells, and a second for cancer-activated vasculature. Both signatures independently identify subsets of aggressive breast cancers. Interestingly, the vascular content signature and a previously identified hypoxia signature both provide prognostic information beyond currently utilized clinical parameters and intrinsic subtype classifications. In these studies, we also examined the relationship that the breast cancer subtypes have with vascular gene expression profiles, and found that claudin-low tumors and cell lines express vascular gene expression profiles and displayed endothelial-like tube formation when grown in three-dimensions. These findings are directly applicable to clinical care and therapeutic treatment design as they identify highly aggressive subsets of tumors with genetic and morphologic vascular properties. reference x sample
2014-01-01 | E-GEOD-37145 | biostudies-arrayexpress
Project description:Breast cancer is a profoundly heterogeneous disease with respect to biological and clinical behavior. Gene expression profiling has been used to dissect this complexity and stratify tumors into intrinsic gene expression subtypes associated with distinct biology, patient outcome and different genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes. We applied global DNA copy number and gene expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy number aberrations and genomic subgroups of breast cancer. We identified 31 genomic regions that were highly amplified in >1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions (66 and 67 with DNA copy number gain and loss, respectively) revealed six genomic subtypes, termed: 17q12, basal-complex, luminal-simple, luminal-complex, amplifier and mixed subtype. Four of them had striking similarity to intrinsic gene expression subtypes and showed association to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having better prognosis while the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene expression subtypes, the former being enriched for 8p12-amplified cases while the mixed subtype included many tumors with predominantly DNA copy number losses and poor prognosis.
2010-06-24 | GSE22133 | GEO