Norway/Stanford Breast Tumors
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE4335 | GEO | 2006/03/07
SECONDARY ACCESSION(S): PRJNA104655
REPOSITORIES: GEO
Similar Datasets
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: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:Microarray analysis has been shown to improve risk stratification of breast cancer. Breast tumors analyzed by hierarchical clustering of expression patterns of "intrinsic" genes have been reported to subdivide into at least four molecular subtypes that are associated with distinct patient outcomes. Using a supervised method, a 70-gene expression profile has been identified that predicts the later appearance or absence of clinical metastasis in young breast cancer patients. Here, we show that distant metastases display both the same molecular breast cancer subtype as well as the 70-gene prognosis signature as their primary tumors. Our results suggest that the capacity to metastasize is an inherent feature of most breast cancers. Furthermore, our data imply that poor prognosis breast carcinomas classified either by the intrinsic gene set or the 70 prognosis genes represent distinct disease entities that seem sustained throughout the metastatic process. Keywords: other
2005-11-23 | GSE2741 | GEO
Project description:Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. cDNA microarrays and a clustering algorithm were used to identify patterns of gene expression in human mammary epithelial cells growing in culture and in primary human breast tumors. Clusters of coexpressed genes identified through manipulations of mammary epithelial cells in vitro also showed consistent patterns of variation in expression among breast tumor samples. By using immunohistochemistry with antibodies against proteins encoded by a particular gene in a cluster, the identity of the cell type within the tumor specimen that contributed the observed gene expression pattern could be determined. Clusters of genes with coherent expression patterns in cultured cells and in the breast tumors samples could be related to specific features of biological variation among the samples. Two such clusters were found to have patterns that correlated with variation in cell proliferation rates and with activation of the IFN-regulated signal transduction pathway, respectively. Clusters of genes expressed by stromal cells and lymphocytes in the breast tumors also were identified in this analysis. These results support the feasibility and usefulness of this systematic approach to studying variation in gene expression patterns in human cancers as a means to dissect and classify solid tumors. This study is described more fully in Perou CM, et al. 1999. Proc Natl Acad Sci USA 96:9212-7
2002-06-27 | E-GEOD-53 | biostudies-arrayexpress
Project description:The cellular heterogeneity of one patient derived orthotopic breast cancer xenograft model PDX was investigated using flow cytometry, combined with assessment of in vivo tumorigenicity and SNP genotyping array for copy number analysis. Epithelial cell adhesion molecule (EpCAM) was revealed as a highly specific cell surface marker of the human tumor cell population in both xenografts. Based on expression patterns observed in primary tumor tissue, SSEA-4 and CD24 were chosen as markers to further subdivide the luminal tumor cells into four subpopulations. FACS sorting was used to isolate four cell subpopulations. Results: In vivo tumorigenicity assay showed that SSEA-4+/CD24+ cells were non-tumorigenic, while the three other subpopulations were tumorigenic. Tumors resulting from the SSEA-4+/CD24- subpopulation of luminal cancer cells, did not express CD24, while tumors arising from the SSEA-4-/CD24-, and SSEA-4-/CD24+ populations both recapitulated the original tumor containing all four subpopulations. Copy number analysis comparing the four subpopulations between eachother, did reveal high similarity. Although there were some minor differencies between the subpopulations, no differences in genome aberrations could explain their difference in tumorigenicity. Discussion: Our results imply that subpopulations from one primary tumor can give rise to dissimilar daughter tumors. These tumors may not necessarily respond to the same targeted treatment, and thereby represent a therapy escape mechanism. This study highlights that to remove the risk of breast cancer recurrence, inhibition of the molecules critical for driving the tumor progression in several tumor cell subpopulations might be essential Four subpopulations were analysed using Infinium HumanOmniExpressExome BeadChip array. Replicates are not included, the HumanOmniExpressExome-8v1-2_A.egt file was used as a reference.
2015-05-26 | E-GEOD-54595 | biostudies-arrayexpress
Project description:Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. cDNA microarrays and a clustering algorithm were used to identify patterns of gene expression in human mammary epithelial cells growing in culture and in primary human breast tumors. Clusters of coexpressed genes identified through manipulations of mammary epithelial cells in vitro also showed consistent patterns of variation in expression among breast tumor samples. By using immunohistochemistry with antibodies against proteins encoded by a particular gene in a cluster, the identity of the cell type within the tumor specimen that contributed the observed gene expression pattern could be determined. Clusters of genes with coherent expression patterns in cultured cells and in the breast tumors samples could be related to specific features of biological variation among the samples. Two such clusters were found to have patterns that correlated with variation in cell proliferation rates and with activation of the IFN-regulated signal transduction pathway, respectively. Clusters of genes expressed by stromal cells and lymphocytes in the breast tumors also were identified in this analysis. These results support the feasibility and usefulness of this systematic approach to studying variation in gene expression patterns in human cancers as a means to dissect and classify solid tumors. This study is described more fully in Perou CM, et al. 1999. Proc Natl Acad Sci USA 96:9212-7 Keywords: other
2002-06-27 | GSE53 | GEO
Project description:The cellular heterogeneity of one patient derived orthotopic breast cancer xenograft model (PDBCX) was investigated using flow cytometry , combined with assessment of in vivo tumorigenicity and whole genome expression profiling. Epithelial cell adhesion molecule (EpCAM) was revealed as a highly specific cell surface marker of the human tumor cell population in both xenografts. Based on expression patterns observed in primary tumor tissue, SSEA-4 and CD24 were chosen as markers to further subdivide the luminal tumor cells into four subpopulations. FACS sorting was used to isolate four cell subpopulations. Results: In vivo tumorigenicity assay showed that SSEA-4+/CD24+ cells were non-tumorigenic, while the three other subpopulations were tumorigenic. Tumors resulting from the SSEA-4+/CD24- subpopulation of luminal cancer cells, did not express CD24, while tumors arising from the SSEA-4-/CD24-, and SSEA-4-/CD24+ populations both recapitulated the original tumor containing all four subpopulations. Whole genome expression analysis revealed distinct transcriptional profiles, and 44 genes were significantly differentially expressed when comparing the tumorigenic vs non-tumorigenic populations. Several interesting genes putatively suppressing the cancer cells ability to initiate tumors in vivo were upregulated in the non-tumorigenic population. We here show that tumor initiating cells within one primary tumor evidently included more than one phenotype. Furthermore, with respect to cell surface marker expression, one of the subpopulations produced tumors unlike both the originating cells, and the original tumor. Discussion: Our results imply that subpopulations from one primary tumor can give rise to dissimilar daughter tumors. These tumors may not necessarily respond to the same targeted treatment, and thereby represent a therapy escape mechanism. This study highlights that to remove the risk of breast cancer recurrence, inhibition of the molecules critical for driving the tumor progression in several tumor cell subpopulations might be essential Gene expression was measured in four cell subpopulations isolated from Patient derived human luminal-like breast cancer xenograft. Four replicates from three subpopulations and three replicates from one subpopulation.
2015-05-26 | E-GEOD-48384 | biostudies-arrayexpress
Project description:Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, incluing methylation profiles of 669 human breast tumors, was utilized for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states. We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates and genomic instability. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation to gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells. Our results suggest that hypermethylation patterns in basal-like breast cancer may have limited influence on tumor progression and instead reflects the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in some luminal breast cancers. Genome-wide DNA methylation analysis of 188 breast cancers using Illumina Human Methylation 450K Beadchips.
2016-02-29 | E-GEOD-75067 | biostudies-arrayexpress
Project description:Aberrant DNA methylation is frequently observed in breast cancer. However, the relationship between methylation patterns and the heterogeneity of breast cancer has not been comprehensively characterized. Whole-genome DNA methylation analysis using 450K Illumina BeadArrays was performed on 188 human breast tumors. Unsupervised bootstrap consensus clustering was performed to identify DNA methylation epigenetic subgroups (epitypes). The Cancer Genome Atlas data, incluing methylation profiles of 669 human breast tumors, was utilized for validation. The identified epitypes were characterized by integration with publicly available genome-wide data, including gene expression levels, DNA copy numbers, whole-exome sequencing data, and chromatin states. We identified seven breast cancer epitypes. One epitype was distinctly associated with basal-like tumors and with BRCA1 mutations, one epitype contained a subset of ERBB2-amplified tumors characterized by multiple additional amplifications and the most complex genomes, and one epitype displayed a methylation profile similar to normal epithelial cells. Luminal tumors were stratified into the remaining four epitypes, with differences in promoter hypermethylation, global hypomethylation, proliferative rates and genomic instability. We observed two dominant patterns of aberrant methylation in breast cancer. One pattern, constitutively methylated in both basal-like and luminal breast cancer, was linked to genes with promoters in a Polycomb-repressed state in normal epithelial cells and displayed no correlation to gene expression levels. The second pattern correlated with gene expression levels and was associated with methylation in luminal tumors and genes with active promoters in normal epithelial cells. Our results suggest that hypermethylation patterns in basal-like breast cancer may have limited influence on tumor progression and instead reflects the repressed chromatin state of the tissue of origin. On the contrary, hypermethylation patterns specific to luminal breast cancer influence gene expression, may contribute to tumor progression, and may present an actionable epigenetic alteration in some luminal breast cancers.
2016-02-29 | GSE75067 | GEO