Project description:Tumor-associated breast stroma was laser-capture microdissected from IDC breast cancer cases. The goal of the study was to characterize the heterogeneity of breast tumor-assocaited stroma and identify gene expression signatures predictive of clinical outcome. Keywords: disease state analysis
Project description:The purpose of this study was to explore the possibility of classifying breast carcinomas based upon variations in gene expression patterns derived from cDNA microarrays, and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing tumor and normal breast tissues from 78 individuals were analyzed by hierarchical-clustering. As reported previously, we identified a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized lluminal epithelial/ER-positiven group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets; first, a set of 456 cDNA clones previously selected to reflect the lintrinsicn properties of the tumors and, second, a gene set identified that highly correlated with patient outcome. Survival analyses on the sub-cohort of 51 patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Keywords: Logical Set
Project description:Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) associated with human traits and diseases. But because the vast majority of these SNPs are located in the noncoding regions of the genome their risk promoting mechanisms are elusive. Employing a new methodology combining cistromics, epigenomics and genotype imputation we annotate the noncoding regions of the genome in breast cancer cells and systematically identify the functional nature of SNPs associated with breast cancer risk. Our results demonstrate that breast cancer risk-associated SNPs are enriched in the cistromes of FOXA1 and ESR1 and the epigenome of H3K4me1 in a cancer and cell-type-specific manner. Furthermore, the majority of these risk-associated SNPs modulate the affinity of chromatin for FOXA1 at distal regulatory elements, which results in allele-specific gene expression, exemplified by the effect of the rs4784227 SNP on the TOX3 gene found within the 16q12.1 risk locus.
Project description:Tumor epithelium and surrounding stromal cells were isolated using laser capture microdissection of human breast cancer to examine differences in gene expression based on tissue types from inflammatory and non-inflammatory breast cancer Keywords: LCM
Project description:Genome-wide association studies (GWASs) have identified thousands of single nucleotide polymorphisms (SNPs) associated with human traits and diseases. But because the vast majority of these SNPs are located in the noncoding regions of the genome their risk promoting mechanisms are elusive. Employing a new methodology combining cistromics, epigenomics and genotype imputation we annotate the noncoding regions of the genome in breast cancer cells and systematically identify the functional nature of SNPs associated with breast cancer risk. Our results demonstrate that breast cancer risk-associated SNPs are enriched in the cistromes of FOXA1 and ESR1 and the epigenome of H3K4me1 in a cancer and cell-type-specific manner. Furthermore, the majority of these risk-associated SNPs modulate the affinity of chromatin for FOXA1 at distal regulatory elements, which results in allele-specific gene expression, exemplified by the effect of the rs4784227 SNP on the TOX3 gene found within the 16q12.1 risk locus. Examination of histone modification H3K4me2 in untreated and E2 treated cells
Project description:The purpose of this study was to explore the possibility of classifying breast carcinomas based upon variations in gene expression patterns derived from cDNA microarrays, and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing tumor and normal breast tissues from 78 individuals were analyzed by hierarchical-clustering. As reported previously, we identified a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized lluminal epithelial/ER-positiven group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets; first, a set of 456 cDNA clones previously selected to reflect the lintrinsicn properties of the tumors and, second, a gene set identified that highly correlated with patient outcome. Survival analyses on the sub-cohort of 51 patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc. Computed