Project description:This SuperSeries is composed of the following subset Series: GSE13914: Molecular profiling of breast cancer cell lines defines relevant tumor models (aCGH) GSE15361: Molecular profiling of breast cancer cell lines defines relevant tumor models (gene expression) Refer to individual Series
Project description:HER2 gene amplification and protein overexpression (HER2+) define a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. Although gene expression profiling has identified an ERBB2 molecular subtype of breast cancer, it is clear that HER2+ tumors reside in all molecular subtypes and represent a genomically and biologically heterogeneous group. Genome-wide DNA copy number profiling, using BAC array comparative genomic hybridization (aCGH) were performed on 200 tumors with mixed clinical characteristics and amplification of HER2. Genomic Identification of Significant Targets in Cancer (GISTIC) was used to identify significant copy number aberrations (CNAs) in HER2+ tumors. This analysis sheds further light on the genomically complex and heterogeneous nature of HER2+ tumors in relation to other subgroups of breast cancer. Genomic profiling of 200 breast tumors using tiling BAC aCGH (32K, 33K and 38K). A number of cases were hybridized as replicates or dye-swaps.
Project description:cDNA aCGH study of pure DCIS (breast duct carcinoma in situ) without invasive tumor, DCIS associated with IDC (breast invasive duct carcinoma) and its IDC component 23 patients: 6 pure DCIS without invasive cancer and no history of invasive cancer, 17 DCIS associated with IDC. Out of the latter 1 tumor had only enough DCIS (#16) for aCGH and one - IDC (#23) Keywords: Comparative clinical study
Project description:Recently, expression profiling of breast carcinomas has revealed gene signatures that predict clinical outcome, and discerned prognostically relevant breast cancer subtypes. Measurement of the degree of genomic instability provides a very similar stratification of prognostic groups. We therefore hypothesized that these features are linked. We used gene expression profiling of 48 breast cancer specimens that profoundly differed in their degree of genomic instability and identified a set of 12 genes that defines the two groups. The biological and prognostic significance of this gene set was established through survival prediction in published datasets from patients with breast cancer. Of note, the gene expression signatures that define specific prognostic subtypes in other breast cancer datasets predicted genomic instability in our samples. This remarkable congruence suggests a biological dependency of poor-prognosis gene signatures, breast cancer subtypes, genomic instability, and clinical outcome. Keywords: disease state analysis 44 samples
Project description:Summary: Breast cancer cell lines have been used widely to investigate breast cancer pathobiology and new therapies. Breast cancer is a molecularly heterogeneous disease, and it is important to understand how well and which cell lines best model that diversity. In particular, microarray studies have identified molecular subtypes (luminal A, luminal B, ERBB2-associated, basal-like and normal-like) with characteristic gene-expression patterns and underlying DNA copy number alterations (CNAs). Here, we studied a collection of breast cancer cell lines to catalog molecular profiles and to assess their relation to breast cancer subtypes. Whole-genome DNA microarrays were used to profile gene expression and CNAs in a collection of 52 widely-used breast cancer cell lines, and comparisons were made to existing profiles of primary breast tumors. Hierarchical clustering was used to identify gene-expression subtypes, and Gene Set Enrichment Analysis (GSEA) to discover biological features of those subtypes. Genomic and transcriptional profiles were integrated to discover within high-amplitude CNAs candidate cancer genes with coordinately altered gene copy number and expression. Transcriptional profiling of breast cancer cell lines identified one luminal and two basal-like (A and B) subtypes. Luminal lines displayed an estrogen receptor (ER) signature and resembled luminal-A/B tumors, basal-A lines were associated with ETS-pathway and BRCA1 signatures and resembled basal-like tumors, and basal-B lines displayed mesenchymal and stem-cell characteristics. Compared to tumors, cell lines exhibited similar patterns of CNA, but an overall higher complexity of CNA (genetically simple luminal-A tumors were not represented), and only partial conservation of subtype-specific CNAs. We identified 80 high-level DNA amplifications and 13 presumptive homozygous deletions, and the resident genes with concomitantly altered gene-expression, highlighting known and novel candidate breast cancer genes. Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes. HEEBO oligonucleotide microarrays from the Stanford Functional Genomics Facility were used to perform gene expression profiling of 50 human breast epithelial cell lines, in comparison to a universal RNA reference. Expression data were analyzed by hierarchical clustering to identify subgroups, and gene set enrichment analysis to identify subgroup-specific gene pathways.
Project description:Advanced prostate cancer is a highly heterogenous disease with few in vitro models. We report generation of seven novel 3D organoid lines of patient-derived prostate cancer. We determine the copy number alterations of these lines using array CGH. They contain may classic alterations of prostate cancer such as lost of the short arm of chromosome 8 and gain of the long arm of chromosome 8. In addition, we found homozygous deleteion of tumor suppressor PTEN and CHD1 as well as the TMPRSS2-ERG interstitial deletion. Prostate cancer organoid lines, ~2 months after in vitro propagation, were used for profiling on Agilent 1M aCGH arrays per manufacturer's instructions. A pooled reference normal DNA was used as the reference.