Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA123169 | ENA |
REPOSITORIES: ENA
Similar Datasets
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
2010-06-25 | E-GEOD-15376 | biostudies-arrayexpress
Project description:Molecular profiling of breast cancer cell lines defines relevant tumor models (gene expression)
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Project description:Three-dimensional (3D) cancer spheroid models provide physiologically relevant platforms for studying tumor biology and therapeutic response. Using the liquid overlay method, we optimized conditions for reproducible spheroid generation from MDA-MB-231 breast cancer cells and extended this approach to 10 human cancer cell lines. Growth outcomes varied, yielding compact spheroids, loose aggregates, or no spheroids, with compactness strongly associated with high breast cancer stem cell (BCSC) content (≥20%). Transcriptomic profiling revealed distinct gene expression programs between spheroid-forming and non-forming cells, highlighting pathways in extracellular matrix remodeling, differentiation, and developmental lineage specification. Notably, PROM1, HOXB4, BMP5, and TENM4 emerged as key regulators, with TENM4 consistently upregulated across compact spheroid models. Drug response assays demonstrated increased chemoresistance in 3D spheroids compared to 2D cultures, with triple-negative breast cancer (TNBC) spheroids exhibiting reduced sensitivity to bortezomib+nedaplatin despite context-dependent synergy. Collectively, these findings establish optimized experimental parameters for spheroid culture, define molecular features linked to spheroid formation and stemness, and underscore the importance of 3D models for evaluating therapeutic efficacy.
2025-11-18 | GSE306569 | GEO
Project description:Integrated molecular profiling of patient-derived ovarian cancer models identifies clinically relevant signatures and tumor vulnerabilities.
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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.
2010-04-14 | E-GEOD-21259 | biostudies-arrayexpress
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
2009-02-01 | GSE10197 | GEO
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
2009-11-30 | E-GEOD-11901 | biostudies-arrayexpress
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.
2010-06-24 | E-GEOD-15361 | biostudies-arrayexpress