Ontology highlight
ABSTRACT:
PROVIDER: PRJNA117105 | 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 (aCGH)
| PRJNA123169 | ENA
Project description:Molecular profiling of breast cancer cell lines defines relevant tumor models (gene expression)
| PRJNA123251 | ENA
Project description:Solid tumors are complex organs comprising neoplastic cells and stroma, yet cancer cell lines remain widely used to study tumor biology, biomarkers and experimental therapy. Here, we performed a fully integrative analysis of global proteomic data comparing human colorectal cancer (CRC) cell lines to primary tumors and normal tissues. We found a significant, systematic difference between cell line and tumor proteomes, with a major contribution from tumor stroma proteomes. Nevertheless, cell lines overall mirrored the proteomic differences observed between tumors and normal tissues, in particular for genetic information processing and metabolic pathways, indicating that cell lines provide a system for the study of the intrinsic molecular programs in cancer cells. Intersection of cell line data with tumor data provided insights into tumor cell specific proteome alterations driven by genomic alterations. Our integration of cell line proteogenomic data with drug sensitivity data highlights the potential of proteomic data in predicting therapeutic response. We identified representative cell lines for the proteomic subtypes of primary tumors, and linked these to drug sensitivity data to identify subtype-specific drug candidates.
2016-12-01 | MSV000080374 | GNPS
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
Project description:Continuous cell lines are important and commonly used in vitro models in breast cancer (BC) research. Selection of the appropriate model cell line is crucial and requires consideration of their molecular characteristics. To characterize BC cell line models in depth, we profiled a panel of 29 authenticated and publicly available BC cell lines by mRNA-sequencing, mutation analysis, and immunoblotting. Gene expression profiles separated BC cell lines in two major clusters that represent basal-like (mainly triple-negative BC) and luminal BC subtypes, respectively. HER2-positive cell lines were located within the luminal cluster. Mutation calling highlighted the frequent aberration of TP53 and BRCA2 in BC cell lines, which, therefore, share relevant characteristics with primary BC. Furthermore, we showed that the data can be used to find novel, potential oncogenic fusion transcripts, e.g., FGFR2::CRYBG1 and RTN4IP1::CRYBG1 in cell line MFM-223, and to elucidate the regulatory circuit of IRX genes and KLF15 as novel candidate tumor suppressor genes in BC. Our data indicated that KLF15 was activated by IRX1 and inhibited by IRX3. Moreover, KLF15 inhibited IRX1 in cell line HCC-1599. Each BC cell line carries unique molecular features. Therefore, the molecular characteristics of BC cell lines described here might serve as a valuable resource to improve the selection of appropriate models for BC research. Raw fastq files are also published at BioStudies: S-BSST1200.
2024-12-03 | E-MTAB-14655 | biostudies-arrayexpress
Project description:Transcriptomic profiling of 62 breast cancer cell lines and PDX models
| PRJNA640820 | ENA
Project description:Molecular Characterization and Subtyping of Breast Cancer Cell Lines Provide Novel Insights into Cancer Relevant Genes
| PRJEB83077 | ENA
Project description:Protein profiling of 18 breast cancer cell lines in triplicates using TMT10-plex.
2020-07-04 | PXD013276 | JPOST Repository
Project description:Integrated molecular profiling of patient-derived ovarian cancer models identifies clinically relevant signatures and tumor vulnerabilities.
| PRJNA648042 | ENA