Unknown,Transcriptomics,Genomics,Proteomics

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Breast cancer endothelial interaction

ABSTRACT: MATERIALS AND METHODS: The genomic effects of tumor-endothelial interactions in cancer are not yet well characterized. To study this interaction in breast cancer, we set up an ex vivo coculture model with human benign and malignant breast epithelial cells with endothelial cells to determine the associated gene expression changes using DNA microarrays. RESULTS: The most prominent response to coculture was the induction of the M-phase cell cycle genes in a subset of breast cancer cocultures that were absent in cocultures with normal breast epithelial cells. In monoculture, tumor cells that contained the stem cell-like CD44(+)/CD24(-) signature had a lower expression of the M-phase cell cycle genes than the CD44(-)/CD24(+) cells, and in the CD44(+)/CD24(-) cocultures, these genes were induced. Pretreatment gene expression profiles of early-stage breast cancers allowed evaluating in vitro effects in vivo. The expression of the gene set derived from the coculture provided a basis for the segregation of the tumors into two groups. In a univariate analysis, early-stage tumors with high expression levels (n = 137) of the M-phase cell cycle genes had a significantly lower metastasis-free survival rate (P = 1.8e - 5, 50% at 10 years) and overall survival rate (P = 5e - 9, 52% at 10 years) than tumors with low expression (n = 158; metastasis-free survival, 73%; overall survival, 84%). CONCLUSIONS: Our results suggest that the interaction of endothelial cells with tumor cells that express the CD44(+)/CD24(-) signature, which indicates a low proliferative potential, might explain the unexpected and paradoxical association of the CD44(+)/CD24(-) signature with highly proliferative tumors that have an unfavorable prognosis. Computed

ORGANISM(S): Homo sapiens

SUBMITTER: Martin Buess

PROVIDER: E-GEOD-20364 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Tumor-endothelial interaction links the CD44(+)/CD24(-) phenotype with poor prognosis in early-stage breast cancer.

Buess Martin M Rajski Michal M Vogel-Durrer Brigitte M L BM Herrmann Richard R Rochlitz Christoph C

Neoplasia (New York, N.Y.) 20091001 10

<h4>Materials and methods</h4>The genomic effects of tumor-endothelial interactions in cancer are not yet well characterized. To study this interaction in breast cancer, we set up an ex vivo coculture model with human benign and malignant breast epithelial cells with endothelial cells to determine the associated gene expression changes using DNA microarrays.<h4>Results</h4>The most prominent response to coculture was the induction of the M-phase cell cycle genes in a subset of breast cancer cocu ...[more]

PMID: 19794958

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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:The first goal of the study was to find the genes that explain the difference in progression of age-related retinal degeneration (ageRD) between the inbred strains C57BL/6J-c2J (B6a) and BALB/cByJ (C). The specific goal was to find the candidate genes that explain the chromosome 6 and chromosome 10 quantitative trait loci (QTL) found in a previous study. Genes differentially expressed in retina between both strains and that map to the QTL are candidate genes. By integrating different approaches: microarray study, knowledge-based candidate gene search and screening of genetic variants, we found 35 candidate genes for chromosome 6 QTL and 14 candidate genes for chromosome 10 QTL. Five genes for each QTL were selected for sequencing and qPCR analysis. One gene, Tnfaip3 was selected for phenotypic testing and was excluded as the quantitative trait gene for chr10 QTL. The second goal of the study was to find biological processes and pathways associated with ageRD by Gene Ontology analysis of the microarray data. We concentrated on GO terms overrepresented in either strain at 8 months; the age when there is a difference in the phenotype (outer nuclear layer thickness). The GO analysis revealed that transcripts associated with inflammation, mitochondrial envelope, DNA repairing and oxidative stress were increased in the ageRD sensitive C strain with age (8 months). In the ageRD resistant B6a strain transcripts associated with antioxidant response, regulation of blood vessel size and growth factor activity were increased with age. Transcripts associated with cell remodeling and lipid metabolism were increased in either strain with age. This study aims to identify gene expression differences in posterior eyecups between the strains C and B6a at 4 months and at 8 months. Twelve animals were used per strain and time point for a total of 48 mice. Total RNA for 3 animals (6 eyes) were pooled giving a total of 4 biological replicates per strain and time point. The 4-month C samples labeled with Cy5 were hybridized with the 4-month B6a samples labeled with Cy3 (4 biological replicates); the 8-month C samples labeled with Cy5 were hybridized with the 8-month B6a samples labeled with Cy3, for 8 arrays (4 biological replicates). A second set of eight arrays were used to analyzed the same RNA samples but with the dye orientation reversed, yielding a total of 16 arrays in the experiment. Set of arrays organized by shared biological context, such as organism, tumors types, processes, etc.

Dataset Information

Breast cancer endothelial interaction

Publications

Tumor-endothelial interaction links the CD44(+)/CD24(-) phenotype with poor prognosis in early-stage breast cancer.

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