Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling by array of human breast epithelium and stroma in normal reduction mammoplasty and invasive breast cancer patients

ABSTRACT: The molecular basis of breast cancer invasion and metastasis is not well understood. Our objective was to analyze transcriptome differences between stromal and epithelial cells in normal breast tissue and invasive breast cancer to define the role stroma plays in invasion. Total RNA was isolated from epithelial and stromal cells that were laser captured from normal breast tissue (n=5) and invasive breast cancer (n=28). Gene expression was measured using Affymetrix U133A 2.0 GeneChips. Differential gene expression was evaluated and compared within a model that accounted for cell type (epithelial [E] versus stromal [S]), diagnosis (cancer [C] versus normal [N]) as well as cell type-diagnosis interactions. Compared to NE, the CE transcriptome was highly enriched with genes in proliferative, motility and ECM ontologies. Differences in CS and NS transcriptomes suggested that the ECM was being remodeled in invasive breast cancer, as genes were over-represented in ECM and proteolysis ontologies. Genes more highly expressed in CS compared to CE were primarily ECM components or were involved in the remodeling of ECM, suggesting that ECM biosynthesis and remodeling were initiated in the tumor stromal compartment. Experiment Overall Design: Breast tissue was collected at surgery from patients undergoing surgical resection for invasive breast cancer (n=28) and reduction mammoplasty (n=5). Tissue was cryopreserved in OCT and serial sections were cut using a cryostat. Sections were stained and epithelial and stromal cells were isolated by laser capture microdissection. Total RNA was isolated and target was prepared using NuGen Ribo-SPIA Ovation Technology. Gene expression was measured using Affymetrix U133A 2.0 GeneChips. Gene expression differences were evaluated using a linear model of the Robust Multichip Average gene expression statistic, a model that accounted for cell type (E and S), patient diagnosis (C and N), as well as cell type-diagnosis interactions. Data were examined to determine false discovery rate and were filtered for fold changes in gene expression and p-value.

ORGANISM(S): Homo sapiens

SUBMITTER: Jeffrey Bond

PROVIDER: E-GEOD-10797 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Molecular signatures suggest a major role for stromal cells in development of invasive breast cancer.

Casey Theresa T Bond Jeffrey J Tighe Scott S Hunter Timothy T Lintault Laura L Patel Osman O Eneman Jonathan J Crocker Abigail A White Jeffrey J Tessitore Joseph J Stanley Mary M Harlow Seth S Weaver Donald D Muss Hyman H Plaut Karen K

Breast cancer research and treatment 20080329 1

<h4>Background</h4>Breast cancer invasion and metastasis involves both epithelial and stromal changes. Our objective was to delineate the pivotal role stroma plays in invasion by comparing transcriptomes among stromal and epithelial cells in normal tissue and invasive breast cancer.<h4>Methods</h4>Total RNA was isolated from epithelial and stromal cells that were laser captured from normal breast tissue (n = 5) and invasive breast cancer (n = 28). Gene expression was measured using Affymetrix U1 ...[more]

PMID: 18373191

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Project description:Background: Epithelial-stromal crosstalk plays a critical role in invasive breast cancer (IBC) pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis. Results: We develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive re-wiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, ER-positive IBC, and ER-negative IBC, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in IBC mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas. Conclusions: Epithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially-localized transcriptomic data. The analysis provides new biological insights into the re-wiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer. 36 flash-frozen human primary breast cancer samples were subjected to laser capture microdissection to separately isolate matched tumor epithelial and tumor-associated stromal components. RNA was isolated, subjected to 2 rounds of amplification, and hybridized on Agilent 4x44K microarrays along with a common reference (single round-amplified commercially obtained Universal Human Reference RNA) in a dyeswap design. For two samples of tumor-associated stroma, a second technical replicate was performed. Samples were labelled as ER-positive based on ESR1 gene expression levels in the tumor epithelium, using univariate Gaussian mixture model-based clustering via the mclust package in R.

Dataset Information

Transcription profiling by array of human breast epithelium and stroma in normal reduction mammoplasty and invasive breast cancer patients

Publications

Molecular signatures suggest a major role for stromal cells in development of invasive breast cancer.

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