Transcriptomes of breast epithelium and stroma in normal reduction mammoplasty and invasive breast cancer patients.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE10797 | GEO | 2008/04/03
SECONDARY ACCESSION(S): PRJNA107497
REPOSITORIES: GEO
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Project description: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.
2009-03-07 | E-GEOD-10797 | biostudies-arrayexpress
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.
2015-05-12 | E-GEOD-68744 | biostudies-arrayexpress
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.
2015-05-12 | GSE68744 | GEO
Project description:Since fibroblasts are a key component of the stroma with an established role in cancer, we investigated the contribution of fibroblasts to the signature observed in the stromal compartment. 13 clonally derived primary stromal fibroblasts were generated from metaplasia, dysplasia and EAC specimens. Expression of a panel of known fibroblast markers and concomitant absence of epithelial markers confirmed their fibroblastic origin. Gene expression profiling of these esophageal fibroblasts demonstrated that three ontologies related to an invasive phenotype (chemotaxis, cell adhesion, regulation of angiogenesis) differentiated cancer associated from BE fibroblasts. Furthermore, the ontologies and KEGG pathways relating to inflammation were all statistically upregulated in the fibroblast signature.
2010-01-22 | GSE19529 | GEO
Project description:Stromal-epithelial interactions play a fundamental role in tissue homeostasis, controlling cell proliferation and differentiation. Not surprisingly, aberrant stromal-epithelial interactions contribute to malignancies. The goals and objectives of this study were 1.) to characterize and validate the molecular identity of human primary epithelial and stromal/mesenchymal breast cells maintained long-term in novel ex vivo culture conditions in serum free medium. 2.) To analyze changes in gene expression profiles of normal human primary epithelial and stromal/mesenchymal breast cells upon long-term ex vivo co-culture when compared to corresponding monocultures 3.) To study the dynamic reciprocity between normal human primary epithelial and stromal/mesenchymal breast cells. 4.) To identify critical molecular pathways and biomarkers controlling epithelial and/or stromal cell growth and quiescence. Human primary epithelial progenitor cells and mesenchymal stem cells bearing fluorescent tags were either co-cultured in novel ex vivo culture conditions on ECM coated meshes in serum free medium (M5) or cultured as monocultures in the same conditions for 30 days. The cultures were then dissociated and epithelial and stromal/mesenchymal cells from either co-cultures or monocultures separated by FACS. Gene expression profiling of epithelial or stromal/mesenchymal cells was performed. Clean gene expression profiles from three different epithelial and stromal/mesenchymal cell extracts either grown in co-cultures or monocultures were successfully obtained.
2015-09-26 | GSE51201 | GEO
Project description:Primary tumor growth induces host tissue responses that are believed to support and promote tumor progression. Identification of the molecular characteristics of the tumor microenvironment and elucidation of its crosstalk with tumor cells may therefore be crucial for improving our understanding of the processes implicated in cancer progression, identifying potential therapeutic targets, and uncovering stromal gene expression signatures that may predict clinical outcome. A key issue to resolve, therefore, is whether the stromal response to tumor growth is largely a generic phenomenon, irrespective of the tumor type, or whether the response reflects tumor-specific properties. To address similarity or distinction of stromal gene expression changes during cancer progression, oligonucleotide-based Affymetrix microarray technology was used to compare the transcriptomes of laser-microdissected stromal cells derived from invasive human breast and prostate carcinoma. Invasive breast and prostate cancer-associated stroma was observed to display distinct transcriptomes, with a limited number of shared genes. Interestingly, both breast and prostate tumor-specific dysregulated stromal genes were observed to cluster breast and prostate cancer patients, respectively, into two distinct groups with statistically different clinical outcomes. By contrast, a gene signature that was common to the reactive stroma of both tumor types did not have survival predictive value. Univariate Cox analysis identified genes whose expression level was most strongly associated with patient survival. Taken together, these observations suggest that the tumor microenvironment displays distinct features according to the tumor type that provides survival-predictive value. 6 samples of stroma surrounding invasive breast primary tumors; 6 matched samples of normal stroma. 6 samples of stroma surrounding invasive prostate primary tumors; 6 matched samples of normal stroma.
2011-03-31 | E-GEOD-26910 | biostudies-arrayexpress
Project description:Type I, II, III and V collagens were commonly identified in human, pig, and mouse breast ECM. Mammary epithelial cells were able to form acini on certain types or combinations of the four collagens at normal breast tissue stiffness levels. Comparison of the collagen species in mouse normal breast and breast tumor ECM revealed common and distinct sets of collagens within the two types of tissues. Elevated collagen type I alpha 1 chain expression was found in human breast cancers. Collagen type XXV alpha 1 chain was identified in mouse breast tumors but not in normal breast tissues. Our data provide insights into modeling human breast pathophysiological structures and functions using native tissue-derived hydrogels and potential contributions of different collagen types or their monomers in breast cancer development.
2023-03-11 | PXD037900 | Pride
Project description:Type I, II, III and V collagens were commonly identified in human, pig, and mouse breast ECM. Mammary epithelial cells were able to form acini on certain types or combinations of the four collagens at normal breast tissue stiffness levels. Comparison of the collagen species in mouse normal breast and breast tumor ECM revealed common and distinct sets of collagens within the two types of tissues. Elevated collagen type I alpha 1 chain expression was found in human breast cancers. Collagen type XXV alpha 1 chain was identified in mouse breast tumors but not in normal breast tissues. Our data provide insights into modeling human breast pathophysiological structures and functions using native tissue-derived hydrogels and potential contributions of different collagen types or their monomers in breast cancer development.
2023-03-11 | PXD037920 | Pride
Project description:The desmoplastic reaction observed in many cancers is a hallmark of disease progression and prognosis, particularly in breast and pancreatic cancer. Stromal-derived extracellular matrix (ECM) is significantly altered in desmoplasia, and as such plays a critical role in driving cancer progression. Using fibroblast-derived matrices (FDMs), we show that cancer cells have increased growth on cancer-associated FDMs, comparing to FDMs derived from non-malignant tissue (normal) fibroblasts. We assess the changes in ECM characteristics from normal to cancer-associated stroma at the primary tumor site. Compositional, structural, and mechanical analyses reveal significant differences, with an increase in abundance of core ECM proteins, coupled with an increase in stiffness and density in cancer-associated FDMs. From compositional changes of FDM we derived a 36-ECM proteins’ signature, which we show largely matching the changes in pancreatic ductal adenocarcinoma (PDAC) tumor and metastases progression, as well as at the transcriptomic level in multiple cancer types in patients, predictive of their survival. Together, our results show relevance of FDMs for cancer modelling and identification of desmoplastic ECM components for further mechanistic studies.
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