Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression data from LCM captured prostate cancer cells

ABSTRACT: The prostate represents a complex mix of cell types and there is a need to analyze distinct cell populations to better understand their potential interactions. This study of cell-type specific gene expression patterns will contribute to understanding of how tumor epithelial cells may be affected by adjacent interstitial stromal cells within the tumor microenvirnonment. LCM and microarray analysis were used to identify gene expression patterns in prostate cancer epithelial and interstitial stromal cell populations. More than 500 genes whose expression levels were significantly different in epithelial cells versus adjacent stromal tissue were identified. Several chemokines and growth factors were more highly expressed in prostate cancer stromal cells while several transcription factors and receptors were more highly expressed in epithelial cells. Five micron serial sections from three different intermediate grade prostate tumors were provided. One section from each had been stained by hematoxylin and eosin and the tumor areas marked for identification. To obtain RNA from 2 different tissue types (glandular epithelium and interstitial stroma) tumor areas observed to have abundant cells of interest were identified. Tumor epithelium and adjacent stromal tissue were collected separately from each slide. We sought to obtain similar populations of cells of each tissue type, so to that end, we examined each slide and and marked areas to direct the laser capture. Approximately 1,000 cells were captured per cap and RNA was extracted and hybridized to Affymetrix microarrays as recommended by manufacturer.

ORGANISM(S): Homo sapiens

SUBMITTER: Gail Fraizer

PROVIDER: E-GEOD-20758 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Analysis of gene expression in prostate cancer epithelial and interstitial stromal cells using laser capture microdissection.

Gregg Jennifer L JL Brown Kathleen E KE Mintz Eric M EM Piontkivska Helen H Fraizer Gail C GC

BMC cancer 20100428

<h4>Background</h4>The prostate gland represents a multifaceted system in which prostate epithelia and stroma have distinct physiological roles. To understand the interaction between stroma and glandular epithelia, it is essential to delineate the gene expression profiles of these two tissue types in prostate cancer. Most studies have compared tumor and normal samples by performing global expression analysis using a mixture of cell populations. This report presents the first study of prostate tu ...[more]

PMID: 20426842

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Project description:Advancing age is associated with substantial increases in the incidence rates of common diseases affecting the prostate including benign prostatic hyperplasia (BPH) and prostate carcinoma. However, to date, there is no established molecular explanation for the age-dependent increases in these pathologies. The prostate is comprised of a functional secretory epithelium supported by a spectrum of cell types and structural elements comprising the stroma. As reciprocal interactions between epithelium and stromal constituents are essential for normal organogenesis and serve to maintain normal functions, discordance within the stromal could permit or promote disease processes. In this study we sought to identify aging-associated alterations in the mouse prostate that could influence pathology. We quantitated transcript levels in microdissected periglandular stroma from young (4 month-old) and old (20-24 month-old) C57BL/6 mice, and identified a significant change in the expression of 1259 genes (p<0.05). These included increases in transcripts encoding genes associated with inflammation (e.g., Ccl8, Ccl12), genotoxic/ oxidative stress (e.g., Apod, Serpinb5) and paracrine-acting proteins (e.g., Cyr61). The expression of several collagen genes (e.g., Col1a1 and Col3a1) exhibited age associated declines. By immunofluorescence and electron microscopy we determined that the aged prostate contains an abundant disorganized collagen matrix and a significant increase in inflammatory infiltrates comprised of macrophages, T cells and, to a lesser extent, B cells. These findings demonstrated that during normal aging the prostate stroma exhibits phenotypic and molecular characteristics plausibly contributing to the striking age associated pathologies affecting the prostate through oxidative stress and inflammatory cell damage. Custom Agilent 44K whole mouse genome expression oligonucleotide microarrays as well as custom mouse cDNA microarrays were used to measure transcript levels in microdissected periglandular stroma from young (4 month-old) and old (20-24 month-old) C57BL/6 mice. All samples were laser-capture microdissected and total RNA isolated and amplified prior to hybridization against a reference pool of normal adult mouse tissues.

Project description:Tumor tissue heterogeneity is a well known feature of several solid tumors. Neuroblastic Tumors (NTs) is a group of paediatric cancers with a great tissue heterogeneity. Most of NTs are composed of undifferentiated, poorly differentiated or differentiating neuroblastic (Nb) cells with very few or absent Schwannian stromal (SS) cells: these tumors are grouped as Neuroblastoma (Schwannian stroma-poor). The remaining NTs are composed of abundant SS cells and classified as Ganglioneuroblastoma (Schwannian stroma-rich) intermixed or nodular and Ganglioneuroma. The importance to understand Nb and SS gene signatures in NTs, is to clarify the complex network mechanism of tumor growth and progression. In order to identify the Nb and SS cells gene signatures, we analyzed the gene expression profiling of 19 cases of neuroblastic tumors: 10 stroma poor (NTs-SP) and 9 stroma rich (NTs-SR), by high density oligonucleotide microarrays. Moreover, the analysis was performed in parallel on both whole and laser microdissected tumor samples: from 4 of 19 cases, was isolated different areas all composed of pure cellular populations. We performed genome wide expression analysis by using Affymetrix technology and we used two different approaches for data analysis: SAM (Significance Analysis of Microarrays) and a method based on Game Theory (GT), to identify genes differently expressed in SS and Nb cells. Differently from the SAM method, the analysis based on GT (Moretti et al. (2006)) gives the advantage of selecting relevant genes not only according to the expression profile of each single gene, but considering also gene interaction. Experiment Overall Design: Tissue samples from 10 primary neuroblastoma stroma-poor (NTs-SP) and 9 ganglioneuroblastoma/ganglioneuroma stroma-rich (NTs-SR) tumors, were obtained at diagnosis from patients at different clinical stage. Frozen samples of NTs-SP had a minimum content of 90% of malignant cells, while NTs-SR had more than 80-90% of schwannian stromal cells. Four out of 19 NTs: 2 neuroblastomas (Schwannian stoma-poor) and 2 ganglioneublastomas (Schwannian stroma-rich), were further analyzed with laser microdissection.

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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

Expression data from LCM captured prostate cancer cells

Publications

Analysis of gene expression in prostate cancer epithelial and interstitial stromal cells using laser capture microdissection.

Similar Datasets

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