Literature DB >> 21281818

Gene expression patterns related to vascular invasion and aggressive features in endometrial cancer.

Monica Mannelqvist1, Ingunn M Stefansson, Geir Bredholt, Trond Hellem Bø, Anne M Oyan, Inge Jonassen, Karl-Henning Kalland, Helga B Salvesen, Lars A Akslen.   

Abstract

The presence of tumor cells entering vascular channels is a prognostic marker for many cancers, including endometrial carcinoma. Vascular invasion is considered to be an early step in the metastatic process and important for the progress of malignant tumors. Here, we investigated the gene expression patterns related to vascular involvement in 57 primary endometrial cancers, using DNA microarray and quantitative PCR techniques. A vascular invasion signature of 18 genes was significantly associated with patient survival and clinicopathological phenotype. Vascular involvement was also related to gene sets for epithelial-mesenchymal transition, wound response, endothelial cells, and vascular endothelial growth factor (VEGF) activity. With immunohistochemical validation, both collagen 8 and matrix metalloproteinase 3 (MMP3) were associated with vascular invasion, whereas ANGPTL4 and IL-8 were associated with patient survival. Our findings indicate that vascular involvement within primary tumors is associated with gene expression profiles related to angiogenesis and epithelial-mesenchymal transition. These data could contribute to an improved understanding of potential targets for metastatic spread and may provide clinically important information for better management of endometrial cancer.
Copyright © 2011 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21281818      PMCID: PMC3070569          DOI: 10.1016/j.ajpath.2010.10.040

Source DB:  PubMed          Journal:  Am J Pathol        ISSN: 0002-9440            Impact factor:   4.307


  52 in total

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  19 in total

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7.  Lipocalin 2 expression is associated with aggressive features of endometrial cancer.

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Review 10.  Gene expression analysis in RA: towards personalized medicine.

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