Classification of renal cell carcinoma based on expression of VEGF and VEGF receptors in both tumor cells and endothelial cells View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2008-07-14

AUTHORS

Harriet M Kluger, Summar F Siddiqui, Cesar Angeletti, Mario Sznol, William K Kelly, Annette M Molinaro, Robert L Camp

ABSTRACT

Recent development of antiangiogenic therapy for renal cell carcinoma (RCC) has significantly improved the treatment of these often refractory tumors. However, not all patients respond to therapy and assays for predicting outcome are needed. As a first step, we analyzed a retrospective cohort of tumors and assessed the ability of VEGF and VEGF receptors (VEGF-R1, -R2 and -R3) to classify tumors. We analyzed tissue microarrays containing 330 RCCs using a novel method of automated quantitative analysis of VEGF and VEGF-R expression by fluorescent immunohistochemistry. Expression of markers was separately quantified within three tissue components: tumor cells, endothelial cells and adjacent normal epithelium. VEGF and VEGF receptors were tightly coexpressed both within tumors and within adjacent normal cells (all P-values <0.001). Tumor cell expression of VEGF-R1 and -R2 was strongly and inversely correlated with vessel area (P<0.0001). Unsupervised hierarchical clustering classified tumors by coordinated expression of VEGF and VEGF-Rs. The distribution of clear cell and papillary tumors was not significantly different between clusters. Clusters with high expression of VEGF and VEGF-Rs in the tumor cells exhibited poor survival when compared with the other clusters on uni- and multivariable analysis. VEGF and VEGF receptors exhibit a complex pattern of coordinated expression in RCC. Clustering tumors by VEGF and VEGF-R in tissue components demonstrates distinct tumor phenotypes with different outcomes, and may provide a means for determining which tumors will respond to what antiangiogenic therapies. More... »

PAGES

962-972

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/labinvest.2008.65

DOI

http://dx.doi.org/10.1038/labinvest.2008.65

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004074271

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/18626467


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