MCAM and LAMA4 are highly enriched in tumor blood vessels of renal cell carcinoma and predict patient outcome

Joseph Wragg, Jonathan Finnity, Jane Anderson, Henry Ferguson, Emilio Porfiri, Rupesh Bhatt, Paul Murray, Victoria Heath, Roy Bicknell

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)
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Abstract

The structure and molecular signature of tumor-associated vasculature are distinct from those of the host tissue, offering an opportunity to selectively target the tumor blood vessels. To identify tumor-specific endothelial markers, we performed a microarray on tumor-associated and nonmalignant endothelium collected from patients with renal cell carcinoma (RCC), colorectal carcinoma (CRC), or colorectal liver metastasis (CRM). We identified a panel of genes consistently upregulated by tumor blood vessels of which melanoma cell adhesion molecule (MCAM) and its extracellular matrix interaction partner laminin alpha 4 (LAMA4) emerged as the most consistently expressed genes. This result was subsequently confirmed by immunohistochemical analysis of MCAM and LAMA4 expression in RCC and CRC blood vessels. Strong MCAM and LAMA4 expression was also shown to predict poor survival in RCC, but not in CRC. Notably, MCAM and LAMA4 were enhanced in locally advanced tumors as well as both the primary tumor and secondary metastases. Expression analysis in 18 different cancers and matched healthy tissues revealed vascular MCAM as highly specific in RCC, where it was induced strongly by VEGF, which is highly abundant in this disease. Lastly, MCAM monoclonal antibodies specifically localized to vessels in a murine model of RCC, offering an opportunity for endothelial-specific targeting of anticancer agents. Overall, our findings highlight MCAM and LAMA4 as prime candidates for RCC prognosis and therapeutic targeting.
Original languageEnglish
Pages (from-to)2314-2326
Number of pages13
JournalCancer Research
Volume76
Issue number8
Early online date26 Feb 2016
DOIs
Publication statusPublished - 15 Apr 2016

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