Working with a line of highly metastatic head and neck cancer cells, a research team at the Winship Cancer Institute and Emory University School of Medicine has found that a specific cell surface receptor present at very low levels in non-metastatic head and neck cancer cells.
These investigators also showed that blocking this receptor suppressed tumor growth and prevented metastatic lesions from forming in the lungs.
Reporting its work in the journal Cancer Research, the team headed by Hyunsuk Shim, Ph.D., isolated the highly metastatic cells by implanting squamous cell carcinomas into mice, isolating metastatic lesions, injecting those cells into a second group of mice, and harvesting metastases again. After a total of four rounds of tumor implantation, harvesting and implanting again, the researchers obtained a highly metastatic population of cells. They then measured messenger RNA expression in the metastatic cell population and the original tumor cells, and by comparing these results, the investigators found that expression levels of mRNA coding for the CXC chemokine receptor-4 (CXCR4) were significantly higher in the metastatic cells.
Laboratory experiments suggested that blocking this receptor eliminated the metastatic capacity of the tumor cells. The investigators then injected the same receptor blocking molecule into animals that had received transplants of the metastatic cells. This experiment showed that tumor shrank dramatically in the treated animals and that lung metastases did not form. To confirm these results, the investigators then injected the CXCR4 antagonist into animals that received metastatic cell injections into their blood streams. Within 30 days, control animals had a large number of lung metastases, while the treated animals had no metastases in lung or any other organ.
This work, which was supported by the National Cancer Institute, is detailed in the paper, "CXC chemokine receptor-4 antagonist blocks both growth of primary tumor and metastasis of head and neck cancer in xenograft mouse models." An abstract of this paper is available through PubMed. View abstract.