NK cells use a variety of receptors to detect abnormal cells, including tumors and their metastases. However, in the case of melanoma, it remains to be determined what specific molecular interactions are involved and whether NK cells control metastatic progression and/or the route of dissemination. Here we show that human melanoma cell lines derived from LN metastases express ligands for natural cytotoxicity receptors (NCRs) and DNAX accessory molecule-1 (DNAM-1), two emerging NK cell receptors key for cancer cell recognition, but not NK group 2 member D (NKG2D). Compared with cell lines derived from metastases taken from other anatomical sites, LN metastases were more susceptible to NK cell lysis and preferentially targeted by adoptively transferred NK cells in a xenogeneic model of cell therapy. In mice, DNAM-1 and NCR ligands were also found on spontaneous melanomas and melanoma cell lines. Interference with DNAM-1 and NCRs by antibody blockade or genetic disruption reduced killing of melanoma cells. Taken together, these results show that DNAM-1 and NCRs are critical for NK cell–mediated innate immunity to melanoma cells and provide a background to design NK cell–based immunotherapeutic strategies against melanoma and possibly other tumors.
Tadepally Lakshmikanth, Shannon Burke, Talib Hassan Ali, Silvia Kimpfler, Francesco Ursini, Loredana Ruggeri, Marusca Capanni, Viktor Umansky, Annette Paschen, Antje Sucker, Daniela Pende, Veronika Groh, Roberto Biassoni, Petter Höglund, Masashi Kato, Kazuko Shibuya, Dirk Schadendorf, Andrea Anichini, Soldano Ferrone, Andrea Velardi, Klas Kärre, Akira Shibuya, Ennio Carbone, Francesco Colucci
Usage data is cumulative from August 2019 through August 2020.
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.