Chronic lymphocytic leukemia (CLL) is characterized by clonal proliferation and progressive accumulation of mature B lymphocytes in the peripheral blood, lymphoid tissues, and bone marrow. CLL is characterized by profound immune defects leading to severe infectious complications. T cells are numerically, phenotypically, and functionally highly abnormal in CLL, with only limited ability to exert antitumor immune responses. Exhaustion of T cells has also been suggested to play an important role in antitumor responses. CLL-mediated T cell exhaustion is achieved by the aberrant expression of several inhibitory molecules on CLL cells and their microenvironment, prominently the programmed cell death ligand 1/programmed cell death 1 (PD-L1/PD-1) receptors. Previously, we showed that CD84, a member of the SLAM family of receptors, bridges between CLL cells and their microenvironment. In the current study, we followed CD84 regulation of T cell function. We showed that cell-cell interaction mediated through human and mouse CD84 upregulates PD-L1 expression on CLL cells and in their microenvironment and PD-1 expression on T cells. This resulted in suppression of T cell responses and activity in vitro and in vivo. Thus, our results demonstrate a role for CD84 in the regulation of immune checkpoints by leukemia cells and identify CD84 blockade as a therapeutic strategy to reverse tumor-induced immune suppression.
Hadas Lewinsky, Avital F. Barak, Victoria Huber, Matthias P. Kramer, Lihi Radomir, Lital Sever, Irit Orr, Vita Mirkin, Nili Dezorella, Mika Shapiro, Yosef Cohen, Lev Shvidel, Martina Seiffert, Yair Herishanu, Shirly Becker-Herman, Idit Shachar
Usage data is cumulative from January 2019 through January 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.