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The sphingolipid sphingosine-1-phosphate (S1P) promotes tumor development through a variety of mechanisms including promoting proliferation, survival, and migration of cancer cells. Moreover, S1P emerged as an important regulator of tumor microenvironmental cell function by modulating, among other mechanisms, tumor angiogenesis. Therefore, S1P was proposed as a target for anti-tumor therapy. The clinical success of current cancer immunotherapy suggests that future anti-tumor therapy needs to consider its impact on the tumor-associated immune system. Hereby, S1P may have divergent effects. On the one hand, S1P gradients control leukocyte trafficking throughout the body, which is clinically exploited to suppress auto-immune reactions. On the other hand, S1P promotes pro-tumor activation of a diverse range of immune cells. In this review, we summarize the current literature describing the role of S1P in tumor-associated immunity, and we discuss strategies for how to target S1P for anti-tumor therapy without causing immune paralysis.
The lung tumor microenvironment plays a critical role in the tumorigenesis and metastasis of lung cancer, resulting from the crosstalk between cancer cells and microenvironmental cells. Therefore, comprehensive identification and characterization of cell populations in the complex lung structure is crucial for development of novel targeted anti-cancer therapies. Here, a hierarchical clustering approach with multispectral flow cytometry was established to delineate the cellular landscape of murine lungs under steady-state and cancer conditions. Fluorochromes were used multiple times to be able to measure 24 cell surface markers with only 13 detectors, yielding a broad picture for whole-lung phenotyping. Primary and metastatic murine lung tumor models were included to detect major cell populations in the lung, and to identify alterations to the distribution patterns in these models. In the primary tumor models, major altered populations included CD324+ epithelial cells, alveolar macrophages, dendritic cells, and blood and lymph endothelial cells. The number of fibroblasts, vascular smooth muscle cells, monocytes (Ly6C+ and Ly6C–) and neutrophils were elevated in metastatic models of lung cancer. Thus, the proposed clustering approach is a promising method to resolve cell populations from complex organs in detail even with basic flow cytometers.