Hepatic cells-induced immune responses exhibit anti-tumor function through non-cytotoxic liver homeostasis pathways 2981

Abstract Description The exact functionality of hepatic immune cells in nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC) remain poorly understood. Utilizing a systems immunology approach, we identified that the reciprocal cell-cell communication networks operate through a dominant-subdominant pattern of ligand-receptor signaling pathways, primarily involved in homeostasis. In healthy controls, immune responses mainly function through homeostatic pathways. Chronic consumption of a Western diet (WD) altered hepatocyte function and led to communication events dominated by hepatic stellate cells (HSCs), cancer cells, and NKT cells, with 80% of NKT cells involved in hepatic homeostasis during NAFLD. During NAFLD-induced HCC, 80% of all immune cells, specifically NKT cells and monocytes, collaborated with hepatocytes and myofibroblasts to restore liver homeostasis. Dietary correction strategies during NAFLD led to divergent outcomes: HCC development was associated with failure to maintain homeostatic immune responses, while tumor prevention correlated with sustained homeostatic immune responses driven mainly by monocytes. Importantly, only 5% of T and NKT cells exhibited apoptosis-inducing functions, mainly engaged in homeostatic turnover of fibroblasts and myofibroblasts. Our results suggest that effective anti-tumor immune responses operate as a system via tissue homeostatic pathways that modulate the microenvironment, rather than direct cytotoxicity against tumors. Funding Sources This work was supported by funding from NIH R01DK105961, 2017-MIP-2, the Office of the Assistant Secretary of Defense for Health Affairs through the Breast Cancer Research Program under W81XWH2210793, the National Center for Advancing Translational Sciences under UL1TR002649, and the VCU Cancer Mouse Models Core Shared Resource supported, in part, by Cancer Center Support Grant P30 CA 016059. Topic Categories Computational and Systems Immunology (COMP)