Cancer cells harness immune checkpoints such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), programmed cell death protein 1 (PD-1) and indoleamine 2,3-dioxygenase 1 (IDO1) to evade immune control. Checkpoint inhibitors have demonstrated durable anti-tumor efficacy in human and preclinical models. Liver toxicity is one of the common immune-related adverse events associated with checkpoint inhibitors (CPIs) and its frequency and severity often increase significantly during CPI combination therapies. We aim to develop a mouse model to elucidate the immune mechanisms of CPI-associated liver toxicity. Co-administration of CTLA-4 blocking antibody, 9D9, and/or an IDO1 inhibitor, epacadostat in wild-type and PD-1 -/- mice (to simulate the effect of PD1 blockade) synergistically induced liver injury and immune cell infiltration. Infiltrated cells were primarily composed of CD8+ T cells and positively associated with hepatocyte necrosis. Strikingly, sites of hepatocyte necrosis were frequently surrounded by clusters of mononuclear immune cells. CPI treatments resulted in increased expression of genes associated with hepatocyte cell death, leukocyte migration and T cell activation in the liver. In conclusion, blockade of immune checkpoints PD-1, CTLA-4, and IDO1 act synergistically to enhance T cell infiltration and activity in the liver, leading to hepatocyte death.
Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and post marketing. The objective of this study was to evaluate the diagnostic performance of promising biomarkers of liver injury—glutamate dehydrogenase (GLDH), cytokeratin-18 (K18), caspase-cleaved K18 (ccK18), osteopontin (OPN), macrophage colony-stimulating factor (MCSF), MCSF receptor (MCSFR), and microRNA-122 (miR-122) in comparison to the traditional biomarker alanine aminotransferase (ALT). Biomarkers were evaluated individually and as a multivariate model in a cohort of acetaminophen overdose (n = 175) subjects and were further tested in cohorts of healthy adults (n = 135), patients with liver damage from various causes (n = 104), and patients with damage to the muscle (n = 74), kidney (n = 40), gastrointestinal tract (n = 37) and pancreas (n = 34). In the acetaminophen cohort, a multivariate model with GLDH, K18 and miR-122 was able to detect DILI more accurately than individual biomarkers alone. Furthermore, the three-biomarker model could accurately predict patients with liver injury compared to healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract and kidney. Expression of K18, GLDH ad miR-122 was evaluated using a database of transcriptomic profiles across multiple tissues/organs in humans and rats. K18 mRNA (Krt18) and MiR-122 were highly expressed in liver whereas GLDH mRNA (Glud1) was widely expressed. We performed a comprehensive, comparative performance assessment of seven promising biomarkers and demonstrated that a three-biomarker multivariate model can accurately detect liver injury.
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