Ferroptosis is an iron- and lipotoxicity-dependent form of regulated cell death (RCD). It is morphologically and biochemically distinct from characteristics of other cell death. This modality has been intensively investigated in recent years due to its involvement in a wide array of pathologies, including cancer, neurodegenerative diseases, and acute kidney injury. Dysregulation of ferroptosis has also been linked to various liver diseases and its modification may provide a hopeful and attractive therapeutic concept. Indeed, targeting ferroptosis may prevent the pathophysiological progression of several liver diseases, such as hemochromatosis, nonalcoholic steatohepatitis, and ethanol-induced liver injury. On the contrary, enhancing ferroptosis may promote sorafenib-induced ferroptosis and pave the way for combination therapy in hepatocellular carcinoma. Glutathione peroxidase 4 (GPx4) and system xc− have been identified as key players to mediate ferroptosis pathway. More recently diverse signaling pathways have also been observed. The connection between ferroptosis and other forms of RCD is intricate and compelling, where discoveries in this field advance our understanding of cell survival and fate. In this review, we summarize the central molecular machinery of ferroptosis, describe the role of ferroptosis in non-cancer hepatic disease conditions and discuss the potential to manipulate ferroptosis as a therapeutic strategy.

Background Alterations in body compositions are related to poor outcomes and the presence of complications in cirrhosis. However, no predictive tools combining all these anthropometric parameters are applicable in the clinical setting. We aimed to clarify the potential utility of body compositions and develop a nomogram incorporating any independent factor for prognosticating long‐term mortality in cirrhosis. Methods A total of 414 patients were randomized into primary (n = 274) and validation (n = 140) cohorts. X‐tile was performed to identify optimal cut points for stratifying participants. Multivariate Cox regression was performed, and nomogram incorporating body compositions were generated. The utility of developed models was evaluated by Harrell concordance index (C‐index), calibration curve, and decision curve analysis (DCA). Results Stratifying by X‐tilederived cut points, low skeletal muscle index (myopenia), high intramuscular adipose tissue content (myosteatosis), and the ratio of high visceral to subcutaneous adipose tissue area (adiposity) was independently associated with 3‐year mortality. A sex‐stratified nomogram incorporating anthropometric indices and clinical factors resulted in moderate discriminative accuracy, with a C‐index of 0.787 (95% CI, 0.736–0.838) and 0.789 (95% CI, 0.727–0.851) in males and females, respectively. The calibration curve showed predictive survival corresponding optimally with the actual outcomes. Our models were feasible in the clinical settings based on DCA. Similar results were observed in the validation cohort. Additionally, participants could be classified into 3 distinct risk groups by the nomogram. Conclusions Our proposed nomogram embedding body compositions rendered an individualized predictive tool for long‐term mortality in cirrhosis.

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Background Liver cirrhosis is characterized by immune dysfunction, contributing to malnutrition. We previously revealed neutrophil‐to‐lymphocyte ratio (NLR) as an indicator of disordered immune system. Herein we aimed to (1) determine the optimal NLR cutoff that best predicts malnutrition risk and (2) clarify the association between NLR and nutrition status. Methods A total of 135 hospitalized patients with cirrhosis were included. Immune dysfunction was evaluated by levels of serum C‐reactive protein (CRP), NLR, and other parameters. Malnutrition was screened by a risk score referring to the Royal Free Hospital–Nutritional Prioritizing Tool (RFH‐NPT). Receiver operating characteristic (ROC) curve was implemented to determine the best NLR cutoff that predicts malnutrition risk. Correlation between NLR and indicators of hepatic and physical function (handgrip strength) were also examined. Multivariable logistic regression was used to assess the association between NLR and malnutrition risk. Results ROC curve revealed that the optimum cutoff to predict malnutrition risk was NLR > 4.2, with a sensitivity of 47.2%, specificity of 81.0%, negative predictive value of 58.0%, and positive predictive value of 74.5%, respectively. Patients with NLR > 4.2 exhibited a higher RFH‐NPT score, serum platelet‐to‐lymphocyte ratio, and CRP. A positive correlation was found between NLR values and Child‐Turcotte‐Pugh (r = 0.22; P = .010), model for end‐stage liver disease (r = 0.36; P < .001), and RFH‐NPT scores (r = 0.31; P < .001). NLR was a risk factor for malnutrition independently of alcoholic liver disease and presence of ascites. Conclusions Immune dysfunction measured by NLR was associated with malnutrition risk estimated by RFH‐NPT in cirrhosis.