Structural insights into the ubiquitylation strategy of the oligomeric CRL2FEM1B E3 ubiquitin ligase.

Cullin-RING E3 ubiquitin ligase (CRL) family members play critical roles in numerous biological processes and diseases including cancer and Alzheimer's disease. Oligomerization of CRLs has been reported to be crucial for the regulation of their activities. However, the structural basis for its regulation and mechanism of its oligomerization are not fully known. Here, we present cryo-EM structures of oligomeric CRL2FEM1B in its unneddylated state, neddylated state in complex with BEX2 as well as neddylated state in complex with FNIP1/FLCN. These structures reveal that asymmetric dimerization of N8-CRL2FEM1B is critical for the ubiquitylation of BEX2 while FNIP1/FLCN is ubiquitylated by monomeric CRL2FEM1B. Our data present an example of the asymmetric homo-dimerization of CRL. Taken together, this study sheds light on the ubiquitylation strategy of oligomeric CRL2FEM1B according to substrates with different scales.

Development of ensemble learning models for prognosis of hepatocellular carcinoma patients underwent postoperative adjuvant transarterial chemoembolization.

Background: Postoperative adjuvant transarterial chemoembolization (PA-TACE) has been increasing widely used to improve the prognosis of hepatocellular carcinoma (HCC) patients. However, clinical outcomes vary from patient to patient, which calls for individualized prognostic prediction and early management. Methods: A total of 274 HCC patients who underwent PA-TACE were enrolled in this study. The prediction performance of five machine learning models was compared and the prognostic variables of postoperative outcomes were identified. Results: Compared with other machine learning models, the risk prediction model based on ensemble learning strategies, including Boosting, Bagging, and Stacking algorithms, presented better prediction performance for overall mortality and HCC recurrence. Moreover, the results showed that the Stacking algorithm had relatively low time consumption, good discriminative ability, and the best prediction performance. In addition, according to time-dependent ROC analysis, the ensemble learning strategies were found to perform well in predicting both OS and RFS for the patients. Our study also found that BCLC Stage, hsCRP/ALB and frequency of PA-TACE were relatively important variables in both overall mortality and recurrence, while MVI contributed more to the recurrence of the patients. Conclusion: Among the five machine learning models, the ensemble learning strategies, especially the Stacking algorithm, could better predict the prognosis of HCC patients following PA-TACE. Machine learning models could also help clinicians identify the important prognostic factors that are clinically useful in individualized patient monitoring and management.

Exosomes derived from human adipose mesenchymal stem cells ameliorate hepatic fibrosis by inhibiting PI3K/Akt/mTOR pathway and remodeling choline metabolism.

Liver fibrosis is a chronic liver disease with the presence of progressive wound healing response caused by liver injury. Currently, there are no approved therapies for liver fibrosis. Exosomes derived from human adipose mesenchymal stem cells (hADMSCs-Exo) have displayed a prominent therapeutic effect on liver diseases. However, few studies have evaluated therapeutic effect of hADMSCs-Exo in liver fibrosis and cirrhosis, and its precise mechanisms of action remain unclear. Herein, we investigated anti-fibrotic efficacy of hADMSCs-Exo in vitro and in vivo, and identified important metabolic changes and the detailed mechanism through transcriptomic and metabolomic profiling. We found hADMSCs-Exo could inhibit the proliferation of activated hepatic stellate cells through aggravating apoptosis and arresting G1 phase, effectively inhibiting the expression of profibrogenic proteins and epithelial-to-mesenchymal transition (EMT) in vitro. Moreover, it could significantly block collagen deposition and EMT process, improve liver function and reduce liver inflammation in liver cirrhosis mice model. The omics analysis revealed that the key mechanism of hADMSCs-Exo anti-hepatic fibrosis was the inhibition of PI3K/AKT/mTOR signaling pathway and affecting the changes of metabolites in lipid metabolism, and mainly regulating choline metabolism. CHPT1 activated by hADMSCs-Exo facilitated formation and maintenance of vesicular membranes. Thus, our study indicates that hADMSCs-Exo can attenuate hepatic stellate cell activation and suppress the progression of liver fibrosis, which holds the significant potential of hADMSCs-Exo for use as extracellular nanovesicles-based therapeutics in the treatment of liver fibrosis and possibly other intractable chronic liver diseases.

The prognostic significance of inflammation-immunity-nutrition score on postoperative survival and recurrence in hepatocellular carcinoma patients.

Background: Inflammation, immunity, and nutrition status play important roles in tumorigenesis, progression, and metastasis. This study aimed to evaluate the prognostic value of Inflammation-Immunity-Nutrition Score (IINS) for overall survival (OS) and progression-free survival (PFS) in patients with hepatocellular carcinoma (HCC) undergoing radical surgery. Methods: A total of 204 HCC patients who met the criteria were included in this retrospective study: 144 in the prediction model and 60 in the validation model. IINS was constructed based on the sum of classification scores of preoperative high-sensitivity C-reactive protein (hsCRP), lymphocyte (LYM), and albumin (ALB). The associations between the IINS group and the clinicopathologic characteristics were analyzed using Pearson's χ2 test or Fisher's exact test. Multivariate Cox regression analysis was used to evaluate variables significant on univariate analysis. Kaplan-Meier survival curves were conducted to investigate the prognostic values of IINS, Alpha-fetoprotein (AFP) and IINS-AFP classification. The prognostic performances of all the potential prognostic factors were further compared by receiver operating characteristic (ROC) curve, and time-dependent ROC curve. The internal validation and external validation were used to ensure the credibility of this prediction model. Results: The patients were divided into low and high IINS groups according to the median of IINS. According to multivariate Cox regression analyses, the Barcelona Clinic Liver Cancer (BCLC) Stage (P=0.003), AFP (P=0.013), and IINS (P=0.028) were independent prognostic factors for OS, and BCLC Stage (P=0.009), microvascular invasion (P=0.030), and IINS (P=0.031) were independent prognostic factors for PFS. High IINS group were associated with significantly worse OS and PFS compared with low IINS group (P<0.001; P=0.004). In terms of clinical prognosis, IINS-AFP classification was good in group I, moderate in group II, and poor in group III. Group I had a longer OS (P<0.001) and PFS (P=0.008) compared with group II and III. ROC analysis revealed that IINS-AFP classification had a better prognostic performance for OS (AUC: 0.767) and PFS (AUC: 0.641) than other predictors, excluding its slightly lower predictive power for PFS than IINS. The time-dependent ROC curves also showed that both IINS (12-month AUC: 0.650; 24-month AUC: 0.670; 36-month AUC: 0.880) and IINS-AFP classification (12-month AUC: 0.720; 24-month AUC: 0.760; 36-month AUC: 0.970) performed well in predicting OS for HCC patients. Furthermore, the internal validation and external validation proved that IINS had good predictive performance, strong internal validity and external applicability, and could be used to establish the prediction model. Conclusion: Inflammation-immunity-nutrition score could be a powerful clinical prognostic indicator in HCC patients undergoing radical surgery. Furthermore, IINS-AFP classification presents better prognostic performance than IINS or AFP alone, and might serve as a practical guidance to help patients adjust treatment and follow-up strategies to improve future outcomes.

Comparative study of indocyanine green (ICG)-R15 and Albumin-Indocyanine Green Evaluation (ALICE) grading system in the prediction of posthepatectomy liver failure and postoperative mortality in patients with hepatic alveolar echinococcosis.

BACKGROUND: A precise evaluation of liver reserve function in patients with hepatic alveolar echinococcosis (HAE) prior to hepatectomy could substantially increase the success rate of the operation and reduce the incidence of postoperative complications. The present study aimed to investigate the significance of the indocyanine green retention test at 15 min (ICG-R15) and the Albumin-Indocyanine Green Evaluation (ALICE) grading system in predicting severe posthepatectomy liver failure (PHLF) and postoperative mortality in HAE patients undergoing liver resection. METHODS: A total of 105 HAE patients undergoing hepatectomy were enrolled in this study. The value of each variable in predicting severe PHLF was evaluated by univariate and multivariate logistic regression analyses. The area under the receiver operating characteristic (ROC) curves (AUC) were calculated to evaluate the predictive ability of the Child-Pugh grade, ICG-R15, and ALICE grading system. Also, patients were classified using the optimal cutoff value for ICG-R15 and different ALICE grades, and the incidence of severe PHLF and postoperative mortality were compared with the predicted values. RESULTS: Out of the 105 HAE patients enrolled in this study, 34 patients (32.4%) developed severe PHLF. The ALICE grade and operative time were identified as independent predictors of severe PHLF. According to ROC analysis, the AUCs of the Child-Pugh grade, ICG-R15, and ALICE grade for predicting severe PHLF were 0.733 (95% confidence interval (CI), 0.637-0.814), 0.823 (95% CI, 0.737-0.891), 0.834 (95% CI, 0.749-0.900). The incidence of severe PHLF and postoperative 90-day mortality in patients with ICG-R15 > 7.2% were significantly higher than those with ICG-R15 ≤ 7.2% (P < 0.001; P = 0.008). Likewise, the incidence of severe PHLF and postoperative 90-day mortality in patients with ALICE grade 2 were higher than those with ALICE grade 1 within the Child-Pugh grade A (P < 0.001; P = 0.083). CONCLUSION: ICG-R15 and ALICE grading system are powerful predictors of severe PHLF and postoperative mortality among HAE patients undergoing hepatectomy. Furthermore, a combination of the preoperative Child-Pugh grade and ALICE grading system may provide an even more precise and objective guidance and facilitate surgical decision-making for HAE patients.

Transmembrane Protein 170B is a Prognostic Biomarker and Associated With Immune Infiltrates in Pancreatic Adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is among the most common types of cancer with a poor prognosis. Transmembrane protein 170B (TMEM170B) has been reported to suppress breast cancer proliferation, metastasis, and tumorigenesis and is related to prognosis. However, its role in PAAD and the underlying molecular mechanisms are yet to be investigated. Patients and methods: We performed a comprehensive analysis of RNA sequencing data obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to determine TMEM170B expression. Immunostaining and real-time polymerase chain reaction (RT-PCR) were done to determine TMEM170B expression in human pancreatic cancer cell lines and tissue specimens. Furthermore, the correlation of TMEM170B with clinicopathological features and PAAD prognosis was investigated, and the mechanisms were explored through enrichment analysis and immune cell infiltration analysis. Results: TCGA and GEO dataset analysis revealed that TMEM170B expression in PAAD tissue samples was significantly lower than that in non-tumorous tissues, which was further confirmed by immunohistochemistry and RT-PCR. Low TMEM170B expression was associated with poor differentiation (p = 0.014). Multivariate analysis identified that TMEM170B is an independent indicator for overall survival [hazard ratio (HR) = 0.116, 95% confidence interval (CI) = 0.014-0.995; p = 0.049] and disease-free survival (HR = 0.19, 95% CI = 0.04-0.910; p = 0.038) in patients with PAAD. Additionally, TMEM170B was involved in immune-related gene sets, including those related to chemokine signaling pathways and innate and adaptive immunity. High TMEM170B expression was linked to antitumor immune microenvironment with a high infiltration of B cells, T cells, dendritic cells, monocytes, M1 macrophages, neutrophil, and natural killer cells and a low infiltration of Tregs and myeloid-derived suppressor cells (all p < 0.05). Plain Language Summary: There is an urgent need to identify clinical prognostic biomarkers and targeted drugs for pancreatic cancer treatment. In this study, the expression status and prognostic value of transmembrane protein 170B (TMEM170B) in pancreatic adenocarcinoma were elucidated. Furthermore, TMEM170B, as a tumor suppressor gene, induced antitumor immune effects, including increased tumor infiltration of immune effector cells and reduced levels of inhibitory immune molecules and regulatory cells. Therefore, TMEM170B could be regarded as a novel target in preventing the progression of pancreatic cancer. Conclusion: The findings suggest that low TMEM170B expression is remarkably correlated with poor PAAD prognosis, which might provide a therapeutic target for PAAD.

Prognostic value of inflammation-immunity-nutrition score in patients with hepatocellular carcinoma treated with anti-PD-1 therapy.

BACKGROUND: There are no validated biomarkers that can predict the clinical benefit of immune checkpoint blockers against the programmed cell death protein 1 (PD-1) treatments in hepatocellular carcinoma (HCC). This study aimed to investigate the prognostic value of inflammation-immunity-nutrition score (IINS) in patients with HCC treated with anti-PD-1 therapy. METHODS: A consecutive series of 101 HCC patients treated with PD-1 inhibitors in Sichuan Provincial People's Hospital between January 2018 and August 2020 were enrolled in the retrospective study. IINS (0-6) was constructed based on pretreatment high-sensitivity C-reactive protein (hsCRP), lymphocyte (LYM), and albumin (ALB). The patients were divided into high and low IINS groups according to IINS values. Prognostic values of each variable were evaluated with univariate and multivariate time-dependent Cox regression analyses. Survival curves were calculated and compared using the Kaplan-Meier method and log-rank test. The prognostic performance of IINS was further compared with that of other traditional prognostic indicators by receiver operating characteristic (ROC) curve and the areas under the ROC curve. RESULTS: Patients with low IINS had longer overall survival (OS) (HR: 4.711, 95% CI: 1.80-12.37, p = .001) and progression-free survival (HR: 3.411, 95% CI: 1.79-6.51, p < .0001) than those with high IINS. The multivariate analysis identified IINS (HR: 3.746, 95% CI: 1.05-13.38, p = .042) and tumor number (HR: 5.111, 95% CI: 1.075-24.299, p = .04) as independent prognostic factors. According to ROC analysis, IINS (AUC =0.729, 95% CI: 0.597-0.861, p = .002) presented better prognostic performance than other traditional prognostic indicators. The area of the IINS-CA19-9 under the ROC curve (AUC) was higher than that of the IINS or CA19-9 levels for the prediction of OS. CONCLUSION: The results suggest that IINS may be an independent prognostic indicator for HCC patients treated with anti-PD-1 therapy. IINS-CA19-9 classification may be more effective in predicting clinical benefit of anti-PD-1 therapy in HCC patients.