Citations

Abstract Infection is a common cause of death in patients with advanced cirrhosis. We aimed to develop a predictive model in Child–Turcotte–Pugh (CTP) class C cirrhotics hospitalized with infection for optimizing treatment and improving outcomes. Clinical information was retrospectively abstracted from 244 patients at Tianjin Third Central Hospital, China (cohort 1). Factors associated with mortality were determined using logistic regression. The model for predicting 90-day mortality was then constructed by decision tree analysis. The model was further validated in 91 patients at Mayo Clinic, Rochester, MN (cohort 2) and 82 patients at Seoul St. Mary's Hospital, Korea (cohort 3). The predictive performance of the model was compared with that of the CTP, model for end-stage liver disease (MELD), MELD-Na, Chronic Liver Failure–Sequential Organ Failure Assessment, and the North American consortium for the Study of End-stage Liver Disease (NACSELD) models. The 3-month mortality was 58%, 58%, and 54% in cohort 1, 2, and 3, respectively. In cohort 1, respiratory failure, renal failure, international normalized ratio, total bilirubin, and neutrophil percentage were determinants of 3-month mortality, with odds ratios of 16.6, 3.3, 2.0, 1.1, and 1.03, respectively (P < .05). These parameters were incorporated into the decision tree model, yielding area under receiver operating characteristic (AUROC) of 0.804. The model had excellent reproducibility in the U.S. (AUROC 0.808) and Korea cohort (AUROC 0.809). The proposed model has the highest AUROC and best Youden index of 0.488 and greatest overall correctness of 75%, compared with other models evaluated. The proposed model reliably predicts survival of advanced cirrhotics with infection in both Asian and U.S. populations.

Key Points Cytokines in the BM microenvironment regulate PD-1 ligand expression and secretion in WM. Secreted PD-1 ligands modulate T-cell function in WM.

AbstractNOTCH1 is the prototype of the NOTCH family of single‐pass transmembrane receptors and regulates many basic processes during embryonic development and human pathogenesis. In core to NOTCH1 activation are proteolytic cleavages that release its intracellular domain (NICD1), which in turn translocates to the nucleus to regulate gene transcription. Macroautophagy (hereafter autophagy) has been shown to promote the degradation of NOTCH1, but the underlying mechanisms remain elusive. Here, we show that autophagy promotes the degradation of NOTCH1 by p62‐dependent binding between NICD1 and LC3, a component of the autophagosomes that execute autophagy. Strikingly, deleting any of the structural NICD1 domains fails to block the degradation of NICD1 by autophagy, and p62 binds to almost all these domains independently, indicating that p62 binds to multiple sites on NICD1 to promote its degradation. Intriguingly, inhibition of autophagy induces the accumulation of NICD1 in not only the cytoplasm but also the nucleus and increases the transcriptional activity of NICD1, and such regulation of nuclear NICD1 by autophagy is unique to NICD1 and not observed for all other NICDs (NICD2‐4). Collectively, our results suggest that autophagy tightly controls nuclear NOTCH1 activity through multiple p62 binding sites, and that modulating autophagy activity may be useful for treating NOTCH1 related human diseases. © 2018 IUBMB Life, 70(10):985–994, 2018

BackgroundPreoperative prediction of tumor recurrence is important in the management of patients with hepatocellular carcinoma (HCC).PurposeTo investigate whether tumor stiffness derived by magnetic resonance elastography (MRE) could predict early recurrence of HCC after hepatic resection.Study TypeRetrospective.PopulationIn all, 99 patients with pathologically confirmed HCCs after surgical resection.Field Strength/Sequence3.0T; preoperative MRE with 60‐Hz mechanical vibrations using an active acoustic driver.AssessmentRegions of interest (ROIs) were manually drawn in the tumors to measure mean tumor stiffness. Surgical specimens were reviewed for histological grade, capsule, vascular invasion, and surgical margins. The early recurrence of HCC was defined as that occurring within 2 years after resection.Statistical TestsCox proportional hazard models were used to evaluate risk factors associated with the time to early recurrence.ResultsHCCs with recurrence had higher tumor stiffness, higher rate of advanced T stage, vascular invasion, lower rate of capsule formation, larger tumor size, higher aspartate aminotransferase (AST), and hepatitis B virus (HBV)‐DNA level and aspartate aminotransferase / alanine aminotransferase ratio (P = 0.031, 0.007, 0.01, <0.001, 0.015, 0.034, 0.01, and 0.014, respectively) than HCCs without recurrence. Vascular invasion (hazard ratio [HR] = 2.922; 95% confidence interval [CI]: [1.079, 7.914], P = 0.035) and mean tumor stiffness (HR = 1.163; 95% CI: [1.055, 1.282], P = 0.002) were risk factors associated with early recurrence. Each 1‐kPa increase in tumor stiffness was associated with a 16.3% increase in the risk for tumor recurrence.Data ConclusionThe mean stiffness of HCCs may be a useful, noninvasive, quantitative biomarker for the prediction of early HCC recurrence after hepatic resection.Level of Evidence: 4Technical Efficacy: Stage 5J. Magn. Reson. Imaging 2019;49:719–730.

11599 Background: It is unclear whether survival varies among breast cancer molecular subtypes without systemic and locoregional therapy. This study aims to evaluate the survival profile by molecular subtypes after surgery. Methods: In total, we evaluated 301 women with invasive breast cancer with stage I, II or III disease. Patients were classified into four major breast cancer subtypes by immunohistochemistry/FISH classifiers: luminal-A (ER+ and/or PR+/HER2-), luminal-B (ER+ and/or PR+/HER2+), HER2-enriched (HER2+/ER-/PR-) or basal-like (ER-/PR-/HER2-; triple-negative). Overall survival (OS) was analyzed by Kaplan-Meier analysis, and log-rank test for differences. Association between clinical outcome and subtype adjusting for breast cancer prognostic factors was assessed by multivariable Cox proportional hazards model. Results: All patients did not receive systemic chemotherapy and hormone therapy as well as radiation therapy. Luminal A was the most common subtype (N = 224), followed by basal-like (N = 43), luminal B (N = 21) and HER2-enriched (N = 13). Median follow-up for OS was 197 months (range: 1 – 273 months). Age at diagnosis was statistically different among the subtypes, with basal-like and luminal B having high proportions less than 50 years (P = 0.047). Patients with basal-like and HER2-enriched had more high grade tumors (P < 0.001). Notably, there was no difference in OS among the four subtypes (log-rank P = 0.983). In multivariable analysis, the adjusted hazard ratio (HR) was 1.1 for luminal A vs. luminal B (P = 0.781), 0.62 in luminal A vs. HER2-enriched (P = 0.273), or 0.67 in luminal A vs. basal-like (P = 0.158). In contrast, the adjusted HR were 2.2 in age less than 50 years (P = 0.0017), and 1.1 for number of positive nodes (P = 0.00074). Conclusions: OS, through long-term clinical follow-up, is not significantly different among molecular subtypes if not controlling for other prognostic factors in patients who only received surgery. Age and number of positive nodes are independent prognostic factors in patients with no systemic and locoregional treatments.