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Background Recurrent hepatocellular carcinoma (HCC) shows strong resistance to sorafenib, and the tumor-repopulating cells (TRCs) with cancer stem cell-like properties are considered a driver for its high recurrent rate and drug resistance. Methods Suppression of TRCs may thus be an effective therapeutic strategy for treating this fatal disease. We evaluated the pharmacology and mechanism of sulfarotene, a new type of synthetic retinoid, on the cancer stem cell-like properties of HCC TRCs, and assessed its preclinical efficacy in models of HCC patient-derived xenografts (PDXs). Results Sulfarotene selectively inhibited the growth of HCC TRCs in vitro and significantly deterred TRC-mediated tumor formation and lung metastasis in vivo without apparent toxicity, with an IC50 superior to that of acyclic retinoid and sorafenib, to which the recurrent HCC exhibits significant resistance at advanced stage. Sulfarotene promoted the expression and activation of RARα, which down-regulated SOS2, a key signal mediator associated with RAS activation and signal transduction involved in multiple downstream pathways. Moreover, sulfarotene selectively inhibited tumorigenesis of HCC PDXs with high expression for SOS2. Conclusions Our study identified sulfarotene as a selective inhibitor for the TRCs of HCC, which targets a novel RARα-SOS2-RAS signal nexus, shedding light on a new, promising strategy of target therapy for advanced liver cancer.

Immunity plays an important role in tumor development. In this study, we aimed to investigate molecular classification and its prognostic value in hepatocellular carcinoma (HCC) based on immune signature. Gene set enrichment analysis (GSEA) was used to calculate scores of immune pathways for HCC and hierarchical clustering in two databases (The Cancer Genome Atlas [TCGA], Liver Cancer-RIKEN, JP [LIRI_JP]). The scores of the immune microenvironment and the proportions of 22 immune cells were also calculated. Single-sample GSEA (ssGSEA) was used to screen survival prognosis-related immune pathways and calculate the hazard radio of differentially expressed immune-related genes (IRGs), which were validated in clinical samples and multiple datasets. Based on the immune characteristics, we identified three HCC subtypes, namely immunity high (Immunity_H), immunity medium (Immunity_M), and immunity low (Immunity_L), and confirmed that the classification was reliable and predictable. Immunity_H with a higher immune and stromal score indicated better survival rate. Cox regression analysis showed that IL18RAP and IL7R were the protective genes. Immune risk score was the independent risk factor of overall survival in HCC patients. These results indicated that immunogenomic classification could distinguish HCC patients with different immune status, which could impact the prognosis of the patients with HCC., Graphical abstract, Weiwei et al. provided an immunogenomic classification based on immune characteristics to distinguish hepatocellular carcinoma (HCC) patients with different immune status, and the prediction model can be used for individual immunotherapy of HCC patients.

Background Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results for stratifying acute pancreatitis (AP) severity. Results We identified 11 markers predictive of AP severity and trained an AP stratification model called APSAVE, which classified AP cases within 24 hours at an average area under the curve (AUC) of 0.74 +/- 0.04. It was further validated in 568 validation cases, achieving an AUC of 0.73, which is similar to that of Ranson's criteria (AUC = 0.74) and higher than APACHE II and BISAP (AUC = 0.69 and 0.66, respectively). Conclusions We developed and validated a venous blood marker-based AP severity stratification model with higher accuracy and broader applicability, which holds promises for reducing SAP mortality and improving its clinical outcomes. Materials and methods Nine hundred and forty-five AP patients were enrolled into this study. Clinical venous blood tests covering 65 biomarkers were performed on AP patients within 24 hours of admission. An SAP prediction model was built with statistical learning to select biomarkers that are most predictive for AP severity.

In this study, we reported a highly sensitive method for detecting carcinoembryonic antigen (CEA) based on an azide cofunctionalized graphene oxide (GO-N3) and carbon dot (CDs) biosensor system. Carbon dots-labeled DNA (CDs-DNA) combined with GO-N3 using copper-free click chemistry (CFCC), which quenched the fluorescence of the CDs via fluorescence resonance energy transfer (FRET). Upon the addition of CEA, fluorescence was recovered due to the combination of CEA and aptamer. Under optimal conditions, the relative fluorescence intensity was linear with CEA concentration in the range of 0.01–1 ng/mL (R2 = 0.9788), and the limit of detection (LOD) was 7.32 pg/mL (S/N = 3). This biosensor had a high sensitivity and good selectivity for CEA detection in serum samples, indicating that the novel sensor platform holds a great potential for CEA and other biomarkers in practical applications.

Background Emerging evidence suggests that competing endogenous RNAs plays a crucial role in the development and progress of pancreatic adenocarcinoma (PAAD). The objective was to identify a new lncRNA-miRNA-mRNA network as prognostic markers, and develop and validate a multi-mRNAs-based classifier for predicting overall survival (OS) in PAAD. Methods Data on pancreatic RNA expression and clinical information of 445 PAAD patients and 328 normal subjects were downloaded from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and Genotype-Tissue Expression (GTEx). The weighted correlation network analysis (WGCNA) was used to analyze long non-coding RNA (lncRNA) and mRNA, clustering genes with similar expression patterns. MiRcode was used to predict the sponge microRNAs (miRNAs) corresponding to lncRNAs. The downstream targeted mRNAs of miRNAs were identified by starBase, miRDB, miRTarBase and Targetscan. A multi-mRNAs-based classifier was develop using least absolute shrinkage and selection operator method (LASSO) COX regression model, which was tested in an independent validation cohort. Results A lncRNA-miRNA-mRNA co-expression network which consisted of 60 lncRNAs, 3 miRNAs and 3 mRNAs associated with the prognosis of patients with PAAD was established. In addition, we constructed a 14-mRNAs-based classifier based on a training cohort composed of 178 PAAD patients, of which the area under receiver operating characteristic (AUC) in predicting 1-year, 3-year, and 5-year OS was 0.719, 0.806 and 0.794, respectively. The classifier also shown good prediction function in independent verification cohorts, with the AUC of 0.604, 0.639 and 0.607, respectively. Conclusions A novel competitive endogenous RNA (ceRNA) network associated with progression of PAAD could be used as a reference for future molecular biology research.

We aimed to examine the therapeutic potential of polysaccharide H-1-2, a bioactive component of Pseudostellaria heterophylla, against pancreatic cancer, as well as to demonstrate the underlying molecular mechanisms. Invasion and migration of pancreatic cells treated with H-1-2 were evaluated. A xenograft tumor mouse model was established to assess the effect of H-1-2 on tumor growth. Expression levels of hypoxic inducible factor-1α (HIF1α) and anterior gradient 2 (AGR2) were measured in pancreatic cells after H-1-2 treatment. Luciferase report and chromatin immunoprecipitation assays were conducted to investigate HIF1α regulation on AGR2. AGR2 expression was re-introduced into pancreatic cells to assess the role of AGR2 as a downstream effector of hypoxia after H-1-2 treatment. H-1-2 inhibited invasion and migration of pancreatic cancer cells, repressed xenograft pancreatic tumor growth, and increased survival of mice. H-1-2 repressed AGR2 expression in pancreatic cancer cells through the hypoxia response element (HRE) in its promoter region. Ectopic AGR2 expression partially negated the H-1-2 inhibitory effect on invasion and migration of pancreatic cells and on xenograft pancreatic tumors growth, and it also compromised the H-1-2 promotional effect on survival of mice. We conclude that H-1-2 suppresses pancreatic cancer by inhibiting hypoxia-induced AGR2 expression, supporting further investigation into its efficacy against pancreatic cancer in clinical settings., Graphical Abstract, The therapeutic potential of polysaccharide H-1-2, a bioactive component of Pseudostellaria heterophylla, against pancreatic cancer was investigated in this study. We found that the polysaccharide H-1-2 suppresses pancreatic cancer by inhibiting hypoxia-induced AGR2 expression, supporting further investigation into its efficacy against pancreatic cancer in clinical settings.

Aim: The current work highlighted a novel colorimetric sensor based on aptamer and molybdenum disulfide (MoS2)-gold nanoparticles (AuNPs) that was developed for cocaine detection with high sensitivity. Materials & methods: Due to the presence of the plasmon resonance band on the surface of AuNPs, AuNPs aggregated and the color was changed from red to blue after adding a certain concentration of NaCl. We used MoS2 to optimize the sensing system of AuNPs. The folded conformation of the aptamer in combination with cocaine enhanced the salt tolerance of the MoS2-AuNPs, effectively preventing their aggregation. Results & conclusion: The detection limit of cocaine was 7.49 nM with good selectivity. The method based on MoS2-AuNPs colorimetry sensor is simple, quick, label-free and low cost.

Objectives The aim was to evaluate the safety and effectiveness of thalidomide, an immunomodulatory agent, in combination with glucocorticoid, for the treatment of COVID-19 patients with life-threatening symptoms. Methods A nonrandomized comparative case series study was performed. Six patients received thalidomide 100 mg per day (with therapy lasting for ≥7 days) plus low-dose short-term dexamethasone, and 6 control patients matched with patients in the thalidomide group, received low-dose short-term treatment with dexamethasone alone. The main outcomes were: the duration of SARS-CoV-2 negative conversion from admission; length of hospital stay; and changes in inflammatory cytokine concentrations and lymphocyte subsets. Results The median thalidomide treatment time was 12.0 days. The median duration of SARS-CoV-2 negative conversion from admission and hospital stay length were briefer in the thalidomide group compared to the control group (respectively, 11.0 vs 23.0 days, P = 0.043; 18.5 vs 30.0 days, P = 0.043). The mean reduction rates at 7–10 days after treatment for serum interleukin-6 and interferon-γ concentrations were greater in the thalidomide group compared to the control group. Alterations in lymphocyte numbers in the subsets between the 2 groups were similar. Conclusions Thalidomide plus short-term glucocorticoid therapy is an effective and safe regimen for the treatment of severely ill COVID-19 patients. The mechanism of action is most likely inhibition of inflammatory cytokine production.

An amendment to this paper has been published and can be accessed via the original article.

Background Acute pancreatitis (AP) is a clinically common acute inflammatory disease in digestive system, leading to systemic inflammatory response syndrome (SIRS) and severe acute pancreatitis (SAP). It was reported that PINK1/PARK2 dependent mitophagy played an important role in various inflammatory diseases. However, its role in AP has not been elucidated. Herein, we explore the effect of mitophagy in the pathogenesis of AP. Methods Firstly, we established cerulein-induced AP group and arginine-induced SAP group based on wild, PINK1-/- and PARK2-/- mice. Pancreatic samples were harvested for further investing the mitochondrial dynamics, mitophagy alterations, NLRP3 inflammatory pathway etc. Furthermore, peripheral blood mononuclear cells from SAP patients were collected to examine the expression of mitophagy-related indicators. Additionally, the interrelationship between mitophagy and NLRP3 inflammasome was also explored in AP. Results It was confirmed that mitochondria were damaged in both AP and SAP models. The expressions of PINK1, PARK2 and mitochondrial autophagosomes were elevated in wild AP group, which were decreased in SAP group over time. Similarly, the expressions of PINK1 and PAKR2 in peripheral blood mononuclear cells were significantly lower in SAP patients. Besides, in PINK1-/- and PARK2-/- mice AP groups, more pronounced inflammatory infiltration, increased apoptotic and necrotic levels and upregulated NLRP3 inflammasome pathway were detected. After injection with MCC950, NLRP3 inflammasome production was notably reduced in PINK1-/-and PARK2-/-mice, which effectively alleviated the pancreatic damage and inflammatory cell infiltration. Conclusion Our study suggested that mitochondrial dysfunction activated PINK1/PARK2-mediated mitophagy in AP, while mitophagy was impaired in SAP. PINK1-/- and PARK2-/- mice were more sensitive to onset of SAP and the deficiency of mitophagy could lead to the formation of NLRP3 inflammasome.

Aim: To develop a trans-omics-based molecular clinicopathological algorithm for predicting pancreatic adenocarcinoma prognosis, we performed a comprehensive analysis of the expression levels of mRNA, DNA methylation and DNA copy number in The Cancer Genome Atlas dataset. Materials & methods: Based on the least absolute shrinkage and selection operator method – COX regression analysis, a trans-omics-based classifier was established to predict overall survival. Nomogram was constructed by combining the classifier band clinical pathological characterization. Results: Based on trans-omics, we developed a 10-gene-based classifier and a molecular-clinicopathologic nomogram for predicting overall survival with satisfactory accuracy. Conclusion: Trans-omics-based classifier and molecule-clinicopathological nomogram based on the classifier can accurately predict the prognosis of pancreatic adenocarcinoma patients

Pancreatic ductal adenocarcinoma (PDAC) has a high mortality rate and poor prognosis. KRAS, TP53, CDKN2A, and SMAD4 are driver genes of PDAC and 30-75% patients have mutations in at least two of these four genes. Herein, we analyzed the relationship between these genes and prognosis of 762 patients in the absence of coexisting mutations, using data from three independent public datasets. Interestingly, we found that compared with mutations in other driver genes, TP53 mutation plays a significant role in leading to poor prognosis of PDAC. Additionally, we found that snoRNA-mediated rRNA maturation was responsible for the progression of cancer in PDAC patients with TP53 mutations. Inhibition of STRAP, which regulates the localization of SMN complexes and further affects the assembly of snoRNP, can effectively reduce maturation of rRNA and significantly suppress progression of TP53-mutant or low p53 expression pancreatic cancer cells in vitro and in vivo. Our study highlighted the actual contribution rate of driver genes to patient prognosis, enriching traditional understanding of the relationship between these genes and PDAC. We also provided a possible mechanism and a new target to combat progression of TP53-mutant PDAC patients.

Background Long noncoding ribonucleic acid (lncRNA) promoter methylation is closely related to the occurrence and development of hepatocellular carcinoma (HCC). Thus, we aim to screen and verify the lncRNA promoter methylation sites associated with overall survival (OS), vascular invasion, pathological grade, and clinical stage in HCC. Methods Methylation-related data including clinical characteristic, transcriptome, methylation, and messenger RNA (mRNA) expression were taken from the Cancer Genome Atlas (TCGA) database. The OS, vascular invasion, pathological grade, and clinical stage-related lncRNA promoter methylation models were developed by the least absolute shrinkage and selection operator (LASSO) algorithm based on the lncRNA promoter methylation sites screened via R software. The Kaplan–Meier analysis, the area under the receiver operating characteristic (ROC) curve (AUC), the calibration curve (C-index) were performed to evaluate the performance of these models. Finally, the methylation-specific polymerase chain reaction (MS-PCR) was performed to verify the accuracy of these models based on 146 HCC tissues from our hospital. Results A total of 10 methylation sites were included in the OS-related lncRNA promoter methylation model that could effectively divide HCC patients into high-risk and low-risk groups (P Conclusion The lncRNA promoter methylation sites are closely correlated with the process of HCC and can be utilized to improve the therapy and prognosis of HCC.

We appreciate to receive commentary from Dr Guangtong Deng and Dr Liang Xiao to our article, “Nomograms based on inflammatory biomarkers for predicting tumor grade and micro-vascular invasion in stage I/II hepatocellular carcinoma”. First, neutrophil-to-lymphocyte ratio (NLR) and derived NLR (dNLR) are two different parameters. Some studies show that NLR is inconsistent with dNRL in prognostic value through multivariate Cox regression, therefore, it is reasonable that both NLR and dNLR entered into multivariate analysis simultaneously. Second, it is common that articles of predictive nomograms turned continuous variables into categorical variables. The reason is that the categorization of patient clinical variables is beneficial to doctors to make decisions based on the risk level of individual patients in clinical. At last, multicenter validation is quite difficult and we have listed the shortcomings in the limitations of our article. Further validation will need the joint efforts by other institutions.

Background Emerging evidence suggests that long non-coding RNA (lncRNA) plays a crucial part in the development and progress of hepatocellular carcinoma (HCC). The objective was to develop novel molecular-clinicopathological prediction methods for overall survival (OS) and recurrence of HCC. Results An 8-lncRNA-based classifier for OS and a 14-lncRNA-based classifier for recurrence were developed by LASSO COX regression analysis, both of which had high accuracy. The tdROC of OS-nomogram and recurrence-nomogram indicates the satisfactory accuracy and predictive power. The classifiers and nomograms for predicting OS and recurrence of HCC were validated in the Test and GEO cohorts. Conclusions These two lncRNA-based classifiers could be independent prognostic factors for OS and recurrence. The molecule-clinicopathological nomograms based on the classifiers could increase the prognostic value. Methods HCC lncRNA expression profiles from the cancer genome atlas (TCGA) were randomly divided into 1:1 training and test cohorts. Based on least absolute shrinkage and selection operator method (LASSO) COX regression model, lncRNA-based classifiers were established to predict OS and recurrence, respectively. OS-nomogram and recurrence-nomogram were developed by combining lncRNA-based classifiers and clinicopathological characterization to predict OS and recurrence, respectively. The prognostic value was accessed by the time-dependent receiver operating characteristic (tdROC) and the concordance index (C-index).

To explore the role of phospholipase D1 (PLD1) mRNA in transition of prostate cancer (PCa) cells to androgen independence, we used Arraystar Human LncRNA Microarray V3.0 to detect and compare the differential expression of PLD1 and its signaling pathway-related gene in standard androgen dependence prostate cancer (ADPC) cell line LNCaP before and after the occurrence of androgen independence prostate cancer (AIPC) transition. In addition, we used the shRNA lentiviral vector to inhibit the PLD1 mRNA expression and observed its effect on LNCaP cell proliferation after AIPC transition by using MTS method. The results showed that the expression level of PLD1 mRNA was increased by 373-fold after AIPC transition (P

Background Several non-invasive diagnostic scores for non-alcoholic fatty liver (NAFL) have been developed, but the clinical application is limited because of their complexity. Aim To develop and validate an easy-to-calculate scoring system to identify ultrasound-diagnosed NAFL. Methods 48,489 patients from 2 centers were included in this study. Multivariable logistic regression models were employed for model development. Ultrasonography was applied to diagnose NAFL. The selected variables were assigned an integer score proportional to the estimated coefficient from the logistic regression analysis, namely NAFL Screening Score (NSS). The ability of the NSS to identify NAFL was assessed by analyzing the area under the receiver operating characteristic curve (AUROC) and was tested in an independent validation cohort. Additionally, the performance of NSS was compared with existing models. Results NSS was developed as a basic score comprising of age, body mass index (BMI), triglyceride (TG), ALT/AST, fasting plasma glucose (FPG) and uric acid (UA) in both sexes. NSS showed a relatively good discriminative power (AUROC = 0.825 for males, 0.861 for females in the validation cohort) in comparison with other models. The optimal cut-off point was 32 for males and 29 for females. Conclusion We developed and validated NSS, an easy-to-use score sheet identify ultrasound-diagnosed NAFL. NSS may be clinically useful for initial diagnosing NAFL.

Background and aim Upper gastrointestinal bleeding (UGIB) is a complication with a high mortality rate in critically ill patients presenting with cirrhosis. Today, there exist few accurate scoring models specifically designed for mortality risk assessment in critically ill cirrhotic patients with upper gastrointestinal bleeding (CICGIB). Our aim was to develop and evaluate a novel nomogram-based model specific for CICGIB. Patients and methods Overall, 540 consecutive CICGIB patients were enrolled. On the basis of Cox regression analyses, the nomogram was constructed to estimate the probability of 30-day, 90-day, 270-day, and 1-year survival. An upper gastrointestinal bleeding-chronic liver failure-sequential organ failure assessment (UGIB-CLIF-SOFA) score was derived from the nomogram. Performance assessment and internal validation of the model were performed using Harrell's concordance index (C-index), calibration plot, and bootstrap sample procedures. UGIB-CLIF-SOFA was also compared with other prognostic models, such as CLIF-SOFA and model for end-stage liver disease, using C-indices. Results Eight independent factors derived from Cox analysis (including bilirubin, creatinine, international normalized ratio, sodium, albumin, mean artery pressure, vasopressin used, and hematocrit decrease>10%) were assembled into the nomogram and the UGIB-CLIF-SOFA score. The calibration plots showed optimal agreement between nomogram prediction and actual observation. The C-index of the nomogram using bootstrap (0.729; 95% confidence interval: 0.689-0.766) was higher than that of the other models for predicting survival of CICGIB. Conclusion We have developed and internally validated a novel nomogram and an easy-to-use scoring system that accurately predicts the mortality probability of CICGIB on the basis of eight easy-to-obtain parameters. External validation is now warranted in future clinical studies.

Background and Aims Developing a preoperative prediction model for estimating the risk of pancreatic ductal adenocarcinoma (PDAC) patients before pancreaticoduodenectomy is a difficult task. The purpose of current study was to develop a prognostic nomogram based on inflammatory markers for PDAC patients. Methods Cox regression analysis was performed to calculate the overall survival (OS) and assess the prognostic factors based on 265 PDAC patients undergone surgery. The nomogram was built to estimate the probability of 1-year, 3-year, and 5-year OS. The predictive accuracy of nomogram was determined by concordance index, calibration curve, and time dependent receiver operating characteristics. Results In multivariable Cox analysis, vascular invasion, Tumor Grade, TNM stage, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and albumin/globulin ratio were significantly associated with OS, which were all assembled into nomogram. The calibration curves for probability of survival showed optimal agreement between nomogram prediction and actual observation. The concordance index for 1-year, 3-year and 5-year OS prediction were 0.860 (95% confidence intervals (CI): 0.837–0.885), 0.837 (95%CI: 0.819–0.856), and 0.809 (95%CI: 0.787–0.829), respectively. The area under time dependent receiver operating characteristics curve of 1-year, 3-year, and 5-year OS prediction were 0.938 (95%CI: 0.886–0.989), 0.844 (95%CI: 0.782–0.906), and 0.884 (95%CI: 0.792–0.976), suggesting high discriminative ability of nomogram. It allowed significant distinction survival outcomes by grouping the patients evenly into three subgroups after sorting by total points. Conclusions Based on clinicopathology characteristics and inflammatory markers, we developed a nomogram providing an individualized risk estimate for PDAC patients.

Background: Critically ill cirrhotic patients have a high mortality, particularly with concomitant respiratory failure on admission. There are no specific models in use for mortality risk assessment in critically ill cirrhotic patients with acute respiratory failure (CICRF). The aim is to develop a risk prediction model specific to CICRF in order to quantify the severity of illness.Methods: We analyzed 949 CICRF patients extracted from the MIMIC-III database. The novel model (ARF-CLIF-SOFA) was developed from the CLIF-SOFA score. Cox regression analysis and AUROC were implemented to test the predictive accuracy, compared with existing scores including the CLIF-SOFA score and MELD-related scores.Results: ARF-CLIF-SOFA contains PaO2/FiO2 ratio, lactate, MAP, vasopressor therapy, bilirubin and creatinine (1 point each; score range: 0–6). Based on our patient cohort, the ARF-CLIF-SOFA score had good predictive accuracy for predicting the 30-, 90-day and 1-year mortality (AUROC = 0.767 at 30-day, 0.768...

Background The presence of vascular invasion (VI) in pathology specimens is a well-known unfavorable prognostic factor of hepatocellular carcinoma (HCC) recurrence and overall survival (OS). We investigated the vascular invasion related microRNA (miRNA) expression profiles and potential of prognostic value in HCC. Methods MiRNA and mRNA expression data for HCC were accessed from The Cancer Genome Atlas (TCGA). LASSO logistic regression models were used to develop a miRNA-based classifier for predicting VI. The predictive capability was accessed by area under receiver operating characteristics (AUC). Concordance index (C-index) and time-dependent receiver operating characteristic (td-ROC) were used to determine its prognostic value. We validated the predictive and prognostic accuracy of this classifier in an external independent cohort of 127 patients. Functionally relevant targets of miRNAs were determined using miRNA target prediction, experimental validation and correlation of miRNA and mRNA expression data. Results A 16-miRNA-based classifier was developed which identified VI accurately, with AUC of 0.731 and 0.727 in TCGA set and validation cohort, respectively. C-index and td-ROC showed that the classifier was able to stratify patients into risk groups strongly associated with OS. When stratified by tumor characteristics, the classifier was still a clinically and statistically significant prognostic model. The predictive and prognostic accuracy of the classifier was confirmed in validation cohort. Vascular invasion related miRNA/target pairs were identified by integrating expression patterns of predicted targets, which were validated in cell lines. Conclusions A multi-miRNA-based classifier developed based on the presence of VI, which could effectively predict OS in HCC.

Steatosis could affect liver stiffness measurement in patients with nonalcoholic fatty liver disease and chronic hepatitis C. In this study, we aimed to investigate the impact of steatosis on liver stiffness in hepatitis B virus (HBV)-infected patients and develop a diagnostic algorithm for prediction of liver fibrosis by liver stiffness based on the controlled attenuation parameter. A total of 488 HBV-infected patients who underwent clinical examination, Fibroscan and liver biopsy were prospectively enrolled. The best liver stiffness measurement (kPa) cut-offs for significant fibrosis (S≥3) and advanced fibrosis (S≥4) were 8.1 and 10.9, respectively. The best controlled attenuation parameter cut-off for severe steatosis (≥30%) was 287 dB/m. Among patients with low-grade fibrosis (S0-S2/S0-S3), mean liver stiffness values were significantly higher in subjects with severe steatosis or controlled attenuation parameter ≥287 dB/m compared with those without. Moreover, in subjects with low-grade fibrosis, a higher rate of false-positive rate was observed in patients with severe steatosis than those in patients without (F0-F2: 28.2% vs 9.7%; F0-F3: 17.0% vs 5.3%), and in patients with CAP≥287 dB/m compared with their counterpart (F0-F2: 23.7% vs 9.2%; F0-F3: 14.1% vs 4.8%). Low-grade fibrosis was accurately identified by γ-glutamyl transpeptidase-to-platelet ratio (GPR) with a cut-off value of 0.17. In patients with GPR

Background Acute-on-chronic hepatitis B liver failure (ACHBLF) is associated with poor short-term prognosis. The aim of the present study was to construct and validate a model for end-stage liver disease (MELD)-based nomogram for the 3-month mortality estimation for patients with ACHBLF. Methods A total of 551 patients with ACHBLF were prospectively enrolled from 2 independent medical centers and divided into 2 cohorts of training and validation, respectively. The 3-month mortality was recorded as the outcome. The MELD-based nomogram was constructed to predict the 3-month mortality for ACHBLF using the training group of 335 patients and validated using an independent cohort of 216 patients. The predictive capability of MELD-based nomogram was compared with the MELD score system by calibration analysis, receiver operating characteristics (ROC) and decision curve analysis in both training cohort and validation cohort. Results Multivariate analysis suggested that age, serum sodium, and MELD score were independent prognostic indicators associated with the 3-month mortality for ACHBLF, and therefore used for developing the nomogram. In terms of calibration, the predicted survival by the MELD-based nomogram was found to be extremely in line with the observed 3-month mortality both in training cohort and validation cohort. Additionally, both ROC and decision curve analyses showed that the MELD-based nomogram was better than MELD, MELD-Na, MELDNa, and iMELD for ACHBLF prognosis prediction. The results were confirmed in the external cohort of validation. Conclusions The MELD-based nomogram provided a user-friendly, accurate and reproducible tool for predicting 3-month mortality of patients with ACHBLF.

Hepatitis B virus (HBV) infection remains a major health problem and HBV-related-decompensated cirrhosis (HBV-DC) usually leads to a poor prognosis. Our aim was to determine the utility of inflammatory biomarkers in predicting mortality of HBV-DC.A total of 329 HBV-DC patients were enrolled. Survival estimates for the entire study population were generated using the Kaplan-Meier method. The prognostic values for model for end-stage liver disease (MELD) score, Child-Pugh score, and inflammatory biomarkers neutrophil/lymphocyte ratio, C-reactive protein-to-albumin ratio (CAR), and lymphocyte-to-monocyte ratio (LMR) for HBV-DC were compared using time-dependent receiver operating characteristic curves and time-dependent decision curves.The survival time was 23.1±15.8 months. Multivariate analysis identified age, CAR, LMR, and platelet count as prognostic independent risk factors. Kaplan-Meier analysis indicated that CAR of at least 1.0 (hazard ratio, 7.19; 95% confidence interval, 4.69-11.03), and LMR less than 1.9 (hazard ratio, 2.40; 95% confidence interval, 1.69-3.41) were independently associated with mortality of HBV-DC. The time-dependent receiver operating characteristic indicated that CAR showed the best performance in predicting mortality of HBV-DC compared with LMR, MELD score, and Child-Pugh score. The results were also confirmed by time-dependent decision curves.CAR and LMR were associated with the prognosis of HBV-DC. CAR was superior to LMR, MELD score, and Child-Pugh score in HBV-DC mortality prediction.

We aimed to evaluate the efficacy of five oral nucleos(t)ide analogues (NAs), including lamivudine, entecavir, adefovir, telbivudine and tenofovir, for the prevention of hepatitis B virus (HBV) reactivation and HBV-related complications in chronic hepatitis B virus (CHB) infected patients with hematological malignancies receiving chemotherapy or hematopoietic stem cell transplantation (HSCT) by network meta-analysis.The search identified 28 articles involving 5 different prophylactic regimens covering 1478 participants.Among five prophylactic regimes, tenofovir (predicted probability, 90%), was the most effective intervention followed by entecavir (88%) in preventing HBV reactivation. There was no significant difference between tenofovir and entecavir for preventing HBV reactivation. With regards to other outcomes, tenofovir and telbivudine was not included to evaluate due to lack of relevant studies. Entecavir was the most effective intervention in reducing the risk of HBV related hepatitis (100%), HBV related death (61%) and all other causes of hepatitis (98%).Tenofovir and entecavir might be the most potent regimes in prevention of HBV reactivation for CHB infected patients with hematological malignancies undergoing chemotherapy or HSCT.

SummaryBackground Inflammation plays a vital role in liver cirrhosis progression and prognosis. Aim To investigate the prognostic significance of inflammatory response markers in decompensated cirrhotic patients without acute-on-chronic liver failure (ACLF). Methods Independent predictors were identified using multivariate Cox model and then assembled into a nomogram to predict survival. Concordance index (C-index) and time-dependent receiver operating characteristics (td-ROC) analysis were adopted to evaluate and compare the performance of nomogram, model for end-stage liver disease (MELD) scores, MELD-Na and Chronic Liver Failure-consortium score for acute decompensated (CLIF-C ADs). Results A total of 902 decompensated cirrhotic patients with different aetiologies were enrolled, with 6-month, 1-year and 3-year mortality of 18.6%, 24.4% and 34.8%, respectively. The cut-off values for neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) determined by X-tile program were 5.7 and 1.1 respectively. Patients with NLR>5.7 or LMR≤1.1 had significantly higher mortality (P

Background and Aims: Platelet-to-lymphocyte ratio (PLR) has been shown to predict prognosis of cancers. We aimed to evaluate the prognostic value of stratification of PLR in patients after curative liver resection (CLR) for hepatocellular carcinoma (HCC). Methods: A total of 1804 patients who underwent CLR for suspected HCC between January 2007 and January 2014 were screened for the study. All of the patients were categorized into equal tertiles according to the number of patients and the distribution of PLR. Prognostic significance was determined for overall survival (OS) and was assessed using Kaplan–Meier analysis. Univariate and multivariate Cox proportional hazard regression analyses were evaluated for association of all independent parameters with disease prognosis. Results: The optimal cut-off points of preoperative PLR were: (T1) 11.98–75.00, (T2) 75.00–113.33 and (T3) 113.33–567.50. There were obvious differences in each PLR tertile with mortality within 36 months of CLR (plog-rank < 0.001). Multivariable analysis suggested that the level of PLR (HR = 1.004, 95%CI: 1.001–1.008, p = 0.006), portal vein thrombosis (HR = 3.406, 95%CI: 1.185–9.794, p = 0.023), number of nodules (HR = 1.810, 95%CI: 1.345–2.437, p < 0.001), Child-Turcotte-Pugh score (HR = 1.741, 95%CI: 1.129–2.684, p = 0.012) and microvascular invasion (HR = 2.730, 95%CI: 1.777–4.196, p < 0.001) were significant predictors of mortality. Kaplan–Meier analysis of overall survival (OS) demonstrated that each PLR tertile showed a progressively worse OS and apparent separation (plog-rank = 0.016). The highest 5-year OS rate following CLR (58%) was revealed in tertile 1. In contrast, the lowest 5-year OS rate (30%) was revealed in tertile 3. Conclusion: Stratified preoperative PLR could strengthen the predictive power for OS in HCC patients with CLR.

Background and Aim Determining individual risk of short-term mortality in patients with acute-on-chronic hepatitis B liver failure (ACHBLF) is a difficult task. We aimed to develop and externally validate a prognostic nomogram for ACHBLF patients. Methods The nomogram was built to estimate the probability of 30-day, 60-day, 90-day, and 60-month survival based on an internal cohort of 246 patients with ACHBLF. The predictive accuracy and discriminative ability of nomogram were determined by a concordance index (C-index), calibration curve, and time-dependent receiver operating characteristics (tdROC), comparing with model for end-stage liver disease (MELD) score. The results were validated using bootstrap resampling and an external cohort of 138 patients. Furthermore, we plotted decision curves to evaluate the clinical usefulness of nomogram. Results Independent factors derived from multivariable Cox analysis of training cohort to predict mortality were age, total bilirubin, serum sodium, and prothrombin activity, which were all assembled into nomogram. The calibration curves for probability of survival showed optimal agreement between nomogram prediction and actual observation. The C-index of nomogram was higher than that of MELD score for predicting survival (30-day, 0.809 vs 0.717, P

Several risk factors are able to predict non-alcoholic fatty liver (NAFL) development, but the predictive value of serum alkaline phosphatase (ALP) remains uncertain. Our aim is to investigate the association between serum ALP levels and NAFL.21,331 NAFL-free subjects were included. Sex-specific ALP quartiles (Q1 to Q4) were defined. With Q1 used as reference, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated across each quartile.After adjusting for confounding variables, values in Q2, Q3 and Q4 had HRs (95%CIs) of 1.16 (0.94-1.43), 1.38 (1.13-1.69), 1.51 (1.24-1.83) in females and 0.99 (0.90-1.09), 1.04 (0.95-1.14), 0.96 (0.87-1.05) in males, respectively. A subgroup analysis of age factors in females, from Q2 to Q4, adjusted HRs (95%CIs) were 1.31 (0.81-1.99), 1.86 (1.23-2.81), 2.44 (1.60-3.71) in their 30 s, 1.13 (0.83-1.54), 1.17 (0.85-1.62), 1.65 (1.22-2.25) in their 40 s, and 0.95 (0.51-1.78), 0.91 (0.52-1.62), 0.89 (0.53-1.52) in their 50 s.Higher serum ALP levels are considered a significant predictor for NAFL development in females aged 30 to 50.

There is a lack of precise and clinical accessible model to predict the prognosis of hepatocellular carcinoma (HCC) in clinic practice currently. Here, an inclusive nomogram was developed by integrating genomic markers and clinicopathologic factors for predicting the outcome of patients with HCC. A total of 365 samples of HCC were obtained from the Cancer Genome Atlas (TCGA) database. The LASSO analysis was carried out to identify HCC-related mRNAs, and the multivariate Cox regression analysis was used to construct a genomic-clinicopathologic nomogram. As results, 9 mRNAs were finally identified as prognostic indicators, including RGCC, CDH15, XRN2, RAB3IL1, THEM4, PIF1, MANBA, FKTN and GABARAPL1, and used to establish a 9-mRNA classifier. Additionally, an inclusive nomogram was built up by combining the 9-mRNA classifier (P 0.001) and clinicopathologic factors including age (P = 0.006) and metastasis (P 0.001) to predict the mortality of HCC patients. Time-dependent receiver operating characteristic, index of concordance and calibration analyses indicated favorable accuracy of the model. Decision curve analysis suggested that appropriate intervention according to the established nomogram will bring net benefit when threshold probability was above 25%. The genomic-clinicopathologic model could be a reliable tool for predicting the mortality, helping determining the individualized treatment and probably improving HCC survival.

Background Colorectal cancer (CRC) is the third most frequent cancer and the second leading cause of cancer-related death worldwide. Increasing evidence indicates that the deregulation of long noncoding RNAs (lncRNAs) contributes to tumor initiation and progression; however, little is known about the biological role of cancer susceptibility candidate 9 (CASC9) in CRC. Methods Novel lncRNAs potentially involved in CRC tumorigenesis were identified from datasets downloaded from The Cancer LncRNome Atlas and The Atlas of Noncoding RNAs in Cancer. The CRC cell lines HCT-116, HCT-116 p53−/−, SW620, SW480, HT-29, LoVo, LS-174T, and RKO were used. Colony-formation, MTS, cell-cycle, apoptosis, and in-vivo tumorigenesis assays were used to determine the role of CASC9 in CRC cell growth in vitro and in vivo. Potential interaction between CASC9 and cleavage and polyadenylation specificity factor subunit 3 (CPSF3) was evaluated using RNA immunoprecipitation and RNA-protein pull-down assays. RNA-sequencing was performed to analyze gene expression following CASC9 knockdown. RT-qPCR, western blotting, and mRNA decay assays were performed to study the mechanisms involved. Results CASC9 was frequently upregulated in CRC, which was correlated with advanced TNM stage, and higher CASC9 levels were associated with poor patient outcomes. Knockdown of CASC9 inhibited growth and promoted apoptosis in CRC cells, whereas ectopic CASC9 expression promoted cell growth in vitro and in vivo. We demonstrated that CPSF3 is a CASC9-interacting protein, and knockdown of CPSF3 mimicked the effects of CASC9 knockdown in CRC cells. Furthermore, we found that CASC9 exerts its oncogenic activity by modulating TGFβ2 mRNA stability and upregulating the levels of TGFβ2 and TERT, resulting in an increase in phosphorylated SMAD3 and activation of TGF-β signaling, and enhanced TERT complex function in CRC cells. Finally, CPSF3 was significantly upregulated in CRC tissues as compared with adjacent or non-adjacent normal colon tissues, and CASC9, CPSF3, and TGFβ2 levels in human CRC tissues were positively correlated. Conclusions CASC9 is a promising prognostic predictor for patients with CRC and the CASC9-CPSF3-TGFβ2 axis is a potential therapeutic target for CRC treatment. Electronic supplementary material The online version of this article (10.1186/s13046-019-1263-3) contains supplementary material, which is available to authorized users.

Acute lung injury (ALI) is a critical event involved in the pathophysiological process of acute pancreatitis (AP). Many methods have been widely used for the treatment of AP-ALI, but few are useful during early inflammation. Lipoxin A4 (LXA4), a potent available anti-inflammatory and novel antioxidant mediator, has been extensively studied in AP-ALI, but its underlying mechanism as a protective mediator is not clear. This research was conducted to identify the possible targets and mechanisms involved in the anti-AP-ALI effect of LXA4. First, we confirmed that LXA4 strongly inhibited AP-ALI in mice. Next, using ELISA, PCR, and fluorescence detection to evaluate different parameters, LXA4 was shown to reduce the inflammatory cytokine production induced by AP and block reactive oxygen species (ROS) generation in vivo and in vitro. In addition, TNF-α treatment activated the nuclear factor E2-related factor 2 (Nrf2) signaling pathway and its downstream gene heme oxygenase-1 (HO-1) in human pulmonary microvascular endothelial cells (HPMECs), and LXA4 further promoted their expression. This study also provided evidence that LXA4 phosphorylates Ser40 and triggers its nuclear translocation to activate Nrf2. Moreover, when Nrf2-knockout (Nrf2-/-) mice and cells were used to further assess the effect of the Nrf2/HO-1 pathway, we found that Nrf2 expression knockdown partially eliminated the effect of LXA4 on the reductions in inflammatory factor levels while abrogating the inhibitory effect of LXA4 on the ROS generation stimulated by AP-ALI. Overall, LXA4 attenuated the resolution of AP-induced inflammation and ROS generation to mitigate ALI, perhaps by modulating the Nrf2/HO-1 pathway. These findings have laid a foundation for the treatment of AP-ALI.

Background Compelling lines of evidence indicate that DNA methylation of non-coding RNAs (ncRNAs) plays critical roles in various tumour progression. In addition, the differential methylation of ncRNAs can predict prognosis of patients. However, little is known about the clear relationship between DNA methylation profile of ncRNAs and the prognosis of pancreatic adenocarcinoma (PAC) patients. Methods The data of DNA methylation, RNA-seq, miRNA-seq and clinical features of PAC patients were collected from TCGA database. The DNA methylation profile was obtained using the Infinium HumanMethylation450 BeadChip array. LASSO regression was performed to construct two methylation-based classifiers. The risk score of methylation-based classifiers was calculated for each patient, and the accuracy of the classifiers in predicting overall survival (OS) was examined by ROC curve analysis. In addition, Cox regression models were utilized to assess whether clinical variables and the classifiers were independent prognostic factors for OS. The targets of miRNA and the genes co-expressed with lncRNA were identified with DIANA microT-CDS and the Multi-Experiment Matrix (MEM), respectively. Moreover, DAVID Bioinformatics Resources were applied to analyse the functional enrichment of these targets and co-expressed genes. Results A total of 4004 CpG sites of miRNA and 11,259 CpG sites of lncRNA were screened. Among these CpG sites, 8 CpG sites of miRNA and 7 CpG sites of lncRNA were found with regression coefficients. By multiplying the sum of methylation degrees of the selected CpGs with these coefficients, two methylation-based classifiers were constructed. The classifiers have shown good performance in predicting the survival rate of PAC patients at varying follow-up times. Interestingly, both of these two classifiers were predominant and independent factors for OS. Furthermore, functional enrichment analysis demonstrated that aberrantly methylated miRNAs and lncRNAs are related to calcium ion transmembrane transport and MAPK, Ras and calcium signalling pathways. Conclusion In the present study, we identified two methylation-based classifiers of ncRNA associated with OS in PAC patients through a comprehensive analysis of miRNA and lncRNA profiles. We are the first group to demonstrate a relationship between the aberrant DNA methylation of ncRNAs and the prognosis of PAC, and this relationship would contribute to individualized PAC therapy. Electronic supplementary material The online version of this article (10.1186/s12935-019-0828-8) contains supplementary material, which is available to authorized users.

The popular sense of the word "cure" implies that a patient treated for a specific disease will return to have the same life expectancy as if he/she had never had the disease. In analytic terms, it translates into the concept of statistical cure which occurs when a group of patients returns to having similar mortality to a reference population. The aim of this study was to assess the probability of being cured from hepatocellular carcinoma (HCC) by hepatic resection.Data from 2,523 patients undergoing resection for HCC were used to fit statistical cure models, to compare disease-free survival (DFS) after surgery to the survival expected for patients with chronic hepatitis and/or cirrhosis and the general population, matched by sex, age, race/ethnicity and year of diagnosis.The probability of resection enabling patients with HCC to achieve the same life expectancy as those with chronic hepatitis and/or cirrhosis was 26.3%. The conditional probability of achieving this result was time-dependent, requiring about 8.9 years to be accomplished with 95% certainty. Considering the general population as a reference, the cure fraction decreased to 17.1%. Uncured patients had a median DFS of 1.5 years. In multivariable analysis, patient's age and the risk of early HCC recurrence (within 2 years) were independent determinants of the chance of cure (p0.001). The chances of being cured ranged between 36.0% for individuals at low risk of early recurrence to approximately 3.6% for those at high risk.Estimates of the chance of being cured of HCC by resection showed that cure is achievable, and its likelihood increases with the passing of recurrence-free time. The data presented herein can be used to inform decision making and to provide patients with accurate information.Data from 2,523 patients who underwent resection for hepatocellular carcinoma were used to estimate the probability that resection would enable treated patients to achieve the same life expectancy as patients with chronic hepatitis and/or cirrhosis, and the general population. Herein, the cure model suggests that in patients with hepatocellular carcinoma, resection can enable patients to achieve the same life expectancy as those with chronic liver disease in 26.3% of cases and as the general population in 17.1% of cases.

Severe acute pancreatitis (SAP) is a challenging disease with high morbidity and mortality, often complicated by multiple organ dysfunction syndrome (MODS). The intestine, a major organ involved in MODS, correlates strongly with the evolution of the disease. In this study, we demonstrated that the DPP4 inhibitor, sitagliptin, protects SAP-associated intestinal injury both in vitro and in vivo. These beneficial effects were achieved by suppressing oxidative stress and inflammatory responses. Moreover, in sitagliptin-treated SAP mice, expression of Nrf2 was induced and that of NF-κB was reduced, compared to the control SAP mice. In addition, we used Nrf2-/- mice to test the protective effect of Nrf2 during sitagliptin treatment of SAP; our results indicated that Nrf2-/- mice had greater pancreatic and intestinal injury than wild-type mice. Taken together, high levels of ROS induced by SAP may be inhibited by sitagliptin, possibly by inactivating the Nrf2-NF-κB pathway.

Background: Increasing evidences reveal that inflammation plays a critical role in tumorigenesis and progression. We aimed to develop the nomograms based on inflammatory biomarkers to predict micro-vascular invasion (MVI) and tumor grade in stage I/II hepatocellular carcinoma (HCC). Methods: A retrospective cohort of 627 patients with stage I/II HCC between January 2007 and December 2014 was included in the study. Logistic regression was performed to identify the independent risk factors of tumor grade and MVI. The significant predictors including neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (dNLR), lymphocyte-to-monocyte ratio (LMR), tumor volume age, and tumor size were subsequently incorporated to build the nomograms. The prediction accuracies of the nomograms were evaluated using the area under the receiver operating characteristic (ROC) curve. Results: The independent risk factors for tumor grade were NLR, dNLR, and tumor volume (P Conclusion: We successfully developed nomograms predicting tumor grade and MVI based on inflammatory biomarkers with high accuracy, leading to a rational therapeutic choice for stage I/II HCC.

Background The Wnt gene family members are known to participate regulating various normal and pathological processes including tumorigenesis. However, the association between Wnt ligands gene family and prognosis in hepatocellular carcinoma has not been systematically studied. Therefore, we evaluated the role of Wnt ligands gene family in hepatocellular carcinoma using publicly available data from The Cancer Genome Atlas (TCGA). Methods Clinical information and RNA-Seq mRNA expression data were derived from TCGA hepatocellular carcinoma cohort. Differences in overall survival (OS) and disease-free survival (DFS) between increased and decreased expression groups (defined by X-tile analyses) of Wnt ligands gene family were compared using Kaplan–Meier method and Cox regression model, with p-values calculated via log-rank test. Gene Set Enrichment Analysis (GSEA) was performed. Results Multivariate analysis adjusted for patient age, sex, BMI, tumor grade, and TMN stage revealed that Wnt1, Wnt3 and Wnt5B expressions were independent prognostic factors for OS and DFS (OS: HR = 0.58, P = 0.006; HR = 0.65, P = 0.03; HR = 0.56, P = 0.023, respectively; DFS: HR = 0.52, P