High level of intercellular adhesion molecule-1 affects prognosis of patients with hepatocellular carcinoma

AIM: To determine the cut-off value of intercellular adhesion molecule-1(ICAM-1) and assess the correlation of ICAM-1 with clinicopathological features and the prognosis of hepatocellular carcinoma(HCC)patients who underwent surgical resection.METHODS: We prospectively collected clinicopathological data from 236 HCC patients who had undergone successful hepatectomy. Receiver operating characteristic curve analysis was performed to determine the optimal cut-off value of ICAM-1. Enzymelinked immunosorbent assay was used to measure the concentration of ICAM-1 in 236 serum samples isolated from HCC patients and the stratified analysis was used to compare the serum level of ICAM-1 in different HCC subgroups. Immunohistochemistry was performed to test the expression level of the ICAM-1 protein in76 cases of HCC tissues and their adjacent normal liver tissues(ANLT). The survival probability of HCC patients was estimated using Kaplan-Meier plots and differences between the groups were obtained using the log-rank test. Furthermore, independent indicatorsof the prognosis were acquired using a stepwise Cox proportional hazard model to analyze a series of predictors that were associated with disease-free survival(DFS) and overall survival(OS) in HCC patients.RESULTS: Our findings suggested that ICAM-1promotes HCC metastasis and high serum ICAM-1 is significantly associated with alpha-fetoprotein(AFP)(P = 0.022), clinical tumor-node-metastasis stage(P< 0.001), portal vein tumor thrombus(P = 0.005),distant metastasis(P = 0.016) and recurrence(P= 0.034). We further detected the ICAM-1 protein in HCC specimens and found that 56 of 76(73.7%)HCC tissues had ICAM-1 positive staining while only23 of 76(30.3%) ANLT were positively stained(P <0.0001). Survival analysis indicated that HCC patients with increased ICAM-1 concentrations had significantly shorter DFS and OS after resection. A multivariate analysis showed that ICAM-1 > 684 ng/mL was an independent factor for DFS(HR = 1.643; 95%CI:1.125-2.401; P = 0.010) and OS(HR = 1.692; 95%CI:1.152-2.486; P = 0.007).CONCLUSION: ICAM-1 may be a promising serological biomarker for HCC diagnosis and an independent predictor of DFS and OS after surgical resection and may provide a useful reference for the prediction of intra- and extrahepatic metastasis.

Novel index for the prediction of significant liver fibrosis and cirrhosis in chronic hepatitis B patients in China

BACKGROUND Noninvasive,practical,and convenient means of detection for the prediction of liver fibrosis and cirrhosis in China are greatly needed.AIM To develop a precise noninvasive test to stage liver fibrosis and cirrhosis.METHODS With liver biopsy as the gold standard,we established a new index,[alkaline phosphatase(U/L)+gamma-glutamyl transpeptidase(U/L)/platelet(109/L)(AGPR)],to predict liver fibrosis and cirrhosis.In addition,we compared the area under the receiver operating characteristic curve(AUROC)of AGPR,gammaglutamyl transpeptidase to platelet ratio,aspartate transaminase to platelet ratio index,and FIB-4 and evaluated the accuracy of these routine laboratory indices in predicting liver fibrosis and cirrhosis.RESULTS Correlation analysis revealed a significant positive correlation between AGPR and liver fibrosis stage(P<0.001).In the training cohort,the AUROC of AGPR was 0.83(95%CI:0.78-0.87)for predicting fibrosis(≥F2),0.84(95%CI:0.79-0.88)for predicting extensive fibrosis(≥F3),and 0.87(95%CI:0.83-0.91)for predicting cirrhosis(F4).In the validation cohort,the AUROCs of AGPR to predict≥F2,≥F3 and F4 were 0.83(95%CI:0.77-0.88),0.83(95%CI:0.77-0.89),and 0.84(95%CI:0.78-0.89),respectively.CONCLUSION The AGPR index should become a new,simple,accurate,and noninvasive marker to predict liver fibrosis and cirrhosis in chronic hepatitis B patients.

Radiomics model based on contrast-enhanced computed tomography to predict early recurrence in patients with hepatocellular carcinoma after radical resection

BACKGROUND Radical resection remains an effective strategy for patients with hepatocellular carcinoma(HCC).Unfortunately,the postoperative early recurrence(recurrence within 2 years)rate is still high.AIM To develop a radiomics model based on preoperative contrast-enhanced computed tomography(CECT)to evaluate early recurrence in HCC patients with a single tumour.METHODS We enrolled a total of 402 HCC patients from two centres who were diagnosed with a single tumour and underwent radical resection.First,the features from the portal venous and arterial phases of CECT were extracted based on the region of interest,and the early recurrence-related radiomics features were selected via the least absolute shrinkage and selection operator proportional hazards model(LASSO Cox)to determine radiomics scores for each patient.Then,the clinicopathologic data were combined to develop a model to predict early recurrence by Cox regression.Finally,we evaluated the prediction performance of this model by multiple methods.RESULTS A total of 1915 radiomics features were extracted from CECT images,and 31 of them were used to determine the radiomics scores,which showed a significant difference between the early recurrence and nonearly recurrence groups.Univariate and multivariate Cox regression analyses showed that radiomics scores and serum alphafetoprotein were independent indicators,and they were used to develop a combined model to predict early recurrence.The area under the receiver operating characteristic curve values for the training and validation cohorts were 0.77 and 0.74,respectively,while the C-indices were 0.712 and 0.674,respectively.The calibration curves and decision curve analysis showed satisfactory accuracy and clinical utilities.Kaplan-Meier curves based on recurrence-free survival and overall survival showed significant differences.CONCLUSION The preoperative radiomics model was shown to be effective for predicting early recurrence among HCC patients with a single tumour.

Preoperative contrast-enhanced computed tomography-based radiomics model for overall survival prediction in hepatocellular carcinoma

BACKGROUND Hepatocellular carcinoma(HCC)is the most common primary liver malignancy with a rising incidence worldwide.The prognosis of HCC patients after radical resection remains poor.Radiomics is a novel machine learning method that extracts quantitative features from medical images and provides predictive information of cancer,which can assist with cancer diagnosis,therapeutic decision-making and prognosis improvement.AIM To develop and validate a contrast-enhanced computed tomography-based radiomics model for predicting the overall survival(OS)of HCC patients after radical hepatectomy.METHODS A total of 150 HCC patients were randomly divided into a training cohort(n=107)and a validation cohort(n=43).Radiomics features were extracted from the entire tumour lesion.The least absolute shrinkage and selection operator algorithm was applied for the selection of radiomics features and the construction of the radiomics signature.Univariate and multivariate Cox regression analyses were used to identify the independent prognostic factors and develop the predictive nomogram,incorporating clinicopathological characteristics and the radiomics signature.The accuracy of the nomogram was assessed with the concordance index,receiver operating characteristic(ROC)curve and calibration curve.The clinical utility was evaluated by decision curve analysis(DCA).Kaplan–Meier methodology was used to compare the survival between the low-and high-risk subgroups.RESULTS In total,seven radiomics features were selected to construct the radiomics signature.According to the results of univariate and multivariate Cox regression analyses,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR)and radiomics signature were included to build the nomogram.The C-indices of the nomogram in the training and validation cohorts were 0.736 and 0.774,respectively.ROC curve analysis for predicting 1-,3-,and 5-year OS confirmed satisfactory accuracy[training cohort,area under the curve(AUC)=0.850,0.791 and 0.823,respectively;validation cohort,AUC=0.905,0.884 and 0.911,respectively].The calibration curve analysis indicated a good agreement between the nomogram-prediction and actual survival.DCA curves suggested that the nomogram had more benefit than traditional staging system models.Kaplan-Meier survival analysis indicated that patients in the low-risk group had longer OS and disease-free survival(all P<0.0001).CONCLUSION The nomogram containing the radiomics signature,NLR and AFP is a reliable tool for predicting the OS of HCC patients.

Regulatory factor X5 promotes hepatocellular carcinoma progression by transactivating tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein theta and suppressing apoptosis

Background:Our previous studies have shown that regulatory factor X5(RFX5),a classical transcription regulator of MHCⅡ genes,was obviously overexpressed in hepatocellular carcinoma(HCC)tumors.However,the role of RFX5 in the carcinogenesis and progress of HCC remains unknown.This study aimed to reveal its biological significance and the underlying mechanism in HCC.Methods:RFX5 mRNA expression level and copy number variation in HCC tumors and cell lines were determined by analyzing deposited data sets in the Cancer Genome Atlas and Gene Expression Omnibus database.The biological significance of RFX5 in HCC was investigated by monitoring the colony formation and subcutaneous tumor growth capacity when RFX5 was silenced with lentiviral short hairpin RNA and CRISPR7Cas9 system in HCC cell lines.The downstream gene transcriptionally activated by RFX5 in HCC cells was determined by chromatin immunoprecipitation and luciferase reporter assay.The involvement of tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein theta(YWHAQ)in HCC development was further determined by performing colony formation rescue assay and subcutaneous tumor growth rescue experiment.The association of YWHAQ with recurrence-free survival of patients with HCC was assessed by Kaplan-Meier analysis.Moreover,apoptosis level and the protein level of p53 pathway were determined to reveal the mechanism of RFX5 in driving HCC development.Results:RFX5 was amplified and highly overexpressed in HCC tumor tissues compared with the corresponding non-tumor tissues.The mRNA expression level of RFX5 was significantly correlated with its DNA copy number(r=0.4,P<0.001).Functional study demonstrated that RFX5 was required for both clonogenic forming in vitro and subcutaneous tumor growth in vivo of HCC cells.Further study identified YWHAQ,namely 14-3-3 tau,as a key downstream transcriptional target gene of RFX5,which was tightly regulated by RFX5 in HCC.Moreover,overexpression of YWHAQ largely rescued the clonogenic growth of HCC cells that was suppressed by RFX5 knockdown.In addition,overexpression of YWHAQ in primary tumor was linked to poor prognosis of patients with HCC.These results demonstrated that YWHAQ was a downstream effector of RFX5 in HCC.Notably,RFX5-YWHAQ pathway could protect cells from apoptosis by suppressing the p53 and Bax in HCC.Conclusion:RFX5 is a putative HCC driver gene that plays an important role in the development and progression of HCC by transactivating YWHAQ and suppressing apoptosis.

Effect of Upregulated DNA Replication and Sister Chromatid Cohesion 1 Expression on Proliferation and Prognosis in Hepatocellular Carcinoma

Background: DNA replication and sister chromatid cohesion 1 (DSCC1) (also called DCC1) is a component of an alternative replication factor C complex that loads proliferating cell nuclear antigen onto DNA during S phase of the cell cycle. It is located at 8q24 and frequently amplified in hepatocellular carcinoma (HCC). However, the role of DSCC1 in the carcinogenesis and progress of HCC has not been fully investigated. Here, we aimed to assert the importance of DSCC1 in the HCC. Methods: In this study, copy number variation data and RNA sequencing data were used to calculate the DNA copy number and mRNA expression of DSCC1 in HCC. Quantitative polymerase chain reaction, Western blotting, and immunohistochemistry analysis were used to determine the mRNA and protein level of DSCC1 in HCC. The Kaplan–Meier analysis and univariate and multivariate Cox regression analysis were used to assess the association of DSCC1 with the overall survival (OS) of HCC patients. Moreover, lentiviral shRNA was used to knockdown DSCC1, and then, colony?forming assay, cell cycle assay, and cell proliferation assay were performed to evaluate the impact of DSCC1 silencing on HCC cell lines. Results: We found that DSCC1 was amplified and highly expressed in HCC tumor tissues than in nontumor tissues. We then found that the overexpression of both mRNA and protein of DSCC1 was linked to the bad prognosis of HCC patients. Astonishingly, the protein level of DSCC1 was an independent prognostic factor for OS (hazard ratio, 1.79; 95% confidence interval, 1.17–2.74; P = 0.007). Furthermore, the clonogenic capacity of DSCC1?amplified HCC cell lines (MHCC?97H, MHCC?97L, and Hep3B) was significantly inhibited by transduction of a lentiviral shRNA that targets DSCC1. We also showed that knockdown of DSCC1 induced G0–G1 cell cycle arrest (increased from 60% to more than 80%) and greatly inhibited the proliferation of HCC cell lines. Conclusion: These results suggest that DSCC1 is a putative HCC driver gene that promotes proliferation and is associated with poor prognosis in HCC.