Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis

BACKGROUND The prognosis for hepatocellular carcinoma(HCC)in the presence of cirrhosis is unfavourable,primarily attributable to the high incidence of recurrence.AIM To develop a machine learning model for predicting early recurrence(ER)of posthepatectomy HCC in patients with cirrhosis and to stratify patients’overall survival(OS)based on the predicted risk of recurrence.METHODS In this retrospective study,214 HCC patients with cirrhosis who underwent curative hepatectomy were examined.Radiomics feature selection was conducted using the least absolute shrinkage and selection operator and recursive feature elimination methods.Clinical-radiologic features were selected through univariate and multivariate logistic regression analyses.Five machine learning methods were used for model comparison,aiming to identify the optimal model.The model’s performance was evaluated using the receiver operating characteristic curve[area under the curve(AUC)],calibration,and decision curve analysis.Additionally,the Kaplan-Meier(K-M)curve was used to evaluate the stratification effect of the model on patient OS.RESULTS Within this study,the most effective predictive performance for ER of post-hepatectomy HCC in the background of cirrhosis was demonstrated by a model that integrated radiomics features and clinical-radiologic features.In the training cohort,this model attained an AUC of 0.844,while in the validation cohort,it achieved a value of 0.790.The K-M curves illustrated that the combined model not only facilitated risk stratification but also exhibited significant discriminatory ability concerning patients’OS.CONCLUSION The combined model,integrating both radiomics and clinical-radiologic characteristics,exhibited excellent performance in HCC with cirrhosis.The K-M curves assessing OS revealed statistically significant differences.

NQO1 Mediates Lenvatinib Resistance by Regulating ROS-induced Apoptosis in Hepatocellular Carcinoma

Objective Hepatocellular carcinoma(HCC)is the third leading cause of cancer-associated death worldwide.As a first-line drug for advanced HCC treatment,lenvatinib faces a significant hurdle due to the development of both intrinsic and acquired resistance among patients,and the underlying mechanism remains largely unknown.The present study aims to identify the pivotal gene responsible for lenvatinib resistance in HCC,explore the potential molecular mechanism,and propose combinatorial therapeutic targets for HCC management.Methods Cell viability and colony formation assays were conducted to evaluate the sensitivity of cells to lenvatinib and dicoumarol.RNA-Seq was used to determine the differences in transcriptome between parental cells and lenvatinib-resistant(LR)cells.The upregulated genes were analyzed by GO and KEGG analyses.Then,qPCR and Western blotting were employed to determine the relative gene expression levels.Afterwards,the intracellular reactive oxygen species(ROS)and apoptosis were detected by flow cytometry.Results PLC-LR and Hep3B-LR were established.There was a total of 116 significantly upregulated genes common to both LR cell lines.The GO and KEGG analyses indicated that these genes were involved in oxidoreductase and dehydrogenase activities,and reactive oxygen species pathways.Notably,NAD(P)H:quinone oxidoreductase 1(NQO1)was highly expressed in LR cells,and was involved in the lenvatinib resistance.The high expression of NQO1 decreased the production of ROS induced by lenvatinib,and subsequently suppressed the apoptosis.The combination of lenvatinib and NQO1 inhibitor,dicoumarol,reversed the resistance of LR cells.Conclusion The high NQO1 expression in HCC cells impedes the lenvatinib-induced apoptosis by regulating the ROS levels,thereby promoting lenvatinib resistance in HCC cells.

Laparoscopic combined with thoracoscopic transdiaphragmatic hepatectomy for hepatitis B-related hepatocellular carcinoma located in segment VII or VIII

Laparoscopic hepatectomy(LH)is considered a safe and effective method of treating liver cancer because of its relatively low level of trauma,bleeding,pain,and short hospital stay as compared with traditional open surgery[1].However,this is not ideal for tumors located in segment VII or VIII of the liver as these tumors are difficult to be exposed during laparoscopy,and the conversion rate is relatively high[2].Although it has been reported that the thoracoscopic transdiaphragmatic segment VII or VIII hepatectomy can obtain better visual field and operation space[3]。

A new staging system for hepatocellular carcinoma associated with portal vein tumor thrombus

Background:A new staging system for patients with hepatocellular carcinoma(HCC)associated with portal vein tumor thrombus(PVTT)was developed by incorporating the good points of the BCLC classification of HCC,and by improving on the currently existing classifications of HCC associated with PVTT.Methods:Univariate and multivariate analysis with Waldχ2 test were used to determinate the clinical prognostic factors for overall survival(OS)in patients with HCC and PVTT in the training cohort.Then the conditional inference trees analysis was applied to establish a new staging system.Results:A training cohort of 2,179 patients from the Eastern Hepatobiliary Surgery Hospital and a validation cohort of 1,550 patients from four major liver centers in China were enrolled into establishing and validating a new staging system.The system was established by incorporating liver function,general health status,tumor resectability,extrahepatic metastasis and extent of PVTT.This staging system had a good discriminatory ability to separate patients into different stages and substages.The median OS for the two cohorts were 57.1(37.2-76.9),12.1(11.0-13.2),5.7(5.1-6.2),4.0(3.3-4.6)and 2.5(1.7-3.3)months for the stages 0 to IV,respectively(P<0.001)in the training cohort.The corresponding figures for the validation cohort were 6.4(4.9-7.9),2.8(1.3-4.4),10.8(9.3-12.4),and 1.5(1.3-1.7)months for the stages II to IV,respectively(P<0.001).The mean survival for stage 0 to 1 were 37.6(35.9-39.2)and 30.4(27.4-33.4),respectively(P<0.001).Conclusions:A new staging system was established which provided a good discriminatory ability to separate patients into different stages and substages after treatment.It can be used to supplement the other HCC staging systems.