Objectives: Preoperative prediction of post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC) is significant for developing appropriate treatment strategies. We aimed to establish a radiomics-based clinical model for preoperative prediction of PHLF in HCC patients using gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI).Methods: A total of 144 HCC patients from two medical centers were included, with 111 patients as the training cohort and 33 patients as the test cohort, respectively. Radiomics features and clinical variables were selected to construct a radiomics model and a clinical model, respectively. A combined logistic regression model, the liver failure (LF) model that incorporated the developed radiomics signature and clinical risk factors was then constructed. The performance of these models was evaluated and compared by plotting the receiver operating characteristic (ROC) curve and calculating the area under the curve (AUC) with 95% confidence interval (CI).Results: The radiomics model showed a higher AUC than the clinical model in the training cohort and the test cohort for predicting PHLF in HCC patients. Moreover, the LF model had the highest AUCs in both cohorts [0.956 (95% CI: 0.955–0.962) and 0.844 (95% CI: 0.833–0.886), respectively], compared with the radiomics model and the clinical model.Conclusions: We evaluated quantitative radiomics features from MRI images and presented an externally validated radiomics-based clinical model, the LF model for the prediction of PHLF in HCC patients, which could assist clinicians in making treatment strategies before surgery.
The relationship between hepatitis B virus (HBV) and the prognosis of hepatocellular carcinoma (HCC) after surgery remains uncertain. A retrospective cohort study was performed to evaluate the impact of pre-S deletions, T1762/A1764, and A1896 mutations on prognosis of HCC after curative resection. A total of 113 patients with positive serum HBV DNA (>200 IU/mL) who had underwent curative resection of pathologically proven HCC were recruited to determine the risk factors affecting the prognosis.The median follow-up time was 36.5 months and recurrence was detected in 67 patients (59.3%). The cumulative recurrence rates and overall survival rates at 1-, 3-, and 5-year after curative resection were 18.0%, 49.7%, 70.3%, and 93.7%, 61.0%, 42.5%, respectively. Patients with pre-S deletions showed significantly higher recurrence rates compared with those with wild type infection (HR: 1.822, P = .018), but not related with a significantly poor survival (HR: 1.388, P = .235). Subgroup analysis indicated that the patients with type III deletion had significant higher tumor recurrence rates than other deletion types (HR: 2.211, 95% confidence intervals [CI]: 1.008–4.846, P = .048). Multivariate analysis revealed that pre-S deletion, tumor size >3 cm in diameter, and the presence of microvascular invasion were independent risk factors for tumor recurrence. HBV pre-S deletions were found to be clustered primarily in the 5′ end of pre-S2 region and were more often found between amino acids 120 and 142 of the pre-S2 domain. The domains most frequently potentially involved were the transactivator domain in pre-S2 and polymerized human serum albumin binding site.Our cohort showed that pre-S deletions at the time of resection could predict tumor recurrence in HCC patients after curative resection.
Background Increasing evidence indicates that RAD50, which is involved in the DNA double-strand break (DSB) repair process, is also involved in cancer outcomes. However, its role in hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) remains unclear.Aim This study was designed to investigate the expression of RAD50 and its prognostic value in HCC patients.Method A total of 207 patientswith HBV-associated HCCfrom two cohorts (107 and 100 patientsfrom the Affiliated Hospital of Youjiang Medical University of Nationalities and the Affiliated Hospital of Nantong University, respectively) were enrolled in the current study.The distribution of the categorical clinical-pathological data and the levels of RAD50 expression were compared with a χ 2 test. IHC staining of RAD50 was performed.A partial likelihood test based onunivariate and multivariate Cox regression analysis was developed to address the influence of independent factors on disease-free survival (DFS) and overall survival (OS). The Oncomine online database was used to analyse and validate the differential expression of RAD50. The Kaplan-Meier method and a log-rank test were performed to assess the influence of RAD50 on survival at different levels.Results RAD50 was highly expressed in HCC tissues compared to normal tissues and was significantly correlated with OS in the TCGA cohort. The validation analysis indicated that significantly increased levels of RAD50 were expressed in HCC tissues in the two independent cohorts, AHYMUN and AHNTU. In addition, HCC patients with elevated RAD50 expression levels showed poor OS and DFSin the AHYMUN cohort and decreased OS and DF Sin the AHNTU cohort. Furthermore, four datasets obtained from the Oncomine database validated the analysis of the differential expression of RAD50 in HCC tumours and normal tissues.Discussion In our study, we demonstrated that RAD50 was positively correlated with poor prognosis in HCC patients in the TCGA cohort. Our study also suggested that increased RAD50 expression in HBV-related HCC is a marker of poor prognosis. In this study, the analysis of the data form the two cohorts supported our hypothesis and clearly demonstrated thehigh expression of RAD50 in tumour tissues from HCC patients, which results inincreases in the HCC recurrence rate and poor overall survival.
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