Jang, Jeong Won

Although hepatitis B virus (HBV) integration into the cellular genome is well known in HCC (hepatocellular carcinoma) patients, its biological role still remains uncertain. This study investigated the patterns of HBV integration and correlated them with TERT (telomerase reverse transcriptase) alterations in paired tumor and non-tumor tissues. Compared to those in non-tumors, tumoral integrations occurred less frequently but with higher read counts and were more preferentially observed in genic regions with significant enrichment of integration into promoters. In HBV-related tumors, TERT promoter was identified as the most frequent site (38.5% (10/26)) of HBV integration. TERT promoter mutation was observed only in tumors (24.2% (8/33)), but not in non-tumors. Only 3.00% (34/1133) of HBV integration sites were shared between tumors and non-tumors. Within the HBV genome, HBV breakpoints were distributed preferentially in the 3’ end of HBx, with more tumoral integrations detected in the preS/S region. The major genes that were recurrently affected by HBV integration included TERT and MLL4 for tumors and FN1 for non-tumors. Functional enrichment analysis of tumoral genes with integrations showed enrichment of cancer-associated genes. The patterns and functions of HBV integration are distinct between tumors and non-tumors. Tumoral integration is often enriched into both human-virus regions with oncogenic regulatory function. The characteristic genomic features of HBV integration together with TERT alteration may dysregulate the affected gene function, thereby contributing to hepatocarcinogenesis.

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.