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Purpose: Intratumoral hepatitis B virus (HBV) integrations and mutations are related to hepatocellular carcinoma (HCC) progression. Circulating cell-free DNA (cfDNA) has shown itself as a powerful noninvasive biomarker for cancer. However, the HBV integration and mutation landscape on cfDNA remains unclear. Experimental Design: A cSMART (Circulating Single-Molecule Amplification and Resequencing Technology)-based method (SIM) was developed to simultaneously investigate HBV integration and mutation landscapes on cfDNA with HBV-specific primers covering the whole HBV genome. Patients with HCC (n = 481) and liver cirrhosis (LC; n = 517) were recruited in the study. Results: A total of 6,861 integration breakpoints including TERT and KMT2B were discovered in HCC cfDNA, more than in LC. The concentration of circulating tumor DNA (ctDNA) was positively correlated with the detection rate of these integration hotspots and total HBV integration events in cfDNA. To track the origin of HBV integrations in cfDNA, whole-genome sequencing (WGS) was performed on their paired tumor tissues. The paired comparison of WGS data from tumor tissues and SIM data from cfDNA confirmed most recurrent integration events in cfDNA originated from tumor tissue. The mutational landscape across the whole HBV genome was first generated for both HBV genotype C and B. A region from nt1100 to nt1500 containing multiple HCC risk mutation sites (OR > 1) was identified as a potential HCC-related mutational hot zone. Conclusions: Our study provides an in-depth delineation of HBV integration/mutation landscapes at cfDNA level and did a comparative analysis with their paired tissues. These findings shed light on the possibilities of noninvasive detection of virus insertion/mutation.

Background: Patients with liver cirrhosis are at higher risk of developing hepatocellular carcinoma (HCC). Due to the low accuracy of current methods, new non-invasive strategies for early HCC diagnosis in cirrhotic patients are needed. Methods: A case-control study recruited a total of 2,250 patients with liver cirrhosis (LC), 508 with HCC, and 476 healthy controls (CTRL), from 13 hospitals in 11 provinces of China. Four genomic features of cell-free DNA (cfDNA), including nucleosome footprint, fragmentation, base mismatch and 5-hydroxymethylcytosines were profiled. Training and validation cohorts helped develop the integrated diagnostic model, and a test cohort was used to evaluate its performance. Findings: We established a classifier of each feature for HCC against non-HCC (cirrhosis & healthy control). By integrating these four genomic features, we developed a novel diagnostic model (HIFI, 5-Hydroxymethylcytosines/base mIsmatch/Fragmentation/nucleosome footprInt), and achieved a higher accuracy in differentiating HCCs from liver cirrhosis (AUC=0.997 [0.994-0.999], sensitivity 95.42%, specificity 97.67% in test set) than AFP or PIVKA-II, irrespective of the following demographics and clinical features, age, HBV status, Child-Pugh score, BCLC stage, tumor size, and AFP status. In AFP positive (AFP>20ug/L) liver cirrhosis patients and AFP/PIVKA-II negative (AFP 400μg/L: 100% in liver cirrhosis patients; AFP

Background. We aimed to determine a discriminant function for prognosis in chronic severe hepatitis B (CSHB), by discriminant analysis of prognostic indexes and probability of death. Methods. In 205 patients with chronic severe hepatitis B (101 patients in the survival group and 104 patients in the death group), we carried out discriminant analysis of serum total bilirubin, prothrombin activity, white blood cells, creatinine, maximum depth of ascites, hepatic encephalopathy, singultus, and digestive tract hemorrhage. Results. The discriminant function was V = 0.00043 × total bilirubin (µM) − 0.025 × prothrombin activity (%) + 0.056 × white blood cells (109/l) + 0.00284 × creatinine (µM) + 0.0014 × maximum depth of ascites (mm) + 0.724 × hepatic encephalopathy score + 0.078 × singultus score + 0.457 × digestive tract hemorrhage score − 2.488. The correctness of the function for predicting death in the death group was 92.3%, and that for predicting survival in the survival group was 96.0%. When the V values were −∞, −4.595, −2.197, −1.386, −0.405, 0.405, 1.386, 2.197, 2.944, 4.595, and ∞, a posterior probabilities of death were 0%, 5%, 10%, 20%, 40%, 60%, 80%, 90%, 95%, 99%, and 100%, respectively. Conclusions. The discriminant function is an objective, convenient, and practical method to assess the prognosis of chronic severe hepatitis B.