Journal of Hepatocellular Carcinoma最新文献

Purpose: Long noncoding RNAs (lncRNAs) might be closely associated with hepatocellular carcinoma (HCC) progression and could serve as diagnostic and prognostic markers. This study aimed to investigate lncRNA-based diagnostic biomarkers for hepatitis B virus (HBV)-associated HCC.

Materials and methods: High-throughput transcriptome sequencing was conducted on the liver tissues of 15 patients with HBV-associated liver diseases (5 with chronic hepatitis B [CHB], 5 with liver cirrhosis [LC], and 5 with HCC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze lncRNA expressions. Potential diagnostic performance for HBV-associated HCC screening was evaluated.

Results: Through trend analysis and functional analysis, we found that 8 lncRNAs were gradually upregulated and 1 lncRNA was progressively downregulated by regulation of target mRNAs and downstream HCC-associated signaling pathways. The validation of dysregulated lncRNAs in peripheral blood mononuclear cells (PBMCs) and HCC tissues by qRT-PCR revealed that ADAMTSL4-AS1, SOCS2-AS1, and AC067931 were significantly increased in HCC compared with CHB and cirrhosis. Moreover, differentially expressed lncRNAs were aberrantly elevated in Huh7, Hep3B, HepG2, and HepG2.215 cells compared with LX2 cells. Furthermore, ADAMTSL4-AS1, SOCS2-AS1, and AC067931 were identified as novel biomarkers for HBV-associated HCC. For distinguishing HCC from CHB, ADAMTSL4-AS1, AC067931, and SOCS2-AS1 combined with alpha-fetoprotein (AFP) had an area under the curve (AUC) of 0.945 (sensitivity, 83.9%; specificity, 89.8%). Similarly, for distinguishing HCC from LC, this combination had an AUC of 0.871 (sensitivity, 91.1%; specificity, 68.2%). Furthermore, this combination showed the highest diagnostic ability to distinguish HCC from CHB and LC (AUC, 0.905; sensitivity, 91.1%; specificity, 75.3%). In particular, this combination identified AFP-negative (AFP < 20 ng/mL) (AUC = 0.814), small (AUC = 0.909), and early stage (AUC = 0.863) tumors.

Conclusion: ADAMTSL4-AS1, SOCS2-AS1, and AC067931 combined with AFP in PBMCs may serve as a noninvasive diagnostic biomarker for HBV-associated HCC, especially AFP-negative, small, and early stage HCC.

Purpose: To observe and assess the efficacy and safety of donafenib combined with transarterial chemoembolization (TACE) to treat unresectable hepatocellular carcinoma (HCC).

Patients and methods: This prospective, single-arm, single-center, phase II clinical study enrolled 36 patients with initial unresectable HCC who had not undergone any systemic treatment. The patients received donafenib plus TACE (n = 26) or donafenib plus TACE plus programmed death receptor 1 inhibitors (n = 10). The primary endpoint was short-term efficacy, with secondary endpoints including progression-free survival (PFS), time to response (TTR), disease control rate (DCR), and adverse events. The tumor feeding artery diameter was also measured.

Results: Efficacy evaluation of all 36 patients revealed 6 cases of complete response, 19 of partial response, 8 of stable disease, and 3 of progressive disease. Six (16.7%) patients successfully underwent conversion surgery, all achieving R0 resection, and 2 (5.6%) achieved a complete pathological response. The objective response rate (ORR) was 69.4% and the DCR was 91.7%. The median PFS was 10.7 months, the median overall survival was not reached, and the median TTR was 1.4 months. The median survival rates at 6, 12, and 18 months were 85.0%, 77.6%, and 71.3%, respectively. The median PFS rates at 6, 12, and 18 months were 65.3%, 45.6%, and 34.2%, respectively. Treatment-related adverse events (TRAEs) occurred in all 25 subjects, including 4 (11.3%) grade 3 TRAEs. No grade 4 or 5 TRAEs occurred. The tumor feeding artery diameter was significantly decreased following treatment (P = 0.036). Multivariable analysis revealed the sum of baseline target lesion diameters, best tumor response, and combined immunotherapy as independent predictors of PFS.

Conclusion: TACE plus donafenib reduced the tumor feeding artery diameter in patients with unresectable HCC. The safety profile was good, and a high ORR was achieved.

Purpose: The impact of visceral adiposity on overall survival (OS) in hepatocellular carcinoma (HCC) receiving immunotherapy was unclear. We aimed to determine how visceral adiposity affected OS and explore the interrelationships between visceral adiposity, body mass index (BMI), and other body compositions.

Patients and methods: Data from three centers were retrospectively analyzed. Skeletal muscle index (SMI), skeletal muscle density (SMD), visceral adipose tissue index (VATI), and subcutaneous adipose tissue index (SATI) were used to define each body composition. The BMI subgroups included the underweight, the normal weight, and the obesity. The Log rank test compared survival curves calculated by the Kaplan-Meier method. The relationships between body compositions and BMI with OS were examined using Cox proportional risk regression models.

Results: A total of 305 patients who met the criteria were included. Patients with low VATI had significantly worse OS (P = 0.001). The protections of VATI (P = 0.011) on OS were independent of covariates. However, after additional adjustment of SMI, the effect of VATI on OS disappeared (P = 0.146), but the effect of SMD on OS did not (P = 0.021). BMI has a significant U-shaped relationship with OS, and the effect of BMI on OS equally disappeared after additional adjustment by SMI.

Conclusion: This study first demonstrated that high VATI and mid-level BMI were protective for the survival of patients with HCC receiving immunotherapy. Skeletal muscle status (including SMI and SMD) may be the better predictor for outcomes of patients with HCC receiving immunotherapy.

Objective: The aim of this study is to develop and verify a magnetic resonance imaging (MRI)-based radiomics model for predicting the microvascular invasion grade (MVI) before surgery in individuals diagnosed with nodular hepatocellular carcinoma (HCC).

Methods: A total of 198 patients were included in the study and were randomly stratified into two groups: a training group consisting of 139 patients and a test group comprising 59 patients. The tumor lesion was manually segmented on the largest cross-sectional slice using ITK SNAP, with agreement reached between two radiologists. The selection of radiomics features was carried out using the LASSO (Least Absolute Shrinkage and Selection Operator) algorithm. Radiomics models were then developed through maximum correlation, minimum redundancy, and logistic regression analyses. The performance of the models in predicting MVI grade was assessed using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix.

Results: There were no notable statistical differences in sex, age, BMI (body mass index), tumor size, and location between the training and test groups. The AP and PP radiomic model constructed for predicting MVI grade demonstrated an AUC of 0.83 (0.75-0.88) and 0.73 (0.64-0.80) in the training group and an AUC of 0.74 (0.61-0.85) and 0.62 (0.48-0.74) in test group, respectively. The combined model consists of imaging data and clinical data (age and AFP), achieved an AUC of 0.85 (0.78-0.91) and 0.77 (0.64-0.87) in the training and test groups, respectively.

Conclusion: A radiomics model utilizing-contrast-enhanced MRI demonstrates strong predictive capability for differentiating MVI grades in individuals with nodular HCC. This model could potentially function as a dependable and resilient tool to support hepatologists and radiologists in their preoperative decision-making processes.