Association between novel genetic variants of Notch signaling pathway genes and survival of hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

Although the Notch pathway plays an important role in formation and progression of hepatocellular carcinoma (HCC), few studies have reported the associations between functional genetic variants and the survival of hepatitis B virus (HBV)-related HCC.

METHODS

In the present study, we performed multivariable Cox proportional hazard regression analysis to evaluate associations between 36,101 SNPs in 264 Notch pathway-related genes and overall survival (OS) of 866 patients with HBV-related HCC.

RESULTS

It was found that three independent SNPs (NEURL1B rs4868192, CNTN1 rs444927 and FCER2 rs1990975) were significantly associated with the HBV-related HCC OS. The number of protective genotypes (NPGs) were significantly associated with better survival in a dose-response manner (ptrend <0.001). Compared with the model with sole clinical factors, the addition of protective genotypes to the predict models significantly increased the AUC, i.e., from 72.72% to 75.13% (p = 0.002) and from 72.04% to 74.76 (p = 0.004) for 3-year and 5-year OS, respectively. The expression quantitative trait loci (eQTL) analysis further revealed that the rs4868192 C allele was associated with lower mRNA expression levels of NEURL1B in the whole blood (p = 1.71 × 10-3), while the rs1990975 T allele was correlated with higher mRNA expression levels of FCER2 in the whole blood and normal liver tissues (p = 3.51 × 10-5 and 0.033, respectively).

CONCLUSIONS

Three potentially functional SNPs of NEURL1B, CNTN1 and FCER2 may serve as potential prognostic biomarkers for HBV-related HCC.

Potentially functional genetic variants in ferroptosis-related CREB3 and GALNT14 genes predict survival of hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

Ferroptosis is a known crucial player in the development of cancers. However, the effect of single nucleotide polymorphisms (SNPs) in ferroptosis-related genes on survival in hepatitis B virus (HBV)-related hepatocellular carcinoma (HBV-HCC) patients remains unknown.

METHODS

We used two-stage multivariable Cox proportional hazards regression analyses to estimate the associations between 48,774 SNPs in 480 ferroptosis-related genes and overall survival (OS) of 866 HBV-HCC patients.

RESULTS

We identified that two potentially functional SNPs (CREB3 rs10814274 C > T and GALNT14 rs17010547 T > C) were significantly independently associated with the OS of HBV-HCC patients (CT + TT verse CC, hazards ratio (HR) = 0.77, 95% confidence interval (CI) = 0.67-0.89, p < 0.001 for rs10814274 and TC + CC verse TT, HR = 0.66, 95% CI = 0.53-0.82, p < 0.001 for rs17010547, respectively). Additional joint assessment of protective genotypes of these two SNPs showed that patients with 1-2 protective genotypes had a significantly better OS compared with those carrying 0 protective genotypes (HR = 0.56, 95% CI = 0.45-0.70, p < 0.001). Moreover, the expression quantitative trait loci (eQTL) analysis revealed that the survival-associated SNP rs10814274 T allele was significantly correlated with reduced CREB3 transcript levels in both normal liver tissues and whole blood cells, while the GALNT14 rs17010547 C allele had a significant correlation with increased GALNT14 transcript levels in whole blood cells.

CONCLUSION

These results suggest that genetic variants of CREB3 and GALNT14 may affect the survival of HBV-HCC patients, likely via transcriptional regulation of respective genes. However, further studies are required to confirm these findings.

Development and Validation of a Prediction Model for Hepatitis B Virus-Related Hepatocellular Carcinoma Patients Receiving Postoperative Adjuvant Transarterial Chemoembolization

Background

Hepatocellular carcinoma (HCC) patients who are at significant risk of tumor recurrence and mortality can benefit from postoperative adjuvant transarterial chemoembolization (PA-TACE). However, the benefits of PA-TACE remain unclear. Herein, we aimed to develop a model for predicting the prognosis of HBV-related patients who undergo PA-TACE and endeavored to guide individualized clinical treatment.

Methods

We included 432 HBV-related patients who underwent PA-TACE after curative resection were included. The dataset was divided into a training set (n=216) and an internal validation set (n=216). For identifying independent risk factors, the least absolute shrinkage and selection operator and univariate and multivariate Cox analyses were performed. We derived a prognostic model from the training set that was internally validated. The concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and risk stratification were used to evaluate the performance of the nomogram.

Results

Patients undergoing PA-TACE had significantly longer overall survival (OS) than those who did not undergo PA-TACE. Age, albumin levels, macrovascular invasion, tumor size, and, stages of Barcelona Clinic Liver Cancer were identified as independent risk variables and concluded into the nomogram to predict the OS of HBV-related patients who received PA-TACE. The nomogram's C-index values OS were 0.710 and 0.652 in the training and internal validation sets, respectively. Both time-dependent AUC and the calibration curve showed good discrimination and model fitness. The risk score -0.12 was kept as the cut-off value that would accurately divide patients into high-risk and low-risk groups; furthermore, the Kaplan-Meier curve showed a high discriminative ability of the model.

Conclusion

We developed a predictive model. comprising a formula and nomogram to predict the OS and provide risk stratification for HBV-related patients undergoing PA-TACE, which could contribute to suitable treatment options for this patient population.

Radiotherapy plus anti-PD1 versus radiotherapy for hepatic toxicity in patients with hepatocellular carcinoma

PURPOSE

In this study, we aimed to compare the radiation-induced hepatic toxicity (RIHT) outcomes of radiotherapy (RT) plus antibodies against programmed cell death protein 1 (anti-PD1) versus RT alone in patients with hepatocellular carcinoma (HCC), evaluate prognostic factors of non-classic radiation-induced liver disease (ncRILD), and establish a nomogram for predicting the probability of ncRILD.

PATIENTS AND METHODS

Patients with unresectable HCC treated with RT and anti-PD1 (RT + PD1, n = 30) or RT alone (n = 66) were enrolled retrospectively. Patients (n = 30) in each group were placed in a matched cohort using propensity score matching (PSM). Treatment-related hepatotoxicity was evaluated and analyzed before and after PSM. The prognostic factors affecting ncRILD were identified by univariable logistic analysis and Spearman's rank test in the matched cohort to generate a nomogram.

RESULTS

There were no differences in RIHT except for increased aspartate aminotransferase (AST) ≥ grade 1 and increased total bilirubin ≥ grade 1 between the two groups before PSM. After PSM, AST ≥ grade 1 occurred more frequently in the RT + PD1 group (p = 0.020), and there were no significant differences in other hepatotoxicity metrics between the two groups. In the matched cohort, V25, tumor number, age, and prothrombin time (PT) were the optimal prognostic factors for ncRILD modeling. A nomogram revealed a good predictive performance (area under the curve = 0.82).

CONCLUSIONS

The incidence of RIHT in patients with HCC treated with RT + PD1 was acceptable and similar to that of RT treatment. The nomogram based on V25, tumor number, age, and PT robustly predicted the probability of ncRILD.

Establishment and validation of a prognostic pomogram in unresectable hepatocellular carcinoma treated with intensity modulated radiotherapy: a real world study

BACKGROUND

To establish a prognostic model to predict the overall survival (OS) in patients with unresectable hepatocellular carcinoma (HCC) treated with intensity modulated radiotherapy (IMRT).

METHODS

The unresectable HCC patients treated with IMRT were retrospectively analyzed and randomized into development cohort (n = 237) and validation cohort (n = 103) in a 7:3 ratio. We developed a prognosis model with the multivariate Cox regression analysis in the development cohort to derive the predictive nomogram, which was then validated in the validation cohort. Model performance was evaluated by the c-index, the area under curve(AUC) and the calibration plot.

RESULTS

A total of 340 patients were enrolled. Tumor numbers > 3 (HR = 1.69, 95% CI = 1.21-2.37), AFP ≥ 400 ng/ml (HR = 1.52, 95% CI = 1.10-2.10), PLT < 100 × 10^9(HR = 1.7495% CI = 1.11-2.73), ALP > 150U/L (HR = 1.65, 95% CI = 1.15-2.37) and prior surgery (HR = 0.63, 95% CI = 0.43-0.93) were independent prognostic factors. The nomogram based on independent factors was constructed. The c-index for OS prediction was 0.658 (95% CI, 0.647-0.804) and 0.683 (95% CI, 0.580-0.785) in the development and validation cohort, respectively. The nomogram demonstrated good discriminative ability with AUC rates of 0.726, 0.739 and 0.753 at 1-year, 2-year and 3-year models in the development cohort, and 0.715, 0.756 and 0.780 in the validation cohort, respectively. Additionally, good prognostic discrimination of the nomogram is also reflected in stratifying patients into two subgroups with distinct prognosis.

CONCLUSIONS

We constructed a prognostic nomogram for predicting the survival of patients with unresectable HCC treated with IMRT.