Outcomes of adolescent and young patients with hepatocellular carcinoma after curative liver resection: a retrospective study

Clinical Characteristics and Prognosis of Early-Onset Hepatocellular Carcinoma: A Retrospective Cohort Study Based on Population Data

BACKGROUND

The incidence of young patients diagnosed with hepatocellular carcinoma (HCC) is projected to rise. This study aimed to investigate the distinctive characteristics of adolescent and young adult (AYA) patients with HCC and identify the risk factors that impact their survival.

METHODS

This study included 1005 AYA patients and 55,435 older adult (OA) patients with HCC, using data from the Surveillance, Epidemiology, and End Results database. Propensity score matching was used to adjust for baseline differences in patient characteristics. The Kaplan-Meier curve and log-rank test are utilized to compare the overall survival between the two groups. The Cox proportional hazards regression model was used for subgroup analysis to identify risk factors for overall survival in AYA patients.

RESULTS

AYA patients exhibited a higher proportion of advanced clinical stage (49.15% vs 37.57%, P < 0.001) and fibrolamellar hepatocellular carcinoma (14.13% vs 0.09%, P < 0.001), but a lower incidence of alpha-fetoprotein positivity (32.04% vs 45.32%, P < 0.001) and cirrhosis (8.86% vs 18.32%, P < 0.001). The subgroup analysis results indicated that AYA patients had a more favorable prognosis than OA patients in most subgroups. Undifferentiated carcinoma emerged as the predominant risk factor for AYA patients (Hazard Ratio [HR], 6.08 [2.53-14.62]), whereas partial hepatectomy was determined to be the most advantageous factor (HR, 0.29 [0.23-0.37]).

CONCLUSIONS

AYA patients with HCC exhibit more aggressive characteristics but demonstrate a better prognosis compared to the OA group, necessitating personalized surveillance and treatment.

TRAF2 inhibits senescence in hepatocellular carcinoma cells via regulating the ROMO1/ NAD+/SIRT3/SOD2 axis

The suppression of tumor proliferation via cellular senescence has emerged as a promising approach for anti-tumor therapy. Tumor necrosis factor receptor-associated factor 2 (TRAF2), an adaptor protein involved in the NF-κB signaling pathway and reactive oxygen species (ROS) production, has been implicated in hepatocellular carcinoma (HCC) proliferation. However, little is currently known about whether TRAF2 promotes HCC development by inhibiting cellular senescence. Replicative senescence model and IR-induced mouse model demonstrated that TRAF2 expression was decrease in senescence cells or liver tissues. Depletion of TRAF2 could inhibit proliferation and arrest the cell cycle via activating p53/p21WAF1 and p16INK4a/pRb signaling pathways in HCC cells and eventually lead to cellular senescence. Mechanistically, TRAF2 deficiency increased the expression of mitochondrial protein reactive oxygen species modulator 1 (ROMO1) and subsequently activated the NAD+/SIRT3/SOD2 pathway to promote the production of ROS and cause mitochondrial dysfunction, which eventually contributed to DNA damage response (DDR). Our findings demonstrate that TRAF2 deficiency inhibits the proliferation of HCC by promoting senescence. Therefore, targeting TRAF2 through various approaches holds therapeutic potential for treating HCC.

Preoperative MRI-based multiparametric model for survival prediction in hepatocellular carcinoma patients with portal vein tumor thrombus following hepatectomy

PURPOSE

To develop a predictive model integrating clinical and MRI features for postoperative survival in patients with hepatocellular carcinoma (HCC) and portal vein tumor thrombus (PVTT).

METHOD

Between January 2008 and May 2021, consecutive HCC patients with PVTT who underwent preoperative contrast-enhanced MRI and surgical resection at a tertiary hospital were retrospectively enrolled. The MR images were independently reviewed by two blinded radiologists. Univariate and multivariate Cox regression analyses were performed to construct a prognostic score for overall survival (OS).

RESULTS

Ninety-four patients were included (mean age, 50.1 years; 84 men). During a median follow-up period of 15.3 months, 72 (76.6%) patients died (median OS, 15.4 months; median disease-free survival [DFS], 4.6 months). The sum size of the two largest tumors (hazard ratio [HR], 3.050; p < 0.001) and tumor growth subtype (HR, 1.928; p = 0.006) on MRI, serum albumin (HR, 0.948; p = 0.02), and age (HR, 0.978; p = 0.04) were associated with OS and incorporated in the prognostic score. Accordingly, patients were stratified into a high-risk or low-risk group, and the OS in the high-risk group was shorter than that in the low-risk group for the entire cohort (11.7 vs. 25.0 months, p < 0.001) and for patients with Cheng's type I (12.1 vs. 25.9 months, p = 0.002) and type II PVTT (11.7 vs. 25.0 months, p = 0.004). The DFS in the high-risk group was shorter than that in the low-risk group for the entire cohort (4.5 vs. 6.1 months, p = 0.001).

CONCLUSIONS

Based on the sum size of the two largest tumors, tumor growth subtype, albumin, and age, the prognostic score allowed accurate preoperative risk stratification in HCC patients with PVTT, independent of Cheng's PVTT classification.

Identification of risk and prognostic factors for intrahepatic vascular invasion in patients with hepatocellular carcinoma: a population-based study

Background

The aim of this study was to develop nomograms to predict the risk of intrahepatic vascular invasion (IVI) of hepatocellular carcinoma (HCC) patients and estimate the overall survival (OS) and cancer-specific survival (CSS) of HCC patients with IVI.

Methods

The Surveillance, Epidemiology, and End Results (SEER) database was used to identify patients with HCC from 2010 to 2015. Ultimately, 1,287 HCC patients with IVI were included in this study and randomly divided into training (n=901) and validation (n=386) cohorts. Multivariate logistic regression analysis and multivariate Cox proportional hazards regression analysis were performed to construct nomograms to visually quantify the risk of IVI in patients with HCC and predict the prognosis. The prediction effect of nomograms was evaluated using Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis (DCA), respectively.

Results

The C-index of the nomogram for risk prediction was 0.730. The C-indices based on the nomogram were 0.762 [95% confidence interval (CI): 0.745-0.779] and 0.770 (95% CI: 0.753-0.787) for OS and CSS prediction in the training cohort, respectively. In the validation cohort, the C-indices were 0.779 (95% CI: 0.752-0.806) and 0.795 (95% CI: 0.768-0.822) for OS prediction and CSS prediction, respectively. Overall, the ROC curve, calibration plots, and DCA indicated the good performance of nomograms.

Conclusions

We identified the relevant risk and prognostic factors for IVI in patients with HCC. The nomograms performed well on validation and may help to facilitate clinical decision-making.