Journal of Hepatocellular Carcinoma最新文献

Introduction: Lenvatinib and sorafenib remain viable first-line (1L) options for patients ineligible for newer therapies. This study uses real-world data (RWD) to compare the effectiveness and safety of lenvatinib and sorafenib, addressing gaps between clinical trials and real-world practice.

Materials and methods: This retrospective, multi-center study utilized the Liver Cancer IN Korea (LINK) database, including HCC patients diagnosed between January 2015 and June 2022 who received 1L lenvatinib or sorafenib. Effectiveness and safety were assessed with real-world overall survival (rwOS), time to treatment discontinuation (rwTTD), time to next treatment (rwTTNT), and incidence of adverse events of special interest (AESI). Propensity score matching was employed to adjust for potential bias.

Results: Post-matching, lenvatinib demonstrated a longer median rwOS of 9.56 months (95% CI: 8.25-10.78) compared to 7.13 months (95% CI: 6.44-7.82) of sorafenib, and longer medians for rwTTD (3.65 months, 95% CI: 3.09-4.07 vs 2.04 months, 95% CI: 1.87-2.30) and rwTTNT (6.51 months, 95% CI: 5.62-7.62 vs 3.71 months, 95% CI: 3.45-4.34). Regarding AESI, lenvatinib was significantly associated with lower rates of hand-foot syndrome (incidence rate ratio, IRR 0.55, 95% CI: 0.33-0.88, p = 0.013) and most hepatotoxicity-related events, but a higher rate of proteinuria (IRR 2.40, 95% CI: 1.49-3.98, p < 0.001).

Conclusion: Leveraging RWD, our study demonstrated that 1L lenvatinib may offer a survival advantage over 1L sorafenib in HCC patients, with both treatments exhibiting safety profiles consistent with clinical trials. RWD complements clinical trials by validating long-term outcomes and addressing patient populations excluded from pivotal studies, guiding therapeutic decisions in clinical practice.

Purpose: Lenvatinib is an effective treatment for patients with intermediate- to advanced-stage unresectable hepatocellular carcinoma (HCC). However, tumor response and survival outcomes vary widely. Traditional machine learning (ML) models have been developed to predict treatment response or survival status at discrete time points. However, an overall prediction of overall survival (OS) and progression-free survival (PFS) incorporating censored survival data is lacking. We aimed to conduct a comprehensive survival analysis of OS and PFS by using ML-based survival models.

Patients and methods: This multicenter, retrospective study included patients with unresectable HCC receiving lenvatinib across five healthcare centers. Demographic data, laboratory results, tumor characteristics, and survival outcomes were collected. Five ML-based survival models were developed and compared using Harrell's concordance index (C-index). The predicted risk scores were used to stratify patients into low-, intermediate-, and high-risk groups and validated in the test set.

Results: 205 patients were included for training and validation. Among the five ML models, the GBM-Cox model achieved the highest C-indices for both OS (0.617) and PFS (0.645) prediction. The predicted risk scores stratified the patients into low-, intermediate-, and high-risk groups for OS (median, 18.7 vs 13.6 vs 8.8 months; p = 0.004) and PFS (median, 8.2 vs 4.0 vs 3.7; p = 0.017). The most influential prognostic factors included albumin-bilirubin (ALBI) score, alanine aminotransferase, and age for OS, and macrovascular invasion, ALBI score, and alpha-fetoprotein for PFS.

Conclusion: ML-based survival models successfully stratified patients into low-, intermediate-, and high-risk groups for OS and PFS. Key features included ALBI score and alanine aminotransferase for OS, and macrovascular invasion and ALBI score for PFS. These models have the potential to guide clinicians' treatment decisions and provide prognostic evaluations. Future prospective studies with larger cohorts, as well as integration of imaging biomarkers are warranted to optimize these predictive models.

Background: There is relatively scant evidence concerning the effects of Lenvatinib and Pembrolizumab together with TACE for advanced HCC Lenvatinib and pembrolizumab have been widely applied in clinical settings. PIVKA-II serving as the sensitive biomarker for evaluating liver cancer was employed by us to further assess the therapeutic effectiveness of TACE combined with Lenvatinib in the treatment of BCLC C.

Methods: In this retrospective study, 260 patients with HCC BCLC C stage were included in the present study. TACE (TL group) included 126 patients, TACE-Lenvatinib-Pembrolizumab (TPB group) consisted of 134 patients. OS and PFS were compared between the two groups. Alternatively, the impact of PIVKA-II in TPB on the PFS of BCLC C stage was also assessed.

Results: The median overall survival (OS) in the TL group was significantly prolonged compared to that in the TPB group (13.7 months versus 9.6 months). Conversely, the median progression - free survival (PFS) was extended in the TPB group as opposed to the TL group (9.3 months versus 6.2 months). The adverse events in the TPB group were controllable and tolerable. After six months of combined treatment, the change in PIVKA - II became less significant. This suggests that PIVKA-II is negatively correlated with PFS, meaning that the greater the decrease in PIVKA-II after 6 months of combined therapy, the longer the PFS time for the patient.

Conclusion: TACE combined with Lenvatinib and Pembrolizumab exhibited remarkable survival benefits for HCC BCLC C patients. Given the extremely dismal prognosis of advanced HCC, the safety and efficacy of TACE in combination with Lenvatinib and Pembrolizumab justify its clinical application.

Background: Transarterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC), but resistance to TACE is a major clinical challenge. This study aimed to identify genes associated with TACE refractoriness and their roles in HCC progression.

Methods: Gene expression profiles from 104 HCC patients treated with TACE were analyzed using unsupervised clustering to identify molecular subtypes. Key genes associated with TACE refractoriness were identified through univariate Cox regression and lasso, with ATP1B3 emerging as a candidate. Functional annotation of ATP1B3 was conducted using KEGG, GO, and GSEA analyses, while immune profiling and immunotherapy response were compared between ATP1B3-high and ATP1B3-low groups. Single-cell RNA sequencing (scRNA-seq) was employed to explore ATP1B3 expression and its cellular interactions. In vitro functional assays validated its role in migration, invasion, cell cycle, chemotherapy sensitivity, and apoptosis.

Results: Unsupervised clustering revealed two distinct molecular subtypes of HCC. Cluster 1 was associated with significantly prolonged overall and recurrence-free survival, whereas Cluster 2 exhibited aggressive tumor behavior and adverse clinical outcomes. ATP1B3 was identified as a pivotal gene linked to TACE refractoriness and poor prognosis. Elevated ATP1B3 expression was strongly correlated with metabolic dysregulation, heightened tumor aggressiveness, immune evasion, and diminished therapeutic responses to TACE, sorafenib, and immunotherapy. scRNA-seq analyses demonstrated widespread ATP1B3 expression across tumor and immune cell subsets, with ATP1B3-positive HCC cells displaying enhanced interactions with immune cells. Functional assays revealed that ATP1B3 overexpression promoted tumor migration, invasion, and chemoresistance, while its silencing induced cell cycle arrest, apoptosis, and increased sensitivity to cisplatin.

Conclusion: This study identifies TACE refractoriness-related gene ATP1B3 as a key regulator of tumor progression, immune evasion, and therapeutic resistance in HCC. These findings highlight ATP1B3 as a promising biomarker for patient stratification and a potential therapeutic target to improve clinical outcomes in HCC.

Objective: Dual-phenotype hepatocellular carcinoma (DPHCC) is a unique subtype of hepatocellular carcinoma (HCC) characterized by strong tumor stemness and invasive capabilities. ARID3A is identified as a potential regulator of tumor stemness in DPHCC by applying transcriptomic analysis. The precise mechanisms of ARID3A on the aggressive behavior of DPHCC remain to be further explored.

Materials and methods: In vitro functional experiments and in vivo tumorigenesis assays were used to validate the malignant behaviors of ARID3A. RNA sequencing was performed on ARID3A-transfected cells to identify ARID3A-mediated regulatory mechanisms. Finally, the impact of ARID3A-TNF-α/NF-κB axis on HCC malignant behavior was analyzed through in vitro blocking or stimulation experiments.

Results: The expression of ARID3A was upregulated in DPHCC and was associated with poor prognosis among these patients (p = 0.006, HR = 3.77, 95% CI:1.762-8.069). In vitro and in vivo experiments indicated that ARID3A facilitated stemness features and tumor progression. Findings from RNA-seq suggested that ARID3A enhanced tumor stemness and activated epithelial-mesenchymal transition through the activation of TNF-α-mediated NF-κB signaling. In vitro stimulation of ARID3A-transfected cells lines with recombinant TNF-α protein or inhibition of TNF-α-mediated NF-κB signaling regulated the ARID3A-mediated invasiveness.

Conclusion: Our study reveals that ARID3A acts as an oncogene and promotes aggressive features of stem-like cells in DPHCC via the ARID3A-TNF-α/NF-κB axis. Thus, it may facilitate the development therapeutic strategy for DPHCC.

Objective: To construct a radiomics-based model for predicting postoperative recurrence in hepatocellular carcinoma (HCC) patients with vessels encapsulating tumor clusters (VETC) positive based on CT scan.

Methods: This retrospective study enrolled patients who underwent surgical resection between January 2016 and January 2024 at Union Hospital, with pathologic confirmation of HCC and VETC status. An external test set was drawn from Chegu Hospital, covering January 2018 to January 2022. Tumor segmentation was performed on portal venous phase CT scan, and then radiomics features were extracted. These features were further analyzed using the LASSO algorithm and combined with clinical features to construct a radiomics-clinical combination model. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Patients were divided into high- and low-risk groups based on model scores, and Kaplan-Meier (KM) curves were compared.

Results: A total of 243 patients were included (median age 56.7 years, 211 males). Nine radiomics features and two clinical features were selected to construct the combined model. The area under the ROC curve (AUC) for predicting 1-year recurrence was 0.898 (95% CI: 0.797-0.999) in the internal test set and 0.804 (95% CI: 0.641-0.967) in the external test set. Calibration curves and DCA demonstrated high net clinical benefit of the combined model. The median recurrence-free survival (RFS) of patients in the high-risk group was significantly lower than that in the low-risk group (internal test set: 13.5 vs 30.0 months, respectively. P=0.004; external test set: 13.0 vs 31.0 months, respectively. P< 0.0001).

Conclusion: The radiomics-clinical combination model showed high accuracy for preoperatively predicting recurrence in patients with VETC-positive HCC receiving hepatectomy.

Background: To evaluate the relationship between soluble CD36 (sCD36) and type 2 diabetes mellitus complicated by hepatocellular carcinoma (T2DM-HCC), and to explore its potential clinical prognostic value.

Methods: A prospective study was conducted enrolling newly diagnosed T2DM-HCC patients from two medical centers, along with control groups including healthy individuals (HC), T2DM patients, and HCC patients. Clinical, biochemical, and pathological data were collected. Serum sCD36 levels were measured by ELISA. Univariate and multivariate analyses were used to identify recurrence risk factors, and ROC analysis was performed to evaluate diagnostic performance.

Results: Among 258 participants, the T2DM-HCC group exhibited the highest sCD36 levels, impaired liver function, lower platelets, and mild chronic inflammation. In this group, sCD36 levels positively correlated with tumor stage, size, and proliferation. In univariable analysis, it was associated with postoperative recurrence (OR = 2.57, 95% CI: 0.68-9.67). The predictive ability of sCD36 for recurrence (AUC = 0.86) was comparable to AFP (AUC = 0.89), while their combination showed the highest accuracy (AUC = 0.94).

Conclusion: sCD36 is associated with tumor progression in T2DM-HCC patients and serves as an independent risk factor for recurrence. To the best of our knowledge, this is the first study to identify sCD36 as a critical clinical biomarker for disease progression in T2DM-HCC, with strong potential for clinical application.

Trial registration: This study was registered in September 2024 with the Chinese Clinical Trial Registry (ChiCTR), registration number: ChiCTR2400089651.

Objective: This study retrospectively analyzed clinical data from adolescent primary liver cancer (PLC) cases over the past decade, summarizing clinical characteristics, diagnostic approaches, and prognostic outcomes to provide guidance for prevention, early diagnosis, and timely treatment of adolescent PLC.

Methods: Clinical data of 497 cases of adolescent PLC patients were collected from January 1, 2014, to December 31, 2024. The baseline demographic data, general condition, imaging, laboratory findings, and pathological features of these patients were described, and the diagnostic and therapeutic processes were analyzed, univariate and multivariate Cox regression analyses were conducted to identify significant prognostic factors.

Results: The age of onset for patients was 13.75 (10.25-19.00) years, with 311 males (62.58%) and 186 females (37.42%), yielding a male-to-female ratio of 1.67:1. Elevated ALT and GGT levels were observed in most patients, while all patients exhibited elevated ChE. Among all patients included in this study, 320 cases (64.39%) were infected with HBV, 469 cases (94.36%) were diagnosed with hepatocellular carcinoma (HCC), 14 cases (2.82%) with intrahepatic cholangiocarcinoma, and 14 cases (2.82%) with mixed hepatocellular-intrahepatic cholangiocarcinoma. The follow-up results showed the 1-year, 2-year, and 3-year survival rates in adolescent PLC patients were 45.27%, 20.32%, and 8.45%, respectively. The univariate Cox regression analysis revealed that adolescent PLC patients who accompanied with portal vein tumor thrombus, ascites, advanced CNLC stage, abnormalities in AFP, ALT, AST, AST/ALT ratio, GGT, ALP and TBIL, high ECOG score and non-surgical treatment had shorter OS (P < 0.05). Multivariate Cox regression analysis showed that portal vein tumor thrombus, advanced CNLC stage, abnormalities in AFP, GGT, and non-surgical treatment were independent prognostic factors influencing the OS of adolescent PLC patients (P < 0.05).

Conclusion: Clinical manifestations and symptoms of adolescent PLC patients lack specificity, and portal vein tumor thrombus, advanced CNLC stage, abnormalities in AFP, GGT, and non-surgical treatment were independent prognostic factors influencing OS in adolescent PLC.

Purpose: Systemic inflammatory response is reported to occupy a crucial role in the progression of hepatocellular carcinoma (HCC). The prognostic significance of SII and PNI in HCC has been explored, but the prognostic significance of aggregate index of systemic inflammation (AISI) in HCC is still unknown. This study was designed to determine the prognostic significance of AISI in HCC and explain the potential underlying mechanisms via gut microbiota and fecal metabolomic profiling.

Patients and methods: A cohort of 109 cases of HCC individuals during January 2023 to August 2024 was included into this clinical research, and the clinical information and fresh fecal samples were collected. The fecal samples were collected for 16S rRNA sequence and metabolomics analysis.

Results: Survival analysis revealed that HCC patients in low AISI group tend to experience relatively longer survival time compared with those in high AISI group. Then, we employed ROC analysis to measure the predictive performance of AISI for the survival outcome, and ROC curve showed that levels of AISI had good predictive performance for the survival status with an AUC of 0.771 (95%CI: 0.671-0.871). 16S rRNA sequencing results revealed that levels of Parabacteroides were up-regulated in the low AISI group, and levels of Fusicatenibacter were up-regulated in the high AISI group. Metabolic analysis demonstrated that cavipetin A, pemptoporphyrin, and 8-Oxo-dGMP with high VIP value were the most distinct fecal metabolites.

Conclusion: AISI is a potential prognostic biomarker in individuals with HCC. A low level of AISI was correlated with high abundance of Parabacteroides and some metabolites, indicating that AISI might affect the prognosis of HCC individuals via the regulations of gut microbes and metabolites.

Hepatocellular carcinoma (HCC) is the most common liver cancer and has a high incidence in China, largely due to the high prevalence of hepatitis B virus (HBV) infection. HBV‑related HCC often presents with aggressive characteristics but preserved liver function. Resection and ablation are approaches to achieve potentially curative outcomes. However, the recurrence rate is high, with up to 70% within five years. Curative surgery or ablation is used more broadly in China than in Western countries, so identifying patients at high risk of recurrence is essential: risk stratification can inform postoperative management, including surveillance intensity and avoidance of over- or under-treatment. Baseline characteristics provide a simple method of prediction, the impacts of which differ in early and late recurrence. To our knowledge, this is the first narrative review to comprehensively understand the identification, prevalence, and impact of risk factors for both early and late HCC recurrence in Chinese patients following curative‑intent resection or ablation. The review suggests that the most impactful risk factors for early recurrence are aggressive tumor features including tumor size, number and vascular invasion. For late recurrence, key risk factors are patient characteristics such as sex, viral infections and liver cirrhosis. As these risk factors are interrelated, several integrated predictive models like nomograms and artificial intelligence (AI) applications have been proposed, which may enhance risk stratification and inform personalized management strategies. These models should be further validated in large prospective studies to achieve clinical application.