Journal of Hepatocellular Carcinoma最新文献

Background: Intratumoral tertiary lymphoid structures (iTLSs) are associated with favorable prognosis and immunotherapy response in hepatocellular carcinoma (HCC). This study aimed to develop an interpretable susceptibility-weighted imaging (SWI)-based radiomics model to non-invasively predict iTLSs in HCC.

Materials and methods: A retrospective cohort of 477 HCC patients undergoing preoperative SWI was used (training: 290; validation: 125; independent validation: 62). Radiomics models were constructed using five machine learning algorithms: logistic regression, random forest (RF), support vector machine, extreme gradient boosting, and K-nearest neighbors. Model performance was evaluated using the area under the ROC curve (AUC), model interpretability was examined using shapley additive explanations (SHAP), and survival analyses were performed to assess clinical relevance.

Results: In the independent validation cohort, the RF algorithm was identified as the optimal classifier, with an AUC of 0.771 (95% CI: 0.641-0.883), sensitivity of 78.6%, and specificity of 67.6%. It significantly outperformed the radiological model (p = 0.046), and showed comparable performance with the hybrid model in predicting iTLSs positivity (iTLSs+) (p > 0.05). SHAP analysis showed that radiomics features (logarithm_firstorder_Minimum and exponential_glszm_ZoneEntropy) were significant predictors of iTLSs+. Kaplan-Meier analysis demonstrated improved time-to-recurrence (TTR) in the iTLSs+ predictor group compared to the iTLSs-negativity (iTLSs-) predictor group (p < 0.05). Furthermore, patients in the iTLSs+ predictor group receiving tyrosine kinase inhibitors combined with immune checkpoint inhibitors (TKI-ICI) therapy exhibited significantly extended TTR (p < 0.05), while no benefit was observed in the iTLSs- predictor group.

Conclusion: The SWI-based radiomics model provided a non-invasive tool for predicting iTLSs+ in HCC and identifying patients who might benefit from TKI-ICI therapy, and it showed potential for future integration into clinical decision-making workflows.

Background: The prognosis of early recurrence of hepatocellular carcinoma (HCC) remains poor. This study aimed to develop and validate a radiomics model and determine potential biomarkers involved in biological pathways for early recurrence of HCC.

Methods: A total of 271 HCC patients from the First Affiliated Hospital of Guilin Medical University were enrolled as the training cohort. Recurrence related radiomics features were determined by analyzing contrast-enhanced CT images, which were used for the construction of Rad-score. For external validation, we utilized both imaging and transcriptome data from 34 HCC patients in TCGA database. The identified radiomics-related genes were further validated using two independent datasets (OEP000321 and GSE14520) and immunohistochemical analysis of EEF1E1 in 38 HCC tissue samples from training cohort.

Results: Rad-scores based on six radiomics features showed predictive value for early HCC recurrence in both cohorts (A465, A466, A839, V105, V250, V291). Relevant radiomics features are associated with metabolism, proliferation, and immune pathways. The most relevant recurrence-related radiomics gene module was determined via weighted correlation network analysis (WGCNA), which contained LRP12, GPD1L, GARS, EEF1E1, and DGKG. The model based on these genes could efficiently predict early HCC recurrence and was verified in the OEP000321 and GSE14520 datasets. Moreover, EEF1E1 was significantly associated with the Rad-score, illustrated prognostic value at the transcription level, and validated by immunohistochemical staining at the protein level.

Conclusion: Rad-score and radiomics gene signatures from enhanced CT effectively predicted early recurrence in HCC, while EEF1E1 might serve as an efficient biomarker for early recurrence prediction for hepatocellular carcinoma.

Purpose: This study aimed to develop a predictive model for the prognosis of patients with hepatocellular carcinoma (HCC) after resection.

Methods: Eighty-two HCC patients were randomly divided into a training cohort (n = 62) and a validation cohort (n = 20). Clinicopathological, multiproteomics features based on CO-Detection by Indexing (Codex), and radiomics features extracted from magnetic resonance imaging (MRI) were used to construct four models: clinicopathological model, radiomics model, proteomics model, and combined model. Model performance was evaluated using the C-index, calibration curves, receiver operating characteristic (ROC) curves, survival curves, and decision curve analysis (DCA).

Results: The combined model, integrating clinicopathological, radiomics, and multi-proteomic features, demonstrated the best performance of overall survival (OS) prediction in both the training cohort (C-index = 0.821, 95% CI: 0.745-0.897) and validation cohort (C-index = 0.791, 95% CI: 0.628-0.954). The calibration curve showed high accuracy of the combined nomogram in predicting OS.

Conclusion: This study innovatively integrates CODEX-based multiproteomics, radiomics, and clinicopathological features to construct a prognostic prediction model for HCC. The combined model demonstrates improved prognostic predictive efficacy compared with single-modality models. This approach establishes a theoretical foundation for personalized diagnosis and treatment. However, its clinical utility requires further validation through large-scale, multi-center studies.

Objective: This study aimed to evaluate setup errors associated with three respiratory motion management techniques in stereotactic body radiation therapy (SBRT) for individuals with hepatic malignancies.

Methods: A retrospective analysis was conducted on data from 55 individuals with hepatic malignancies who underwent SBRT. Respiratory motion was managed using the Active Breathing Coordinator (ABC) in 11 cases, the BodyFIX system in 6 cases, and a thermoplastic body film combined with an airbag in 38 cases. Cone-beam computed tomography (CBCT) was conducted prior to each treatment session and registered with the reference computed tomography (CT) images acquired during the treatment planning phase to quantify setup errors in three dimensions: left-right (LR), superior-inferior (SI), and anterior-posterior (AP).

Results: In the LR direction, the BodyFIX group had a 1.07 mm lower setup error than the ABC group, and the airbag group showed a 2.13 mm reduction compared to ABC and 1.06 mm compared to BodyFIX. In the SI direction, BodyFIX showed a 4.66 mm reduction and the airbag group a 5.45 mm reduction versus ABC. In the AP direction, reductions were 1.99 mm for BodyFIX and 2.86 mm for the airbag group compared to ABC. All differences were statistically significant. The airbag group also had relatively small planning target volume (PTV) margins.

Conclusion: The airbag-based respiratory motion management technique demonstrated superior positioning accuracy, improved reproducibility, and the potential for PTV margin reduction in SBRT for hepatic malignancies. Further investigations are needed to verify the superiority of this approach in different populations and settings.

Aim: To investigate the effect of IDO1 expression levels in HCC on the distribution, infiltration, and anti-tumor immune response of mature DCs.

Methods: Multiplex immunohistochemical staining was applied to detect the expression level of IDO1 and the infiltration of DCs in the HCC tissue microarray, including total 96 human HCC samples and 82 samples of matched adjacent normal tissues. In vitro, CCK-8, Key Fluor 488 Click-iT Edu, wound healing, and transwell assays were performed to explore the effect of IDO1 on the viability, proliferation, migration and invasion ability of HCC cell line SK-HEP1. In vivo, a subcutaneous xenograft tumor model of nude mice was established by subcutaneously inoculating SK-HEP1 and treated with IDO1 catalytic inhibitor epacadostat (EPA) to observe the effect of IDO1 on tumor growth and immune cells infiltration.

Results: Results of clinical tissue microarrays showed that compared with corresponding paracancerous tissues, the infiltration of mature DCs was significantly reduced in HCC cancer tissues with high expression of IDO1. Meanwhile, IDO1 was highly expressed in HCC cancer tissues with pathological grade I-II, high AFP levels (≥200µg/L), HBV-positivie, cirrhosis, distant metastasis and recurrence. Survival analysis showed that low IDO1 and high mature DCs cell infiltration were significantly associated with superior overall survival (OS). Correlation analysis further showed that IDO1 was negatively correlated with mature DCs. The in vitro cellular and in vivo animal experiments in this study showed that inhibition IDO1 helped to decrease the malignant biological behavior of HCC and enhance the response of immune cells to tumor cells.

Conclusion: IDO1 suppresses anti-tumor immunity in HCC, at least in part, by curtailing mDC infiltration. Targeting IDO1 may represent a promising immunotherapeutic strategy. However, its immunomodulatory effects must be validated in immunocompetent or humanized animal systems before clinical translation.

Background: Systematic reviews (SRs) are indispensable for presenting reliable evidence of the effectiveness of treatments. However, methodological flaws can affect their reliability and validity.

Aim: This cross-sectional study aimed to evaluate the methodological quality of SRs on liver cancer (LC) treatments and identify potential factors affecting their reliability.

Methods: A comprehensive literature search was carried out on four databases to identify eligible SRs published between January 2014 and October 2023. We appraised the methodological quality of included SRs by Assessing the Methodological Quality of Systematic Reviews 2 (AMSTAR 2) tool. Multivariable regression analysis was employed to investigate the factors influencing the methodological quality.

Results: A total of 119 SRs were included and appraised. Only one SR (0.8%) was rated as high overall quality. One (0.8%), nine (7.6%), and 108 (90.8%) were appraised as moderate, low, and critical low quality, respectively. SRs published more recently, with higher journal impact factors, or with corresponding author from Europe have better performance.

Conclusion: The methodological quality of SRs on LC treatments was unsatisfactory. Future SR authors should improve quality of SRs through registering an a priori protocol, providing explanation for selection of study designs, using a comprehensive literature search strategy, listing all excluded studies and justifying their reasons, describing the included studies in adequate detail, and reporting funding resources of primary studies.

Purpose: Amid the era of targeted-immunotherapy for hepatocellular carcinoma (HCC), the selection of second-line therapy following failure of diverse first-line regimens remains inadequately explored. This multicenter study aimed to assess how first-line treatment strategies impact the efficacy and safety of second-line regorafenib-either alone or in combination with PD-1 inhibitors-in patients with unresectable HCC (uHCC). Specifically, we focused on two key populations: patients who failed first-line tyrosine kinase inhibitor (TKI) monotherapy, and a rapidly expanding cohort who progressed after first-line TKI plus PD-1 inhibitor combination therapy, and to address the critical clinical dilemma of whether to continue immunotherapy in the second line.

Patients and methods: This retrospective study enrolled 288 uHCC patients from five centers, stratified into two cohorts based on first-line therapy: 126 patients with first-line TKI monotherapy (Pre-Monotherapy cohort) and 162 with first-line TKI+PD-1 combination therapy (Pre-Combination cohort). All received second-line regorafenib alone or with PD-1 inhibitors. Primary endpoints were overall survival (OS) and progression-free survival (PFS); secondary endpoints included progression-free survival (PFS),objective response rate (ORR), disease control rate (DCR), and safety.

Results: In the Pre-Monotherapy cohort, regorafenib plus PD-1 significantly improved outcomes versus regorafenib alone: mPFS (10.5 vs 4.7 months, p<0.001), mOS (18.9 vs 14.0 months, p=0.003), ORR (29.69% vs 4.84%, p<0.001), and DCR (89.06% vs 67.74%, p=0.004). In the Pre-Combination cohort, no significant differences were observed in PFS (9.2 vs 6.3 months, p=0.062), OS (16.2 vs 13.2 months, p=0.13), ORR (22.33% vs 15.25%, p=0.276), or DCR (82.52% vs 74.58%, p=0.227).

Conclusion: Second-line regorafenib plus PD-1 inhibitors yields significant clinical benefits in uHCC patients who failed first-line TKI monotherapy. However, in those who progress following first-line TKI plus PD-1 inhibitor therapy, continuing immunotherapy in the second line confers no additional efficacy, underscoring the need to explore alternative strategies. This study provides the first evidence-based guidance for the unmet clinical scenario of "first-line targeted-immunotherapy failure", highlighting the importance of precision sequential therapy tailored to first-line regimens.

Purpose: Hepatocellular carcinoma (HCC) remains challenges in treatment, particularly when tumors are unresectable and huge. This study aimed to assess the safety and efficacy of combining transarterial chemoembolization (TACE) with hepatic arterial infusion chemotherapy (HAIC) for this patient population.

Patients and methods: A retrospective review was conducted on patients with unresectable huge HCC (>10 cm) who received either TACE-HAIC or TACE as initial regional treatment from January 2020 to December 2023. Tumor response, progression-free survival (PFS), overall survival (OS), and adverse events were evaluated by propensity score matching (PSM).

Results: Among the 242 patients included, 132 received TACE-HAIC and 110 received TACE. After PSM, 77 matched pairs were analyzed. The TACE-HAIC group had significantly higher objective response (74.0% vs 58.4%, P = 0.040) and disease control rates (93.5% vs 72.7%, P = 0.001) than the TACE group. TACE-HAIC therapy also led to longer PFS (median: 12.3 vs 7.4 months, P < 0.001) and prolonged OS (median: 26.8 vs 20.4 months, P = 0.006). Stratified analysis showed that patients in Barcelona Clinical Liver Cancer stage C had longer survival benefits in the TACE-HAIC group (median PFS: 10.5 vs 5.6 months, P < 0.001; median OS: 24.5 vs 19.8 months, P = 0.013). Among grade 3/4 adverse events, liver abscesses (P = 0.018) were more common in the TACE group.

Conclusion: Compared to TACE alone, TACE-HAIC therapy presented an acceptable safety profile, and offered improved local efficacy and prolonged survival benefits in patients with unresectable huge HCC (> 10 cm).

Objective: This study aims to develop a CT-based radiomics nomogram for preoperative prediction of vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma (HCC).

Patients and methods: The retrospective, single-center study included 231 (77 VETC+ and 154 VETC-) HCC patients who underwent preoperative CT scan, and were randomly divided into training and validation cohorts at a 7:3 ratio. Radiomics features were extracted from CT images during the plain, arterial and venous phases. These features were then selected using the Least Absolute Shrinkage and Selection Operator (LASSO). Predictive factors were chosen through univariate and multivariate logistic regression. A prognostic nomogram integrating clinical factor and radiomics features was developed and validated. The model's predictive accuracy was systematically evaluated using the area under the receiver operating characteristic curve (AUC), while calibration curves assessed agreement between predicted and observed outcomes. To quantify clinical utility, decision curve analysis (DCA) was implemented. Furthermore, the model's prognostic performance for postoperative disease-free survival (DFS) was examined through Kaplan-Meier analysis.

Results: The nomogram integrating four radiomics features and alpha-fetoprotein (AFP) exhibited robust predictive performance, with AUC values of 0.782 (95% confidence interval [CI]: 0.708-0.856) in the training cohort and 0.755 (95% CI: 0.628-0.882) in the validation cohort. Calibration curves demonstrated excellent agreement between predicted and observed outcomes in both cohorts. DCA revealed significant clinical utility of the nomogram. Additionally, the model-stratified VETC+ HCC patients showed significantly worse DFS compared to VETC- counterparts (log-rank p = 0.035).

Conclusion: The CT-based radiomics nomogram, integrating radiomics features and AFP, provides a non-invasive and reliable tool for predicting VETC and stratifying prognosis in HCC patients.

Purpose: This study aimed to evaluate the association of tumor compression in the hepatic or portal vein with the presence of microvascular invasion (MVI) and satellite nodules in patients with hepatocellular carcinoma (HCC).

Patients and methods: HCC patients at the Barcelona Clinic Liver Cancer (BCLC) stages 0-A who underwent a radical liver resection in our hospitals from January 2016 to December 2022 were collected. The tumor compression of the portal or hepatic vein in individual patients was analyzed by preoperative imaging and postoperative pathology. Their MVI, satellite nodules, overall survival (OS), and recurrence-free survival (RFS) were analyzed, and the potential risk factors for the MVI and satellite nodules of patients were analyzed by univariable and multivariable logistic analyses.

Results: A total of 390 patients were included with 333 male and 263 patients <60 years old. Of them, 51 (13.1%) HCC patients had tumor venous compression, which was not significantly associated with OS and RFS, but significantly related to higher positive rates of MVI and satellite nodules than those without tumor-venous compression (MVI, 51.0% vs 36.6%, P = 0.025; satellite nodules, 19.6% vs 9.1%, P = 0.023). Tumor venous compression was an independent risk factor for the development of MVI (OR = 1.902, 95% CI: 1.049-3.447; P = 0.034) and satellite nodules (OR = 2.871, 95% CI: 1.277-6.458; P = 0.011).

Conclusion: Preoperative tumor venous compression is an independent predictor of MVI and satellite nodules in HCC patients at BCLC stages 0-A and may serve as an imaging biomarker for determining the resection margin and treatment planning.