Journal of Hepatocellular Carcinoma最新文献

Objective: To explore the value of intravoxel incoherent motion (IVIM) sequences in predicting intra-tumoral tertiary lymphoid structures (TLSs).

Materials and methods: This prospective study pre-operatively enrolled hepatocellular carcinoma (HCC) patients who underwent magnetic resonance imaging including IVIM sequences, between January 2019 and April 2021. Intra-tumoral TLSs presence was assessed on pathological slide images. Clinical and radiological characteristics were collected. IVIM quantitative parameters and radiomics features were obtained based on the whole delineated tumor volume. By using feature selection techniques, 22 radiomics features, clinical-radiological features (lymphocyte count and satellite nodules), and IVIM parameters (apparent diffusion coefficient (ADC_90Percentile), perfusion fraction (f_Maximum)) were selected. The logistic regression algorithm was used to construct the prediction model based on the combination of these features. The diagnostic performance was assessed using the area under the receiver operating characteristic (AUC). The recurrence-free survival (RFS) was evaluated with Kaplan-Meier curves.

Results: A total of 168 patients were divided into training (n=128) and testing (n=40) cohorts (mean age: 56.83±14.43 years; 149 [88.69%] males; 130 TLSs+). In testing cohort, the model combining multimodal features demonstrated a good performance (AUC: 0.86) and significantly outperformed models based on single-modality features. The model based on radiomics features (AUC: 0.80) had better performance than other features, including IVIM parameter maps (ADC_90Percentile and f_Maximum, AUC: 0.72) and clinical-radiological characteristics (satellite nodules and lymphocyte counts, AUC: 0.59). TLSs+ patients had higher RFS than TSLs- patients (all p <0.05).

Conclusion: The nomogram based on the proposed model can be used as a pre-operative predictive biomarker of TLSs.

Critical relevance statement: The nomogram incorporating IVIM sequences may serve as a pre-operative predictive biomarker of intra-tumoral tertiary lymphoid structure (TLS) status.

Purpose: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality with a challenging prognosis. HCC lacks effective prognostic biomarkers. We investigated the diagnostic and prognostic value of COIL expression in HCC.

Patients and methods: This study evaluated the expression and prognostic significance of COIL using data from the TCGA and local hospital samples, with 374 and 118 liver cancer patients in the TCGA database and local hospital, respectively. The techniques include bioinformatics analysis, qRT-PCR, immunohistochemistry (IHC), and in vitro cell experiments, which encompass CCK-8 assays, wound healing assays, and Transwell invasion assays. The relationship between COIL expression and clinical outcomes was assessed, and COIL's biological function in HCC was investigated through cellular assays.

Results: Analysis of cell lines and HCC tissue samples revealed that COIL mRNA or protein expression levels were significantly higher in HCC cell lines/tissues compared to normal liver cells/tissues. Univariate and multivariate analyses indicated that COIL is an independent prognostic factor for overall survival (OS) in HCC. Additionally, 14% of HCC patients had alterations in the COIL gene, and patients with COIL gene alterations had significantly lower OS (p<0.001) and disease-free survival (DFS) (p<0.001) compared to those without gene alterations. Knockdown of COIL expression inhibited the proliferation, migration, and invasion of Hep3B, HepG2, and Huh7. Compared to the control group, COIL knockdown cells showed a marked reduction in CDC25C and CCNB1 protein levels, suggesting that COIL knockdown leads to G2/M phase cell cycle arrest. After COIL knockdown, caspase-3 and BCL-2 protein levels were downregulated, while cleaved caspase and BAX protein levels were upregulated, indicating that COIL knockdown promotes apoptosis in liver cancer cells.

Conclusion: COIL is an independent predictor of prognosis. COIL's association with poor OS and its role in enhancing cancer cell proliferation and invasion highlight its potential as a therapeutic target.

Purpose: Primary liver cancer, predominantly hepatocellular carcinoma (HCC), constitutes a substantial global health challenge, characterized by a poor prognosis, particularly in regions with high prevalence of hepatitis B virus (HBV) infection, such as China. This study sought to develop and validate a machine learning-based prognostic model to predict survival outcomes in patients with HBV-related HCC following radical resection, with the potential to inform personalized treatment strategies.

Patients and methods: This study retrospectively analyzed clinical data from 146 patients at Xinjiang Medical University and 75 patients from The Cancer Genome Atlas (TCGA) database. A prognostic model was developed using a machine learning algorithm and evaluated for predictive performance using the concordance index (C-index), calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves.

Results: Key predictors for constructing the best model included body mass index (BMI), albumin (ALB) levels, surgical resection method (SRM), and the American Joint Committee on Cancer (AJCC) stage. The model achieved a C-index of 0.736 in the training set and performed well in both training and validation datasets. It accurately predicted 1-, 3-, and 5-year survival rates, with Area Under the Curve (AUC) values of 0.843, 0.797, and 0.758, respectively. Calibration curve analysis and Decision Curve Analysis (DCA) further validated the model's predictive capability, suggesting its potential use in clinical decision-making.

Conclusion: The study highlights the importance of BMI, ALB, SRM, and AJCC staging in predicting HBV-related HCC outcomes. The machine learning model aids clinicians in making better treatment decisions, potentially enhancing patient outcomes.

Purpose: The treatment outcomes and risk factors for the prognosis of acute variceal bleeding (AVB) in hepatocellular carcinoma (HCC) patients remain unclear. Hence, we assessed the clinical outcomes and prognostic factors of these patients.

Methods: This study retrospectively enrolled 1532 AVB patients with cirrhosis from January 2016 to December 2022. Of these patients, 310 had HCC, and after 1:1 individual matching, 306 of them were matched with 306 patients without HCC. Six-week mortality, one-year mortality, and five-day treatment failure were recorded.

Results: In the matched-pair analysis, patients with HCC had a higher rate of 6-week and 1-year mortality than those without HCC (6-week: 24.5% vs 7.8%, P < 0.001; 1-year: 45.9% vs 16.2%, P < 0.001). The rate of 5-day treatment failure was similar between the two groups (21.1% vs 16.7%, P = 0.213). Among AVB patients with HCC, the multivariate analysis revealed that the Child-Pugh score (HR, 1.239, 95% CI, 1.121-1.370; P < 0.001) and Barcelona Clinic Liver Cancer (BCLC) stage (C-D vs 0-B) (HR, 14.409; 95% CI, 5.758-36.055; P < 0.001) were independently associated with 6-week mortality. Moreover, the rate of 6-week mortality was 60.2% in patients who had a high Child-Pugh score (≥9) and advanced BCLC stage (C-D), much higher than in those with low Child-Pugh score (<9) and earlier BCLC stage (0-B) (P < 0.001).

Conclusion: Among patients with cirrhosis and AVB, patients with HCC had significantly worse outcomes than those without. The severity of liver disease and the stage of HCC are the main determinants of mortality in HCC patients.

Purpose: Hepatocellular carcinoma (HCC) is a prevalent malignancy that not only imposes a substantial financial burden but also significantly impacts the quality of life and overall survival of affected individuals. Heat shock proteins (HSPs) are a protein class with significant involvement in safeguarding and restoring cellular integrity. They help restore proper protein structure by binding to and refolding denatured proteins. However, the specific role of HSPs in HCC requires further investigation.

Methods: We analyzed the genomic characteristics of HSPs in liver cancer in the TCGA and ICGC databases, and functional enriched analysis of HSPs. Construction of an HSPs-Related Prognostic Model for patients with hepatocellular carcinoma. HSP-related risk score (HRRS) was identified as an independent prognostic factor in patients with hepatocellular carcinoma, and the clinical pathological characteristics and immune microenvironment of high-risk and low-risk groups were compared. Further, we studied HRRS-based liver cancer treatment strategies and confirmed the protein expression of HSPD1 and DNAJC5 in normal liver tissues and hepatocellular carcinoma tissues by collecting human hepatocellular carcinoma tissues.

Results: We observed elevated expression levels of most HSPs across HCC tissues. In addition, 14 hSPs were found to be related to prognostic significance among HCC patients and utilized to develop HRRS prognostic model for prognosis prediction and risk stratification. The prognostic and immunotherapeutic response predictive value of HRRS was validated utilizing data from TCGA and GEO cohorts. Moreover, we created a nomogram to assess HRRS clinical utility and verified its efficiency through various methods. Through IHC was found that HSPD1 and DNAJC5 were significantly overexpressed in hepatocellular carcinoma tissues.

Conclusion: Our results lead us to conclude that HCC's development and progression are intimately associated with HSPs, and the HRRS model represents a potentially robust prognostic model that could assist in clinical decision-making regarding chemotherapy and immunotherapy for HCC patients. Moreover, HSPD1 and DNAJC5 have the potential to serve as therapeutic targets for HCC.

Purpose: The apolipoprotein E (APOE) gene is one of the strongest genetic determinants of the risk of developing late-onset Alzheimer's disease (AD) and may also increase the risk of cancer. However, its importance goes far beyond this. The aim of this study was to comprehensively analyze the potential role and prognostic value of APOE in hepatocellular carcinoma (HCC) using bioinformatics and multiplex fluorescence immunohistochemistry (mIHC).

Methods: Clinicopathologic samples from 90 hCC patients enrolled between April 2007 and June 2012 were included in this study. Researchers used tissue microarrays (HLiv180Su09) and multiple fluorescent immunohistochemical analyses to validate APOE protein expression and patient prognosis. Several online databases were used to investigate APOE expression and prognosis in HCC, followed by a comprehensive analysis of correlations between APOE and clinicopathologic features, immune cell infiltration levels, immune checkpoint genes, mutations, and functional enrichment analysis. The distribution of APOE in immune cell populations was also determined using a single-cell database.

Results: APOE mRNA was significantly overexpressed in HCC at both transcriptional and translational levels. Survival analysis suggested that APOE might be a favorable prognostic indicator for HCC patients. In addition to its involvement in immune cell infiltration, immune checkpoint gene expression, genetic variation, immunomodulatory genes, and methylation alterations in HCC, enrichment analysis showed that APOE was involved in multiple cancer-related signaling pathways.

Conclusion: This study comprehensively examines the critical role of APOE in HCC and highlights its significant potential as a biomarker and therapeutic target. This finding not only paves the way for new avenues of research in HCC, but also provides valuable insights into clinical diagnosis and treatment strategies.

Purpose: To investigate the incidence patterns and risk factors of acute abdominal pain following hepatic arterial infusion chemotherapy (HAIC) in liver cancer patients and develop a preliminary prediction model for post-HAIC abdominal pain.

Patients and methods: Four hundred hepatocellular carcinoma patients who underwent HAIC at the Affiliated Cancer Hospital of Shandong First Medical University from January 2021 to March 2023 were retrospectively analyzed. The patients were categorized into two groups (abdominal pain and no abdominal pain) based on the occurrence of acute moderate to severe abdominal pain within 24 h after HAIC. Univariate analysis was performed on data from the two groups. Statistically significant factors were subjected to logistic regression analysis to construct a preliminary prediction model, and the predictive performance was evaluated.

Results: A total of 358 hAIC procedures were performed in 242 patients who met the inclusion criteria. Of the 242 eligible patients, 88 (36.4%) experienced moderate to severe abdominal pain, while 154 (63.6%) had no significant pain. Age, tumor diameter, distance between the tumor and liver capsule, presence of portal vein tumor thrombus, oxaliplatin preparation time, and oxaliplatin manufacturer were independent predictors of acute moderate to severe abdominal pain following HAIC. The final prediction model demonstrated good predictive ability with an area under the receiver operating characteristic curve of 0.795 (95% confidence interval: 0.740-0.853).

Conclusion: The model developed in this study effectively predicted the risk of acute moderate to severe abdominal pain following HAIC and may provide a basis for more precise prevention and intervention strategies in clinical practice.

Purpose: This study aimed to develop a novel nomogram to predict recurrence-free survival (RFS) for microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) patients after curative resection.

Patients and methods: A total of 143 pathologically confirmed MVI-negative HCC patients were analyzed retrospectively. Baseline MRI features and inflammatory markers were collected. We used univariable and multivariable Cox regression analysis to identify the independent risk factors for RFS. And we established a nomogram based on significant MRI features and inflammatory marker. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve were used to evaluate the predictive accuracy and discriminative ability of the nomogram. The decision curve analysis (DCA) was performed to validate the clinical utility of the nomogram.

Results: In multivariate Cox regression analysis, neutrophil-to-lymphocyte ratio (NLR) (P = 0.018), tumor size (P = 0.002), and tumor capsule (P = 0.000) were independent significant variables associated with RFS. Nomogram with independent factors was developed and achieved a good C-index of 0.730 (95% confidence interval [CI]: 0.656-0.804) for predicting RFS. In ROC analysis, the areas under curve of the nomogram for 1-, 3- and 5-year RFS prediction were 0.725, 0.784 and 0.798, respectively. The risk score calculated by nomogram could divide MVI-negative HCC patients into high-risk group or low-risk group (P < 0.0001). DCA analysis revealed that the nomogram could increase net benefit and exhibited a wider range of threshold probabilities by the risk stratification than the independent risk factors in the prediction of MVI-negative HCC recurrence.

Conclusion: The nomogram prognostic model based on MRI features and NLR for predicting RFS showed high accuracy in MVI-negative HCC patients after curative resection. It can help clinicians make treatment decisions for MVI-negative HCC patients and identify high-risk patients for timely intervention.

Background: Radiotherapy offers potential benefits for patients with hepatocellular carcinoma (HCC); however, the distinct role of intraoperative radiotherapy (IORT) during narrow-margin hepatectomy remains inadequately defined. This study aims at assessing the safety and effectiveness of IORT for centrally located HCCs during narrow-margin hepatectomy.

Methods: This single-center, retrospective research incorporated 659 patients with centrally located HCCs. After applying exclusion criteria, 607 patients remained and were divided into two groups: IORT integrated with liver resection (IORT+LR, 54 patients) and mere liver resection (LR, 553 patients). Propensity score matching (PSM) was performed to balance baseline characteristics. Post PSM, surgical outcomes, long-term recurrence, survival rates and adverse events were analyzed.

Results: A total of 54 patients were successfully matched, without significant differences upon baseline characteristics (standardized mean difference, SMD <0.15). Post-matching analysis revealed that overall survival (OS) and disease-free survival (DFS) were notably improved in the IORT+LR group (P =0.027 and 0.015, respectively). Multivariate Cox regression identified IORT as an independent prognostic factor for better DFS and OS. Among the 108 patients included after matching, 57 experienced HCC recurrence, 23 in the IORT group and 34 in the LR group, showing a clear difference in recurrence rates (P =0.034). Also, there were no apparent differences in mild/severe complications between IORT and RT groups (96.3% vs 98.2%, P =0.558, respectively).

Conclusion: IORT is an effective and well-tolerated therapy for HCC patients. The combination of narrow-margin hepatectomy and IORT enhances patient prognosis, with IORT identified as an independent prognostic factor.

Background: Maximum diameter and number are the main parameters of tumor burden in hepatocellular carcinoma (HCC). Tumor burden score (TBS) shows its distinguished ability to stratify patients with HCC undergoing transcatheter arterial chemoembolization (TACE). However, the prognostic accuracy of TBS in HCC undergoing liver resection and its association with the BCLC stage has not been well evaluated.

Methods: A total of 3044 treatment-naïve HCC patients from six independent medical centers undergoing liver resection were retrospectively analyzed. Survival analyses were conducted by plotting Kaplan-Meier curves and the Log rank test. We further investigated whether the tumor burden score was a feasible subclassification criterion across the BCLC stage. Then, we also used TBS to identify HCC patients beyond BCLC criteria who could benefit most from surgical resection. Finally, univariate and multivariate cox analysis was used to determine independent prognostic predictors.

Results: About 44.2% (n=1343) of patients had low TBS, 38.8% (n=1182) had intermediate TBS and 17% (n=519) had high TBS. Overall survival (OS) and recurrence-free survival deteriorated incrementally with increasing TBS (P<0.0001). Subgroup analysis indicated that there was a significant survival difference among the three TBS groups across the BCLC stage (P<0.0001). Low TBS group of patients beyond BCLC criteria reported acceptable outcomes compared to intermediate TBS group patients within BCLC criteria, even better than high TBS group (5-year OS: 64.3%, 69.8%, and 56.3%). Finally, low TBS was identified as an independent protective prognostic factor.

Conclusion: Tumor burden score is a feasible and reliable prognostic tool for prognosis prediction and clinical decisions.