Recent progress in molecular mechanisms of postoperative recurrence and metastasis of hepatocellular carcinoma

METTL3-mediated SMPDL3A promotes cell growth, metastasis and immune process of hepatocellular carcinoma by regulating LRPPRC

BACKGROUND

Methyltransferase-like protein 3 (METTL3) has been confirmed to act as a tumor promoter to regulate hepatocellular carcinoma (HCC) progression. Therefore, more roles and mechanisms of METTL3 in HCC progression deserve to be further revealed.

METHODS

The mRNA and protein levels of METTL3, sphingomyelin phodiesterase acid-like 3 A (SMPDL3A), and leucine rich pentatricopeptide repeat containing (LRPPRC) were determined by qRT-PCR and western blot. Cell proliferation, apoptosis, invasion and migration were detected by CCK8 assay, EdU assay, flow cytometry, transwell assay and wound healing assay. HCC cells were co-cultured with phytohemagglutinin-stimulated peripheral blood mononuclear cells, cytokine-induced killer cells, or CD8 + T-cells. IFN-γ, TNF-α levels, HCC cell survival rate and CD8 + T-cell apoptosis were determined to assess cell immune process. The interaction between METTL3, SMPDL3A and LRPPRC was assessed by MeRIP assay, RIP assay, dual-luciferase reporter assay or Co-IP assay. Animal experiments were performed to evaluate the effect of METTL3 knockdown on HCC tumorigenesis and lung metastasis.

RESULTS

METTL3 was upregulated in HCC tissues and cells, and its knockdown repressed HCC cell proliferation, invasion, migration, immune process and promoted apoptosis. METTL3 increased SMPDL3A mRNA stability by m6A methylation modification, and this modification could be recognized by IGF2BP1. SMPDL3A overexpression reversed the inhibitory effect of METTL3 knockdown on HCC cell growth, metastasis and immune process. SMPDL3A interacted with LRPPRC to positively regulate its expression, and LRPPRC overexpression also eliminated the regulation of SMPDL3A silencing on HCC progression. In addition, downregulation of METTL3 repressed HCC tumorigenesis and lung metastasis via mediating SMPDL3A/LRPPRC axis.

CONCLUSION

METTL3 accelerated HCC cell growth, metastasis and immune process by regulating SMPDL3A/LRPPRC axis, providing a potential target for HCC treatment.

Construction of a 2.5D Deep Learning Model for Predicting Early Postoperative Recurrence of Hepatocellular Carcinoma Using Multi-View and Multi-Phase CT Images

Purpose

To construct a 2.5-dimensional (2.5D) CT radiomics-based deep learning (DL) model to predict early postoperative recurrence of hepatocellular carcinoma (HCC).

Patients and Methods

We retrospectively analyzed the data of patients who underwent HCC resection at 2 centers. The 232 patients from center 1 were randomly divided into the training (162 patients) and internal validation cohorts (70 patients); 91 patients from center 2 formed the external validation cohort. We developed a 2.5D DL model based on a central 2D image with the maximum tumor cross-section and adjacent slices. Multiple views (transverse, sagittal, and coronal) and phases (arterial, plain, and portal) were incorporated. Multi-instance learning techniques were applied to the extracted data; the resulting comprehensive feature set was modeled using Logistic Regression, RandomForest, ExtraTrees, XGBoost, and LightGBM, with 5-fold cross validation and hyperparameter optimization with Grid-search. Receiver operating characteristic curves, calibration curves, DeLong test, and decision curve analysis were used to evaluate model performance.

Results

The 2.5D DL model performed well in the training (AUC: 0.920), internal validation (AUC: 0.825), and external validation cohorts (AUC: 0.795). The 3D DL model performed well in the training cohort and poorly in the internal and external validation cohorts (AUCs: 0.751, 0.666, and 0.567, respectively), indicating overfitting. The combined model (2.5D DL+clinical) performed well in all cohorts (AUCs: 0.921, 0.835, 0.804). The Hosmer-Lemeshow test, DeLong test, and decision curve analysis confirmed the superiority of the combined model over the other signatures.

Conclusion

The combined model integrating 2.5D DL and clinical features accurately predicts early postoperative HCC recurrence.

Analytical and Diagnostic Performance of a Dual-Target Blood Detection Test for Hepatocellular Carcinoma

BACKGROUND

Surveillance approaches with high sensitivity and specificity for hepatocellular carcinoma (HCC) are still urgently needed. Previous studies have shown that methylation of GNB4 and Riplet can effectively diagnose HCC.

AIMS

This study plan to analyze the performance of a blood test for detecting HCC using GNB4 and Riplet methylation.

METHODS AND RESULTS

This study mainly investigated the analytical performance of the dual-target HCC blood test (DT-HBT), including cut-off value, limit of detection (LOD), precision, analytical specificity, and coincidence rate. In addition, the detection performance for HCC was validated in 1030 clinical plasma samples (214 HCC and 816 non-HCC). Plasma samples from 25 HCC patients after hepatectomy were collected to assess the feasibility of the kit for postoperative recurrence monitoring. All analytical performance of the DT-HBT met prespecified requirements. The LOD for GNB4, Riplet, and β-actin was 1% methylation/100 copies/μL with cut-offs of 43, 43, and 35, respectively. The DT-HBT showed excellent precision, within 5% CV. It had a specificity of 91.5% for detecting other cancers, and 100% for breast, lung, and bladder cancer. No cross-reactions were observed with 9 potential interfering substances. The DT-HBT achieved a 100% coincidence rate in detecting reference and clinical samples. The clinical performance study found that the kit showed a sensitivity of 81.7% for stage I HCC, and an overall sensitivity and specificity of 87.4% and 92.3%, respectively. The detection sensitivity for postoperative recurrent patients was 95.8%, with a specificity of 100%.

CONCLUSION

The analytical performance of the DT-HBT met prespecified criteria. It provided HCC patients with a reliable and high-performing new blood test for the HCC diagnosis and surveillance.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT05685524.

The Effects of Hypoxia on the Immune-Metabolic Interplay in Liver Cancer

M2-like macrophages promote tumor growth and cancer immune evasion. This study used an in vitro model to investigate how hypoxia and tumor metabolism affect macrophage polarization. Liver cancer cells (HepG2 and VX2) and macrophages (THP1) were cultured under hypoxic (0.1% O2) and normoxic (21% O2) conditions with varying glucose levels (2 g/L or 4.5 g/L). Viability assays and extracellular pH (pHe) measurements were conducted over 96 hours. Macrophages were exposed to the tumor-conditioned medium (TCM) from the cancer cells, and polarization was assessed using arginase and nitrite assays. GC-MS-based metabolic profiling quantified TCM meta-bolites and correlated them with M2 polarization. The results showed that pHe in TCMs decreased more under hypoxia than normoxia (p < 0.0001), independent of glucose levels. The arginase assay showed hypoxia significantly induced the M2 polarization of macrophages (control group: p = 0.0120,0.1%VX2-TCM group: p = 0.0149, 0.1%HepG2-TCM group: p < 0.0001, 0.1%VX2-TCMHG group: p = 0.0001, and 0.1%HepG2-TCMHG group: p < 0.0001). TCMs also induced M2 polarization under normoxic conditions, but the strongest M2 polarization occurred when both tumor cells and macrophages were incubated under hypoxia with high glucose levels. Metabolomics revealed that several metabolites, particularly lactate, were correlated with hypoxia and M2 polarization. Under normoxia, elevated 2-amino-butanoic acid (2A-BA) strongly correlated with M2 polarization. These findings suggest that targeting tumor hypoxia could mitigate immune evasion in liver tumors. Lactate drives acidity in hypoxic tumors, while 2A-BA could be a therapeutic target for overcoming immunosuppression in normoxic conditions.

Intravoxel incoherent motion and enhanced T2*-weighted angiography for preoperative prediction of microvascular invasion in hepatocellular carcinoma

Objective

To investigate the value of the combined application of intravoxel incoherent motion (IVIM) and enhanced T2*-weighted angiography (ESWAN) for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Materials and methods

76 patients with pathologically confirmed HCC were retrospectively enrolled and divided into the MVI-positive group (n=26) and MVI-negative group (n=50). Conventional MRI, IVIM, and ESWAN sequences were performed. Three region of interests (ROIs) were placed on the maximum axial slice of the lesion on D, D*, and f maps derived from IVIM sequence, and R2* map derived from ESWAN sequence, and intratumoral susceptibility signal (ITSS) from the phase map derived from ESWAN sequence was also automatically measured. Receiver operating characteristic (ROC) curves were drawn to evaluate the ability for predicting MVI. Univariate and multivariate logistic regression were used to screen independent risk predictors in clinical and imaging information. The Delong's test was used to compare the differences between the area under curves (AUCs).

Results

The D and D* values of MVI-negative group were significantly higher than those of MVI-positive group (P=0.038, and P=0.023), which in MVI-negative group were 0.892×10-3 (0.760×10-3, 1.303×10-3) mm2/s and 0.055 (0.025, 0.100) mm2/s, and in MVI-positive group were 0.591×10-3 (0.372×10-3, 0.824×10-3) mm2/s and 0.028 (0.006, 0.050)mm2/s, respectively. The R2* and ITSS values of MVI-negative group were significantly lower than those of MVI-positive group (P=0.034, and P=0.005), which in MVI-negative group were 29.290 (23.117, 35.228) Hz and 0.146 (0.086, 0.236), and in MVI-positive group were 43.696 (34.914, 58.083) Hz and 0.199 (0.155, 0.245), respectively. After univariate and multivariate analyses, only AFP (odds ratio, 0.183; 95% CI, 0.041-0.823; P = 0.027) was the independent risk factor for predicting the status of MVI. The AUCs of AFP, D, D*, R2*, and ITSS for prediction of MVI were 0.652, 0.739, 0.707, 0.798, and 0.657, respectively. The AUCs of IVIM (D+D*), ESWAN (R2*+ITSS), and combination (D+D*+R2*+ITSS) for predicting MVI were 0.772, 0.800, and, 0.855, respectively. When IVIM combined with ESWAN, the performance was improved with a sensitivity of 73.1% and a specificity of 92.0% (cut-off value: 0.502) and the AUC was significantly higher than AFP (P=0.001), D (P=0.038), D* (P=0.023), R2* (P=0.034), and ITSS (P=0.005).

Conclusion

The IVIM and ESWAN parameters showed good efficacy in prediction of MVI in patients with HCC. The combination of IVIM and ESWAN may be useful for noninvasive prediction of MVI before clinical operation.

IL-6 Released from Hepatic Stellate Cells Promotes Glycolysis and Migration of HCC Through the JAK1/vWF/TGFB1 Axis

Purpose

The crosstalk between hepatocellular carcinoma (HCC) cells and hepatic stellate cells (HSCs) is one of the important mechanisms of liver cancer metastasis. The relationship between liver cancer metastasis and glycolysis has been extensively studied recently. However, the role of von Willebrand factor (vWF) mediated glycolysis mechanism in liver cancer metastasis is currently unknown.

Methods

Western blot was used to verify the expression of vWF in HCC cells. PAS staining, glycogen and L-lactate content assays were used to reflect cellular glycolysis levels. The ability of cell migration was explored by Wound-healing and Transwell assays. Besides, the effect of vWF on the progression of HCC in vivo was also studied using subcutaneous xenograft model.

Results

vWF derived from HCC cells promoted tumor migration by mediating glycolysis. Besides, vWF participated in the crosstalk between HCC cells and HSCs. HCC cells activated HSCs through vWF-mediated TGFB1 expression and secretion, and activated HSCs upregulated vWF expression in HCC cells through IL-6 secretion feedback. Further, in vitro and in vivo experiments also confirmed the importance of the JAK1/vWF/TGFB1 axis in regulating HSCs-derived IL-6 mediated HCC migration and growth.

Conclusion

In summary, this article demonstrated that IL-6 released from hepatic stellate cells enhanced glycolysis and migration ability of liver cancer cells by activating JAK1/vWF/TGFB1 axis which may also be a potential target for inhibiting liver cancer metastasis.

Nomogram for Predicting Postoperative Pulmonary Metastasis in Hepatocellular Carcinoma Based on Inflammatory Markers

BACKGROUND

Uncertainty surrounds the usefulness of inflammatory markers in hepatocellular carcinoma (HCC) patients for predicting postoperative pulmonary metastasis (PM). The purpose of this study was to assess the predictive value of inflammatory markers as well as to create a new nomogram model for predicting PM.

METHODS

Cox regression was utilized to identify independent prognostic variables and to create a nomogram that predicted PM for comparison with a validation cohort and other prediction systems. We retrospectively analyzed a total of 1109 cases with HCC were included.

RESULTS

The systemic inflammatory response index (SIRI) and aspartate aminotransferase-to-platelet ratio index (APRI) were independent risk factors for PM, with a concordance index of .78 (95% CI: .74-.81) for the nomogram. The areas under the curve of the nomograms for PM predicted at 1-, 3-, and 5-year were .82 (95% CI: .77-.87), .82 (95% CI: .78-.87) and .81 (95% CI: .75-.86), respectively, which were better than those of Barcelona Clinic Liver Cancer and China liver cancer stage. Decision curve analyses demonstrated a broader range of nomogram threshold probabilities.

CONCLUSION

A nomogram based on SIRI and APRI can accurately predict postoperative PM in HCC.

Development of a machine learning-based model for predicting risk of early postoperative recurrence of hepatocellular carcinoma

BACKGROUND

Surgical resection is the primary treatment for hepatocellular carcinoma (HCC). However, studies indicate that nearly 70% of patients experience HCC recurrence within five years following hepatectomy. The earlier the recurrence, the worse the prognosis. Current studies on postoperative recurrence primarily rely on postoperative pathology and patient clinical data, which are lagging. Hence, developing a new pre-operative prediction model for postoperative recurrence is crucial for guiding individualized treatment of HCC patients and enhancing their prognosis.

AIM

To identify key variables in pre-operative clinical and imaging data using machine learning algorithms to construct multiple risk prediction models for early postoperative recurrence of HCC.

METHODS

The demographic and clinical data of 371 HCC patients were collected for this retrospective study. These data were randomly divided into training and test sets at a ratio of 8:2. The training set was analyzed, and key feature variables with predictive value for early HCC recurrence were selected to construct six different machine learning prediction models. Each model was evaluated, and the best-performing model was selected for interpreting the importance of each variable. Finally, an online calculator based on the model was generated for daily clinical practice.

RESULTS

Following machine learning analysis, eight key feature variables (age, intratumoral arteries, alpha-fetoprotein, pre-operative blood glucose, number of tumors, glucose-to-lymphocyte ratio, liver cirrhosis, and pre-operative platelets) were selected to construct six different prediction models. The XGBoost model outperformed other models, with the area under the receiver operating characteristic curve in the training, validation, and test datasets being 0.993 (95% confidence interval: 0.982-1.000), 0.734 (0.601-0.867), and 0.706 (0.585-0.827), respectively. Calibration curve and decision curve analysis indicated that the XGBoost model also had good predictive performance and clinical application value.

CONCLUSION

The XGBoost model exhibits superior performance and is a reliable tool for predicting early postoperative HCC recurrence. This model may guide surgical strategies and postoperative individualized medicine.

EMT-related gene risk model establishment for prognosis and drug treatment efficiency prediction in hepatocellular carcinoma

This study was designed to evaluate the prognosis and pharmacological therapy sensitivity of epithelial mesenchymal transition-related genes (EMTRGs) that obtained from the EMTome database in hepatocellular carcinoma (HCC) using bioinformatical method. The expression status of EMTRGs were also investigated using the clinical information of HCC patients supported by TCGA database and the ICGC database to establish the TCGA cohort as the training set and the ICGC cohort as the validation set. Analyze the EMTRGs between HCC tissue and liver tissue in the TCGA cohort in the order of univariate COX regression, LASSO regression, and multivariate COX regression, and construct a risk model for EMTRGs. In addition, enrichment pathways, gene mutation status, immune infiltration, and response to drugs were also analyzed in the high-risk and low-risk groups of the TCGA cohort, and the protein expression status of EMTRGs was verified. The results showed a total of 286 differentially expressed EMTRGs in the TCGA cohort, and EZH2, S100A9, TNFRSF11B, SPINK5, and CCL21 were used for modeling. The TCGA cohort was found to have a worse outcome in the high-risk group of HCC patients, and the ICGC cohort confirmed this finding. In addition, EMTRGs risk score was shown to be an independent prognostic factor in both cohorts by univariate and multivariate COX regression. The results of GSEA analysis showed that most of the enriched pathways in the high-risk group were associated with tumor, and the pathways enriched in the low-risk group were mainly associated with metabolism. Patients in various risk groups had varying immunological conditions, and the high-risk group might benefit more from targeted treatments. To sum up, the EMTRGs risk model was developed to forecast the prognosis for HCC patients, and the model might be useful in assisting in the choice of treatment drugs for HCC patients.

The tumor microenvironment in the postsurgical liver: Mechanisms and potential targets of postoperative recurrence in human hepatocellular carcinoma

Surgery remains to be the mainstay of treatment for hepatocellular carcinoma (HCC). Nonetheless, its therapeutic efficacy is significantly impaired by postoperative recurrence, which occurs in more than half of cases as a result of intrahepatic metastasis or de novo tumorigenesis. For decades, most therapeutic strategies on inhibiting postoperative HCC recurrence have been focused on the residual tumor cells but satisfying therapeutic outcomes are barely observed in the clinic. In recent years, a better understanding of tumor biology allows us to shift our focus from tumor cells toward the postoperative tumor microenvironment (TME), which is gradually identified to play a pivotal role in tumor recurrence. In this review, we describe various surgical stress and surgical perturbation on postoperative TME. Besides, we discuss how such alternations in TME give rise to postoperative recurrence of HCC. Based on its clinical significance, we additionally highlight the potential of the postoperative TME as a target for postoperative adjuvant therapeutics.

Genipin-activating PPARγ impedes CCR2-mediated macrophage infiltration into postoperative liver to suppress recurrence of hepatocellular carcinoma

A high postoperative tumour recurrence rate has significantly rendered a poorer prognosis in hepatocellular carcinoma (HCC) patients. The aim of this study is to identify a natural compound genipin as a potential and effective candidate to suppress the postoperative recurrence of HCC. Clinical analysis revealed that infiltration of macrophage into the adjacent tissue but not HCC predicted patients' poor prognosis on recurrence-free survival. Genipin intervention suppressed the Ly6C+CD11b+F4/80+ pro-inflammatory macrophage infiltration in the postoperative liver of mice. Adoptive transfer of pro-inflammatory monocytic cells completely abolished the inhibitory effect of genipin on HCC recurrence. Transcriptomic analysis on FACs-sorted macrophages from the postoperative livers of mice revealed that PPARγ signalling was involved in the regulatory effect of genipin. Genipin is directly bound to PPARγ, causing PPARγ-induced p65 degradation, which in turn suppressed the transcriptional activation of CCR2 signalling. PPARγ antagonist GW9662 abrogated the effects of genipin on CCR2-medaited macrophage infiltration as well as HCC recurrence. Cytokine array analysis identified that genipin intervention potently suppressed the secretion of CCL2 further partially contributed to the pro-inflammatory macrophage infiltration into the postoperative liver. Multiplex immunostaining on tissue array of human HCC revealed that PPARγ expression was inversely associated with CCL2 and the macrophage infiltration in the adjacent liver of HCC patients. Our works provide scientific evidence for the therapeutic potential of genipin as a PPARγ agonist in preventing postoperative recurrence of HCC.

The Emerging Role of Metformin in the Treatment of Hepatocellular Carcinoma: Is There Any Value in Repurposing Metformin for HCC Immunotherapy?

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. There has been significant progress in understanding the risk factors and epidemiology of HCC during the last few decades, resulting in efficient preventative, diagnostic and treatment strategies. Type 2 diabetes mellitus (T2DM) has been demonstrated to be a major risk factor for developing HCC. Metformin is a widely used hypoglycemic agent for patients with T2DM and has been shown to play a potentially beneficial role in improving the survival of patients with HCC. Experimental and clinical studies evaluating the outcomes of metformin as an antineoplastic drug in the setting of HCC were reviewed. Pre-clinical evidence suggests that metformin may enhance the antitumor effects of immune checkpoint inhibitors (ICIs) and reverse the effector T cells' exhaustion. However, there is still limited clinical evidence regarding the efficacy of metformin in combination with ICIs for the treatment of HCC. We appraised and analyzed in vitro and animal studies that aimed to elucidate the mechanisms of action of metformin, as well as clinical studies that assessed its impact on the survival of HCC patients.