S100P as a novel biomarker of microvascular invasion and portal vein tumor thrombus in hepatocellular carcinoma

MR radiomics to predict microvascular invasion status and biological process in combined hepatocellular carcinoma-cholangiocarcinoma

OBJECTIVES

To establish an MRI-based radiomics model for predicting the microvascular invasion (MVI) status of cHCC-CCA and to investigate biological processes underlying the radiomics model.

METHODS

The study consisted of a retrospective dataset (82 in the training set, 36 in the validation set) and a prospective dataset (25 patients in the test set) from two hospitals. Based on the training set, logistic regression analyses were employed to develop the clinical-imaging model, while radiomic features were extracted to construct a radiomics model. The diagnosis performance was further validated in the validation and test sets. Prognostic aspects of the radiomics model were investigated using the Kaplan-Meier method and log-rank test. Differential gene expression analysis and gene ontology (GO) analysis were conducted to explore biological processes underlying the radiomics model based on RNA sequencing data.

RESULTS

One hundred forty-three patients (mean age, 56.4 ± 10.5; 114 men) were enrolled, in which 73 (51.0%) were confirmed as MVI-positive. The radiomics model exhibited good performance in predicting MVI status, with the area under the curve of 0.935, 0.873, and 0.779 in training, validation, and test sets, respectively. Overall survival (OS) was significantly different between the predicted MVI-negative and MVI-positive groups (median OS: 25 vs 18 months, p = 0.008). Radiogenomic analysis revealed associations between the radiomics model and biological processes involved in regulating the immune response.

CONCLUSION

A robust MRI-based radiomics model was established for predicting MVI status in cHCC-CCA, in which potential prognostic value and underlying biological processes that regulate immune response were demonstrated.

CRITICAL RELEVANCE STATEMENT

MVI is a significant manifestation of tumor invasiveness, and the MR-based radiomics model established in our study will facilitate risk stratification. Furthermore, underlying biological processes demonstrated in the radiomics model will offer valuable insights for guiding immunotherapy strategies.

KEY POINTS

MVI is of prognostic significance in cHCC-CCA, but lacks reliable preoperative assessment. The MRI-based radiomics model predicts MVI status effectively in cHCC-CCA. The MRI-based radiomics model demonstrated prognostic value and underlying biological processes. The radiomics model could guide immunotherapy and risk stratification in cHCC-CCA.

Exosomal mRNA in plasma serves as a predictive marker for microvascular invasion in hepatocellular carcinoma

BACKGROUND AND AIM

There is a pressing need for non-invasive preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). This study investigates the potential of exosome-derived mRNA in plasma as a biomarker for diagnosing MVI.

METHODS

Patients with suspected HCC undergoing hepatectomy were prospectively recruited for preoperative peripheral blood collection. Exosomal RNA profiling was conducted using RNA sequencing in the discovery cohort, followed by differential expression analysis to identify candidate targets. We employed multiplexed droplet digital PCR technology to efficiently validate them in a larger sample size cohort.

RESULTS

A total of 131 HCC patients were ultimately enrolled, with 37 in the discovery cohort and 94 in the validation cohort. In the validation cohort, the expression levels of RSAD2, PRPSAP1, and HOXA2 were slightly elevated while CHMP4A showed a slight decrease in patients with MVI compared with those without MVI. These trends were consistent with the findings in the discovery cohort, although they did not reach statistical significance (P > 0.05). Notably, the expression level of exosomal PRPSAP1 in plasma was significantly higher in patients with more than 5 MVI than in those without MVI (0.147 vs 0.070, P = 0.035).

CONCLUSION

This study unveils the potential of exosome-derived PRPSAP1 in plasma as a promising indicator for predicting MVI status preoperatively.

A Grading System of Microvascular Invasion for Patients with Hepatocellular Carcinoma Undergoing Liver Resection with Curative Intent: A Multicenter Study

Background

Microvascular invasion (MVI) is closely correlated with poor clinical outcomes in patients with hepatocellular carcinoma (HCC). A grading system of MVI is needed to assist in the management of HCC patient.

Methods

Multicenter data of HCC patients who underwent liver resection with curative intent was analyzed. This grading system was established by detected number and distance from tumor boundary of MVI. Survival outcomes were compared among patients in each group. This system was verified by time-receiver operating characteristic curve, time-area under the curve, calibration curve, and decision curve analyses. Cox regression analysis was performed to study the associated factors of prognosis. Logistic analysis was used to study the predictive factors of MVI.

Results

All patients were classified into 4 groups: M0: no MVI; M1: 1~5 proximal MVIs (≤1 cm from tumor boundary); M2a: >5 proximal MVIs (≤1 cm from tumor boundary); M2b: ≥1 distal MVIs (>1 cm from tumor boundary). The recurrence-free survival (RFS), overall survival (OS), and early RFS rates among all the individual groups were significantly different. Based on the number of proximal MVI (0~5 vs >5), patients in the M2b group were further divided into two subgroups which also showed different prognosis. Multiple methods showed this grading system to be significantly better than the MVI two-tiered system in prognostic evaluation. Four multivariate models for RFS, OS, early RFS, late RFS, and a predictive model of MVI were then established and were shown to satisfactorily evaluate prognosis and have a great discriminatory power, respectively.

Conclusion

This MVI grading system could precisely evaluate prognosis of HCC patients after liver resection with curative intent and it could be employed in routine pathological reports. The severity of MVI from both adjacent and distant from tumor boundary should be stated. A hypothesis about two occurrence modes of distal MVI was proposed.

Quantitative Proteomics of Tissue-Infiltrating T Cells From CRC Patients Identified Lipocalin-2 Induces T-Cell Apoptosis and Promotes Tumor Cell Proliferation by Iron Efflux

T cells play the most pivotal roles in antitumor immunity; the T-cell proteome and the differentially expressed proteins in the tumor immune microenvironment have rarely been identified directly from the clinical samples, especially for tumors that lack effective immunotherapy targets, such as colorectal cancer (CRC). In this study, we analyzed the protein expression pattern of the infiltrating T cells isolated from CRC patients using quantitative proteomics. CD4+ and CD8+ T cells were isolated from clinical samples and labeled by tandem mass tag reagents, and the differentially expressed proteins were quantified by mass spectrometry. The T-cell proteome profiling revealed dysfunctions in these tumor-infiltrating T cells. Specifically, antitumor immunity was suppressed because of differentially expressed metal ion transporters and immunity regulators. For the first time, lipocalin-2 (LCN2) was shown to be significantly upregulated in CD4+ T cells. Quantitative proteomic analysis of LCN2-overexpressed Jurkat cells showed that LCN2 damaged T cells by changes in iron transport. LCN2 induced T-cell apoptosis by reducing cellular iron concentration; moreover, the iron that was transported to the tumor microenvironment aided tumor cell proliferation, promoting tumor development. Meanwhile, LCN2 also influenced tumor progression through immune cytokines and cholesterol metabolism. Our results demonstrated that LCN2 has immunosuppressive functions that can promote tumor development; therefore, it is a potential immunotherapy target for CRC.

Roles and Molecular Mechanisms of Biomarkers in Hepatocellular Carcinoma with Microvascular Invasion: A Review

Hepatocellular carcinoma (HCC) being a leading cause of cancer-related death, has high associated mortality and recurrence rates. It has been of great necessity and urgency to find effective HCC diagnosis and treatment measures. Studies have shown that microvascular invasion (MVI) is an independent risk factor for poor prognosis after hepatectomy. The abnormal expression of biomacromolecules such as circ-RNAs, lncRNAs, STIP1, and PD-L1 in HCC patients is strongly correlated with MVI. Deregulation of several markers mentioned in this review affects the proliferation, invasion, metastasis, EMT, and anti-apoptotic processes of HCC cells through multiple complex mechanisms. Therefore, these biomarkers may have an important clinical role and serve as promising interventional targets for HCC. In this review, we provide a comprehensive overview on the functions and regulatory mechanisms of MVI-related biomarkers in HCC.

Preoperative prediction and risk assessment of microvascular invasion in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and highly lethal tumors worldwide. Microvascular invasion (MVI) is a significant risk factor for recurrence and poor prognosis after surgical resection for HCC patients. Accurately predicting the status of MVI preoperatively is critical for clinicians to select treatment modalities and improve overall survival. However, MVI can only be diagnosed by pathological analysis of postoperative specimens. Currently, numerous indicators in serology (including liquid biopsies) and imaging have been identified to effective in predicting the occurrence of MVI, and the multi-indicator model based on deep learning greatly improves accuracy of prediction. Moreover, several genes and proteins have been identified as risk factors that are strictly associated with the occurrence of MVI. Therefore, this review evaluates various predictors and risk factors, and provides guidance for subsequent efforts to explore more accurate predictive methods and to facilitate the conversion of risk factors into reliable predictors.

Progress on the molecular mechanism of portal vein tumor thrombosis formation in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors, with poor prognosis and high mortality. Early-stage HCC has no obvious clinical symptoms, and most patients are already at an advanced stage when they are diagnosed. Portal vein tumor thrombus (PVTT) is the most common complication and a poor prognostic factor for HCC, which frequently leads to portal vein hypertension, ascites, gastrointestinal bleeding, and tumor metastasis. The formation of PVTT is related to the complex structure and hemodynamic changes of the portal vein and is closely related to changes at the cellular and molecular levels. The differentially-expressed genes (DEGs) between PVTT and primary tumor (PT) suggest that the two tissues may have different clonal origins. Epigenetic and proteomic analyses also suggest complex and diverse mechanisms for the formation of PVTT. In addition, the tumor microenvironment and energy metabolism pathways are interrelated in regulating the invasion and progression of PVTT. Aerobic glycolysis and the tumor immune microenvironment have been the focus of recent studies on PVTT. In this review, we summarize the mechanism of PVTT formation at the cellular and molecular levels to provide information to guide better prevention and treatment of PVTT in the clinic.

Portal vein tumor thrombosis in hepatocellular carcinoma: molecular mechanism and therapy

Portal vein tumor thrombosis (PVTT), a common complication of advanced hepatocellular carcinoma (HCC), remains the bottleneck of the treatments. Liver cancer cells potentially experienced multi-steps during PVTT process, including cancer cells leave from cancer nest, migrate in extracellular matrix, invade the vascular barrier, and colonize in the portal vein. Accumulated evidences have revealed numerous of molecular mechanisms including genetic and epigenetic regulation, cancer stem cells, immunosuppressive microenvironment, hypoxia, et al. contributed to the PVTT formation. In this review, we discuss state-of-the-art PVTT research on the potential molecular mechanisms and experimental models. In addition, we summarize PVTT-associated clinical trials and current treatments for PVTT and suppose perspectives exploring the molecular mechanisms and improving PVTT-related treatment for the future.

Lysyl hydroxylase LH1 promotes confined migration and metastasis of cancer cells by stabilizing Septin2 to enhance actin network

BACKGROUND

Excessive extracellular matrix deposition and increased stiffness are typical features of solid tumors such as hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC). These conditions create confined spaces for tumor cell migration and metastasis. The regulatory mechanism of confined migration remains unclear.

METHODS

LC-MS was applied to determine the differentially expressed proteins between HCC tissues and corresponding adjacent tissue. Collective migration and single cell migration microfluidic devices with 6 μm-high confined channels were designed and fabricated to mimic the in vivo confined space. 3D invasion assay was created by Matrigel and Collagen I mixture treat to adherent cells. 3D spheroid formation under various stiffness environment was developed by different substitution percentage GelMA. Immunoprecipitation was performed to pull down the LH1-binding proteins, which were identified by LC-MS. Immunofluorescent staining, FRET, RT-PCR, Western blotting, FRAP, CCK-8, transwell cell migration, wound healing, orthotopic liver injection mouse model and in vivo imaging were used to evaluate the target expression and cellular phenotype.

RESULTS

Lysyl hydroxylase 1 (LH1) promoted the confined migration of cancer cells at both collective and single cell levels. In addition, LH1 enhanced cell invasion in a 3D biomimetic model and spheroid formation in stiffer environments. High LH1 expression correlated with poor prognosis of both HCC and PDAC patients, while it also promoted in vivo metastasis. Mechanistically, LH1 bound and stabilized Septin2 (SEPT2) to enhance actin polymerization, depending on the hydroxylase domain. Finally, the subpopulation with high expression of both LH1 and SEPT2 had the poorest prognosis.

CONCLUSIONS

LH1 promotes the confined migration and metastasis of cancer cells by stabilizing SEPT2 and thus facilitating actin polymerization.

S100 Proteins in Fatty Liver Disease and Hepatocellular Carcinoma

Non-alcoholic fatty liver disease (NAFLD) is a highly prevalent and slow progressing hepatic pathology characterized by different stages of increasing severity which can ultimately give rise to the development of hepatocellular carcinoma (HCC). Besides drastic lifestyle changes, few drugs are effective to some extent alleviate NAFLD and HCC remains a poorly curable cancer. Among the deregulated molecular mechanisms promoting NAFLD and HCC, several members of the S100 proteins family appear to play an important role in the development of hepatic steatosis, non-alcoholic steatohepatitis (NASH) and HCC. Specific members of this Ca²⁺-binding protein family are indeed significantly overexpressed in either parenchymal or non-parenchymal liver cells, where they exert pleiotropic pathological functions driving NAFLD/NASH to severe stages and/or cancer development. The aberrant activity of S100 specific isoforms has also been reported to drive malignancy in liver cancers. Herein, we discuss the implication of several key members of this family, e.g., S100A4, S100A6, S100A8, S100A9 and S100A11, in NAFLD and HCC, with a particular focus on their intracellular versus extracellular functions in different hepatic cell types. Their clinical relevance as non-invasive diagnostic/prognostic biomarkers for the different stages of NAFLD and HCC, or their pharmacological targeting for therapeutic purpose, is further debated.

A Promising Preoperative Prediction Model for Microvascular Invasion in Hepatocellular Carcinoma Based on an Extreme Gradient Boosting Algorithm

Background

The non-invasive preoperative diagnosis of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is vital for precise surgical decision-making and patient prognosis. Herein, we aimed to develop an MVI prediction model with valid performance and clinical interpretability.

Methods

A total of 2160 patients with HCC without macroscopic invasion who underwent hepatectomy for the first time in West China Hospital from January 2015 to June 2019 were retrospectively included, and randomly divided into training and a validation cohort at a ratio of 8:2. Preoperative demographic features, imaging characteristics, and laboratory indexes of the patients were collected. Five machine learning algorithms were used: logistic regression, random forest, support vector machine, extreme gradient boosting (XGBoost), and multilayer perception. Performance was evaluated using the area under the receiver operating characteristic curve (AUC). We also determined the Shapley Additive exPlanation value to explain the influence of each feature on the MVI prediction model.

Results

The top six important preoperative factors associated with MVI were the maximum image diameter, protein induced by vitamin K absence or antagonist-II, α-fetoprotein level, satellite nodules, alanine aminotransferase (AST)/aspartate aminotransferase (ALT) ratio, and AST level, according to the XGBoost model. The XGBoost model for preoperative prediction of MVI exhibited a better AUC (0.8, 95% confidence interval: 0.74–0.83) than the other prediction models. Furthermore, to facilitate use of the model in clinical settings, we developed a user-friendly online calculator for MVI risk prediction based on the XGBoost model.

Conclusions

The XGBoost model achieved outstanding performance for non-invasive preoperative prediction of MVI based on big data. Moreover, the MVI risk calculator would assist clinicians in conveniently determining the optimal therapeutic remedy and ameliorating the prognosis of patients with HCC.

Stathmin 1 is a biomarker for diagnosis of microvascular invasion to predict prognosis of early hepatocellular carcinoma

Microvascular invasion (MVI) is presently evaluated as a high-risk factor to be directly relative to postoperative prognosis of hepatocellular carcinoma (HCC). Up to now, diagnosis of MVI mainly depends on the postoperative pathological analyses with H&E staining assay, based on numbers and distribution characteristics of MVI to classify the risk levels of MVI. However, such pathological analyses lack the specificity to discriminate MVI in HCC specimens, especially in complicated pathological tissues. In addition, the efficiency to precisely define stages of MVI is not satisfied. Thus, any biomarker for both conforming diagnosis of MVI and staging its levels will efficiently and effectively promote the prediction of early postoperative recurrence and metastasis for HCC. Through bioinformatics analysis and clinical sample verification, we discovered that Stathmin 1 (STMN1) gene was significantly up-regulated at the locations of MVI. Combining STMN1 immunostaining with classic H&E staining assays, we established a new protocol for MVI pathological diagnosis. Next, we found that the degrees of MVI risk could be graded according to expression levels of STMN1 for prognosis prediction on recurrence rates and overall survival in early HCC patients. STMN1 affected epithelial-mesenchymal transformation (EMT) of HCC cells by regulating the dynamic balance of microtubules through signaling of “STMN1-Microtubule-EMT” axis. Inhibition of STMN1 expression in HCC cells reduced their lung metastatic ability in recipients of mouse model, suggesting that STMN1 also could be a potential therapeutic target for inhibiting HCC metastasis. Therefore, we conclude that STMN1 has potentials for clinical applications as a biomarker for both pathological diagnosis and prognostic prediction, as well as a therapeutic target for HCC.

Hepatocellular Carcinoma in 2021: An Exhaustive Update

Primary liver cancer is a challenging global health concern with an estimated more than a million persons to be affected annually by the year 2025. The commonest type is hepatocellular carcinoma (HCC), which has been increasing in incidence the world over, mostly due to chronic viral hepatitis B infection. In the last decade, paradigm changes in the etiology, understanding of molecular biology, and pathogenesis, including the role of gut microbiota; medical and surgical treatments, and outcome trends are notable. The application of omics-based technology has helped us unlock the molecular and immune landscape of HCC, through which novel targets for drug treatment such as immune-checkpoint inhibitors have been identified. Novel tools for the surveillance and diagnosis of HCC include protein-, genomics-, and composite algorithm-based clinical/biomarker panels. Magnetic resonance imaging-based novel techniques have improved HCC diagnosis through ancillary features that enhance classical criteria while positron emission tomography has shown value in prognostication. Identification of the role of gut microbiota in the causation and progression of HCC has opened areas for novel therapeutic research. A select group of patients still benefit from modified surgical and early interventional radiology treatments. Improvements in radiotherapy protocols, identification of parameters of futility among radiological interventions, and the emergence of novel first-line systemic therapies that include a combination of antiangiogenic and immune-checkpoint inhibitors have seen a paradigm change in progression-free and overall survival. The current review is aimed at providing exhaustive updates on the etiology, molecular biology, biomarker diagnosis, imaging, and recommended treatment options in patients with HCC.

Screening potential prognostic biomarkers for portal vein emboli in patients with hepatocellular carcinoma

Background

The formation of portal vein tumor thrombus (PVTT) is closely related to the prognosis of patients with hepatocellular carcinoma (HCC). However, the mechanisms by which PVTTs form and the biomarkers involved are still little understood.

Methods

The Genome Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were used to obtain transcriptome data from normal tissue, HCC tissue, primary tumors (PTs) of HCC, and paired PVTT tissue. Differentially expressed genes (DEGs) in PTs and PVTTs were analyzed. The differentially expressed immune genes were further investigated in terms of their prognostic significance, immune infiltration, function. Finally, we explored the relationship between risk scores and drug sensitivity based on the R package.

Results

In the two datasets, there were 458 DEGs identified in the PT and PVTT tissues, of which, 58 were immune-related genes. The differentially expressed immune genes may promote the progression of PVTT by participating in the regulation of non-cellular components such as the extracellular matrix, inflammatory factors, and chemokines. Furthermore, the immune genes KDR, AKT3, FCGR2B, KIAA1429, and TPT1 were correlated with the prognosis of HCC in patients with PVTT. Using this data, a model was constructed to predict the prognosis of patients, thus allowing for the identification of high- and low-risk patients.

Conclusions

This study demonstrated that immune-related genes may be involved in the regulation of the extracellular matrix and acellular components, and subsequently, in the formation of PVTT. These five genes KDR, AKT3, FCGR2B, KIAA1429, and TPT1 may be potential prognostic biomarkers and treatment targets for HCC patients with PVTT.

Comprehensive Analysis of the Prognosis and Correlations With Immune Infiltration of S100 Protein Family Members in Hepatocellular Carcinoma

S100 protein family members (S100s) are commonly dysregulated in various tumors including hepatocellular carcinoma (HCC). However, the diverse expression, mutation, prognosis and associations with immune infiltration of S100s in HCC have yet to be analyzed. Herein we investigated the roles of S100s in HCC from the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas, Kaplan-Meier Plotter, cBioPortal and TIMER databases. Compared with para-cancer tissues, the expression levels of S100A4/S100A6/S100A10/S100A11/S100A13/S100A14/S100P were higher in HCC tissues, while the expression levels of S100A8/S100A9/S100A12 were decreased in tumor tissues. The mRNA levels of S100A2/S100A7/S100A7A/S100A8/S100A9/S100A11 were correlated with advanced tumor stage. Besides, higher mRNA expressions of S100A6/S100A10/S100A11/S100A13/S100A14/S100P were shown to have shorter overall survival (OS), while higher expression of S100A12 was associated with favorable OS. Further, the mutation rate of S100s was investigated, and the high mutation rate (53%) was associated with shorter OS. Additionally, the expressions of S100s were found to be significantly associated with various immune infiltrating cells. Hence, our results showed that S100A6/S100A10/S100A11/S10012/S100A13/S100A14/S100P may be regarded as new prognostic or therapeutic markers and S100s inhibitors may be helpful in the combination of immunotherapies.