Grade Of Hepatocellular Carcinoma Research Articles

CT-based radiomics for predicting pathological grade in hepatocellular carcinoma.

To construct and validate radiomics models for hepatocellular carcinoma (HCC) grade predictions based on contrast-enhanced CT (CECT). Patients with pathologically confirmed HCC after surgery and underwent CECT at our institution between January 2016 and December 2020 were enrolled and randomly divided into training and validation datasets. With tumor segmentation and feature extraction, radiomic models were constructed using univariate analysis, followed by least absolute shrinkage and selection operator (LASSO) regression. In addition, combined models with clinical factors and radiomics scores (Radscore) were constructed using logistic regression. Finally, all models were evaluated using the receiver operating characteristic (ROC) curve with the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). In total 242 patients were enrolled in this study, of whom 170 and 72 formed the training and validation datasets, respectively. The arterial phase and portal venous phase (AP+VP) radiomics model were evaluated as the best for predicting HCC pathological grade among all the models built in our study (AUC = 0.981 in the training dataset; AUC = 0.842 in the validation dataset) and was used to build a nomogram. Furthermore, the calibration curve and DCA indicated that the AP+VP radiomics model had a satisfactory prediction efficiency. Low- and high-grade HCC can be distinguished with good diagnostic performance using a CECT-based radiomics model.

SUMOylation of annexin A6 retards cell migration and tumor growth by suppressing RHOU/AKT1–involved EMT in hepatocellular carcinoma

BackgroundThe protein annexin A6 (AnxA6) is involved in numerous membrane-related biological processes including cell migration and invasion by interacting with other proteins. The dysfunction of AnxA6, including protein expression abundance change and imbalance of post-translational modification, is tightly related to multiple cancers. Herein we focus on the biological function of AnxA6 SUMOylation in hepatocellular carcinoma (HCC) progression.MethodsThe modification sites of AnxA6 SUMOylation were identified by LC-MS/MS and amino acid site mutation. AnxA6 expression was assessed by immunohistochemistry and immunofluorescence. HCC cells were induced into the epithelial-mesenchymal transition (EMT)-featured cells by 100 ng/mL 12-O-tetradecanoylphorbol-13-acetate exposure. The ability of cell migration was evaluated under AnxA6 overexpression by transwell assay. The SUMO1 modified AnxA6 proteins were enriched from total cellular proteins by immunoprecipitation with anti-SUMO1 antibody, then the SUMOylated AnxA6 was detected by Western blot using anti-AnxA6 antibody. The nude mouse xenograft and orthotopic hepatoma models were established to determine HCC growth and tumorigenicity in vivo. The HCC patient’s overall survival versus AnxA6 expression level was evaluated by the Kaplan–Meier method.ResultsLys579 is a major SUMO1 modification site of AnxA6 in HCC cells, and SUMOylation protects AnxA6 from degradation via the ubiquitin-proteasome pathway. Compared to the wild-type AnxA6, its SUMO site mutant AnxA6K579R leads to disassociation of the binding of AnxA6 with RHOU, subsequently RHOU-mediated p-AKT1ser473 is upregulated to facilitate cell migration and EMT progression in HCC. Moreover, the SENP1 deSUMOylates AnxA6, and AnxA6 expression is negatively correlated with SENP1 protein expression level in HCC tissues, and a high gene expression ratio of ANXA6/SENP1 indicates a poor overall survival of patients.ConclusionsAnxA6 deSUMOylation contributes to HCC progression and EMT phenotype, and the combination of AnxA6 and SENP1 is a better tumor biomarker for diagnosis of HCC grade malignancy and prognosis.

Multiphase MRI-Based Radiomics for Predicting Histological Grade of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer. Accurate preoperative prediction of histological grade holds potential for improving clinical management and disease prognostication. To evaluate the performance of a radiomics signature based on multiphase MRI in assessing histological grade in solitary HCC. Retrospective. A total of 405 patients with histopathologically confirmed solitary HCC and with liver gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI within 1 month of surgery. Contrast-enhanced T1-weighted spoiled gradient echo sequence (LAVA) at 1.5 or 3.0 T. Tumors were graded (low/high) according to results of histopathology. Basic clinical characteristics (including age, gender, serum alpha-fetoprotein (AFP) level, history of hepatitis B, and cirrhosis) were collected and tumor size measured. Radiomics features were extracted from Gd-EOB-DTPA-enhanced MRI data. Three feature selection strategies were employed sequentially to identify the optimal features: SelectFromModel (SFM), SelectPercentile (SP), and recursive feature elimination with cross-validation (RFECV). Probabilities of five single-phase radiomics-based models were averaged to generate a radiomics signature. A combined model was built by combining the radiomics signature and clinical predictors. Pearson χ2 test/Fisher exact test, Wilcoxon rank sum test, interclass correlation coefficient (ICC), univariable/multivariable logistic regression analysis, area under the receiver operating characteristic (ROC) curve (AUC), DeLong test, calibration curve, Brier score, decision curve, Kaplan-Meier curve, and log-rank test. A P-value <0.05 was considered statistically significant. High-grade HCCs were present in 33.8% of cases. AFP levels (odds ratio [OR] 1.89) and tumor size (>5 cm; OR 2.33) were significantly associated with HCC grade. The combined model had excellent performance in assessing HCC grade in the test dataset (AUC: 0.801), and demonstrated satisfactory calibration and clinical utility. A model that combined a radiomics signature derived from preoperative multiphase Gd-EOB-DTPA-enhanced MRI and clinical predictors showed good performance in assessing HCC grade. 3 TECHNICAL EFFICACY: Stage 5.

The significance of HAUS1 and its relationship with immune microenvironment in hepatocellular carcinoma.

Background: HAUS Augmin-like complex subunit 1(HAUS1), as a controlling gene, which affected the production of spindle was firstly discovered in Drosophila cells. Although HAUS1 has been intensively studied, but its significance and relationship with the immune microenvironment in Hepatocellular carcinoma (HCC) remain unclear. Materials and Methods: All data of HCC in this paper were obtained from The Cancer Genome Atlas(TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO) and the Human Protein Atlas(HPA) database. The role and potential value of HAUS1 in the tumorigenesis and development of HCC were studied by applying plenty of bioinformatics analysis methods. Knocked down the expression of HAUS1 through siRNA and further investigated the function of HAUS1 in HCC Results: HAUS1 was highly expressed in HCC, which led to a poor prognosis. ROC curve analysis showed that HAUS1 had a excellent diagnostic value. It was also associated with clinical stage, pathological grade and AFP of HCC. Univariate and multivariate COX regression analysis showed that HAUS1 was an independent prognostic factor for HCC patients. HAUS1 was associated with immune cells infiltrate and immune checkpoints in HCC, and it could generate significative therapeutic results when combined with anti-CTLA4 and anti-CD274 treatment. In vitro experiments, HAUS1 was found to promote the proliferation, invasion and metastasis, participated in cell cycle regulation and inhibited apoptosis of HCC. Conclusion: These results suggested that HAUS1 might serve as a potential therapeutic target, as well as a diagnostic, prognostic, and survival biomarker for HCC.

Identification of ABCC3 and its isoforms as potential biomarker in hepatocellular carcinoma

Liver diseases preceding the occurrence of hepatocellular carcinoma (HCC) play a crucial role in the progression and establishment of HCC, a malignancy ranked as the third deadliest cancer worldwide. Late diagnosis, alongside ineffective treatment, leads patients to a poor survival rate. This scenario argues for seeking novel alternatives for detecting liver alterations preceding the early occurrence of HCC. Experimental studies have reported that ABCC3 protein increases within HCC tumors but not in adjacent tissue. Therefore, we analyzed ABCC3 expression in public databases and investigated the presence of ABCC3 and its isoforms in plasma, urine and its release in extracellular vesicles (EVs) cargo from patients bearing cirrhosis and HCC. The UALCAN and GEPIA databases were used to analyze the expression of ABCC3 in HCC. The results were validated in a case-control study including 41 individuals bearing cirrhosis and HCC, and the levels of ABCC3 in plasma and urine samples, as well as EVs, were analyzed by ELISA and western blot. Our data showed that ABCC3 expression was higher in HCC tissues than in normal tissues and correlated with HCC grade and stage. ABCC3 protein levels were highly increased in both plasma and urine and correlated with liver disease progression and severity. The isoforms MRP3A and MRP3B of ABCC3 were significantly increased in both EVs and plasma/urine of patients bearing HCC. ABCC3 expression gradually increases in HCC tissues, and its protein levels are increased in both plasma and urine of patients with cirrhosis and HCC. MRP3A and MRP3B isoforms have the potential to be prognostic biomarkers of HCC.

Pseudouridine synthase 1 promotes hepatocellular carcinoma through mRNA pseudouridylation to enhance the translation of oncogenic mRNAs.

Pseudouridine is a prevalent RNA modification and is highly present in the serum and urine of patients with HCC. However, the role of pseudouridylation and its modifiers in HCC remains unknown. We investigated the function and underlying mechanism of pseudouridine synthase 1 (PUS1) in HCC. By analyzing the TCGA data set, PUS1 was found to be significantly upregulated in human HCC specimens and positively correlated with tumor grade and poor prognosis of HCC. Knockdown of PUS1 inhibited cell proliferation and the growth of tumors in a subcutaneous xenograft mouse model. Accordingly, increased cell proliferation and tumor growth were observed in PUS1-overexpressing cells. Furthermore, overexpression of PUS1 significantly accelerates tumor formation in a mouse HCC model established by hydrodynamic tail vein injection, while knockout of PUS1 decreases it. Additionally, PUS1 catalytic activity is required for HCC tumorigenesis. Mechanistically, we profiled the mRNA targets of PUS1 by utilizing surveying targets by apolipoprotein B mRNA-editing enzyme 1 (APOBEC1)-mediated profiling and found that PUS1 incorporated pseudouridine into mRNAs of a set of oncogenes, thereby endowing them with greater translation capacity. Our study highlights the critical role of PUS1 and pseudouridylation in HCC development, and provides new insight that PUS1 enhances the protein levels of a set of oncogenes, including insulin receptor substrate 1 (IRS1) and c-MYC, by means of pseudouridylation-mediated mRNA translation.

The expression of VEGF and cyclin D1/EGFR in common primary liver carcinomas in Egypt: an immunohistochemical study.

The most common types of primary malignant liver tumours are hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA). Treatment options for patients who are inoperable/advanced, or recurring are challenging. Cyclin D1, epidermal growth factor (EGFR) and vascular endothelial growth factor (VEGR) are common carcinogenic proteins that have potential therapeutic targets in various cancers. They have been implicated in the development of HCC and CCA. In this study, we aimed to evaluate the oncogenic function expression of cyclin D1, EGFR and VEGF in HCC and CCA of Egyptian patients. This could help to validate their therapeutic potential. Tumour cases were selected from 82 cases of primary liver carcinomas, with 58 cases being from HCC and 24 cases from CCA compared to 51 non-tumour adjacent liver cases and 18 from normal liver tissue. The immunohistochemical study of cyclin D1, EGFR and VEGR was conducted. Cyclin D1, EGFR and VEGF are overexpressed in HCC and CCA as compared to the control group (p < 0.001). Cyclin D1 was related to well-differentiated grade and early pathologic stage in HCC (p = 0.016 and p = 0.042, respectively). The well-differentiated grade showed significantly higher VEGF levels (p = 0.04). In the CCA group, however, EGFR was strongly related to high tumour size (p = 0.047). EGFR and VEGF were overexpressed in HCC raised in the non-cirrhotic liver compared to those developed in post-hepatitic liver cirrhosis (p = 0.003 and p = 0.014). Cyclin D1, EGFR and VEGF shared significant overexpression in HCC and CCA. EGFR and VEGF may play an oncogenic function in the development of HCC in non-cirrhotic liver. Furthermore, cyclin D1 and VEGF may play a good prognostic function in HCC, but EGFR may play a bad prognostic role in CCA.

EZH2-H3K27me3-mediated silencing of mir-139-5p inhibits cellular senescence in hepatocellular carcinoma by activating TOP2A

BackgroundEpigenetic alterations play an important role in hepatocellular carcinoma (HCC) development. Enhancer of zeste homolog 2 (EZH2) is a well-known epigenetic modifier that functions as an oncogene in tumors by promoting the H3K27me3-mediated transcriptional repression of tumor suppressor genes. “Senescent cells” has been proposed as a possible core component of the hallmarks of cancer conceptualization. Induction of cell senescence and targeted elimination of these senescent tumor cells are new strategies for tumor therapy. However, the role of EZH2 in regulating cellular senescence remains poorly understood.MethodsBioinformatics analyses suggested that EZH2 and DNA topoisomerase II alpha (TOP2A) are coexpressed in tumors, including HCC. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses and gene set enrichment analyses (GSEA) suggests a correlation of EZH2 and TOP2A expression with cellular senescence in HCC. MicroRNA (miRNA) inhibitor and mimics, siRNA, PLKO-shRNA, and plenti6.3-miR-139 were used to upregulate or downregulate the expression of target genes. CCK8, EdU, clone formation, and senescence-associated β-galactosidase (SA-β-gal) staining assays were performed to assess cell proliferation and cellular senescence phenotypes. Dual-luciferase reporter and chromatin immunoprecipitation assays were performed to investigate the targeted binding and inhibition of TOP2A 3′ untranslated region (UTR) by miR-139-5p and the DNA enrichment of miR139-5p by EZH2 and H3K27me3. BALB/c nude mice were used to establish a xenograft tumor model and verify the phenotypes upon EZH2 and TOP2A silencing and miR-139 overexpression in vivo. In addition, tissue microarrays were used to analyze the expression patterns and correlations among EZH2, TOP2A, and miR-139-5p expression in HCC.ResultsBioinformatics analysis revealed that EZH2 and TOP2A are coexpressed in HCC. In vitro gain- and loss-of-function experiments showed that inhibition of EZH2 and TOP2A induces cellular senescence and inhibits proliferation of HCC cells. In vivo tumorigenesis assays indicated that EZH2 and TOP2A knockdown inhibits tumorigenesis by inducing cellular senescence. Mechanistically, EZH2 promotes TOP2A expression by regulating the H3K27me3-mediated epigenetic silencing of miR-139-5p. TOP2A is a direct target of miR-139-5p, and inhibition of miR-139-5p can reverse the promotion by EZH2 of TOP2A expression. The overexpression of miR-139-5p induces cellular senescence and inhibits proliferation of HCC cells both in vitro and in vivo. Clinically, expression of EZH2 and TOP2A are higher in HCC tissues than in normal tissues, and this high coexpression indicates a worse outcome of patients with HCC. Moreover, expression of EZH2 and TOP2A is significantly correlated with tumor differentiation grade, tumor invasion, and TNM stage in HCC. miR-139-5p expression is lower in HCC tumors than in normal tissues and is correlated with better prognosis of HCC patients.ConclusionsOur study revealed the role of the EZH2/miR-139-5p/TOP2A axis in regulating cellular senescence and cell proliferation in HCC, enriching the molecular mechanisms of EZH2-mediated epigenetic regulation in HCC. Therefore, our results provide insight into the therapeutic potential of targeting EZH2 to induce cellular senescence and then destroy senescent cells for HCC.Graphic

Kidney-type glutaminase is a biomarker for the diagnosis and prognosis of hepatocellular carcinoma: a prospective study

PurposeThe pathological diagnosis and prognosis prediction of hepatocellular carcinoma (HCC) is challenging due to the lack of specific biomarkers. This study aimed to validate the diagnostic and prognostic efficiency of Kidney-type glutaminase (GLS1) for HCC in prospective cohorts with a large sample size.MethodsA total of 1140 HCC patients were enrolled in our prospective clinical trials. Control cases included 114 nontumour tissues. The registered clinical trial (ChiCTR-DDT-14,005,102, chictr.org.cn) was referred to for the exact protocol. GLS1 immunohistochemistry was performed on the whole tumour section. The diagnostic and prognostic performances of GLS1 was evaluated by the receiver operating characteristic curve and Cox regression model.ResultsThe sensitivity, specificity, positive predictive value, negative predictive value, Youden index, and area under the curve of GLS1 for the diagnosis of HCC were 0.746, 0.842, 0.979, 0.249, 0.588, and 0.814, respectively, which could be increased to 0.846, 0.886, 0.987,0.366, 0.732, and 0.921 when combined with glypican 3 (GPC3) and alpha-fetoprotein (AFP), indicating better diagnostic performance. Further, we developed a nomogram with GPC3 and GLS1 for identifying HCC which showed good discrimination and calibration. GLS1 expression was also related with age, T stage, TNM stage, Edmondson–Steiner grade, microvascular invasion, Ki67, VEGFR2, GPC3, and AFP expression in HCC. GLS1 expression was negatively correlated with disease-free survival (P < 0.001) probability of patients with HCC.ConclusionsIt was validated that GLS1 was a sensitive and specific biomarker for pathological diagnosis of HCC and had prognostic value, thus having practical value for clinical application.

MRI features for predicting the pathological grade of HCC in patients undergoing liver transplantation

BackgroundContrast-enhanced magnetic resonance imaging (MRI) plays a crucial role in the diagnosis of hepatocellular carcinoma (HCC). This study aims to assess the performance of MRI features for evaluating hepatocellular carcinoma (HCC) aggressiveness in living liver transplantation in patients.Material and methodsThis retrospective study included patients who underwent liver transplantation in our hospital between 2015 and 2020. Abdominal contrast-enhanced MRIs of these patients were reviewed, and clinical, radiological, and histopathological findings of HCCs were recorded. The prognostic features of HCCs as determined by MRI were compared with Edmondson-Steiner (E-S) grades. Liver parenchyma fibrosis based on an apparent diffusion coefficient (ADC) map was correlated with histological subclassification of cirrhosis using the Laennec staging system.ResultsThe study subjects included 37 men and 8 women with a mean age of 59.56 ± 7.81 (range: 25–72). The mean tumour size was 37.33 ± 22.27 mm (range: 10–118 mm), and nine tumours (23.1%) involved portal vein tumour thrombosis. There was a significant correlation between tumour grade and size (p = 0.007) and intratumoral fat (p = 0.014) even though no significant correlations between grade and mean ADC value, capsule appearance, presence of satellite lesions, smooth margin, imaging of the tumour feeding artery, and corona enhancement of HCC (p > 0.05) were found. There was a statistically significant correlation between mild (stage 4A) and moderate (stage 4B) fibrosis of non-tumorous liver parenchyma and ADC value (p < 0.001).ConclusionOur study found that ADC values can be used to distinguish mild cirrhotic livers from moderate cirrhotic livers. Diffusion MRI might be used to diagnose the degree of liver fibrosis without histopathological analysis. According to our results, only intralesional fat and tumour size correlated with tumour grade, and as such, these parameters could be used as prognostic MRI biomarkers for HCC.

Prognostic model of hepatocellular carcinoma based on cancer grade.

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. With highly invasive biological characteristics and a lack of obvious clinical manifestations, HCC usually has a poor prognosis and ranks fourth in cancer mortality. The aetiology and exact molecular mechanism of primary HCC are still unclear. To select the characteristic genes that are significantly associated with the prognosis of HCC patients and construct a prognosis model of this malignancy. By comparing the gene expression levels of patients with different cancer grades of HCC, we screened out differentially expressed genes associated with tumour grade. By protein-protein interaction (PPI) network analysis, we obtained the top 2 PPI networks and hub genes from these differentially expressed genes. By using least absolute shrinkage and selection operator Cox regression, 13 prognostic genes were selected for feature extraction, and a prognostic risk model of HCC was established. The model had significant prognostic ability in HCC. We also analysed the biological functions of these prognostic genes. By comparing the gene profiles of patients with different stages of HCC, We have constructed a prognosis model consisting of 13 genes that have important prognostic value. This model has good application value and can be explained clinically.

Multimodal label-free imaging of murine hepatocellular carcinoma with a subcellular resolution.

We demonstrate label-free imaging of genetically induced hepatocellular carcinoma (HCC) in a murine model provided by two- and three-photon fluorescence microscopy of endogenous fluorophores excited at the central wavelengths of 790, 980 and 1250 nm and reinforced by second and third harmonic generation microscopy. We show, that autofluorescence imaging presents abundant information about cell arrangement and lipid accumulation in hepatocytes and hepatic stellate cells (HSCs), harmonics generation microscopy provides a versatile tool for fibrogenesis and steatosis study. Multimodal images may be performed by a single ultrafast laser source at 1250 nm falling in tissue transparency window. Various grades of HCC are examined revealing fibrosis, steatosis, liver cell dysplasia, activation of HSCs and hepatocyte necrosis, that shows a great ability of multimodal label-free microscopy to intravital visualization of liver pathology development.

Correlation Between Serum ESPL1 and Hepatitis B Virus-related Hepatocellular Carcinoma Histological Grade: A Chinese Single-center Case-control Study.

Serum markers to determine the histological grade of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) are still limited. This study aimed to investigate if serum extra spindle pole bodies-like 1 (ESPL1) protein could reflect the histological grade of HBV-related HCC. A total of 154 patients with HBV-related HCC were enrolled in the experimental group and 41 non-HBV-related patients in the control. Enzyme-linked immunosorbent assay was used to detect serum ESPL1 levels. The differences in serological ESPL1, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) were compared between the two groups. HCC tumor diameter was measured, and pathological examination was performed to compare the relationship between ESPL1, AFP, and DCP and tumor size and histological grade. Serum AFP and DCP levels showed no significant difference between experimental group and control group, and increased when the tumor diameter increased but were not related to HCC histological grade. Serological ESPL1 levels were higher in the experimental group than those in the control group, and positively correlated with the histological grade. In the experimental group, tumor size and histological grade were almost independent (Kappa=0.000); patients with medium size tumors had the highest serum ESPL1 levels and the highest proportion of poorly differentiated carcinomas, whereas 75.6% of patients with small size tumors had moderately differentiated carcinomas and only 20% well differentiated carcinomas. Serum ESPL1 can reflect the malignant degree of HBV-related HCC and is helpful in identifying small size HCC tumors.

Five machine learning-based radiomics models for preoperative prediction of histological grade in hepatocellular carcinoma.

To compare the efficacy of radiomics models via five machine learning algorithms in predicting the histological grade of hepatocellular carcinoma (HCC) before surgery and to develop the most stable model to classify high-risk HCC patients. Contrast-enhanced computed tomography (CECT) images of 175 HCC patients before surgery were analysed, and radiomics features were extracted from CECT images (including arterial and portal phases). Five machine learning models, including Bayes, random forest (RF), k-nearest neighbors (KNN), logistic regression (LR), and support vector machine (SVM), were applied to establish the model. The stability of the five models was weighed by the relative standard deviation (RSD), and the lowest RSD value was chosen as the most stable model to predict the histological grade of HCC. The area under the curve (AUC) and Delong tests were devoted to assessing the predictive efficacy of the models. High-grade HCC accounted for 28.57% (50/175) of the 175 patients. The RSD value of AUC via the RF machine learning model was the lowest (2.3%), followed by Bayes (3.2%), KNN (6.4%), SVM (8.7%) and LR (31.3%). In addition, the RF model (AUC = 0.995) was better than the other four models in the training set (p < 0.05), as well as obtained good predictive performance in the test set (AUC = 0.837). Among the five machine learning models, the RF-based radiomics model was the most stable and performed excellently in identifying high histological grade of HCC.

Radiomics models for preoperative prediction of the histopathological grade of hepatocellular carcinoma: A systematic review and radiomics quality score assessment

ObjectiveTo systematically review the efficacy of radiomics models derived from computed tomography (CT) or magnetic resonance imaging (MRI) in preoperative prediction of the histopathological grade of hepatocellular carcinoma (HCC). MethodsSystematic literature search was performed at databases of PubMed, Web of Science, Embase, and Cochrane Library up to 30 December 2022. Studies that developed a radiomics model using preoperative CT/MRI for predicting the histopathological grade of HCC were regarded as eligible. A pre-defined table was used to extract the data related to study and patient characteristics, characteristics of radiomics modelling workflow, and the model performance metrics. Radiomics quality score and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) were applied for research quality evaluation. ResultsEleven eligible studies were included in this review, consisting of 2245 patients (range 53–494, median 165). No studies were prospectively designed and only two studies had an external test cohort. Half of the studies (five) used CT images and the other half MRI. The median number of extracted radiomics features was 328 (range: 40–1688), which was reduced to 11 (range: 1–50) after feature selection. The commonly used classifiers were logistic regression and support vector machine (both 4/11). When evaluated on the two external test cohorts, the area under the curve of the radiomics models was 0.70 and 0.77. The median radiomics quality score was 10 (range 2–13), corresponding to 28% (range 6–36%) of the full scale. Most studies showed an unclear risk of bias as evaluated by QUADAS-2. ConclusionRadiomics models based on preoperative CT or MRI have the potential to be used as an imaging biomarker for prediction of HCC histopathological grade. However, improved research and reporting quality is required to ensure sufficient reliability and reproducibility prior to implementation into clinical practice.

Identification of immune-related target and prognostic biomarkers in PBMC of hepatocellular carcinoma

Background Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide, and is characterized by insidious onset, rapid progression, and poor prognosis. Immunotherapy is a first-line treatment for advanced HCC. The identification of immune-related prognostic markers may be an effective strategy to predict and improve clinical response rate of immunotherapy.Methods The DESeq2, edgeR, and limma R packages were used to compare the transcriptomes of HCC with different prognoses. Cancer-related databases such as UALCAN, TNMplot, GEPIA, muttarget and Human Protein Atlas (HPA), and the Kaplan–Meier Plotter platform were used to analyze the relationship between CLDN18 and the clinical characteristics, as well as prognosis of HCC. The co-expressed genes of CLDN18 were obtained from LinkedOmics platform, and GO functional enrichment and KEGG pathway analysis were performed. The CIBERSORT, TIMER, Timer 2.0 and TISIDB algorithms were used to analyze immune infiltration.Results CLDN18 was differentially expressed in HCC patients with different prognoses, and its expression level in PBMC was positively correlated with the stage of BCLC. In addition, CLDN18 was significantly overexpressed in HCC tumor tissues compared to adjacent non-tumor tissues, which was consistent with PBMC sequencing results and immunohistochemical data from human protein profiles. CLDN18 was also positively correlated with HCC staging and grading, and high expression levels of CLDN18 predicted shorter overall survival. Functional annotation of CLDN18 in HCC revealed enrichment of the cellular senescence and protein activation cascade, along with biological processes such as cell cycle, inflammatory response, and cellular ketone metabolism. In addition, CLDN18 was also associated with tumor infiltrating immune cells, suppressive immune cell markers, T lymphocyte depletion and activation of HCC, and low expression of CLDN18 was associated with higher CD8 + T cell infiltration and better survival rates.ConclusionsCLDN18 is a potential prognostic marker and immunotherapeutic target for HCC.

Hepatocellular carcinoma histopathological images grading with a novel attention-sharing hybrid network based on multi-feature fusion

Throughout history until today, hepatocellular carcinoma (HCC) remains one of the most serious illnesses worldwide due to its high mortality rates. One of the most essential steps to diagnose HCC and its differentiated degree is histopathological image analysis, which is implemented by experienced pathologists. However, this method is time-consuming and difficult for young pathologists to implement. Nowadays, few researchers have proposed approaches based on computer-aided systems to automatically grade HCC due to the complexity of hepatocellular carcinoma histopathological images. Therefore, this paper proposes a novel dual channel attention-sharing hybrid network (DCAH-Net) based on multi-feature fusion to automatically grade HCC histopathological images to assist pathologists in diagnosing HCC. To solve the problem that large scale histopathological images cannot be utilized to train networks directly, patch-based method is utilized in this work to divide large scale image into patches. To effectively extract local and global features, convolutional neural networks and transformers are deployed in the DCAH-Net. A novel attention-sharing mechanism containing a simplified outlook attention and a feature projection block is proposed in DCAH-Net to provide detailed information for both channels. The performance of DCAH-Net compared with existing methods achieves the highest accuracy, macro recall, macro precision and macro F1-score of 88.36%, 82.14%, 83.00% and 82.30% on HCC histopathological dataset. In addition, LC25000 and BreakHis dataset are utilized to validate the generalization ability of DCAH-Net. The results obtained show that DCAH-Net has great potential in other medical classification tasks.

CD38 marks the exhausted CD8+ tissue-resident memory T cells in hepatocellular carcinoma.

Despite recent advances in immunotherapy for hepatocellular carcinoma (HCC), the overall modest response rate underscores the need for a better understanding of the tumor microenvironment (TME) of HCC. We have previously shown that CD38 is widely expressed on tumor-infiltrating leukocytes (TILs), predominantly on CD3+ T cells and monocytes. However, its specific role in the HCC TME remains unclear. In this current study, we used cytometry time-of-flight (CyTOF), bulk RNA sequencing on sorted T cells, and single-cell RNA (scRNA) sequencing to interrogate expression of CD38 and its correlation with T cell exhaustion in HCC samples. We also employed multiplex immunohistochemistry (mIHC) for validating our findings. From CyTOF analysis, we compared the immune composition of CD38-expressing leukocytes in TILs, non-tumor tissue-infiltrating leukocytes (NIL), and peripheral blood mononuclear cells (PBMC). We identified CD8+ T cells as the dominant CD38-expressing TILs and found that CD38 expression was significantly higher in CD8+ TRM in TILs than in NILs. Furthermore, through transcriptomic analysis on sorted CD8+ TRM from HCC tumors, we observed a higher expression of CD38 along with T cell exhaustion genes, including PDCD1 and CTLA4, compared to the circulating memory CD8 T cells from PBMC. This was validated by scRNA sequencing that revealed co-expression of CD38 with PDCD1, CTLA4, and ITGAE (CD103) in T cells from HCC tumors. The protein co-expression of CD38 and PD-1 on CD8+ T cells was further demonstrated by mIHC on HCC FFPE tissues, marking CD38 as a T cell co-exhaustion marker in HCC. Lastly, the higher proportions of CD38+PD-1+ CD8+ T cells and CD38+PD-1+ TRM were significantly associated with the higher histopathological grades of HCC, indicating its role in the aggressiveness of the disease. Taken together, the concurrent expression of CD38 with exhaustion markers on CD8+ TRM underpins its role as a key marker of T cell exhaustion and a potential therapeutic target for restoring cytotoxic T cell function in HCC.

AATF inhibition exerts antiangiogenic effects against human hepatocellular carcinoma.

Angiogenesis is a key factor in the growth and metastasis of hepatic tumors and thus a potential therapeutic target in hepatocellular carcinoma (HCC). In this study, we aim to identify the key role of apoptosis antagonizing transcription factor (AATF) in tumor angiogenesis and its underlying mechanisms in HCC. HCC tissues were analyzed for AATF expression by qRT-PCR and immunohistochemistry. Stable clones of control and AATF knockdown (KD) were established in human HCC cells. The effect of AATF inhibition on the angiogenic processes was determined by proliferation, invasion, migration, chick chorioallantoic membrane (CAM) assay, zymography, and immunoblotting techniques. We identified high levels of AATF in human HCC tissues compared to adjacent normal liver tissues, and the expression was found to be correlated with the stages and tumor grades of HCC. Inhibiting AATF in QGY-7703 cells resulted in higher levels of pigment epithelium-derived factor (PEDF) than controls due to decreased matric metalloproteinase activity. Conditioned media from AATF KD cells inhibited the proliferation, migration, and invasion of human umbilical vein endothelial cells as well as the vascularization of the chick chorioallantoic membrane. Furthermore, the VEGF-mediated downstream signaling pathway responsible for endothelial cell survival and vascular permeability, cell proliferation, and migration favoring angiogenesis was suppressed by AATF inhibition. Notably, PEDF inhibition effectively reversed the anti-angiogenic effect of AATF KD. Our study reports the first evidence that the therapeutic strategy based on the inhibition of AATF to disrupt tumor angiogenesis may serve as a promising approach for HCC treatment.

TMEM147 Correlates with Immune Infiltration and Serve as a Potential Prognostic Biomarker in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most prevalent malignancies and is associated with high mortality. Transmembrane protein 147 (TMEM147) is a seven-transmembrane protein that may mediate immune regulation. However, the relevance of TMEM147 to immune regulation in HCC and the prognosis of HCC patients are unclear. We analyzed TMEM147 expression in HCC by using the Wilcoxon rank-sum test. Real time quantitative PCR (RT-qPCR) and Western blot analysis of tumor tissues and cell lines were used to verify TMEM147 expression in HCC. The influence of TMEM147 on HCC prognosis was assessed using Kaplan-Meier analysis, Cox regression analysis, and a prognostic nomogram. The functions of the TMEM147-related differentially expressed genes (DEGs) were identified by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses and gene set enrichment analysis (GSEA). In addition, we examined the associations between TMEM147 expression and immune infiltration using single-sample gene set enrichment analysis (ssGSEA) and immunofluorescence staining of HCC tissues. Our results showed that the expression of TMEM147 was significantly higher in human HCC tissues than in adjacent normal liver tissues, with similar findings in human HCC cell lines. High TMEM147 expression was correlated with T stage, pathological stage, histological grade, race, alpha-fetoprotein level, and vascular invasion in HCC. Moreover, we revealed that high TMEM147 expression was associated with shorter survival times and that TMEM147 could be a risk factor for overall survival, along with T stage, M stage, pathological stage, and tumor status. Mechanistic studies revealed that high TMEM147 expression was linked to the B lymphocyte, antigen response, IL6 signaling pathway, cell cycle, Kirsten rat sarcoma viral oncogene homolog (KRAS) signaling pathway, and myelocytomatosis oncogene (MYC) targets. Correspondingly, TMEM147 expression was positively associated with the infiltration of immune cells, including Th2 cells, follicular helper T cells, macrophages, and NK CD56 bright cells in HCC. TMEM147 might be a biomarker for poor prognosis and is related to immune cell infiltration in HCC.