Edmondson-Steiner Grade Research Articles

Uncovering gene expression signatures and diagnostic – Biomarkers in hepatocellular carcinoma through multinomial logistic regression analysis

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide, and classifying the developmental stages of HCC can help with early prognosis and treatment. This study aimed to investigate diagnostic and prognostic molecular signatures underlying the progression of HCC, including tumor initiation and growth, and to classify its developmental stages based on gene expression levels. We integrated data from two cancer systems, including 78 patients with Edmondson-Steiner (ES) grade and 417 patients with TNM stage cancer. Functional profiling was performed using identified signatures. Using a multinomial logistic regression model (MLR), we classified controls, early-stage HCC, and advanced-stage HCC. The model was validated in three independent cohorts comprising 45 patients (neoplastic stage), 394 patients (ES grade), and 466 patients (TNM stage). Multivariate Cox regression was employed for HCC prognosis prediction. We identified 35 genes with gradual upregulation or downregulation in both ES grade and TNM stage patients during HCC progression. These genes are involved in cell division, chromosome segregation, and mitotic cytokinesis, promoting tumor cell proliferation through the mitotic cell cycle. The MLR model accurately differentiated controls, early-stage HCC, and advanced-stage HCC across multiple cancer systems, which was further validated in various independent cohorts. Survival analysis revealed a subset of five genes from TNM stage (HR: 3.27, p < 0.0001) and three genes from ES grade (HR: 7.56, p < 0.0001) that showed significant association with HCC prognosis. The identified molecular signature not only initiates tumorigenesis but also promotes HCC development. It has the potential to improve clinical diagnosis, prognosis, and therapeutic interventions for HCC. This study enhances our understanding of HCC progression and provides valuable insights for precision medicine approaches.

Postoperative adjuvant hepatic arterial infusion chemotherapy combined with donafenib in hepatocellular carcinoma with solitary large tumor and microvascular invasion: A multicenter, prospective, single-arm, phase II trial.

e16227 Background: Hepatocellular carcinoma (HCC) with solitary large tumor (≥ 5 cm) and microvascular invasion (MVI) was associated with high 5-year recurrence rate and poor survival prognosis. Postoperative adjuvant hepatic arterial infusion chemotherapy (HAIC) was found to improve the recurrence-free survival (RFS) with acceptable safety profiles in HCC patients with MVI. However, the prognosis of HCC who received adjuvant HAIC after hepatectomy still remain far from satisfactory. Several studies have shown that the combination of HAIC and tyrosine kinase inhibitors (TKIs) could exhibit a synergistic anticancer effect and improve the survival outcomes of advanced HCC. Thus, the present study was conducted to explore the efficacy and safety of adjuvant HAIC plus the novel multikinase inhibitor donafenib in HCC with solitary tumor ≥ 5 cm and MVI. Methods: This prospective, single-arm phase II study was conducted in three medical centers in China. HCC patients with both solitary tumor ≥ 5 cm and MVI, no evidence of recurrence at radiological follow-up at 4-8 weeks after hepatectomy, no previous treatment for HCC other than hepatectomy, Child-Pugh score A or B7 were enrolled. Eligible patients received one cycle of HAIC with oxaliplatin, fluorouracil, and leucovorin (HAIC-FOLFOX4), and followed by donafenib (200 mg orally twice daily) for up to 1 year until disease recurrence or unacceptable toxicity. The primary endpoint was 1-year recurrence-free survival rate (1-year RFS rate). Secondary endpoints included RFS, overall survival (OS) and safety. Results: A total of 18 patients were included for analysis. The median age was 59 years (range, 28–75), the median maximum tumor size was 7.0 cm (interquartile range [IQR], 6.2–7.8), 88.9% had low-risk MVI, 61.1% had Edmondson-Steiner grade III-IV and 44.4% had incomplete tumour capsule. As of November 27, 2023, 4 of 18 patients (22.2%) recurrenced and no deaths occurred with a median follow-up of 15.0 months (95% confidence interval [CI], 5.1–19.1). The 1-year RFS rate was 64.9% (95%CI, 39.2%–100%), and current immature median RFS was 14.3 months (95%CI, not available [NA], 11.2–NA). The most common treatment-related adverse events (TRAEs) were hand-foot skin reaction (72.2%), diarrhea (38.9%), decreased platelet count (22.2%), hypoalbuminemia (22.2%), and alopecia (22.2%). Grade 3 TRAEs occurred in 6 patients (33.3%), and no grade 4 or 5 TRAEs occurred. Conclusions: In this prospective study, the preliminary data indicated that HAIC combined with donafenib is an encouraging adjuvant therapy with well-tolerated safety profiles for HCC patients with solitary tumor ≥ 5 cm and MVI. Clinical trial information: NCT04962958 .

An Investigative Analysis of Therapeutic Strategies in Hepatocellular Carcinoma: A Raetrospective Examination of 23 Biopsy-Confirmed Cases Emphasizing the Significance of Histopathological Insights

Background: The Liver Imaging Reporting and Data System (LI-RADS) combines standardized terminology with a classification system for imaging findings in patients with HCC, therefore rendering diagnostic biopsy unnecessary in many cases. This retrospective study included 23 patients with a biopsy diagnosis of HCC, performed either before or after local interventional procedures, in order to evaluate the histopathologic changes induced by previous procedures and their potential influence on the response to immune therapy. Material and Methods: The study encompassed a cohort of patients diagnosed with Hepatocellular Carcinoma (HCC). Diagnosis was established via contrast-enhanced computer tomography or magnetic resonance imaging that identified LI-RADS-5 nodules in conjunction with historical liver disease and elevated alpha-fetoprotein (AFP) levels or via histological examination confirming positivity for glypican3, heat shock protein 70, and glutamine synthetase. The study detailed the liver disease etiology, LI-RADS scores, characteristics and dimensions of HCC nodules, serum AFP concentrations, Edmondson–Steiner grading, and the expression of programmed cell death ligand 1 (PD-L1) in the tumor cells. Results: Among the study’s cohort of Hepatocellular Carcinoma (HCC) patients, a portion had not received any prior treatments, while the remainder experienced local HCC recurrence following trans-arterial chemoembolization or radiofrequency ablation. Observations indicated elevated alpha-fetoprotein (AFP) levels in those who had not undergone any previous interventions, showing statistical significance. The Edmondson–Steiner classification predominantly identified grade III differentiation across patients, irrespective of their treatment history. Furthermore, an increase in intra-tumoral programmed cell death ligand 1 (PD-L1) expression was noted in patients who had not been subjected to previous therapies. Conclusion: Liver biopsy offers valuable insights for patients with Hepatocellular Carcinoma (HCC), assisting in the tailoring of immune therapy strategies, particularly in cases of recurrence following prior local interventions.

Development and Validation of a Risk Prediction Algorithm for Evaluating the Efficacy of Postoperative Adjuvant TACE Therapy for Hepatocellular Carcinoma.

There is a lack of a reliable outcome prediction model for patients evaluating the feasibility of postoperative adjuvant transarterial chemoembolization (PATACE) therapy. Our goal was to develop an easy-to-use tool specifically for these patients. From January 2013 to June 2017, patients with hepatocellular carcinoma from the Liver Center of the First Affiliated Hospital of Chongqing Medical University received postoperative adjuvant Transarterial chemoembolization (TACE) therapy after liver cancer resection. A Cox proportional hazards model was established for these patients, followed by internal validation (enhanced bootstrap resampling technique) to further evaluate the predictive performance and discriminanceevaluate the predictive performance and discriminance, and compare it with other predictive models. The prognostic factors considered included tumour number, maximum tumor diameter, Edmondson-Steiner (ES) grade, Microvascular invasion (MVI) grade, Ki67, age, sex, hepatitis B surface antigen, cirrhosis, Alpha-fetoprotein (AFP), Albumin-bilirubin (ALBI) grade, Childpugh grade, body mass index (BMI), Neutrophil-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR). The endpoint of the study was overall survival. The median overall survival was 36 (95%CI: 34.0-38.0) months, with 1-year, 2-year and 3-year survival rates being 96.3%, 84.0% and 75.3%, respectively. Tumour number, MVI grade, and BMI was incorporated into the model, which had good differentiation and accuracy. Internal validation (enhanced bootstrap) suggested that Harrell's C statistic is 0.72. The model consistently outperforms other currently available models. This model may be an easy-to-use tool for screening patients suitable for PA-TACE treatment and guiding the selection of clinical protocols. But further research and external validation are required.

Abstract 6175: Deep learning-based survival prediction for hepatocellular carcinoma using whole slide images

Abstract There is an increasing need for classifiers to effectively stratify prognosis in patients with hepatocellular carcinoma (HCC). Deriving interpretable prognostic features using deep-learning (DL)-based prognostic models from pathology images remains a challenge. In this study, we developed a computational approach based on DL to predict the overall survival (OS) of HCC patients from formalin-fixed paraffin-embedded histopathology whole slide images. A DL model for classifying good and poor prognosis was developed on a total of 460 patients with 2 independent cohorts from Seoul St. Mary's Hospital. The primary outcome was OS. The training set (SSM1, n = 292) included HCC patients that had undergone surgical resection. The classifier was then independently tested on the second HCC dataset (SSM2, n = 168). The area under the curve (AUC) for the receiver operating characteristic (ROC) curves was 0.850 and 0.781 for SSM1 and SSM2 datasets, respectively. In addition, we have tried to establish DL model for prediction of OS based on clinicopathological features, including Edmondson-Steiner grade, pT stage, vascular invasion, Ki-67 index, and cytokeratin 19 immunohistochemical expression. Random forest model was applied to classify the good and poor prognosis groups and The AUROCs for the random forest was 0.705 for the SSM1 dataset, which are inferior to that of DL prediction. These findings suggest that the DL techniques can be applied to refine the prognostic prediction of HCC patients. Citation Format: Sung Hak Lee, Hyun-Jong Jang. Deep learning-based survival prediction for hepatocellular carcinoma using whole slide images [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6175.

Characterization of lymphocyte-rich hepatocellular carcinoma and the prognostic role of tertiary lymphoid structures.

Lymphocyte-rich hepatocellular carcinoma (LR-HCC) is largely unknown and a rare subtype of HCC with immune-rich stroma. Tertiary lymphoid structures (TLS), frequently observed in LR-HCC, are known to be prognostically significant in various malignancies; however, their significance in HCC remains unevaluated. Clinicopathologic data of 191 cases of surgically resected conventional HCC (C-HCC, n = 160) and LR-HCC (n = 31) were retrieved. Immunohistochemistry, multiplex immunofluorescence staining, RNA sequencing and proteomic analysis were conducted. Differences between the subtypes were statistically evaluated. LR-HCC was significantly correlated to larger tumour size, higher Edmondson-Steiner grade, presence of TLS and higher CD3-, CD8- and FOXP3-positive T cell, high PD-1 and PD-L1 expression (p < .001 for all) compared to C-HCC. Patients with LR-HCC exhibited significantly better overall survival (OS) (p = .044) and recurrence-free survival (RFS) (p = .025) than C-HCC. LR-HCC demonstrated TLS signatures with significantly higher proteomic-based immune scores in 14 of 17 types of tumour-infiltrating immune cells. Furthermore, C-HCC with secondary follicles, the most mature form of TLS, exhibited significantly better OS (p = .031) and RFS (p = .033) than those without. Across the global proteome, LR-HCC was well-differentiated from C-HCC and a map of protein-protein interactions between tumour-infiltrating lymphocytes and HCC in tumour microenvironment was completed. LR-HCC is clinicopathologically and molecularly distinct and shows better prognosis compared to C-HCC. Also, the presence of secondary follicle can be an important prognostic marker for better prognosis in both LR-HCC and C-HCC.

Perfusion of hepatocellular carcinomas measured by diffusion-derived vessel density biomarker: Higher hepatocellular carcinoma perfusion than earlier intravoxel incoherent motion reports.

Diffusion-derived vessel density (DVDD) is a physiological surrogate of the area of microvessels per unit tissue area. DDVD is calculated according to DDVD(b0b2) = Sb0/ROIarea0 - Sb2/ROIarea2, where Sb0 and Sb2 refer to the liver signal when b is 0 or 2 s/mm2. Pathohistological studies and contrast-enhanced CT/MRI data showed higher blood volume in hepatocellular carcinoma (HCC) relative to native liver tissue. With intravoxel incoherent motion (IVIM) imaging, most authors paradoxically reported a decreased perfusion fraction of HCC relative to the adjacent liver. This study applied DDVD to assess the perfusion of HCC. MRI was performed with a 3.0-T magnet. Diffusion-weighted images with b-values of 0 and 2 s/mm2 were acquired in 72 HCC patients. Thirty-two patients had microvascular invasion (MVI(+)) and 40 patients did not have microvascular invasion (MVI(-)). Fifty-eight patients had Edmondson-Steiner grade I or II HCC, and 14 patients had Edmondson-Steiner grade III or IV HCC. DDVD measurement was conducted on the axial slice that showed the largest HCC size. DDVD(b0b2) T/L = HCC DDVD(b0b2)/liver DDVD(b0b2). DDVD(b0b2) T/L median (95% confidence interval) of all HCCs was 2.942 (2.419-3.522), of MVI(-) HCCs was 2.699 (2.030-3.522), of MVI(+) HCCs was 2.988 (2.423-3.990), of Edmondson-Steiner grade I/II HCCs was 2.873 (2.277-3.465), and of Edmondson-Steiner grade III/IV HCCs was 3.403 (2.008-4.485). DDVD(b0b2) T/L approximately agrees with contrast agent dynamically enhanced CT/MRI literature data, whereas it differs from earlier IVIM study results, where HCC perfusion fraction was paradoxically lower relative to native liver tissue. A weak trend was noted with MIV(+) HCCs had a higher DDVD(b0b2) T/L than that of MVI(-) HCCs, and a weak trend was noted with the poorly differentiated group of HCCs (Edmondson-Steiner grade III and IV) had a higher DDVD(b0b2) T/L than that of the better differentiated group of HCCs (Edmondson-Steiner grade I and II).

Establishing and Externally Validating a Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score-Based Nomogram for Predicting Early Recurrence in BCLC Stage 0/A Hepatocellular Carcinoma Patients After Radical Liver Resection: A Multi-Center Study.

Early recurrence (ER) is associated with poor prognosis in hepatocellular carcinoma (HCC). In this study, we developed and externally validated a nomogram based on the hemoglobin, albumin, lymphocytes, and platelets (HALP) score to predict ER for patients with BCLC stage 0/A HCC who underwent radical liver resection. A total of 808 BCLC stage 0/A HCC patients from six hospitals were included in this study, and they were assigned to a training cohort (n = 500) and an external validation cohort (n = 308). We used univariate and multivariate Cox regression analysis to identify the independent risk factors for disease-free survival (DFS). We also established and externally validated a nomogram based on these risk predictors. The nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), the concordance index (C-index), the calibration curve, decision curve analysis (DCA), and Kaplan‒Meier analysis. Multivariate COX regression showed that HBV DNA ≥10,000 IU/mL (P < 0.001), HALP score ≤38.20 (P < 0.001), tumor size (P = 0.003), clinically significant portal hypertension (P = 0.001), Edmondson-Steiner grade (III-IV) (P = 0.007), satellite nodules (P < 0.001), and MVI (P = 0.001) were independent risk factors for post-operative tumor recurrence. The AUC of our nomogram for predicting the 2-year and 5-year DFS was 0.756 and 0.750, respectively, in the training cohort and 0.764 and 0.705, respectively, in the external validation cohort. We divided the patients into low-, intermediate- and high-risk groups according to the risk score calculated by the nomogram. There were statistically significant differences in the DFS and overall survival (OS) among the three groups of patients (P < 0.001). We developed and externally validated a new nomogram, which is accurate and can predict ER in BCLC stage 0/A HCC patients after curative liver resection.

Exploring the MRI and Clinical Features of P53-Mutated Hepatocellular Carcinoma.

To study the MRI features (based on LI-RADS) and clinical characteristics of P53-mutated hepatocellular carcinoma (HCC) patients. This study enrolled 344 patients with histopathologically confirmed HCC (P53-mutated group [n = 196], non-P53-mutated group [n = 148]). We retrospectively evaluated the preoperative MRI features, clinical and pathologic features of the lesions and assigned each lesion according to the LI-RADS. MRI findings, clinical features, and pathologic findings were compared using the Student's t test, χ2 test, and multivariable regression analysis. Most HCC patients were categorized as LR-5. On multivariate analysis, the Edmondson-Steiner grade (odds ratio, 2.280; 95% CI: 1.268, 4.101; p = 0.006) and rim enhancement (odds ratio, 2.517; 95% CI: 1.095, 5.784; p = 0.030) were found to be independent variables associated with P53-mutated HCC. In the group of HCC lesions with the largest tumor diameter (LTD) greater than or equal to 10mm and less than or equal to 20mm, enhancing capsule was an independent predictor of P53-mutated HCC (odds ratio, 6.200; 95% CI: 1.116, 34.449; p = 0.037). Among the HCC lesions (20 mm ˂ LTD ≤ 50 mm), corona enhancement (odds ratio, 2.102; 95% CI: 1.022, 4.322; p = 0.043) and nodule-in-nodule architecture (odds ratio, 2.157; 95% CI: 1.033, 4.504; p = 0.041) were found to be independent risk factors for P53 mutation. Among the HCC lesions (50 mm ˂ LTD ≤ 100 mm), diameter (odds ratio, 1.035; 95% CI: 1.001, 1.069; p = 0.044) and AFP ≥ 400 (ng/mL) (odds ratio, 3.336; 95% CI: 1.052, 10.577; p = 0.041) were found to be independent variables associated with P53-mutated HCC. Poor differentiation and rim enhancement are potential predictive biomarkers for P53-mutated HCC, while HCCs of different diameters have different risk factors for predicting P53 mutations.

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.

CT Radiomics Features of Abdominal Adipose and Muscle Tissues Can Predict the Postoperative Early Recurrence of Hepatocellular Carcinoma

To investigate the potential of computed tomography radiomics features extracted from abdominal adipose and muscle in predicting early recurrence (ER) of hepatocellular carcinoma (HCC) after surgery. This retrospective study enrolled 252 patients with HCC who underwent curative resection from twoindependent institutions. In the training cohort of 178 patients from institution A, radiomics signatures extracted from abdominal visceral adipose, subcutaneous adipose, and muscle were applied to establish the radiomics score using the least absolute shrinkage and selection operator regression. Using multivariable Cox regression analysis, two models were developed: one incorporated preoperative variables, and the other incorporated both pre- and postoperative variables. The external validation of the twomodels was conducted at institution B with 74 patients. The preoperative model incorporated tumor size, alpha-fetoprotein, body mass index, and radiomics score, whereas the postoperative model additionally integrated Edmondson-Steiner grade on the basis of the aforementioned parameters. In both cohorts, both models demonstrated superior performance to traditional staging systems and corresponding clinical models (P<0.01), with time-dependent area under the curveexceeding 0.81 and concordance indices exceeding 0.72. Furthermore, the two models exhibited lower prediction errors (integrated Brier score < 0.19), well-calibrated calibration curves, and greater net clinical benefits. Finally, the two radiomics-based models facilitated risk stratification by accurately distinguishing the high-, intermediate-, and low-risk groups for ER (P<0.01). Statistical models integrating the radiomics data of abdominal adipose and muscle can provide accurate and reliable predictions of postoperative ER for patients with HCC.

A Novel Nomogram for the Preoperative Prediction of Edmondson-Steiner Grade III-IV in Hepatocellular Carcinoma Patients.

Edmondson-Steiner (E-S) grade is a pathological indicator of the degree of hepatocellular carcinoma (HCC) differentiation, and E-S grade III-IV is a poor prognostic factor for HCC patients. Predicting poorly differentiated HCC has essential significance for clinical decision-making. Although some studies have developed predictive models based on magnetic resonance imaging (MRI) and radiomics, radiomic features that require specific software for analysis are impractical for clinical work. This study aims to develop a novel and user-friendly nomogram model to predict E-S grade III-IV. Medical data on patients meeting the inclusion criteria were obtained from the Nanjing Drum Tower Hospital HCC database (January 2020 to December 2022). Univariate analysis was used to screen for risk factors associated with E-S grade III-IV. A novel nomogram was established based on the subsequent multivariate logistic regression analysis. The performance of the established model was evaluated through diagnostic ability, calibration, and clinical benefits. Overall, 240 HCC patients were included in this study. Among them, 103 were highly differentiated (E-S grade I-II) HCC and 137 were poorly differentiated (E-S grade III-IV) HCC. A nomogram model that integrated alpha-fetoprotein (AFP), des-γ-carboxy prothrombin (DCP), hepatitis B virus surface antigen (HBsAg), hepatitis C virus antibodies (HCVAb), aspartate aminotransferase to lymphocyte ratio index (ALRI), and macrovascular invasion was established. The novel model had a good diagnostic performance with an area under the curve (AUC) value of 0.763. Meanwhile, the model had a diagnostic accuracy of 72.5%, a sensitivity of 78.1%, and a specificity of 65.1%. The calibration curve showed good calibration of the nomogram model (mean absolute error = 0.043), and the decision curve analysis (DCA) demonstrated that the clinical benefit was provided. Our developed nomogram model could successfully predict E-S grade III-IV in HCC patients, which may be helpful in clinical decision-making.

Non-invasive preoperative prediction of Edmondson-Steiner grade of hepatocellular carcinoma based on contrast-enhanced ultrasound using ensemble learning.

This study aimed to explore the clinical value of non-invasive preoperative Edmondson-Steiner grade of hepatocellular carcinoma (HCC) using contrast-enhanced ultrasound (CEUS). 212 cases of HCCs were retrospectively included, including 83 cases of high-grade HCCs and 129 cases of low-grade HCCs. Three representative CEUS images were selected from the arterial phase, portal vein phase, and delayed phase and stored in a 3-dimensional array. ITK-SNAP was used to segment the tumor lesions manually. The Radiomics method was conducted to extract high-dimensional features on these contrast-enhanced ultrasound images. Then the independent sample T-test and the Least Absolute Shrinkage and Selection Operator (LASSO) were employed to reduce the feature dimensions. The optimized features were modeled by a classifier based on ensemble learning, and the Edmondson Steiner grading was predicted in an independent testing set using this model. A total of 1338 features were extracted from the 3D images. After the dimension reduction, 10 features were finally selected to establish the model. In the independent testing set, the integrated model performed best, with an AUC of 0.931. This study proposed an Edmondson-Steiner grading method for HCC with CEUS. The method has good classification performance on independent testing sets, which can provide quantitative analysis support for clinical decision-making.

Integrated exome sequencing and microarray analyses detected genetic defects and underlying pathways of hepatocellular carcinoma

We performed whole exome sequencing (WES) and microarray analysis to detect somatic variants and copy number alterations (CNAs) for underlying mechanisms in a case series of hepatocellular carcinoma (HCC) with paired DNA samples from tumor and adjacent nontumor tissues. Clinicopathologic findings based on Edmondson-Steiner (E-S) grading, Barcelona-Clinic Liver Cancer (BCLC) stages, recurrence, and survival status and their associations with tumor mutation burden (TMB) and CNA burden (CNAB) were evaluated. WES from 36 cases detected variants in the TP53, AXIN1, CTNNB1, and SMARCA4 genes, amplifications of the AKT3, MYC, and TERT genes, and deletions of the CDH1, TP53, IRF2, RB1, RPL5, and PTEN genes. These genetic defects affecting the p53/cell cycle control, PI3K/Ras, and β-catenin pathways were observed in approximately 80% of cases. A germline variant in the ALDH2 gene was detected in 52% of the cases. Significantly higher CNAB in patients with poor prognosis by E-S grade III, BCLC stage C, and recurrence than patients with good prognosis by grade III, stage A, grade III and nonrecurrence was noted. Further analysis on a large case series to correlate genomic profiling with clinicopathologic classifications could provide evidence for diagnostic interpretation, prognostic prediction, and target intervention on involved genes and pathways.

RAD54L promotes progression of hepatocellular carcinoma via the homologous recombination repair pathway.

Hepatocellular carcinoma (HCC) is a malignant tumor with high incidence worldwide. The underlying mechanisms remain poorly understood. The DNA metabolic process of homologous recombination repair (HRR) has been linked to a high probability of tumorigenesis and drug resistance. This study aimed to determine the role of HRR in HCC and identify critical HRR-related genes that affect tumorigenesis and prognosis. A total of 613 tumor and 252 para-carcinoma tissue samples were collected from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) to obtain differentially expressed genes (DEGs). HRR-related genes were assessed using gene enrichment and pathway analyses. Survival analysis was performed using the Kaplan-Meier method in the Gene Expression Profiling Interactive Analysis portal. The levels of RAD54L in the HRR pathway were detected by RT-qPCR and western blotting in para-carcinoma and HCC tissues and in L02 normal human liver cells and Huh7 HCC cells. Immunohistochemistry (IHC) was performed on the clinical specimens to determine the connection between gene expression and clinical features. Bioinformatics analysis revealed that the HRR pathway was enriched in HCC tissues. Upregulation of HRR pathway DEGs in HCC tissues was positively correlated with tumor pathological staging and negatively associated with patient overall survival. RAD54B, RAD54L, and EME1 genes in the HRR pathway were screened as markers for predicting HCC prognosis. RT-qPCR identified RAD54L as the most significantly expressed of the three genes. Western blotting and IHC quantitative analyses further demonstrated that RAD54L protein levels were higher in HCC tissues. IHC analysis of 39 pairs of HCC and para-carcinoma tissue samples also revealed an association between RAD54L and Edmondson-Steiner grade and the proliferation-related gene Ki67. The collective findings positively correlate RAD54L in the HRR signaling pathway with HCC staging and implicate RAD54L as a marker to predict HCC progression.

Prognostic Analysis of Single Large Hepatocellular Carcinoma Following Radical Resection: A Single-Center Study.

To investigate the survival and independent prognostic factors for single large hepatocellular carcinoma (SLHCC) after surgical resection. Patients with SLHCC who underwent radical resection from January 2013 to December 2017 were retrospectively analyzed. The Kaplan-Meier method was used to analyze the overall survival (OS) rate and recurrence-free survival (RFS) rates. Cox forward stepwise regression was performed to analyze the independent prognostic factors. A total of 485 cases were included. The average age was 51.2±11.2 years, 88.9% had a history of hepatitis B virus infection, and most patients had normal liver function. The average tumor diameter was 8.8±3.0 cm. The 1-, 3-, and 5-year OS and RFS rates were 76.8%, 56.7%, and 45.7%, and 61.0%, 46.2%, and 34.7%, respectively. Multivariate analysis showed that liver cirrhosis (HR=1.456, P=0.004), total bilirubin (TB) ≥17.1 μmol/L (HR=1.437, P=0.011), glutamyl transferase (GGT) >60 U/L (HR=1.438, P=0.020), lactate dehydrogenase (LDH) >225 U/L (HR=1.442, P=0.007), blood loss ≥400 mL (HR=1.339, P=0.027), microvascular invasion (MVI) (HR=1.492, P=0.004), satellite lesions (HR=1.859, P<0.0001) and Edmondson-Steiner grade III+IV (HR=1.740, P=0.018) were independent risk factors for reduced OS in SLHCC patients. Sex (HR=1.763, P=0.003), liver cirrhosis (HR=1.382, P=0.007), GGT >60 U/L (HR=1.512, P=0.003), LDH >225 U/L (HR=1.480, P=0.002), MVI (HR=1.545, P=0.001), and satellite lesions (HR=1.564, P=0.001) were independent risk factors for reduced RFS. OS and RFS nomograms were constructed using risk factors with C-index values of 0.692 (95% CI: 0.659-0.724) and 0.659 (95% CI: 0.623-0.693), respectively. The Hosmer-Leme test demonstrated the good fit of both nomograms. Surgical resection is the standard and effective treatment for SLHCC patients. Sex, liver cirrhosis, TB≥17.1 μmol/L, GGT>60 U/L, LDH>225 U/L, blood loss≥400 mL, MVI, Edmondson-Steiner grade III+IV, and satellite lesions were found to be independent prognostic factors in SLHCC patients following radical resection. The OS and RFS nomograms accurately predicted the prognosis of SLHCC patients.

A model incorporating histopathology and preoperative gadoxetic acid-enhanced MRI to predict early recurrence of hepatocellular carcinoma without microvascular invasion after curative hepatectomy.

To assess the predictive value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features and postoperative histopathological grading for early recurrence of hepatocellular carcinoma (HCC) without microvascular invasion (MVI) after curative hepatectomy. A total of 85 MVI-negative HCC cases were retrospectively analyzed. Cox analyses were used to identify the independent predictors of early recurrence (within a 24 months span). The clinical prediction Model-1 or Model-2 was established without or with postoperative pathological factor, respectively. Nomogram models were constructed and receiver operating characteristic (ROC) curve analysis was used to assess the models' predictive ability. Internal validation of the prediction models for early HCC recurrence was performed using a bootstrap re-sampling approach. In the multivariate cox regression analysis, Edmondson-Steiner grade, peritumoral hypointensity on hepatobiliary phase (HBP), and relative intensity ratio (RIR) in HBP were identified as independent variables associated with early recurrence. The C-index of the nomogram models and internal validation were both between 0.7 and 0.8, showing good model fitting and calibration effects. The area under the ROC curve (AUC) was 0.781 for Model-1 based on the two preoperative MRI factors. When a third factor, the Edmondson-Steiner grade, was included (Model-2), the AUC increased to 0.834, and the sensitivity increased from 71.4 to 96.4%. Edmondson-Steiner grade, peritumoral hypointensity on HBP, and RIR on HBP can help predict early recurrence of MVI-negative HCC. In comparison with Model-1 (only imaging features), Model-2 (imaging features + histopathological grades) increases the sensitivity in predicting early recurrence of HCC without MVI. Preoperative GA-enhanced MRI signs are of great value in predicting early postoperative recurrence of HCC without MVI, and a combined pathological model was established to evaluate the feasibility and effectiveness of this technique.

Imbalance in ALR ubiquitination accelerates the progression of nonalcoholic steatohepatitis to hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer. Accumulating evidence indicates that non-alcoholic steatohepatitis (NASH) is a key predisposing factor for HCC occurrence. However, the precise mechanisms driving NASH transition to HCC remain largely obscure. Augmenter of liver regeneration (ALR) is a sulfhydryl oxidase and cytochrome c reductase that functions as an important regulator of mitochondrial dynamics. In this study, we focused on ALR ubiquitination-mediated degradation and its potential contribution to NASH-driven HCC progression at the mitochondrial level. Hepatic ALR expression in HCC patients was determined using immunohistochemical analysis. Mice with liver-specific deletion of ALR (ALRCKO) and ALRWT mice were fed a western diet (WD) and high-sugar solution for induction of NASH. HCC in animals was induced via peritoneal administration of CCl4. ALR expression was markedly decreased in liver tissues of patients with NASH and HCC compared with non-NASH and non-tumor tissues. Similarly, in ALRWT mice, the ALR level in tumor tissue was reduced relative to that in para-tumor tissue. In the ALRCKO group, mice fed WD plus CCl4 developed HCC starting at week 12 while ALRWT mice fed WD plus CCl4 developed HCC at week 24. Analysis of protein posttranslational modifications revealed ubiquitylation (Ub) and deubiquitination (DUb) of ALR by murine double minute 2 (MDM2) and ubiquitin-specific protease 36 (USP36), respectively. Imbalance between Ub and DUb of ALR resulted in profound ALR degradation, which appeared to be reversibly associated with Edmondson-Steiner tumor grade. Rescue of ALR levels via gene transfection abolished tumor malignant features to a certain extent in vitro. Notably, ALR deletion substantially enhanced mitochondrial fission by activating Drp1 phosphorylation at Ser616, thus disrupting the balance of mitochondrial dynamics between fission and fusion and severely impairing oxidative phosphorylation (OXPHOS) and ATP synthesis, instead enhancing anaerobic metabolism, which might be attributed to steatotic hepatocyte transition into the malignant HCC phenotype. Hepatic ALR depletion via dysregulation of ubiquitination is a critical aggravator of NASH-HCC progression and represents a promising therapeutic target for related liver diseases.

High expression of aurora kinase B predicts poor prognosis in hepatocellular carcinoma after curative surgery and its effects on the tumor microenvironment.

Currently, the only broadly used biomarker for hepatocellular carcinoma (HCC), alpha fetoprotein (AFP), has multiple limitations and the need for novel biomarkers is urgent. Aurora kinase B (AURKB) is a key mitotic protein kinase which performs a critical function in cell cycle progression. Nonetheless, neither the function nor the mechanism of AURKB in HCC following curative surgery is fully grasped at this time. This study sought to evaluate the impact of AURKB on prognosis and the tumor immune microenvironment (TIME) in HCC. We evaluated both the expression profile of AURKB in HCC and its clinical value using online databases and clinical specimens. The prognostic value of AURKB was studied by Kaplan-Meier survival analysis, and the link between AURKB and tumor-infiltrating immune cells (TIICs) were analyzed. We found the mRNA expression patterns of AURKB were remarkably upregulated in HCC in contrast with adjoining normal tissues (P<0.001). Upregulation of the AURKB protein in HCC was additionally verified by clinical samples. The expression of AURKB was substantially associated with Child-Pugh, microvascular invasion (MVI), Edmondson-Steiner grade, and tumor recurrence. Furthermore, patients diagnosed with HCC who had a low AURKB expression had a better. Our data suggested age [hazard ratio (HR): 1.34], alanine aminotransferase (ALT) (HR: 1.65), tumor size (HR: 1.99), mor number (HR: 1.60), MVI (HR: 1.93), grade (HR: 5.58), and AURKB expression (HR: 3.63) independently functioned as prognostic risk indicators for HCC (P<0.05). Importantly, we also found AURKB expression was inversely linked to resting natural killer (NK) cells, M2 macrophages, activated mast cells, and naive B cells, and positively linked to M0 macrophages, T follicular helper cells (Tfh), regulatory T cells (Treg), and resting myeloid dendritic cells. In addition, AURKB expression was also positively linked to the immune checkpoints of PDCD1, CD274, CTLA4, and LAG3. Finally, 1,696 DEGs were discovered, and were predominantly implicated in chromosome segregation, cell cycle, xenobiotic metabolic process, calcium signaling pathway, bile secretion, tyrosine metabolism, and DNA replication. AURKB may be a potential prognostic biomarker for HCC after curative surgery, which correlates with MVI and the TIME in HCC.