Grade Of Hepatocellular Carcinoma Research Articles

Comparative Study of Amide Proton Transfer Imaging and Intravoxel Incoherent Motion Imaging for Predicting Histologic Grade of Hepatocellular Carcinoma.

Background: Preoperative grading of hepatocellular carcinoma (HCC) is an important factor associated with prognosis after liver resection. The promising prediction of the differentiation of HCC remains a challenge. The purpose of our study was to investigate the value of amide proton transfer (APT) imaging in predicting the histological grade of HCC, compared with the intravoxel incoherent motion (IVIM) imaging.Methods: From September 2018 to February 2020, 88 patients with HCC were enrolled and divided into four groups (G1, G2, G3, and G4) based on the histologic grades. Preoperative APT signal intensity (SI), apparent diffusion coefficient (ADC), true molecular diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f ) of HCC were independently measured by two radiologists. The averaged values of those parameters were compared using an analysis of variance. The Spearman rank analysis was used to compare the correlation between those imaging parameters and the histological grades. Receiver operating characteristic (ROC) curve analysis was used to explore the predictive performance.Results: There were significant differences in APT SI, ADC, D, and f among the four grades of HCC (all P < 0.001). A moderate to good relationship was found between APT SI and the histologic grade of HCC (r = 0.679, P < 0.001). APT SI had an area under the ROC curve (AUC) of 0.890 (95% CI: 0.805–0.947) for differentiating low- from high-grade HCC, and the corresponding sensitivity and specificity were 85.71% and 82.05%, respectively. Comparison of ROC curves demonstrated that the AUC of APT SI was significantly higher than those of IVIM-derived parameter (Z = 2.603, P = 0.0092; Z = 2.099, P = 0.0358; Z = 4.023, P = 0.0001; Z = 2.435, P = 0.0149, compared with ADC, D, D*, and f , respectively). Moreover, the combination of both techniques further improved the diagnostic performance, with an AUC of 0.929 (95% CI: 0.854–0.973).Conclusion: APT imaging may be a potential noninvasive biomarker for the prediction of histologic grading of HCC and complements IVIM imaging for the more accurate and comprehensive characterization of HCC.

Construction and analysis of macrophage infiltration related circRNA-miRNA-mRNA regulatory networks in hepatocellular carcinoma.

BackgroundMacrophage play a crucial role in regulating tumor progression. This study intended to investigate the circular RNA (circRNA) regulatory network associated with macrophage infiltration in hepatocellular carcinoma (HCC).MethodsThe immune cell fractions of HCC from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium were calculated by Estimation of the Proportion of Immune and Cancer cells algorithm. The differentially expressed mRNAs (DEmRNAs), microRNAs (DEmiRNAs) and circRNAs (DEcircRNAs) were identified from HCC and adjacent non-tumor cases of TCGA or Gene Expression Omnibus database. The DEmRNAs related to macrophage were selected by weighted gene co-expression network analysis and then utilized to generate the circRNA-miRNA-mRNA network. A hub circRNA regulatory network was established based on the co-expressed DEmiRNAs and DEmRNAs owning contrary correlation with the clinical characteristics, survival and macrophage infiltration level. A gene signature based on the DEmRNAs in hub network was also generated for further evaluation. The circRNA binding bite for miRNA was detected by luciferase assay.ResultsHigh macrophage fraction predicted good survival for HCC. A circRNA-miRNA-mRNA network was constructed by 27 macrophage related DEmRNAs, 21 DEmiRNAs, and 15 DEcircRNAs. Among this network, the expression of hsa-miR-139-5p was negatively correlated with CDCA8, KPNA2, PRC1 or TOP2A. Hsa-miR-139-5p low or targeted DEmRNA high expression was associated with low macrophage infiltration, high grade, advanced stage and poor prognosis of HCC. Additionally, the risk score generated by 4-DEmRNA signature could reflect the macrophage infiltration status and function as an independent prognostic factor for HCC. Finally, hsa_circ_0007456 acting on hsa-miR-139-5p related network was viewed as the hub circRNA regulatory network. Taken together, some circRNA regulatory networks may be associated with macrophage infiltration, which provides clues for mechanism study and therapeutic strategies of HCC.

Amide Proton Transfer Imaging vs Diffusion Kurtosis Imaging for Predicting Histological Grade of Hepatocellular Carcinoma.

BackgroundTo investigate the value of amide proton transfer (APT) imaging in predicting the histological grade of hepatocellular carcinoma (HCC), compared with diffusion kurtosis imaging (DKI).MethodsA total of 88 patients with HCC were enrolled and divided into four groups (G1, G2, G3, and G4) based on histologic grades. Preoperative APT signal intensity (SI), mean diffusivity (MD), mean kurtosis (MK) of HCC were measured and compared. Those quantitative magnetic resonance imaging (qMRI) parameters were compared using an analysis of variance. The correlations between the qMRI parameters and the histological grades were determined using Spearman's rank analysis. In addition, the predictive performance for differentiating low- (G1 and G2) from high-grade (G3 and G4) HCC was evaluated using receiver operating characteristic (ROC) curve analysis.ResultsSignificant differences were found in APT SIs, MD, and MK among the four groups (P<0.05). Moderate to good relationships were found between the histologic grade of HCC and APT SI and MK (r=0.679, P<0.001 and r=0.539, P<0.001, respectively). The area under the ROC curves (AUCs) of APT SI, MK, and MD for differentiating low- from high-grade HCC were 0.890 (95%CI: 0.805–0.947), 0.765 (95%CI: 0.662–0.849) and 0.717 (95%CI: 0.611–0.808), respectively. Comparison of ROC curves showed a significantly higher AUC of APT SI compared with those of the DKI-derived parameters (P <0.05).ConclusionThe APT imaging may be more accurate than DKI for predicting the histological grade of HCC.

CircRNA ZFR stimulates the proliferation of hepatocellular carcinoma through upregulating MAP2K1.

The aim of the study was to illustrate the function of circRNA ZFR in aggravating the development of hepatocellular carcinoma (HCC) by upregulating MAP2K1. CircRNA ZFR levels in 62 paired HCC and paracancerous species were detected. The influence of circRNA ZFR on clinical data of HCC patients was analyzed. After the overexpression or knockdown of circRNA ZFR, changes in viability and clonality of Bel-7402 and Hep3B cells were assessed, respectively. The involvement of circRNA ZFR/MAP2K1 axis in the development of HCC was explored through Luciferase assay and rescue experiments. CircRNA ZFR was highly expressed in HCC species than the paracancerous ones. Higher level of circRNA ZFR predicted more advanced tumor grading of HCC. The knockdown of circRNA ZFR attenuated the proliferative ability of HCC cells, while the overexpression of circRNA ZFR obtained opposite results. MAP2K1 level was positively correlated to that of circRNA ZFR. Luciferase assay uncovered that circRNA ZFR can be targeted by MAP2K1 through specific binding sites. In addition, the overexpression of MAP2K1 could reverse the influence of silenced circRNA ZFR on proliferative ability of HCC cells. CircRNA ZFR is upregulated in HCC and closely linked to tumor grading. It promotes proliferative ability in HCC by upregulating MAP2K1.

Texture Analysis of Hepatocellular Carcinoma on Magnetic Resonance Imaging: Assessment for Performance in Predicting Histopathologic Grade.

The aim of the study was to evaluate the performance of texture analysis for discriminating the histopathological grade of hepatocellular carcinoma (HCC) on magnetic resonance imaging. Preoperative magnetic resonance imaging data from 101 patients with HCC, including T2-weighted imaging, arterial phase, and apparent diffusion coefficient mapping, were analyzed using texture analysis software (TexRAD). Differences among the histological groups were analyzed using the Mann-Whitney U test. The performance of texture features was evaluated using receiver operating characteristic analysis. Entropy was the most significantly relevant texture feature for distinguishing each histological grade group of HCC (P < 0.05). In ROC analysis, entropy with spatial scale filter 3 (area under curve the receiver operating characteristic curve [AUC], 0.778), mean with coarse filter (spatial scale filter 5; AUC, 0.670), and skewness without filtration (AUC, 0.760) had the highest AUC value on T2-weighted imaging, arterial phase, and apparent diffusion coefficient maps, respectively. Magnetic resonance imaging texture analysis demonstrated potential for predicting the histopathological grade of HCCs.

Neutrophil to lymphocyte ratio and albumin bilirubin grade in hepatocellular carcinoma: A systematic review.

BACKGROUNDHepatocellular carcinoma (HCC) is a frequent cause of cancer related death globally. Neutrophil to lymphocyte ratio (NLR) and albumin bilirubin (ALBI) grade are emerging prognostic indicators in HCC.AIMTo study published literature of NLR and ALBI over the last five years, and to validate NLR and ALBI locally in our centre as indicators of HCC survival.METHODSA systematic review of the published literature on PubMed of NLR and ALBI in HCC over the last five years. The search followed the guidelines of the preferred reporting items for systematic reviews and meta-analyses. Additionally, we also investigated HCC cases between December 2013 and December 2018 in our centre.RESULTSThere were 54 studies describing the relation between HCC and NLR and 95 studies describing the relation between HCC and ALBI grade over the last five years. Our local cohort of patients showed NLR to have a significant negative relationship to survival (P = 0.011). There was also significant inverse relationship between the size of the largest HCC nodule and survival (P = 0.009). Median survival with alpha fetoprotein (AFP) < 10 KU/L was 20 mo and with AFP > 10 KU/L was 5 mo. We found that AFP was inversely related to survival, this relationship was not statically significant (P = 0.132). Mean survival for ALBI grade 1 was 37.7 mo, ALBI grade 2 was 13.4 months and ALBI grade 3 was 4.5 mo. ALBI grades performed better than Child Turcotte Pugh score in detecting death from HCC.CONCLUSIONNLR and ALBI grade in HCC predict survival better than the conventional alpha fetoprotein. ALBI grade performs better than Child Turcotte Pugh score. These markers are done as part of routine clinical care and in cases of normal alpha fetoprotein, these markers could give a better understanding of the patient disease progression. NLR and ALBI grade could have a role in modified easier to learn staging and prognostic systems for HCC.

Quantitative analysis of multiphase magnetic resonance images may assist prediction of histopathological grade of small hepatocellular carcinoma.

BackgroundThe aim of the study was to investigate whether preoperative quantitative analysis of multiphase magnetic resonance images may assist in predicting the pathological grade of small hepatocellular carcinoma (HCC).MethodsA total of 49 patients with small HCCs (≤3 cm) underwent multiphase magnetic resonance imaging (MRI) and were retrospectively reviewed. Routine unenhanced and post gadobenate dimeglumine (Gd-BOPTA)-enhanced MRI were preoperatively performed. Signal intensity (SI) was measured within the designated region of interest (ROI) including those of the lesion and paraspinous muscles. The lesion-to-paraspinous muscle relative contrast ratio (RCR) on T2-weighted (T2W) imaging, diffusion-weighted (DW) imaging, and dynamic phase Gd-BOPTA-enhanced T1W (T1-weighted) imaging were calculated, and statistical analysis was performed to determine the predictive power for the histological grade.ResultsIn all, 49 cases were included comprising 3 well-differentiated (WD) HCCs, 36 moderately differentiated (MD) HCCs, and 10 poorly differentiated (PD) HCCs. There was a negative correlation between the RCR and pathological grade of small HCC in the arterial phase [correlation coefficient (ρ)=−0.305, P<0.05]. However, there was no correlation between RCR in other phases and pathological grade (P>0.05 for all). There was also no correlation between tumor margin, tumor location, cystic/necrotic change, intratumoral fat, enhancement pattern, tumor capsule, tumor boundary or tumor size, and any of the differentiation categories (P>0.05 for all).ConclusionsThe lesion-to-paraspinous muscle RCR on arterial phase Gd-BOPTA-enhanced T1W imaging may be useful for the prediction of the histological characteristics of small HCC.

Preoperative prediction for pathological grade of hepatocellular carcinoma via machine learning-based radiomics.

To investigate the efficacy of contrast-enhanced computed tomography (CECT)-based radiomics signatures for preoperative prediction of pathological grades of hepatocellular carcinoma (HCC) via machine learning. In this single-center retrospective study, data collected from 297 consecutive subjects with HCC were allocated to training dataset (n = 237) and test dataset (n = 60). Manual segmentation of lesion sites was performed with ITK-SNAP, the radiomics features were extracted by the Pyradiomics, and radiomics signatures were synthesized using recursive feature elimination (RFE) method. The prediction models for pathological grading of HCC were established by using eXtreme Gradient Boosting (XGBoost). The performance of the models was evaluated using the AUC along with 95% confidence intervals (CIs) and standard deviation, sensitivity, specificity, and accuracy. The radiomics signatures were found highly efficient for machine learning to differentiate high-grade HCC from low-grade HCC. For the clinical factors, when they were merely applied to train a machine learning model, the model achieved an AUC of 0.6698, along with 95% CI and standard deviation of 0.5307-0.8089 and 0.0710, respectively (sensitivity, 0.6522; specificity, 0.4595; accuracy, 0.5333). Meanwhile, when the radiomics signatures were applied in association with clinical factors to train a machine learning model, the performance of the model remarkably increased with AUC of 0.8014, along with 95% CI and standard deviation of 0.6899-0.9129 and 0.0569, respectively (sensitivity, 0.6522; specificity, 0.7297; accuracy, 0.7000). The radiomics signatures could non-invasively explore the underlying association between CECT images and pathological grades of HCC. • The radiomics signatures may non-invasively explore the underlying association between CECT images and pathological grades of HCC via machine learning. • The radiomics signatures of CECT images may enhance the prediction performance of pathological grading of HCC, and further validation is required. • The features extracted from arterial phase CECT images may be more reliable than venous phase CECT images for predicting pathological grades of HCC.

Does the change in volumetric functional MR metrics post-TACE predict histopathologic grading of hepatocellular carcinoma?

To evaluate whether the change in volumetric ADC (vADC) and volumetric venous enhancement (vVE) after transarterial chemoembolization (TACE) can predict the histologic grading of hepatocellular carcinoma (HCC). This HIPPA-compliant retrospective study was approved by our institutional review board. The study population included 106 HCC patients (147 index lesions) who had MR imaging within 3months before and after TACE and pathologic report of the HCC either by biopsy or liver transplantation/resection between 2001 and 2017. Volumetric measurements of venous enhancement (VE) and apparent diffusion coefficient (ADC) were performed on baseline and post-TACE MRI. The tumors were histologically classified into two low-grade and high-grade groups. The parameters between two groups were compared using bivariate and multivariate analyses. Median change in vADC, vVE, and absolute vADC skewness after TACE was higher in low-grade HCCs as compared with high-grade HCCs (p < 0.001, p = 0.005, p = 0.04, respectively). Combining ΔvADC, ΔvVE, and the etiology for background liver disease in multivariate analysis had the highest accuracy in distinguishing high-grade tumors (AUC = 91%). ΔvADC and ΔvVE after TACE are potential predictors of HCC histopathological grading. Combining functional MRI biomarkers with the etiology of liver disease can enhance the accuracy in assessing degree of differentiation. • Change in volumetric functional MRI biomarkers after TACE can be a non-invasive method to evaluate tumor histopathology in HCC. • The etiology of background liver disease might be a predictor of tumor degree of differentiation.

Serum betatrophin and irisin levels in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) development is a complex process with well-known risk factors, however the role of betatrophin/angiopoietin-like protein 8 and irisin has been poorly investigated thus far. The aim of this study is to measure betatrophin and irisin serum levels in HCC, cirrhotic patients and controls, assess their relationship with cancer etiology and grade, metabolic abnormalities and liver dysfunction severity. Serum betatrophin and irisin concentrations were measured with commercially available ELISA kits in 69 cirrhotic patients with HCC, 24 patients with non-viral cirrhosis and 20 healthy volunteers. The severity of liver disfunction was assessed according to Child-Pugh (C-P) score, while HCC grade according to the Barcelona clinic liver cancer (BCLC) staging system. Serum betatrophin concentration was significantly higher (33.7 ± 13.4 versus 12.3 ± 2.0 ng/ml; P < 0.001), while serum irisin level significantly lower in HCC patients compared to controls (2.52 ± 1.14 versus 4.46 ± 1.34 μg/ml; P = 0.02). Betatrophin level was also significantly elevated among cirrhotic patients compared to healthy volunteers. More evident serum betatrophin increase was found in patients with viral disease (34.8 ± 12.9 versus 26.1 ± 13.8 ng/ml; P < 0.001). Serum irisin concentration was significantly decreased in more advanced HCC cases (stage A versus C according to BCLC: 3.4 ± 1.3 versus 1.89 ± 1.1 μg/ml; P = 0.02). Decline of serum irisin (A: 3.4 ± 1.2; B: 2.42 ± 0.8; C: 1.91 ± 1.19 μg/ml; P = 0.03) and up-regulation of serum betatrophin levels (A: 24.1 ± 13.8; B: 39.3 ± 11.4; C: 46.2 ± 9.4 ng/ml; P = 0.03) were observed in patients with more advanced cirrhosis according to C-P score. We concluded that betatrophin serum level increased in cirrhotic patients, compared to controls. Since there was no difference between cirrhotic patients with and without intercurrent HCC, we suppose it may have an influence on fibrosis development, however not hepatocarcinogensis. Irisin serum level decreased in HCC patients, especially with more advanced disease grade, and was inversely related to the severity of liver disfunction.

Evaluation of Glypican-3 Expression in Hepatocellular Carcinoma by Using IDEAL IQ Magnetic Resonance Imaging

To investigate the value of iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL IQ) and gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) for evaluating Glypican-3 (GPC3) expression in hepatocellular carcinoma (HCC). Seventy-six patients with histopathologic diagnosis of HCC were retrospectively included in this study. In all patients IDEAL IQ and Gd-EOB-DTPA-enhanced MRI were performed preoperatively using a 3 T MRI system. For an identical slice through the liver of each patient a region of interest was drawn on the tumor in the hepatobiliary phase image and copied to the R2* map and fat fraction map produced by IDEAL IQ. A Mann-Whitney U test was used to compare the region of interest values of R2*, fat fraction and uptake of Gd-EOB-DTPA values between patients with positive and negative GPC3 expression HCC. Receiver operating characteristic analysis was used to determine the diagnostic performances of each of the MRI parameters in evaluating GPC3 expression and histological grade in HCC. R2* value was significantly higher in cases of positive than negative GPC3 expression HCCs (p < 0.001), whereas there were no significant differences in fat fraction and uptake of Gd-EOB-DTPA between the 2 groups (both p > 0.05). R2* value had higher areas under receiver operating characteristic (0.881), sensitivity (85.96%), and specificity (84.21%) compared to the fat fraction and uptake of Gd-EOB-DTPA. R2* value yielded from IDEAL IQ could reliably predict GPC3 expression in HCC prior to surgery.

SPARC Negatively Correlates With Prognosis After Transarterial Chemoembolization and Facilitates Proliferation and Metastasis of Hepatocellular Carcinoma via ERK/MMP Signaling Pathways.

Background: Transarterial chemoembolization (TACE) represents a widely accepted treatment procedure for intermediate stage or unresectable hepatocellular carcinoma (HCC). However, few studies have evaluated serologic prognosis factors in patients with HCC before TACE. Secreted protein acidic and rich in cysteine (SPARC) is a matricellular glycoprotein affecting tumorigenesis and metastasis, and leading to poor prognosis in HCC. Therefore, to further explore the potential prognosis value of SPARC, the expression levels in the plasma of patients and its potential molecular mechanisms underlying the regulation of HCC were investigated in this study.Materials and Methods: The study population included 43 patients with HCC who underwent TACE. To evaluate the expression of SPARC in different grades of pathological tissues, the immunohistochemistry was performed on tissues from 89 patients with HCC. Lentiviral vectors carrying interference sequences, as well as vectors harboring the complete open reading frame of SPARC for the knockdown or overexpression of SPARC in HuH-7 or HepG2 cells, respectively, allowed us to determine the biological functions of SPARC in vitro and in vivo. We also evaluated the levels of phosphorylated extracellular signal-regulated kinases 1/2 (p-ERK1/2) and matrix metalloproteinases 2/9 (MMP2/9) activation.Results: The association between serum levels of SPARC and the survival at different TNM and Barcelona-Clinic Liver Cancer (BCLC) stages in patients with HCC undergoing TACE were evaluated. We observed a significant upregulation of SPARC in high grade HCC tissues, predicting unfavorable prognosis, and suggesting an important tumor-promoting effect of SPARC. Functional studies indicated that downregulation of SPARC contributed to the inhibition of proliferation and metastasis of HuH-7 cells in vitro, whereas its overexpression led to opposite phenotypes. Mechanistically, decreased expression of SPARC resulted in dephosphorylation of ERK1/2 and deactivation of MMP2/9, thereby inhibiting growth and metastasis of HCC. Importantly, low expression levels of SPARC inhibited the formation of subcutaneous tumors in nude mice.Conclusions: SPARC was found to facilitate proliferation and metastasis of HCC via modulation of the ERK1/2-MMP2/9 signaling pathways. Our research has provided a glimpse on the biological mechanism of SPARC and might contribute to the eventual treatment of liver cancer.

Diagnostic Value of Imaging Methods in the Histological Four Grading of Hepatocellular Carcinoma.

We attempted to establish an ultrasound (US) imaging-diagnostic system for histopathological grades of differentiation of hepatocellular carcinoma (HCC). We conducted a retrospective study of histopathologically confirmed 200 HCCs, classified as early (45 lesions), well- (31 lesions), moderately (68 lesions) or poorly differentiated (diff.) (56 lesions) HCCs. We performed grayscale US to estimate the presence/absence of halo and mosaic signs, Sonazoid contrast-enhanced US (CEUS) to determine vascularity (hypo/iso/hyper) of lesion in arterial and portal phase (PP), and echogenicity of lesion in post-vascular phase (PVP). All findings were of significance for the diagnosis of some (but not all) histological grades (p < 0.001–0.05). Combined findings with a relatively high diagnostic efficacy for early, poorly and moderately diff. HCC were a combination of absence of halo sign and isoechogenicity in PVP of CEUS (accuracy: 93.0%, AUC: 0.908), hypovascularity in PP (accuracy: 78.0%, area under the curve (AUC): 0.750), and a combination of isovascularity in PP and hypoechogenicity in PVP (accuracy: 75.0%, AUC: 0.739), respectively. On the other hand, neither any individual finding nor any combination of findings yielded an AUC of over 0.657 for the diagnosis of well-diff. HCC. Our study provides encouraging data on Sonazoid CEUS in the histological differential diagnosis of HCC, especially in early HCC, and the effectiveness of this imaging method should be further proved by prospective, large sample, multicenter studies.

The predictive value of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid enhanced MRI imaging features combined with quantitative parameters for the pathologic grading of hepatocellular carcinoma

Objective: To investigate the predictive value of gadolinium-ethoxybenzyl- diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI imaging features combined with quantitative parameters for the pathologic grading of hepatocellular carcinoma (HCC). Methods: Eighty patients (65 males, 15 females; range 30-74 years,average age (59±11) years old) with HCC who underwent curative resection or biopsy from June 2016 to June 2019 in the First Affiliated Hospital of Soochow University after Gd-EOB-DTPA-enhanced MRI were evaluated retrospectively.According to the pathological results of the postoperative pathology, eighty patients were divided into poorly differentiated group (26 cases, 22 males, 4 females) and moderately-well differentiated group (54 cases, 43 males, 11 females). In Gd-EOB-DTPA-enhanced MRI, qualitative parameters were assessed. Quantitative parameters including tumor size, tumor-to-liver signal intensity ratio(SIR) of arterial phase (AP), portal vein phase (PP), equilibrium phase (EP) and hepatobiliary phase (HBP), contrast enhancement ration AP (CER-AP)were measured and calculated. Clinical data and qualitative parameters between poorly differentiated group and moderately-well differentiated group were analyzed by using χ(2) test.Quantitative parameters were analyzed by using independent sample t test. Statistically significant qualitative parameters, quantitative parameters, qualitative combined with quantitative parameters and AFP combined with qualitative and quantitative parameters were included in binary logistic regression model. The receiver operating characteristic (ROC) curves were used to evaluate the diagnostic performance of the four prediction model for the pathologic grading of HCC. Results: There was a statistical difference between poorly differentiated group and moderately-well differentiated group in AFP, arterial peritumoral enhancement, arterial rim enhancement, peritumoral hypointensity on HBP and tumor signal (all P<0.05). In two groups, tumor size, SIR-AP and SIR-PP were (7.0±3.7) vs (3.9±2.4)cm,1.11±0.29 vs 1.31±0.32 and 0.89±0.21 vs 1.03±0.27 (all P<0.05). AUC of qualitative parameters, quantitative parameters, qualitative combined with quantitative parameters and AFP combined with qualitative and quantitative parameters were 0.805, 0.804, 0.855, 0.892.There was a statistical difference between qualitative parameters and qualitative combined with quantitative parameters in sensitivity(80.8% vs 92.3%, P<0.05). Conclusion: Gd-EOB-DTPA-enhanced MRI imaging features combined with quantitative parameters can be used to predict the pathologic grading of HCC preoperatively, which has a great applicative value.

The association between genomic variations and histological grade in hepatocellular carcinoma.

BackgroundHistological grade (HG) is an important prognostic factor for hepatocellular carcinoma. With the development of precision medicine, diagnosis with a sequencing technology has become increasingly accepted. It is vital to discuss their similarities and differences to bridge or improve the traditional HG diagnosis with the novel sequencing technique.MethodsA total of 658 tumor samples were collected from 602 Chinese hepatocellular carcinoma patients and sequenced for a panel of pan-cancer genes. Nucleotide usage bias, genomic variation-related scores, driver genes, and biological processes were compared among different HGs. These results were further verified using a cohort dataset from the Western population.ResultsGenomic variation subtypes, such as C>G substitution, maximum somatic allele frequency (MSAF), and TP53, and biological processes including “angiogenesis” and “regulation of homotypic cell-cell adhesion” were found to be significantly associated with HG in both Chinese and Western populations.ConclusionsThe association identified between genomic variation and HG could aid our understanding of HG as an important clinical measure, and potentially be used to predict HG for hepatocellular carcinoma.

RCC2 contributes to tumor invasion and chemoresistance to cisplatin in hepatocellular carcinoma.

Tumor metastasis and chemoresistance are the main causes of treatment failure and high mortality in hepatocellular carcinoma (HCC). Therefore, it is critical to clarify the biological action and potential mechanisms in HCC cells to develop novel therapeutics. The regulator of chromosome condensation 2 (RCC2), a component of the chromosomal passenger complex, was shown to have important roles in tumor development andradio-chemotherapyresistance.However, its role in theaggressive phenotypes and cisplatin (DDP)-resistance of HCC is not known. Therefore, this study aimed to investigate the role of RCC2 in HCC pathogenesis. Interestingly, we found that RCC2 was upregulated in HCC patient specimens and HCC cell lines and was correlated with the pathological grade of HCC. To evaluate the function of RCC2 in HCC cell,lentivirus vector-based shRNAs were transfected into HCC cells. Silencing RCC2 inhibited the HCC cell proliferation, migration, invasion, and increased the apoptosis rate upon DDP treatment. Further analysis showed that RCC2-mediated downregulation of the expression of survival proteins occurred via the AKTand Bcl2pathways.Our results suggest that RCC2 might act as an oncogenic protein promoting metastatic behaviors andcisplatinresistancein HCC cells, and thereby could be a potential prognostic biomarker and therapeutic target for HCC.

HMex-3A is associated with poor prognosis and contributes to the progression of hepatocellular carcinoma

BackgroundHMex-3A, an RNA-binding protein, was found to be associated with tumorigenesis. However, the roles of hMex-3A in hepatocellular carcinoma (HCC) progression remained unclear. MethodsThe different expression of hMex-3A between HCC tissues and non-tumor tissues was evaluated using The Cancer Genome Atlas database. Thereafter, the hMex-3A expression was evaluated in HCC tissues using Western blotting and qRT-PCR. Immunohistochemistry was performed to investigate the association between hMex-3A level and clinicopathological features including prognosis in HCC patients. In addition, we used si-hMex-3A to knockdown hMex-3A in HCC cells to test Cell Counting Kit-8, colony formation, cell migration and invasion. ResultsThe hMex-3A expression was significantly elevated in HCC tissues. Analysis of the clinicopathological parameters suggested that hMex-3A expression was significantly associated with pathological grade (P = 0.019) and TNM stage (P = 0.001) in HCC. Moreover, univariate and multivariate Cox-regression analyses revealed that high hMex-3A expression (HR = 1.491, 95% CI: 1.107–2.007; P = 0.009) was an independent risk factor for overall survival in HCC patients. Finally, we confirmed that si-hMex-3A could significantly inhibit HCC cell proliferation, migration, and invasion in vitro. ConclusionsHMex-3A may contribute to the progression of HCC and might be used as a novel therapeutic target and prognostic marker in HCC.

Identification of 13 Key Genes Correlated With Progression and Prognosis in Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis.

Hepatocellular carcinoma (HCC) remains hard to diagnose early and cure due to a lack of accurate biomarkers and effective treatments. Hence, it is necessary to explore the tumorigenesis and tumor progression of HCC to discover new biomarkers for clinical treatment. We performed weighted gene co-expression network analysis (WGCNA) to explore hub genes that have high correlation with clinical information. In this study, we found 13 hub genes (GTSE1, PLK1, NCAPH, SKA3, LMNB2, SPC25, HJURP, DEPDC1B, CDCA4, UBE2C, LMNB1, PRR11, and SNRPD2) that have high correlation with histologic grade in HCC by analyzing TCGA LIHC dataset. All of these 13 hub genes could be used to effectively distinguish high histologic grade from low histologic grade of HCC through analysis of the ROC curve. The overall survival and disease-free survival information showed that high expression of these 13 hub genes led to poor prognosis. Meanwhile, these 13 hub genes had significantly different expression in HCC tumor and non-tumor tissues. We downloaded GSE6764, which contains corresponding clinical information, to validate the expression of these 13 hub genes. At the same time, we performed quantitative real-time PCR to validate the differences in the expression tendencies of these 13 hub genes between HCC tumor tissues and non-tumor tissues and high histologic grade and low histologic grade. We also explored mutation and methylation information of these 13 hub genes for further study. In summary, 13 hub genes correlated with the progression and prognosis of HCC were discovered by WGCNA in our study, and these hub genes may contribute to the tumorigenesis and tumor progression of HCC.

CCNB2, NUSAP1 and TK1 are associated with the prognosis and progression of hepatocellular carcinoma, as revealed by co-expression analysis.

The mortality rate associated with hepatocellular carcinoma (HCC) is the third highest among all digestive system tumors. However, the causes of HCC development and the underlying mechanisms have remained to be fully elucidated. In the present bioinformatics study, genetic markers were identified and their association with HCC was determined. The mRNA expression datasets GSE87630, GSE74656 and GSE76427 were downloaded from the Gene Expression Omnibus (GEO) database. A total of 96 differentially expressed genes (DEGs) were screened from the 3 GEO datasets, including 25 upregulated and 71 downregulated genes. DEGs were uploaded to the database for Annotation, Visualization and Integrated Discovery to screen for enriched Gene Ontology terms in various categories and the Search Tool for the Retrieval of Interacting Genes/Proteins was used to identify the interactions and functions of the DEGs. A total of 3 genetic markers were identified in a stepwise pathway and functional analysis in a previous study. The association of the genetic markers with prognosis was analysed using the UALCAN online analysis tool. Regression analysis was also performed to identify the relationship between HCC grade and disease recurrence and the expression of genetic markers using The Cancer Genome Atlas HCC dataset. In addition, the expression of the 3 genetic markers in HCC tissues was determined using reverse transcription-quantitative PCR, the Oncomine database and the Human Protein Atlas database. The expression levels of the 3 genetic markers cyclin B2 (CCNB2), nucleolar and spindle-associated protein 1 (NUSAP1) and thymidine kinase 1 (TK1) were significantly correlated with each other and high mRNA expression of CCNB2 was significantly associated with poor overall survival of patients with HCC. Receiver operating characteristic curve analysis indicated that NUSAP1 and TK1 were capable of distinguishing between recurrent and non-recurrent HCC. Furthermore, CCNB2, NUSAP1 and TK1 were highly correlated with the HCC grade. It was also indicated that the mRNA expression of CCNB2, NUSAPA and TK1 was increased in primary HCC tissues when compared with that in adjacent tissues. The present study identified that the CCNB2, NUSAP1 and TK1 genes may serve as prognostic markers for HCC, and may be of value from the perspectives of basic research and clinical treatment of HCC.

Expression, immune infiltration and clinical significance of SPAG5 in hepatocellular carcinoma: A gene expression-based study.

Overexpression of sperm-associated antigen 5 (SPAG5) is a marker of poor prognosis in numerous tumors and is recognized as an index of tumor proliferation; however, its expression in liver cancer remains unclear. The Oncomine (https://www.oncomine.org) and Timer (https://cistrome.shinyapps.io/timer) databases were used to analyze the expression of SPAG5 in liver hepatocellular carcinoma (HCC) and normal liver tissues. The relationship between the expression of SPAG5 and immune infiltration of HCC was investigated using the Timer and GEPIA (http://gepia.cancer-pku.cn) databases, and the mechanism was analyzed using Gene Set Enrichment Analysis. A Kaplan-Meier Plotter (http://kmplot.com/analysis) was used to evaluate the effect of SPAG5 on the prognosis of patients with HCC. The results revealed that the SPAG5 expression level was positively correlated with the infiltration levels of CD8+ T cells, macrophages, neutrophils, and especially B cells and dendritic cells. In addition, SPAG5 expression was significantly associated with T cell exhaustion. The overall survival time, progression-free survival time, recurrence-free survival time and disease-specific survival time were significantly reduced for HCC patients with high SPAG5 expression (p < 0.01) and high expression of SPAG5 was significantly associated with a poor overall survival time and progression-free survival time of grade and stage II-III HCC (p < 0.05) but not with stage I HCC (p > 0.05). Additionally, the expression of SPAG5 is related to the p53 and cell cycle signal pathways. In conclusion, SPAG5 is not only a marker of immune infiltration and poor prognosis, but also a potential therapeutic target for liver cancer.