DNA topoisomerase IIα and Ki67 are prognostic factors in patients with hepatocellular carcinoma

Preoperative prediction of microvascular invasion classification in hepatocellular carcinoma based on clinical features and MRI parameters

Microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is a critical pathological factor and the degree of MVI influences treatment decisions and patient prognosis. The present study aimed to predict the MVI classification based on preoperative MRI features and clinical parameters. The present retrospective cohort study included 150 patients (training cohort, n=108; validation cohort, n=42) with pathologically confirmed HCC. Clinical and imaging characteristics data were collected from Shengli Oilfield Central Hospital (Dongying, China). Univariate and multivariate logistic regression analyses were conducted to assess the association of clinical variables and MRI parameters with MVI (grade M1 and M2) and the M2 classification. Nomograms were developed based on the predictive factors of MVI and the M2 classification. The discrimination capability, calibration and clinical usefulness of the nomograms were evaluated. Multivariate analysis revealed an association between the Lens culinaris agglutinin-reactive fraction of α-fetoprotein, protein induced by vitamin K absence-II and tumor margin and MVI-positive status, while peritumoral enhancement and tumor size were demonstrated to be marginal predictors, but were also included in the nomogram. However, among MVI-positive patients, only peritumoral hypointensity and tumor size were demonstrated to be risk factors for the M2 classification. The nomograms, incorporating these variables, exhibited a strong ability to discriminate between MVI-positive and MVI-negative patients with HCC in both the training and validation cohort [area under the curve (AUC), 0.877 and 0.914, respectively] and good performance in predicting the M2 classification in the training and validation cohorts (AUC, 0.720 and 0.782, respectively). Nomograms incorporating clinical parameters and preoperative MRI features demonstrated promising potential as straightforward and effective tools for predicting MVI and the M2 classification in patients with HCC. Such predictive tools could aid in the judicious selection of optimal clinical treatments.

Predicting Ki-67 expression in hepatocellular carcinoma: nomogram based on clinical factors and contrast-enhanced ultrasound radiomics signatures

PURPOSE

To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC).

METHODS

A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated.

RESULTS

Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram.

CONCLUSION

The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment.

Role of the Clinical Features and MRI Parameters on Ki-67 Expression in Hepatocellular Carcinoma Patients: Development of a Predictive Nomogram

PURPOSE

To develop a nomogram using clinical features and the MRI parameters for preoperatively predicting the expression of Ki-67 in patients with hepatocellular carcinoma (HCC).

METHODS

One hundred and forty patients (training cohorts: n = 108; validation cohorts: n = 32) with confirmed HCC were investigated. Mann-Whitney U test, independent sample t-test, and chi-squared test were used to analyze the continuous and categorical variables. Univariate and multivariate logistic regression analyses were performed to examine the clinical variables and parameters from MRI associated with Ki-67 expression. As a result, a nomogram was developed based on these associations in patients with HCC. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves.

RESULTS

In the training set, multivariable logistic regression analysis revealed that lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3) levels, protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels, and tumor shape were independent predictors for Ki-67 expression (p < 0.05). These three variables and the apparent diffusion coefficient (ADC) value were used to establish a nomogram, while the ADC value was found to be a marginal significant predictor. The model demonstrated a strong ability to discriminate Ki-67 expression in both the training and validation cohorts (AUC = 0.862, 0.877).

CONCLUSION

A non-invasive preoperative prediction method, which incorporates MRI variables and clinical features was developed, and showed effectiveness in evaluating Ki-67 expression in HCC patients.

Radiomic Analysis Based on Gd-EOB-DTPA Enhanced MRI for the Preoperative Prediction of Ki-67 Expression in Hepatocellular Carcinoma

RATIONALE AND OBJECTIVES

To develop and validate a random forest model based on radiomic features in Gd-EOB-DTPA enhanced MRI for predicting the Ki-67 expression in solitary HCC.

MATERIALS AND METHODS

This retrospective study analyzed 258 patients with solitary HCC. Significant clinicoradiological factors were identified through univariate and multivariate analyses for distinguishing HCC with high (>20%) and low (≤20%) Ki-67 expression. Radiomic features were extracted at Gd-EOB-DTPA enhanced MRI. The recursive feature elimination (RFE) strategy was employed to screen robust radiomic features, and the Random Forest (RF) algorithm was utilized to rank radiomic features and construct prediction models. The AUC, accuracy, precision, recall, and f1-score were used to evaluate the performance of RF models.

RESULTS

Multivariate analysis identified serum AFP level, tumor size, growth type, and peritumoral enhancement as independent predictors for HCC with high Ki-67 expression. The clinicoradiological-radiomic model that incorporated the clinicoradiological predictors and the top ten radiomic features outperformed the clinicoradiological model in the training set (AUCs 0.876 vs. 0.780; p < 0.001), though the test set did not have a statistical significance (AUCs 0.809 vs. 0.723; p = 0.123). The addition of clinicoradiological predictors did not yield a significant improvement in the performance of radiomic features in both sets (training, p = 0.692; test, p = 0.229). Decision curve analysis further confirmed the clinical utility of the RF models.

CONCLUSION

The RF models based on radiomic features of Gd-EOB-DTPA enhanced MRI achieved satisfactory performance in preoperatively predicting Ki-67 expression in HCC.

Radiomics analysis of R2* maps to predict early recurrence of single hepatocellular carcinoma after hepatectomy

Objectives

This study aimed to evaluate the effectiveness of radiomics analysis with R2* maps in predicting early recurrence (ER) in single hepatocellular carcinoma (HCC) following partial hepatectomy.

Methods

We conducted a retrospective analysis involving 202 patients with surgically confirmed single HCC having undergone preoperative magnetic resonance imaging between 2018 and 2021 at two different institutions. 126 patients from Institution 1 were assigned to the training set, and 76 patients from Institution 2 were assigned to the validation set. A least absolute shrinkage and selection operator (LASSO) regularization was conducted to operate a logistic regression, then features were identified to construct a radiomic score (Rad-score). Uni- and multi-variable tests were used to assess the correlations of clinicopathological features and Rad-score with ER. We then established a combined model encompassing the optimal Rad-score and clinical-pathological risk factors. Additionally, we formulated and validated a predictive nomogram for predicting ER in HCC. The nomogram's discrimination, calibration, and clinical utility were thoroughly evaluated.

Results

Multivariable logistic regression revealed the Rad-score, microvascular invasion (MVI), and α fetoprotein (AFP) level > 400 ng/mL as significant independent predictors of ER in HCC. We constructed a nomogram based on these significant factors. The areas under the receiver operator characteristic curve of the nomogram and precision-recall curve were 0.901 and 0.753, respectively, with an F1 score of 0.831 in the training set. These values in the validation set were 0.827, 0.659, and 0.808.

Conclusion

The nomogram that integrates the radiomic score, MVI, and AFP demonstrates high predictive efficacy for estimating the risk of ER in HCC. It facilitates personalized risk classification and therapeutic decision-making for HCC patients.

Clinical-Radiologic Morphology-Radiomics Model on Gadobenate Dimeglumine-Enhanced MRI for Identification of Highly Aggressive Hepatocellular Carcinoma: Temporal Validation and Multiscanner Validation

BACKGROUND

Highly aggressive hepatocellular carcinoma (HCC) is characterized by high tumor recurrence and poor outcomes, but its definition and imaging characteristics have not been clearly described.

PURPOSE

To develop and validate a fusion model on gadobenate dimeglumine-enhanced MRI for identifying highly aggressive HCC.

STUDY TYPE

Retrospective.

POPULATION

341 patients (M/F = 294/47) with surgically resected HCC, divided into a training cohort (n = 177), temporal validation cohort (n = 77), and multiscanner validation cohort (n = 87).

FIELD STRENGTH/SEQUENCE

3T, dynamic contrast-enhanced MRI with T1-weighted volumetric interpolated breath-hold examination gradient-echo sequences, especially arterial phase (AP) and hepatobiliary phase (HBP, 80-100 min).

ASSESSMENT

Clinical factors and diagnosis assessment based on radiologic morphology characteristics associated with highly aggressive HCCs were evaluated. The radiomics signatures were extracted from AP and HBP. Multivariable logistic regression was performed to construct clinical-radiologic morphology (CR) model and clinical-radiologic morphology-radiomics (CRR) model. A nomogram based on the optimal model was established. Early recurrence-free survival (RFS) was evaluated in actual groups and risk groups calculated by the nomogram.

STATISTICAL TESTS

The performance was evaluated by receiver operating characteristic curve (ROC) analysis, calibration curves analysis, and decision curves. Early RFS was evaluated by using Kaplan-Meier analysis. A P value <0.05 was considered statistically significant.

RESULTS

The CRR model incorporating corona enhancement, cloud-like hyperintensity on HBP, and radiomics signatures showed the highest diagnostic performance. The area under the curves (AUCs) of CRR were significantly higher than those of the CR model (AUC = 0.883 vs. 0.815, respectively, for the training cohort), 0.874 vs. 0.769 for temporal validation, and 0.892 vs. 0.792 for multiscanner validation. In both actual and risk groups, highly and low aggressive HCCs showed statistically significant differences in early recurrence.

DATA CONCLUSION

The clinical-radiologic morphology-radiomics model on gadobenate dimeglumine-enhanced MRI has potential to identify highly aggressive HCCs and non-invasively obtain prognostic information.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Intratumoral and peritumoral radiomics model based on abdominal ultrasound for predicting Ki-67 expression in patients with hepatocellular cancer

Background

Hepatocellular cancer (HCC) is one of the most common tumors worldwide, and Ki-67 is highly important in the assessment of HCC. Our study aimed to evaluate the value of ultrasound radiomics based on intratumoral and peritumoral tissues in predicting Ki-67 expression levels in patients with HCC.

Methods

We conducted a retrospective analysis of ultrasonic and clinical data from 118 patients diagnosed with HCC through histopathological examination of surgical specimens in our hospital between September 2019 and January 2023. Radiomics features were extracted from ultrasound images of both intratumoral and peritumoral regions. To select the optimal features, we utilized the t-test and the least absolute shrinkage and selection operator (LASSO). We compared the area under the curve (AUC) values to determine the most effective modeling method. Subsequently, we developed four models: the intratumoral model, the peritumoral model, combined model #1, and combined model #2.

Results

Of the 118 patients, 64 were confirmed to have high Ki-67 expression while 54 were confirmed to have low Ki-67 expression. The AUC of the intratumoral model was 0.796 (0.649-0.942), and the AUC of the peritumoral model was 0.772 (0.619-0.926). Furthermore, combined model#1 yielded an AUC of 0.870 (0.751-0.989), and the AUC of combined model#2 was 0.762 (0.605-0.918). Among these models, combined model#1 showed the best performance in terms of AUC, accuracy, F1-score, and decision curve analysis (DCA).

Conclusion

We presented an ultrasound radiomics model that utilizes both intratumoral and peritumoral tissue information to accurately predict Ki-67 expression in HCC patients. We believe that incorporating both regions in a proper manner can enhance the diagnostic performance of the prediction model. Nevertheless, it is not sufficient to include both regions in the region of interest (ROI) without careful consideration.

Gadoxetic acid-enhanced MRI combined with T1 mapping and clinical factors to predict Ki-67 expression of hepatocellular carcinoma

Objectives

To explore the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) combined with T1 mapping and clinical factors for Ki-67 expression in hepatocellular carcinoma (HCC).

Methods

A retrospective study was conducted on 185 patients with pathologically confirmed solitary HCC from two institutions. All patients underwent preoperative T1 mapping on gadoxetic acid-enhanced MRI. Patients from institution I (n = 124) and institution II (n = 61) were respectively assigned to the training and validation sets. Univariable and multivariable analyses were performed to assess the correlation of clinico-radiological factors with Ki-67 labeling index (LI). Based on the significant factors, a predictive nomogram was developed and validated for Ki-67 LI. The performance of the nomogram was evaluated on the basis of its calibration, discrimination, and clinical utility.

Results

Multivariable analysis showed that alpha-fetoprotein (AFP) levels > 20ng/mL, neutrophils to lymphocyte ratio > 2.25, non-smooth margin, tumor-to-liver signal intensity ratio in the hepatobiliary phase ≤ 0.6, and post-contrast T1 relaxation time > 705 msec were the independent predictors of Ki-67 LI. The nomogram based on these variables showed the best predictive performance with area under the receiver operator characteristic curve (AUROC) 0.899, area under the precision-recall curve (AUPRC) 0.946 and F1 score of 0.912; the respective values were 0.823, 0.879 and 0.857 in the validation set. The Kaplan-Meier curves illustrated that the cumulative recurrence probability at 2 years was significantly higher in patients with high Ki-67 LI than in those with low Ki-67 LI (39.6% [53/134] vs. 19.6% [10/51], p = 0.011).

Conclusions

Gadoxetic acid-enhanced MRI combined with T1 mapping and several clinical factors can preoperatively predict Ki-67 LI with high accuracy, and thus enable risk stratification and personalized treatment of HCC patients.

Diffusion-Weighted Imaging as a Quantitative Imaging Biomarker for Predicting Proliferation Rate in Hepatocellular Carcinoma: Developing a Radiomics Nomogram

PURPOSE

This study aimed to explore the predictive performance of diffusion-weighted imaging with apparent diffusion coefficient map in predicting the proliferation rate of hepatocellular carcinoma and to develop a radiomics-based nomogram.

METHODS

This was a single-center retrospective study. A total of 110 patients were enrolled. The sample included 38 patients with low Ki67 expression (Ki67 ≤10%) and 72 with high Ki67 expression (Ki67 >10%) as demonstrated by surgical pathology. Patients were randomly divided into either a training (n = 77) or validation (n = 33) cohort. Diffusion-weighted imaging with apparent diffusion coefficient maps was used to extract radiomic features and the signal intensity values of tumor (SItumor), normal liver (SIliver), and background noise (SIbackground) from all samples. Subsequently, the clinical model, radiomic model, and fusion model (with clinical data and radiomic signature) were developed and validated.

RESULTS

The area under the curve (AUC) of the clinical model for predicting the Ki67 expression including serum α-fetoprotein level (P = 0.010), age (P = 0.015), and signal noise ratio (P = 0.026) was 0.799 and 0.715 in training and validation cohorts, respectively. The AUC of the radiomic model constructed by 9 selected radiomic features was 0.833 and 0.772 in training and validation cohorts, respectively. The AUC of the fusion model containing serum α-fetoprotein level (P = 0.011), age (P = 0.019), and rad score (P < 0.001) was 0.901 and 0.781 in training and validation cohorts, respectively.

CONCLUSIONS

Diffusion-weighted imaging as a quantitative imaging biomarker can predict Ki67 expression level in hepatocellular carcinoma across various models.

Protective Effects of Naringin-Dextrin Nanoformula against Chemically Induced Hepatocellular Carcinoma in Wistar Rats: Roles of Oxidative Stress, Inflammation, Cell Apoptosis, and Proliferation

Nanotechnology holds great promise for the development of treatments for deadly human diseases, such as hepatocellular carcinoma (HCC). In the current study, we compared the hepatoprotective effects of naringin-dextrin nanoparticles (NDNPs) against HCC in male Wistar rats with those of pure naringin and investigated the underlying cellular and molecular mechanisms. HCC was induced by intraperitoneal injection of diethylnitrosamine (DEN, 150 mg/kg body weight (b.w.) per week) for two weeks, followed by oral administration of 2-acetylaminofluorene (2AAF, 20 mg/kg b.w.) four times per week for three weeks. DEN/2AAF-administered rats were divided into three groups that respectively received 1% carboxymethyl cellulose (as vehicle), 10 mg/kg b.w. naringin, or 10 mg/kg b.w. NDNP every other day by oral gavage for 24 weeks. Both naringin and NDNP significantly attenuated the harmful effects of DEN on liver function. Both compounds also suppressed tumorigenesis as indicated by the reduced serum concentrations of liver tumor markers, and this antitumor effect was confirmed by histopathological evaluation. Additionally, naringin and NDNP prevented DEN-induced changes in hepatic oxidative stress and antioxidant activities. In addition, naringin and NDNP suppressed inflammation induced by DEN. Moreover, naringin and NDNP significantly reduced the hepatic expression of Bcl-2 and increased Bax, p53, and PDCD5 expressions. Naringin and NDNP also reduced expression of IQGAP1, IQGAP3, Ras signaling, and Ki-67 while increasing expression of IQGAP2. Notably, NDNP more effectively mitigated oxidative stress and inflammatory signaling than free naringin and demonstrated improved antitumor efficacy, suggesting that this nanoformulation improves bioavailability within nascent tumor sites.

Nomogram development and validation to predict Ki-67 expression of hepatocellular carcinoma derived from Gd-EOB-DTPA-enhanced MRI combined with T1 mapping

Objective

As an important biomarker to reflect tumor cell proliferation and tumor aggressiveness, Ki-67 is closely related to the high early recurrence rate and poor prognosis, and pretreatment evaluation of Ki-67 expression possibly provides a more accurate prognosis assessment and more better treatment plan. We aimed to develop a nomogram based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) combined with T1 mapping to predict Ki-67 expression in hepatocellular carcinoma (HCC).

Methods

This two-center study retrospectively enrolled 148 consecutive patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI T1 mapping and surgically confirmed HCC from July 2019 to December 2020. The correlation between quantitative parameters from T1 mapping, ADC, and Ki-67 was explored. Three cohorts were constructed: a training cohort (n = 73) and an internal validation cohort (n = 31) from Shunde Hospital of Southern Medical University, and an external validation cohort (n = 44) from the Sixth Affiliated Hospital, South China University of Technology. The clinical variables and MRI qualitative and quantitative parameters associational with Ki-67 expression were analyzed by univariate and multivariate logistic regression analyses. A nomogram was developed based on these associated with Ki-67 expression in the training cohort and validated in the internal and external validation cohorts.

Results

T1rt-Pre and T1rt-20min were strongly positively correlated with Ki-67 (r = 0.627, r = 0.607, P < 0.001); the apparent diffusion coefficient value was moderately negatively correlated with Ki-67 (r = -0.401, P < 0.001). Predictors of Ki-67 expression included in the nomogram were peritumoral enhancement, peritumoral hypointensity, T1rt-20min, and tumor margin, while arterial phase hyperenhancement (APHE) was not a significant predictor even included in the regression model. The nomograms achieved good concordance indices in predicting Ki-67 expression in the training and two validation cohorts (0.919, 0.925, 0.850), respectively.

Conclusions

T1rt-Pre and T1rt-20min had a strong positive correlation with the Ki-67 expression in HCC, and Gd-EOB-DTPA enhanced MRI combined with T1 mapping-based nomogram effectively predicts high Ki-67 expression in HCC.

TOP2A inhibition reverses drug resistance of hepatocellular carcinoma to regorafenib

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death attributed to high frequency of metastasis and multiple drug resistance. We aim to examine the underlying molecular mechanism and to seek potential strategies to reverse primary/acquired resistance to regorafenib. Topoisomerase IIα (TOP2A) is critical for tumorigenesis and carcinogenesis. Clinically, high-TOP2A expression was correlated to shorter overall survival (OS) of patients, but its role in drug resistance of HCC remains unknown. Here, we screened the expression profiling of TOP2A in HCC and identified TOP2A as an upregulated gene involved in the resistance to regorafenib. Sustained exposure of HCC cells to regorafenib could upregulate the expression of TOP2A. Silencing TOP2A enhanced HCC cells' sensitivity to regorafenib. TOP2A inhibition by doxorubicin or epirubicin synergized with regorafenib to suppress the growth of sorafenib-resistant HCC tumors that possessed the sorafenib-resistant features both in vitro and in vivo. Thus, targeting TOP2A may be a promising therapeutic strategy to alleviate resistance to regorafenib and thus improving the efficacy of HCC treatment.

Exploring pathological signatures for predicting the recurrence of early-stage hepatocellular carcinoma based on deep learning

Background

Postoperative recurrence impedes the curability of early-stage hepatocellular carcinoma (E-HCC). We aimed to establish a novel recurrence-related pathological prognosticator with artificial intelligence, and investigate the relationship between pathological features and the local immunological microenvironment.

Methods

A total of 576 whole-slide images (WSIs) were collected from 547 patients with E-HCC in the Zhongshan cohort, which was randomly divided into a training cohort and a validation cohort. The external validation cohort comprised 147 Tumor Node Metastasis (TNM) stage I patients from The Cancer Genome Atlas (TCGA) database. Six types of HCC tissues were identified by a weakly supervised convolutional neural network. A recurrence-related histological score (HS) was constructed and validated. The correlation between immune microenvironment and HS was evaluated through extensive immunohistochemical data.

Results

The overall classification accuracy of HCC tissues was 94.17%. The C-indexes of HS in the training, validation and TCGA cohorts were 0.804, 0.739 and 0.708, respectively. Multivariate analysis showed that the HS (HR= 4.05, 95% CI: 3.40-4.84) was an independent predictor for recurrence-free survival. Patients in HS high-risk group had elevated preoperative alpha-fetoprotein levels, poorer tumor differentiation and a higher proportion of microvascular invasion. The immunohistochemistry data linked the HS to local immune cell infiltration. HS was positively correlated with the expression level of peritumoral CD14+ cells (p= 0.013), and negatively with the intratumoral CD8+ cells (p&lt; 0.001).

Conclusions

The study established a novel histological score that predicted short-term and long-term recurrence for E-HCCs using deep learning, which could facilitate clinical decision making in recurrence prediction and management.

Nomogram Based on CT Radiomics Features Combined With Clinical Factors to Predict Ki-67 Expression in Hepatocellular Carcinoma

Objectives

The study developed and validated a radiomics nomogram based on a combination of computed tomography (CT) radiomics signature and clinical factors and explored the ability of radiomics for individualized prediction of Ki-67 expression in hepatocellular carcinoma (HCC).

Methods

First-order, second-order, and high-order radiomics features were extracted from preoperative enhanced CT images of 172 HCC patients, and the radiomics features with predictive value for high Ki-67 expression were extracted to construct the radiomic signature prediction model. Based on the training group, the radiomics nomogram was constructed based on a combination of radiomic signature and clinical factors that showed an independent association with Ki-67 expression. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to verify the performance of the nomogram.

Results

Sixteen higher-order radiomic features that were associated with Ki-67 expression were used to construct the radiomics signature (AUC: training group, 0.854; validation group, 0.744). In multivariate logistic regression, alfa-fetoprotein (AFP) and Edmondson grades were identified as independent predictors of Ki-67 expression. Thus, the radiomics signature was combined with AFP and Edmondson grades to construct the radiomics nomogram (AUC: training group, 0.884; validation group, 0.819). The calibration curve and DCA showed good clinical application of the nomogram.

Conclusion

The radiomics nomogram developed in this study based on the high-order features of CT images can accurately predict high Ki-67 expression and provide individualized guidance for the treatment and clinical monitoring of HCC patients.

Noninvasively predict the micro-vascular invasion and histopathological grade of hepatocellular carcinoma with CT-derived radiomics

Objectives

Methods

Results

Conclusion

Prognostic significance and oncogene function of cathepsin A in hepatocellular carcinoma

Cathepsin A (CTSA) is a lysosomal protease that regulates galactoside metabolism. The previous study has shown CTSA is abnormally expressed in various types of cancer. However, rarely the previous study has addressed the role of CTSA in hepatocellular carcinoma (HCC) and its prognostic value. To study the clinical value and potential function of CTSA in HCC, datasets from the Cancer Genome Atlas (TCGA) database and a 136 HCC patient cohort were analyzed. CTSA expression was found to be significantly higher in HCC patients compared with normal liver tissues, which was supported by immunohistochemistry (IHC) validation. Both gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that CTSA co-expressed genes were involved in ATP hydrolysis coupled proton transport, carbohydrate metabolic process, lysosome organization, oxidative phosphorylation, other glycan degradation, etc. Survival analysis showed a significant reduction both in overall survival (OS) and recurrence-free survival (RFS) of patients with high CTSA expression from both the TCGA HCC cohort and 136 patients with the HCC cohort. Furthermore, CTSA overexpression has diagnostic value in distinguishing between HCC and normal liver tissue [Area under curve (AUC) = 0.864]. Moreover, Gene set enrichment analysis (GSEA) showed that CTSA expression correlated with the oxidative phosphorylation, proteasome, and lysosome, etc. in HCC tissues. These findings demonstrate that CTSA may as a potential diagnostic and prognostic biomarker in HCC.

Evaluation of the Therapeutic Effect of Adjuvant Transcatheter Arterial Chemoembolization Based on Ki67 After Hepatocellular Carcinoma Surgery

Background and aims

This study aimed to determine the relationship between Ki67 expression and the efficacy of postoperative adjuvant transcatheter arterial chemoembolization (PA-TACE) in patients with hepatocellular carcinoma.

Methods

The Kaplan-Meier method was used to analyze the recurrence-free survival (RFS) and overall survival (OS) rates between the sub-groups in the ki67 low expression group and the ki67 high expression group and analyze the relationship between the expression of Ki67 and the efficacy of TACE.

Results

After PSM, there was no significant difference in the RFS and OS between the surgery + TACE and surgery subgroups after 1, 2, or 3 years (RFS: 63.9%, 55.6%, and 42.9% vs. 83.3%, 63.9%, and 55.6%, respectively, P = 0.279; OS: 91.7%, 83.3%, and 74.3% vs. 91.7%, 88.9%, and 71.4%, respectively, P = 0.890) in the Ki67 low-expression group. The RFS and OS were higher in the surgery + TACE subgroup than the surgery subgroup after 1, 2, and 3 years (RFS: 80.0%, 77.5%, and 69.2% vs. 53.5%, 39.5%, and 32.6%, respectively, P<0.001; OS: 97.5%, 85.0%, and 79.5% vs. 79.1%, 48.8%, and 42.9%, respectively, P = 0.001) in the Ki67 high expression group. The RFS was higher in the Ki67 high-expression subgroup than the low-expression subgroup after 1, 2, and 3 years, and OS had no significant difference (RFS: 80.0%, 79.5%, and 69.2% vs. 67.4%, 56.5%, and 46.7%, respectively, P = 0.035; OS: 97.5%, 85.0%, and 79.5% vs. 93.5%, 82.6%, and 75.6%, respectively, P = 0.665) in the surgery + TACE group.

Conclusions

For patients with hepatocellular carcinoma and high expression of Ki67 (Ki67≥20%), adjuvant hepatic artery chemoembolization after radical liver tumor resection effectively reduced the probability of tumor recurrence after surgery and prolonged the OS of patients. High Ki67 expression during the post-operative follow-up evaluation of hepatocellular carcinoma patients is an indicator for adjuvant TACE therapy.

MiR-195-3p inhibits cell proliferation in cervical cancer by targeting BCDIN3D

BACKGROUND

Cervical cancer (CC) is one of the most prevailing cancers among females. Accumulated studies concentrated on the regulatory role of micro RNA in cancers. This research is to explore the potential role of mir-195-3p in cervical cancer progression.

METHODS

Bioinformatics tools were used to investigate differential expression of mir-195-3p and BCDIN3D in cervical cancer. RNA expression patterns of both mir-195-3p and BCDIN3D were detected by RT-PCR in CC cell lines. The protein expression of BCDIN3D was measured by Western Blot. Hela and Siha cell lines were transfected with mir-195-3p inhibitors, mir-195-3p mimics and BCDIN3D si-RNA, si-NC. Luciferase reporter assays were adopted to confirm the binding. The interplays between mir-195-3p and BCDIN3D were explored in CC cell lines. CCK-8 assays checked how mir-195-3p regulated cell proliferation and Ki67 was examined by Western blot for its protein expressions as a biomarker for CC cell proliferation.

RESULTS

MiR-195-3p was downregulated while BCDIN3D was upregulated in cervical cancer cell lines. The binding was confirmed via Luciferase Assay. RT-PCR suggested that upregulation of mir-195-3p inhibited BCDIN3D and downregulation of BCDIN3D in return induced mir-195-3p. CCK-8 pointed out that overexpression of mir-195-3p inhibited the cell viability. Ki67 protein expression was inhibited by miR-195-3p mimics or silence of BCDIN3D.

CONCLUSION

The present research led us to a conclusion that mir-195-3p might inhibit cervical cancer cell proliferation and was reversely regulated by BCDIN3D. This suggests that miR-195-3p mimics/ BCDIN3D si-RNA might be used in the treatments of cervical cancer in the future after various animal assays and clinical trials.

Selenoprotein P inhibits cell proliferation and ROX production in HCC cells

Selenoprotein P (SEPP1) is a kind of secretory glycoproteins with an antioxidant effect during the development of some diseases. In this study, we attempted to observe the expression of SEPP1 in livers from the patients with hepatocellular carcinoma (HCC) and explore its effect on HCC cells. All the tissues from patients with HCC were obtained from Affiliated Hospital of Nantong University. Western blot and immunohistochemical results showed that SEPP1 was reduced in HCC liver tissues. Its expression was negatively correlated with Ki67 expression in tissues. The expression of SEPP1 in normal liver cell line was significantly higher than those in the liver cancer cell lines. Serum starvation and release experiment demonstrated that SEPP1 expression was reduced and PCNA expression was increased, when the serum was re-added into cell culture system and the cells were on a proliferation state. After SEPP1 over-expression plasmid was transfected into HepG2 cells, cell proliferation of HepG2 cells and PCNA expression level were all inhibited by SEPP1. Results obtained via 8-isoprostane ELISA further indicated that inhibited ROS level was found in HepG2 cells transfected with SEPP1 over-expression plasmid. In addition, RT-qPCR results demonstrated that GPX1 expression levels increased in HepG2 cells transfected with SEPP1 over-expression plasmid. In conclusion, SEPP1 may inhibit the proliferation of HCC cells, accompanied by the reduction of ROS production and the increasing of GPX1 expression.

Sorafenib and Mesenchymal Stem Cell Therapy: A Promising Approach for Treatment of HCC

Hepatocellular carcinoma (HCC) is the fifth most commonly diagnosed cancer and the second most common cause of cancer-related death worldwide. Sorafenib (Sora) is used as a targeted therapy for HCC treatment. Mesenchymal stem cells (MSCs) are applied as a new approach to fight malignancies. Drug resistance and side effects are the major concerns with Sora administration. The effect of using the combination of sorafenib and MSCs on tumor regression in xenograft HCC models was evaluated in this study. Methods and Materials. Human hepatocellular carcinoma cell lines (HepG2) were subcutaneously implanted into the flank of 18 nude mice. The animals were randomly divided into six groups (n = 3); each received Sora (oral), MSCs (IV injection), MSCs (local injection), Sora + MSCs (IV injection), Sora + MSCs (local injection), or no treatment (the control group). Six weeks after tumor implantation, the mice were scarified and tumoral tissues were resected in their entirety. Histopathological and immunohistochemical evaluations were used to measure tumor proliferation and angiogenesis. Apoptotic cells were quantified using the TUNEL assay. Results. No significant difference was found in the tumor grade among the treatment groups. Differentiation features of the tumoral cells were histopathologically insignificant in all the groups. Tumor necrosis was highest in the hpMSC (local) + Sora group. Tumor cell proliferation was reduced in hpMSC (local) + Sora-treated and hpMSC (IV) + Sora-treated mice compared with the other groups. Apoptotic-positive cells occupied a greater proportion in the Sora, hpMSC (IV) + Sora, and hpMSC (local) + Sora groups. Conclusion. A combination of chemotherapy and MSC can yield to more favorable results in the treatment of HCC.

Preoperative prediction of hepatocellular carcinoma with highly aggressive characteristics using quantitative parameters derived from hepatobiliary phase MR images

Background

To prospectively determine whether the quantitative imaging parameters derived from the hepatobiliary phase (HBP) can be used for the preoperative prediction of hepatocellular carcinoma (HCC) with highly aggressive characteristics.

Methods

One hundred and three patients with surgical-proven HCC were included from July 2015 to June 2018. Two independent reviewers measured signal intensity (SI) of liver and tumor, and quantitative parameters, including relative tumor enhancement (RTE), tumor to liver contrast ratio (TLR), tumor enhancement index (TEI), and relative enhancement ratio (RER) were calculated. The aggressive characteristics of HCC were identified by using the Ki-67 labeling index (LI), and patients were classified into low aggressive (Ki-67 LI ≤10%) and high aggressive (Ki-67 LI >10%) groups. The difference of quantitative parameters between two groups was assessed, and the correlation between quantitative parameters and Ki-67 LI was explored. Receiver operating characteristic analyses was used to evaluate the predictive performance of quantitative parameters.

Results

The values of RTE, TLR, TEI, and RER, were significantly lower in the highly aggressive group than low aggressive group (P<0.05), and negative correlations were obtained between these quantitative parameters and Ki-67 LI (r ranges from -0.41 to -0.22, P<0.05). TLR demonstrated the highest predictive performance with the area under curve (AUC) of 0.83 [95% confidence interval (CI): 0.75-0.90], sensitivity of 89.0% and specificity of 63.3%, and subsequent with RER, TEI, and RTE with AUC of 0.78 (95% CI: 0.68-0.85), 0.74 (95% CI: 0.64-0.82) and 0.68 (95% CI: 0.58-0.77), respectively. Good inter-observer and intra-observer agreement were found in all parameters.

Conclusions

TLR showed the highest predictive performance in highly aggressive HCC. Quantitative parameters based on HBP could preoperatively predict the aggressiveness of HCC.

Hepatocellular carcinoma in non-alcoholic fatty liver disease (NAFLD) - pathological evidence for a predominance of steatohepatitic inflammatory non-proliferative subtype

OBJECTIVES

This study evaluated clinical and pathological aspects of patients with hepatocellular carcinoma (HCC) secondary to non-alcoholic fatty liver disease (NAFLD) and related these factors to immunohistochemical markers representative of the proliferative class.

METHODS

We evaluated 35 HCC nodules from 21 patients diagnosed with NAFLD undergoing liver resection (n=12) or liver transplantation (n=8) or both (n=1). Demographic, clinical and biochemical data were compared to histological features and to immunohistochemical reactivity for K19 and Ki-67.

RESULTS

Cirrhosis was present in 58% of patients. Ages ranged from 50 to 77 years. Sixteen patients (76%) were male and had type 2 diabetes mellitus, 81% had arterial hypertension, and 90% had BMI above 25 kg/m². Alpha-fetoprotein levels were normal in 62% of patients. Twenty-five (70%) nodules were diagnosed as "steatohepatitic HCC". Only 32% of the nodules presented high levels of Ki-67 (>10%) and/or K19 (>5%), although 63% were poorly differentiated (G.3/G.4) according to Edmondson & Steiner grading system. K19 positivity (>5%) was associated with higher degree of intratumoral inflammation (G.2/G.3), and with fibrosis, both at the center of the tumor and at the tumor front, whereas Ki-67 positivity (>10%) was associated with ballooning of neoplastic cells and occurred in more than 70% in non-cirrhotic patients.

CONCLUSION

NAFLD-related HCC was found in non-cirrhotic patients in 42% of cases, alpha-fetoprotein level was normal in 63% and "steatohepatitic HCC" was the predominant histological type. Immunoexpression of K19 and/or Ki-67 occurred in 32% of the nodules and were associated with intratumoral inflammation and ballooning, suggesting that HCC in MtS may be preferentially "an inflammatory, non-proliferative subtype of HCC".

Prognostic value and oncogene function of heterogeneous nuclear ribonucleoprotein A1 overexpression in HBV-related hepatocellular carcinoma

Previous study has shown heterogeneous nuclear ribonucleoprotein A1(HNRNPA1) is highly expressed in various human cancers. In order to study the clinical value and potential function of HNRNPA1 in HBV-related hepatocellular carcinoma (HCC), three datasets from the GEPIA, GEO and TCGA were analyzed. HNRNPA1 expression was found to be significantly higher in HBV-positive HCC samples, which was supported with IHC validation. Both GO and KEGG analyses demonstrated that HNRNPA1 co-expressed genes were involved in translation, ribonucleoprotein complex biogenesis and assembly, ribosome biogenesis, RNA processing, RNA splicing, etc. Survival analysis showed a significant reduction in overall survival of patients with high HNRNPA1 expression from both the GSE14520 cohort and 151 patients with HBV-related HCC cohort. Furthermore, Gene set enrichment analysis (GSEA) revealed that HNRNPA1 may regulate HCC progression by influencing the cell cycle and WNT signaling pathway, etc. HNRNPA1 overexpression has diagnostic value in distinguishing between HCC and non-HCC liver tissue (AUC = 0.730). Finally, HNRNPA1 was a directly target gene of miR-22 manifested by the reduced luciferase activity and decreased HNRNPA1 expression in the cells with overexpression of miR-22. HNRNPA1 might function as an oncogene through the EGFR signaling pathway in HBV-related HCC, which has not been reported in previous studies.

Aquaporin 5 expression correlates with tumor multiplicity and vascular invasion in hepatocellular carcinoma

Aquaporins (AQPs) are a family of water channel transmembrane proteins that play a key role in transcellular water movement and transport. Recent studies have reported that AQPs are involved in cancer biology and can be a novel biomarker for predicting prognosis. The aim of this study was to identify clinical significance and prognostic impact of AQP5 in surgically resected hepatocellular carcinomas (HCCs). We analyzed the association between the expression of AQP5, Ki-67, and E-cadherin. Immunohistochemical stains for AQP5, KI-67, and E-cadherin were performed on 72 surgically resected HCCs. As a result, 46 patients (63.9%) showed AQP5 expression, 46 patients (63.9%) revealed high expression of Ki-67, and E-cadherin loss was identified in 8 patients (11.1%). No significant relationship among the three markers was found (all P > 0.05). AQP5 expression was associated with tumor multiplicity (P = 0.039), microvascular invasion (P = 0.040), and major vessel invasion (P = 0.044). High expression of Ki-67 was related to high serum AFP level (P = 0.006), tumor grade (P = 0.002), and microvascular invasion (P = 0.040). AQP5 expression tended to be associated with worse overall survival (OS) (P = 0.093) in the univariate analysis, but no significance was found in the multivariate survival analysis. High expression of Ki-67 was associated with shorter recurrence-free survival (RFS) in both univariate (P = 0.012) and multivariate analysis (P = 0.020). In conclusion, AQP5 might be a prognostic marker in HCC based on its association with tumor multiplicity, microvascular invasion, and major vessel invasion; and Ki-67 is an independent prognostic factor in HCC.

Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: A prospective study

Objective

To investigate the value of whole-lesion texture analysis on preoperative gadoxetic acid enhanced magnetic resonance imaging (MRI) for predicting tumor Ki-67 status after curative resection in patients with hepatocellular carcinoma (HCC).

Methods

This study consisted of 89 consecutive patients with surgically confirmed HCC. Texture features were extracted from multiparametric MRI based on whole-lesion regions of interest. The Ki-67 status was immunohistochemical determined and classified into low Ki-67 (labeling index ≤15%) and high Ki-67 (labeling index >15%) groups. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were applied for generating the texture signature, clinical nomogram and combined nomogram. The discrimination power, calibration and clinical usefulness of the three models were evaluated accordingly. Recurrence-free survival (RFS) rates after curative hepatectomy were also compared between groups.

Results

A total of 13 texture features were selected to construct a texture signature for predicting Ki-67 status in HCC patients (C-index: 0.878, 95% confidence interval: 0.791-0.937). After incorporating texture signature to the clinical nomogram which included significant clinical variates (AFP, BCLC-stage, capsule integrity, tumor margin, enhancing capsule), the combined nomogram showed higher discrimination ability (C-index: 0.936vs. 0.795, P<0.001), good calibration (P>0.05 in Hosmer-Lemeshow test) and higher clinical usefulness by decision curve analysis. RFS rate was significantly lower in the high Ki-67 group compared with the low Ki-67 group after curative surgery (63.27%vs. 85.00%, P<0.05).

Conclusions

Texture analysis on gadoxetic acid enhanced MRI can serve as a noninvasive approach to preoperatively predict Ki-67 status of HCC after curative resection. The combination of texture signature and clinical factors demonstrated the potential to further improve the prediction performance.

Prognostic value of heterogeneous ribonucleoprotein A1 expression and inflammatory indicators for patients with surgically resected hepatocellular carcinoma: Perspectives from a high occurrence area of hepatocellular carcinoma in China

Heterogeneous ribonucleoproteinA1 (hnRNPA1) is a documented tumor biomarker known to be aberrantly expressed in a number of types of human cancer. However, to the best of our knowledge, its prognostic value for surgically resected HCC (RHCC) in the high incidence areas of China has not been described; the association between hnRNPA1 expression, pre-operative neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) is also not understood. In the present study, hnRNPA1 expression was retrospectively measured in two independent cohorts of patients with hepatocellular carcinoma (HCC) who underwent surgery to remove the primary cancer at one center in Fujian, an area with a high incidence of HCC in China. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR), western blotting and immunohistochemistry (IHC) were used to quantify hnRNPA1 expression in RHCC tissues. The survival curves were plotted using the Kaplan-Meier method, and the prognostic significance of hnRNPA1, NLR and PLR was analyzed using the log-rank test. The relevant prognostic factors were identified by multivariate Cox regression analysis. RT-qPCR and western blotting revealed that hnRNPA1 was upregulated in HCC tissues (P<0.001), and particularly overexpressed in tumor tissues of patients with recurrent HCC (P<0.001) (cohort 1; 54 patients). Differential hnRNPA1 expression was measured in 426HCC tissues with IHC; 259 exhibited high hnRNPA1 expression and 167 exhibited low expression. High hnRNPA1 expression was significantly associated with Tumor-Node-Metastasis stage (P=0.024), tumor size (P=0.027), vascular invasion (P<0.001), Edmonson grade (P<0.001), pre-operative serum α-fetoprotein (AFP) (P<0.001), NLR (P<0.001) and PLR (P<0.001). In addition, multivariate Cox regression analysis confirmed that high hnRNPA1 expression was associated with relapse-free survival (RFS; HR, 0.685; 95% CI, 0.506-0.928; P=0.015) and overall survival (OS; HR, 0.629; 95% CI, 0.454-0.871; P=0.005). Multivariate analysis confirmed that higher pre-operative serum AFP had an unfavorable impact on RFS (HR, 1.350; 95% CI, 1.006-1.811; P=0.045) and OS (HR=1.564; 95% CI, 1.151-2.126; P=0.004), while higher pre-operative NLR had an unfavorable impact on OS (HR, 1.758; 95% CI, 1.161-2.661; P=0.008) (cohort 2;426 patients). The expression of hnRNPA1 was also positively correlated with NLR (Spearman's correlation; r=0.122, P=0.012) and PLR (Spearman's correlation; r=0.140, P=0.004). In conclusion, high hnRNPA1 expression was revealed as prognostic for poor survival in patients with RHCC, and detection of hnRNPA1 protein in tumor tissues demonstrated potential in estimating survival for patients with RHCC in areas with high incidence rates. Furthermore, the combination of high hnRNPA1 expression and pre-operative serum AFP levels (>400 µg) proved to be a good diagnostic and prognostic biomarker for this specific population of patients. Finally, a correlation may also exist between hnRNPA1 expression and other markers of systemic inflammation.