A model combining TNM stage and tumor size shows utility in predicting recurrence among patients with hepatocellular carcinoma after resection

Optimizing hepatocellular carcinoma disease staging systems by incorporating tumor micronecrosis: A multi-institutional retrospective study

Tumor micronecrosis is a pathological feature that reflects malignant biological behavior in hepatocellular carcinoma (HCC). However, whether micronecrosis can optimize HCC staging systems remains unilluminated. A total of 1632 HCC patients who underwent curative hepatectomy in four institutions from January 2014 to December 2021 were enrolled in this study. Independent prognostic factors were identified, and optimized staging models were established using a training cohort (n = 934). The performance of optimized staging models was validated using an external cohort consisting of cases from three other institutions (n = 232). In addition, patients from our prospectively collected database (n = 379) tested the application effectiveness of the models. Harrel's c-statistics and the corrected Akaike information criterion (AICc) were used to assess the performance of staging models. In most of Barcelona Clinic Liver Cancer (BCLC) and tumor (T) stages, HCC patients with tumor micronecrosis showed poorer prognosis than those without. Tumor micronecrosis, microvascular invasion, multiple tumors and tumor size >2 cm were independent prognostic-related factors. The BCLC and T staging models incorporating tumor micronecrosis showed better performance than the original systems (c-statistic, 0.712 and 0.711 vs. 0.664 and 0.679; AICc, 2314.8 and 2322.3 vs. 2338.2 and 2338.1; respectively). Furthermore, the external validation cohort confirmed that the optimized staging models had improved efficiency compared with the original ones. Moreover, the prospective cohort demonstrated the applicability of the optimized staging systems. Tumor micronecrosis plays a stage-ascending role in HCC patients. The BCLC and T staging systems incorporating tumor micronecrosis can improve the prognosis stratification efficiency of patients.

Combination of Hepatitis B Virus Pre-S2 Gene Deletion Mutation and Tumor-Node-Metastasis Stage Predicts Higher Hepatocellular Carcinoma Recurrence after Curative Surgical Resection

Hepatocellular carcinoma (HCC) is one of the most frequent and life-threatening human cancers worldwide. Despite curative resection surgery, the high recurrence rate of HCC leads to poor patient survival. Chronic hepatitis B virus (HBV) infection is a major etiological factor for HCC. HBV pre-S2 gene deletion mutation leads to the expression of an important oncoprotein called a pre-S2 mutant. It represents an independent prognostic biomarker for HCC recurrence. This study aimed to identify other independent prognostic biomarkers from clinicopathological characteristics of 75 HBV-related HCC patients receiving resection surgery and to validate their potential to be combined with pre-S2 gene deletion mutation as a combination biomarker for HCC recurrence. Patients with both the presence of pre-S2 gene deletion mutation and tumor-node-metastasis (TNM) stage IIIA–IIIC had a higher HCC recurrence risk than patients with either one or none of these two factors. Moreover, the combination of pre-S2 gene deletion mutation and TNM stage exhibited better performance than either of these two factors alone in discriminating patients from patients without HCC recurrence. Collectively, this study proposed that the TNM stage held significance as a combination biomarker with pre-S2 gene deletion mutation with a greater performance in predicting HCC recurrence after curative surgical resection.

Construction of a Novel Clinical Stage-Related Gene Signature for Predicting Outcome and Immune Response in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) with high heterogeneity is one of the most frequent malignant tumors. However, there were no studies to create a clinical stage-related gene signature for HCC patients. Differentially expressed genes (DEGs) associated with clinical stage of HCC were analyzed based on TCGA datasets. Functional enrichment analysis was carried out by the use of stage-related DEGs. Then, the least absolute shrinkage and selection operator (LASSO) regression and univariate Cox regression were performed to reduce the overfit and the number of genes for further analysis. Next, survival and ROC assays were carried out to demonstrate the model using TCGA. Functional analysis and immune microenvironment analysis related to stage-related DEGs were performed. Reverse transcriptase polymerase chain reaction (RT-PCR) and Cell Counting Kit-8 (CCK-8) assays were applied to examine the expression and function of PNCK in HCC. In this research, there were 21 DEGs between HCC specimens with stage (I-II) and HCC specimens with stage (III-IV), including 20 increased genes and 1 decreased genes. A novel seven-gene signature (including PITX2, PNCK, GLIS1, SCNN1G, MMP1, ZNF488, and SHISA9) was created for the prediction of outcomes of HCC patients. The ROC curves confirmed the prognostic value of the new model. Cox assays demonstrated that the seven-gene signature can independently forecast overall survival. The immune analysis revealed that patients with low risk score exhibited more immune activities. Moreover, we confirmed that PNCK expressions were distinctly increased in HCC, and its silence suppressed the proliferation of HCC cells. Overall, our research offered a robust and reliable gene signature which displayed an important value in the prediction of overall survival of HCC patients and might deliver more effective personalized therapies.

Macrotrabecular-Massive Hepatocellular Carcinoma: Light and Shadow in Current Knowledge

The subject of this narrative review is macrotrabecular-massive hepatocellular carcinoma (MTM‐HCC). Despite their rarity, these tumours are of general interest because of their epidemiological and clinical features and for representing a distinct model of the interaction between the angiogenetic system and neoplastic cells. The MTM‐HCC subtype is associated with various adverse biological and pathological parameters (the Alfa-foetoprotein (AFP) serum level, tumour size, vascular invasion, and satellite nodules) and is a key determinant of patient prognosis, with a strong and independent predictive value for early and overall tumour recurrence. Gene expression profiling has demonstrated that angiogenesis activation is a hallmark feature of MTM-HCC, with overexpression of both angiopoietin 2 (ANGPT2) and vascular endothelial growth factor A (VEGFA).

5-year recurrence prediction after hepatocellular carcinoma resection: deep learning vs. Cox regression models

Deep learning algorithms have yet to be used for predicting clinical prognosis after cancer surgery. Therefore, this study compared performance indices and permutation importance of potential confounders in three models for predicting 5-year recurrence after hepatocellular carcinoma (HCC) resection: a deep-learning deep neural network (DNN) model, a recurrent neural network (RNN) model, and a Cox proportional hazard (CPH) regression model. Data for 725 patients who had received HCC resection at three medical centers in southern Taiwan between April, 2011, and December, 2015, were randomly divided into three datasets: a training dataset containing data for 507 subjects was used for model development, a testing dataset containing data for 109 subjects was used for internal validation, and a validating dataset containing data for 109 subjects was used for external validation. Feature importance analysis was also performed to identify potential predictors of recurrence after HCC resection. Univariate Cox proportional hazards regression analyses were performed to identify potential significant predictors of 5-year recurrence after HCC resection, which were included in the forecasting models (P < 0.05). All performance indices for the DNN model were significantly higher than those for the RNN model and the conventional CPH model (P < 0.001). The most important potential predictor of 5-year recurrence after HCC resection was surgeon volume followed by, in order of importance, hospital volume, preoperative Beck Depression Scale score, preoperative Beck Anxiety Scale score, co-residence with family, tumor stage, and tumor size. The feature importance analysis performed to investigate interpretability in this study elucidated the potential use of deep learning models for predicting recurrence after HCC resection and for identifying predictors of recurrence. Further experiments using the proposed DNN model would clarify its potential uses for developing, promoting, and improving health policies for treating HCC patients after surgery.

A Predictive Nomogram of Early Recurrence for Patients with AFP-Negative Hepatocellular Carcinoma Underwent Curative Resection

Background: Alpha-fetoprotein-negative (<20 ng/mL) hepatocellular carcinoma (AFP-NHCC) cannot be easily diagnosed in clinical practice, which may affect early treatment and prognosis. Furthermore, there are no reliable tools for the prediction of AFP-NHCC early recurrence that have been developed currently. The objective of this study was to identify the independent risk factors for AFP-NHCC and construct an individual prediction nomogram of early recurrence of these patients who underwent curative resection. Methods: A retrospective study of 199 patients with AFP-NHCC who had undergone curative resection and another 231 patients with AFP-positive HCC were included in case-controlled analyses. All AFP-NHCC patients were randomly divided into training and validation datasets at a ratio of 7:3. The univariate and multivariate Cox proportional hazards regression analyses were applied to identify the risk factors, based on which the predictive nomogram of early recurrence was constructed in the training dataset. The area under the curve (AUC), calibration curve, and decision curve was used to evaluate the predictive performance and discriminative ability of the nomogram, and the results were validated in the validation dataset. Results: Compared to AFP-positive patients, the AFP-negative group with lower values of laboratory parameters, lower tumor aggressiveness, and less malignant magnetic resonance (MR) imaging features. AST (HR = 2.200, p = 0.009), tumor capsule (HR = 0.392, p = 0.017), rim enhancement (HR = 2.825, p = 0.002) and TTPVI (HR = 5.511, p < 0.001) were independent predictors for early recurrence of AFP-NHCC patients. The nomogram integrated these independent predictors and achieved better predictive performance with AUCs of 0.89 and 0.85 in the training and validation datasets, respectively. The calibration curve and decision curve analysis both demonstrated better predictive efficacy and discriminative ability of the nomogram. Conclusions: The nomogram based on the multivariable Cox proportional hazards regression analysis presented accurate individual prediction for early recurrence of AFP-NHCC patients after surgery. This nomogram could assist physicians in personalized treatment decision-making for patients with AFP-NHCC.

Alpha-Fetoprotein Ratio Predicts Alpha-Fetoprotein Positive Hepatocellular Cancer Patient Prognosis after Hepatectomy

BACKGROUND

This study was conducted to investigate the effect of alpha-fetoprotein (AFP) ratio on the prognosis of AFP-positive hepatocellular carcinoma (HCC) patients after hepatectomy.

METHODS

We retrospectively included 879 HCC patients with AFP-positive who underwent hepatectomy from February 2012 to October 2017 and randomly divided into training cohort and validation cohort. AFP ratio was equal to the AFP level within one week before hepatectomy to AFP level within 20-40 days after surgery. The end point of follow-up was disease-free survival (DFS) and overall survival (OS).

RESULTS

AFP ratio was not associated with clinical characteristics in training cohort and validation cohort. According to the X-tile software, the optimum cut-off point was 17.8 for AFP ratio. Significant differences between AFP ratio high and AFP ratio low were observed in DFS and OS in both cohort (p < 0.05). Kaplan-Meier curves and receiver-operating curves were showed that AFP ratio was better than AFP level preoperation in predicting the prognosis of AFP-positive HCC patients after hepatectomy. The multivariate analysis demonstrated that AFP ratio was a significant independent risk factor for both OS and DFS in HCC patients with AFP-positive.

CONCLUSIONS

AFP ratio might be a prognosis predictor for HCC patients with AFP-positive after hepatectomy.

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

Objectives

Methods

Results

Conclusion

A Model Based on Artificial Intelligence Algorithm for Monitoring Recurrence of HCC after Hepatectomy

BACKGROUND

There is no satisfactory indicator for monitoring recurrence after resection of hepatocellular carcinoma (HCC). This retrospective study aimed to design and validate an HCC monitor recurrence (HMR) model for patients without metastasis after hepatectomy.

METHODS

A training cohort was recruited from 1179 patients with HCC without metastasis after hepatectomy between February 2012 and December 2015. An HMR model was developed using an AdaBoost classifier algorithm. The factors included patient age, TNM staging, tumor size, and pre/postoperative dynamic variations of alpha-fetoprotein (AFP). The diagnostic efficacy of the model was evaluated based on the area under the receiver operating characteristic curves (AUCs). The model was validated using a cohort of 695 patients.

RESULTS

In preoperative patients with positive or negative AFP, the AUC of the validation cohort in the HMR model was .8877, which indicated better diagnostic efficacy than that of serum AFP (AUC, .7348). The HMR model predicted recurrence earlier than computed tomography/magnetic resonance imaging did by 191.58 ± 165 days. In addition, the HMR model can predict the prognosis of patients with HCC after resection.

CONCLUSIONS

The HMR model established in this study is more accurate than serum AFP for monitoring recurrence after hepatectomy for HCC and can be used for real-time monitoring of the postoperative status in patients with HCC without metastasis.

Hepatocellular Carcinoma Staging: Differences Between Radiologic and Pathologic Systems and Relevance to Patient Selection and Outcomes in Liver Transplantation

Liver transplant is indicated with curative intent for patients with early-stage hepatocellular carcinoma (HCC). The radiologic T category is used to determine candidacy and priority of patients on the waiting list. After transplant, the explant liver pathologic TNM stage is used as a predictor of postoperative outcomes and overall prognosis. Although the comparison of radiologic and pathologic T categories for concordance is often considered to be straightforward, the staging conventions significantly differ. Not accounting for these differences is in part the reason for the high rates of radiologic-pathologic discordance reported in the literature, with inconsistent terminology being an additional source of confusion when evaluating concordance. These factors may affect the understanding of important radiopathologic phenotypes of disease and the adequate investigation of their prognostic capabilities. The aims of this article are to provide an overview of the pathologic and radiologic TNM staging systems for HCC while describing staging procedures, emphasize the differences between these staging systems to highlight the limitations of radiologic-pathologic stage correlation, present a review of the literature on the prognostic value of individual features used for HCC staging; and signal significant aspects of preoperative risk stratification that could be improved to positively impact posttransplant outcomes.

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Background

Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence.

Methods

The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database.

Results

Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group.

Conclusions

Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08827-z.

Expression pattern and prognostic value of N6-methyladenosine RNA methylation key regulators in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is still one of the most common malignancies worldwide. The accuracy of biomarkers for predicting the prognosis of HCC and the therapeutic effect is not satisfactory. N6-methyladenosine (m6A) methylation regulators play a crucial role in various tumours. Our research aims further to determine the predictive value of m6A methylation regulators and establish a prognostic model for HCC. In this study, the data of HCC from The Cancer Genome Atlas (TCGA) database was obtained, and the expression level of 15 genes and survival was examined. Then we identified two clusters of HCC with different clinical factors, constructed prognostic markers and analysed gene set enrichment, proteins’ interaction and gene co-expression. Three subgroups by consensus clustering according to the expression of the 13 genes were identified. The risk score generated by five genes divided HCC patients into high-risk and low-risk groups. In addition, we developed a prognostic marker that can identify high-risk HCC. Finally, a novel prognostic nomogram was developed to accurately predict HCC patients’ prognosis. The expression levels of 13 m6A RNA methylation regulators were significantly upregulated in HCC samples. The prognosis of cluster 1 and cluster 3 was worse. Patients in the high-risk group show a poor prognosis. Moreover, the risk score was an independent prognostic factor for HCC patients. In conclusion, we reveal the critical role of m6A RNA methylation modification in HCC and develop a predictive model based on the m6A RNA methylation regulators, which can accurately predict HCC patients’ prognosis and provide meaningful guidance for clinical treatment.

A new model based on gamma-glutamyl transpeptidase to platelet ratio (GPR) predicts prognostic outcome after curative resection of solitary hepatocellular carcinoma

BACKGROUND

This study intends to explore the potential clinical value of gamma-glutamyl transpeptidase to platelet ratio (GPR) and the new multi-factor scoring model for recurrence and prognosis prediction in solitary HCC patients who received radical resection.

METHODS

This study retrospectively analyzed 295 HCC patients after curative resection. According to the Receiver Operating Characteristic (ROC) curve, the optimal cut-off value of GPR for predicting prognosis of HCC after resection was determined. The Kaplan Meier method and Cox regression analysis were performed to assess the important potential factors in the prognosis of HCC and determine the independent risk factors. Assign a value to each independent risk factor and establish a new scoring model. Then, using GPR and the new scoring model to evaluate overall survival (OS) and postoperative recurrence probability.

RESULTS

When GPR's cut-off value was selected as 0.30, its predictive efficiency for postoperative prognosis was more favorable than those of other cut-off values (0.76, 0.84 and 0.94). GPR, tumor size, microvascular invasion and neutrophil to lymphocyte ratio (NLR) were identified as independent prognostic predictors. Using these variables, a novel prognostic scoring model was devised and established to identify different levels of risk: high, intermediate and low risk groups. We found that patients with high GPR level and of high risk group would have a poorer OS and a higher recurrence rate after radical resection.

CONCLUSIONS

GPR may serve as a promising predictor for postoperative prognosis and recurrence probability of HCC, and the new prognostic scoring model may be available for postoperative management among HCC patients.

A prognostic nomogram based on LASSO Cox regression in patients with alpha-fetoprotein-negative hepatocellular carcinoma following non-surgical therapy

Background

Alpha-fetoprotein-negative hepatocellular carcinoma (AFP-NHCC) (< 8.78 ng/mL) have special clinicopathologic characteristics and prognosis. The aim of this study was to apply a new method to establish and validate a new model for predicting the prognosis of patients with AFP-NHCC.

Methods

A total of 410 AFP-negative patients with clinical diagnosed with HCC following non-surgical therapy as a primary cohort; 148 patients with AFP-NHCC following non-surgical therapy as an independent validation cohort. In primary cohort, independent factors for overall survival (OS) by LASSO Cox regression were all contained into the nomogram1; by Forward Stepwise Cox regression were all contained into the nomogram2. Nomograms performance and discriminative power were assessed with concordance index (C-index) values, area under curve (AUC), Calibration curve and decision curve analyses (DCA). The results were validated in the validation cohort.

Results

The C-index of nomogram1was 0.708 (95%CI: 0.673–0.743), which was superior to nomogram2 (0.706) and traditional modes (0.606–0.629). The AUC of nomogram1 was 0.736 (95%CI: 0.690–0.778). In the validation cohort, the nomogram1 still gave good discrimination (C-index: 0.752, 95%CI: 0.691–0.813; AUC: 0.784, 95%CI: 0.709–0.847). The calibration curve for probability of OS showed good homogeneity between prediction by nomogram1 and actual observation. DCA demonstrated that nomogram1 was clinically useful. Moreover, patients were divided into three distinct risk groups for OS by the nomogram1: low-risk group, middle-risk group and high-risk group, respectively.

Conclusions

Novel nomogram based on LASSO Cox regression presents more accurate and useful prognostic prediction for patients with AFP-NHCC following non-surgical therapy. This model could help patients with AFP-NHCC following non-surgical therapy facilitate a personalized prognostic evaluation.

COCH predicts survival and adjuvant TACE response in patients with HCC

The aim of the present study was to measure the expression of Cochlin (COCH) and analyze its association with survival, recurrence and the benefits from adjuvant transarterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC) following hepatectomy. Patients with high COCH expression levels had a poorer prognosis in terms of overall and disease-free survival rate compared with those with low COCH expression levels. Further analysis revealed that patients with low COCH expression who received TACE experienced markedly lower early recurrence rates compared with those who did not receive TACE. However, patients with high COCH expression with and without adjuvant TACE after resection experienced no difference in disease recurrence rates. The expression of COCH was found to be associated with hepatitis B virus infection, portal vein tumor thrombosis and Barcelona Clinic Liver Cancer stage in HCC. Therefore, the findings of the present study indicated that clinical detection of COCH expression may help estimate the prognosis of patients with HCC, as well as determine whether to administer TACE after surgery to prevent recurrence.

Adjuvant Transarterial Chemoembolization for Barcelona Clinic Liver Cancer Stage A Hepatocellular Carcinoma After Hepatectomy

Introduction

The care for patients with hepatocellular carcinoma (HCC) is challenging. This study is to evaluate the effect of adjuvant transarterial chemoembolization (TACE) for Barcelona Clinic Liver Cancer (BCLC) stage A HCC patients after hepatectomy.

Methods

Consecutive HCC patients with BCLC stage A, treated by hepatectomy alone (HA) or hepatectomy with TACE (HT), were retrospectively enrolled. Propensity score matching (PSM) was used to balance baseline differences. The recurrence-free survival (RFS) and overall survival (OS) were evaluated using the Kaplan-Meier. The impact of TACE on survival outcome was determined by Cox hazard regression.

Results

After PSM, 230 patients (115 HT and 115 HA) were enrolled in the analysis. The 1-, 3-, and 5-year RFS rates were 87.0, 63.5, and 50.4%, respectively, for the HT group, and 87.8, 67.0, and 58.3% for the HA group. The OS rates at 1-, 3-, and 5-year were 99.1, 93.9, and 87%, respectively, for the HT group, and 100, 92.2, and 88.7% for the HA group. No significant differences were seen in either the RFS (log-rank test, χ² = 0.891, p = 0.345) or OS (log-rank test, χ² = 0.146, p = 0.702) between the specific pairs of two groups. Cox regression identified that TACE was not the factor affecting RFS or OS (p = 0.399; HR 0.847; 95% CI 0.576–1.245 for RFS vs. p = 0.989; HR 0.995; 95% CI 0.471–2.100 for OS).

Conclusion

Our data indicate that TACE is not an effective intervention in the adjuvant setting for BCLC stage A HCC after hepatectomy.

Reveal the Regulation Patterns of Prognosis-Related miRNAs and lncRNAs Across Solid Tumors in the Cancer Genome Atlas

Background

The dysregulation of non-coding RNAs (ncRNAs) such as miRNAs and lncRNAs are associated with the pathogenesis and progression in multiple cancers including solid tumors. Comprehensive investigations of prognosis-related ncRNA markers could promote the development of therapeutic strategies for solid tumors, but rarely reported.

Methods

By taking advantage of The Cancer Genome Atlas (TCGA), pan-cancer prognosis analysis (PCPA) models were firstly constructed based on miRNA and lncRNA expression profiles of 8,450 samples in 19 solid tumors. Further, the co-occurrence and exclusivity among ncRNA markers were systematically analyzed for different cancers.

Results

In identified ncRNA makers, 71% of the miRNA markers were shared in multiple cancers, whereas 96% of the lncRNA markers were cancer-specific. Moreover, to analyze the regulation patterns of prognosis-related ncRNAs at the pan-cancer level, miRNA markers were further annotated into eight carcinogenic pathways. Results represented that approximately 86% of these miRNA markers could regulate the PI3K-Akt signaling pathway, while only 48% for the Notch signaling pathway. Finally, among 126 common genes that participated in eight carcinogenic pathways, BCL2, CSNK2A1, EGFR, PDGFRA, and VEGFA were proposed as potential drug targets for multiple cancers.

Conclusion

The prognosis analysis and regulation characteristics of ncRNAs presented in this study may help to facilitate the discovery of anti-cancer drugs for multiple solid tumors.

Integrated nomogram based on five stage-related genes and TNM stage to predict 1-year recurrence in hepatocellular carcinoma

Background

The primary tumor, regional lymph nodes and distant metastasis (TNM) stage is an independent risk factor for 1-year hepatocellular carcinoma (HCC) recurrence but has insufficient predictive efficiency. We attempt to develop and validate a nomogram to predict 1-year recurrence in HCC and improve the predictive efficiency of the TNM stage.

Methods

A total of 541 HCC patients were enrolled in the study. The risk score (RS) model was established with the logistic least absolute shrinkage and selector operation algorithm. The predictive nomogram was further validated in the internal testing cohort and external validation cohort. The area under the receiver operating characteristic curves (AUCs), decision curves and clinical impact curves were used to evaluate the predictive accuracy and clinical value of the nomogram.

Results

In the training cohort, we identified a RS model consisting of five stage-related genes (NUP62, EHMT2, RANBP1, MSH6 and FHL2) for recurrence at 1 year. The 1-year disease-free survival of patients was worse in the high-risk group than in the low-risk group (P < 0.0001), and 1-year recurrence was more likely in the high-risk group (Hazard ratio: 3.199, P < 0.001). The AUC of the nomogram was 0.739, 0.718 and 0.693 in the training, testing and external validation cohort, respectively, and these values were larger than the corresponding AUC of the TNM stage (0.681, 0.688 and 0.616, respectively).

Conclusions

A RS model consisting of five stage-related genes was successfully identified for predicting 1-year HCC recurrence. Then, a novel nomogram based on the RS model and TNM stage to predict 1-year HCC recurrence was also developed and validated.

Association of Hepatitis B Virus DNA Level and Follow-up Interval With Hepatocellular Carcinoma Recurrence

IMPORTANCE

Antiviral treatment is important in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) comprehensive therapy. A high HBV DNA level is an independent risk factor for HBV-related HCC, but no quantifiable clinical index is available to date.

OBJECTIVE

To evaluate the feasibility and availability of the novel HBV DNA quantitation-time index (HDQTI), which includes HBV DNA quantitation and follow-up, to predict HBV-related HCC prognosis.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective prognostic study of patients with HCC from multiple centers in China was performed from January 1, 2002, to December 31, 2016. The median follow-up time was 18 months, and the longest follow-up time was 147 months. Data analysis was performed from January 1, 2017, to December 31, 2018.

MAIN OUTCOMES AND MEASURES

Clinical characteristics, antitumor management, antiviral treatment, HDQTI scores, follow-up information, and overall survival were recorded and analyzed. A receiver operating characteristic curve and accompanying area under the curve were calculated for HDQTI.

RESULTS

A total of 842 patients (mean [SD] age, 61.80 [9.85] years; 513 [60.9%] male) were included in the study. Of all included patients, 734 received no antiviral therapy before diagnosis (no previous diagnosis of HBV infection), 43 underwent nonstandard antiviral therapy, and 65 received regular antiviral therapy. Compared with the group without antiviral treatment, the Barcelona Clinic Liver Cancer (BCLC) stage was earlier (A:B:C, 73.8%:26.2%:0% to 5.7%:65.5%:28.8%, P < .001), the mean (SD) tumor size was smaller (2.89 [1.26] to 7.56 [3.28] cm, P < .001), the ratio of baseline HBV DNA level of more than 105 copies/mL was lower (10.8% to 40.6%, P < .001), and the ratio of the α1-fetoprotein level more than 400 ng/mL was less (21.5% to 78.2%, P < .001) in the standard antiviral treatment group, whereas the nonstandard treatment group was between the 2 groups. Recurrence occurred in 39 of 109 BCLC stage A cases. Patients with HDQTI scores higher than 34 had high risk of recurrence; at this cutoff level, the sensitivity of the HDQTI was 76.9% and the specificity was 92.9%, with an area under curve of 0.928. Patients in various BCLC stages had similar trends in overall survival and HDQTI scores (BCLC stage A: HDQTI score <34, not applicable; HDQTI score ≥34, 44.0 months; 95% CI, 38.3-49.7 months; BCLC stage B: HDQTI score <34, 35.0 months; 95% CI, 33.3-36.7 months; HDQTI score ≥34, 17.0 months; 95% CI, 14.5-19.5 months; P = .002; BCLC stage C: HDQTI score <34, 18.0 months; 95% CI, 16.5-19.6 months; HDQTI scores ≥34, 10.0 months; 95% CI, 8.5-11.5 months; P = .005).

CONCLUSIONS AND RELEVANCE

The findings suggest that the HDQTI can be used as an independent prognostic indicator of recurrence in HBV-related HCC. Shorter follow-up intervals and accurate imaging evaluation are recommended in patients with HDQTI scores of 34 or higher.

Increased expression of protease-activated receptors 2 indicates poor prognosis in HBV related hepatocellular carcinoma

OBJECTIVE

To investigate the potential role of protease-activated receptor 2 (PAR2) in the prognosis of hepatocellular carcinoma (HCC).

METHODS

A total of 202 HCC patients who underwent liver resections were included. Tissue microarray was established with specimens of both HCC and paired adjacent liver tissues. PAR2 expression was detected by immunohistochemistry (IHC) assays.. A semi-quantification method was used to define the expression level of PAR2. The correlations between PAR2 expression and clinical features of patients with HCC was explored. The association of different PAR2 expressions with both overall survival and disease-free survival was analyzed.

RESULTS

Results showed that the expression of PAR2 in HCC tissues was higher than that in paired para-cancerous liver tissues (4.12 ± 3.55 vs. 2.71 ± 2.56, P < 0.001). Higher expression of PAR2 was associated with poor differentiation (P < 0.001) and advanced tumor-node-metastasis stage (P = 0.015). Kaplan-Meier survival analysis indicated that HCC patients with high PAR2 expression had decreased overall survival (P = 0.033) and disease-free survival (P = 0.043) compared to patients with lower PAR2 expression. Multivariate analysis indicated that PAR2 expression (P = 0.032) was a significant independent prognostic factor for both overall survival and disease-free survival (P = 0.032; P = 0.032, respectively).

CONCLUSION

Our data revealed that PAR2 expression was increased in HCC. High PAR2 expression was correlated with both decreased overall survival and disease-free survival in patients with HCC. High PAR2 expression indicated a poor prognosis.

A stage-specific cancer chemotherapy strategy through flexible combination of reduction-activated charge-conversional core-shell nanoparticles

Precision medicine has increased the demand for stage-specific cancer chemotherapy. Drugs with different properties are needed for different stages of tumor development, which is, inducing rapid destruction in the early stage and facilitating deep penetration in the advanced stage. Herein, we report a novel reduction-activated charge-conversional core-shell nanoparticle (CS NP) formula based on ring-closing metathesis of the thiamine disulfide system (TDS) to deliver the chemotherapeutic agent-gambogic acid (GA). Methods: The shell consisted of hyaluronic acid-all-trans retinoid acid with a disulfide bond as the linker (HA-SS-ATRA). The core was selected from poly (γ-glutamic acid) with different grafting rates of the functional group (Fx%) of TDS. GA/CF100%S NPs, with the strongest reduction-responsive drug release, and GA/CF60%S NPs with the strongest penetration have been finally screened. On this basis, a stage-specific administration strategy against a two-stage hepatocellular carcinoma was proposed. Results: The developed CS NPs have been confirmed as inducing reduction-activated charge conversion from about -25 to +30 mV with up to 95% drug release within 48 h. The administration strategy, GA/CF100%S NPs for the early-stage tumor, and sequential administration of GA/CF60%S NPs followed by GA/CF100%S NPs for the advanced-stage tumor, achieved excellent tumor inhibition rates of 93.86±2.94% and 90.76±6.43%, respectively. Conclusions: Our CS NPs provide a novel platform for charge conversion activated by reduction. The stage-specific administration strategy showed great promise for cancer therapy.