Preoperative prealbumin-to-fibrinogen ratio to predict survival outcomes in hepatocellular carcinoma patients after hepatic resection

BackgroundThis study aimed to evaluate the clinical application of the preoperative prealbumin-to-fibrinogen ratio (PFR) in the clinical diagnosis of hepatocellular carcinoma (HCC) patients and its prognostic value.MethodsThe clinical and laboratory data of 269 HCC patients undergoing surgical treatment from January 2012 to January 2017 in Taizhou Hospital were retrospectively analysed. The Cox regression model was used to analyse the correlation between the PFR and other clinicopathological factors in overall survival (OS) and disease-free survival (DFS).ResultsCox regression analysis showed that the PFR (hazard ratio (HR)=2.123; 95% confidence interval (95% CI), 1.271-3.547; P=0.004) was an independent risk factor affecting the OS of HCC patients. Furthermore, a nomogram was built based on these risk factors. The C-index for the OS nomogram was 0.715.ConclusionsNomograms based on the PFR can be recommended as the correct and actual model to evaluate the prognosis of patients with HCC.     

Development and validation of a CTNNB1-associated metabolic prognostic model for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy closely related to metabolic reprogramming. We investigated how CTNNB1 mutation regulates the HCC metabolic phenotype and thus affects the prognosis of HCC. We obtained the mRNA expression profiles and clinicopathological data from The Cancer Genome Atlas (TCGA), the International Cancer Genomics Consortium (ICGC) and the Gene Expression Omnibus database ( GSE14520 and GSE116174 ). We conducted gene set enrichment analysis on HCC patients with and without mutant CTNNB1 through TCGA dataset. The Kaplan-Meier analysis and univariate Cox regression analysis assisted in screening metabolic genes related to prognosis, and the prognosis model was constructed using the Lasso and multivariate Cox regression analysis. The prognostic model showed good prediction performance in both the training cohort (TCGA) and the validation cohorts (ICGC, GSE14520 , GSE116174 ), and the high-risk group presented obviously poorer overall survival compared with low-risk group. Cox regression analysis indicated that the risk score can be used as an independent predictor for the overall survival of HCC. The immune infiltration in different risk groups was also evaluated in this study to explore underlying mechanisms. This study is also the first to describe an metabolic prognostic model associated with CTNNB1 mutations and could be implemented for determining the prognoses of individual patients in clinical practice.     

Competing endogenous RNA network and prognostic nomograms for hepatocellular carcinoma patients who underwent R0 resection

The prognosis of hepatocellular carcinoma (HCC) after R0 resection is unsatisfactory due to the high rate of recurrence. In this study, we investigated the recurrence-related RNAs and the underlying mechanism. The long noncoding RNA (lncRNA), microRNA (miRNA), and messenger RNA (mRNA) expression data and clinical information of 247 patients who underwent R0 resection patients with HCC were obtained from The Cancer Genome Atlas. Comparing the 1-year recurrence group (n = 56) with the nonrecurrence group (n = 60), we detected 34 differentially expressed lncRNAs (DElncRNAs), five DEmiRNAs, and 216 DEmRNAs. Of these, three DElncRNAs, hsa-mir-150-5p, and 11 DEmRNAs were selected for constructing the competing endogenous RNA (ceRNA) network. Next, two nomogram models were constructed based separately on the lncRNAs and mRNAs that were further selected by Cox and least absolute shrinkage and selection operator regression analysis. The two nomogram models that showed a high prediction accuracy for disease-free survival with the concordance indexes at 0.725 and 0.639. Further functional enrichment analysis of DEmRNAs showed that the mRNAs in the ceRNA network and nomogram models were associated with immune pathways. Hence, we constructed a hsa-mir-150-5p-centric ceRNA network and two effective nomogram prognostic models, and the related RNAs may be useful as potential biomarkers for predicting recurrence in patients with HCC.     

Diagnostic and prognostic value of circular RNAs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the sixth most common malignant tumour, which has posed a heavy health and financial burden worldwide. Due to limited symptoms at the early stage and the limitation in current biomarkers, HCC patients are usually diagnosed at the advanced stage with a pessimistic overall survival rate. Circular RNAs (circRNAs) are a subclass of single-stranded RNAs characterized by a covalently closed loop structure without 3’- or 5’-end. With advances in high-throughput sequencing technology and bioinformatics, accumulating studies have demonstrated the promotor or suppressor roles of circRNAs in the carcinogenesis, progression, and metastasis of HCC. Moreover, circRNAs are characteristic of higher abundance, stability and conservation compared with linear RNAs. Therefore, circRNAs have emerged as one of the most promising diagnostic and prognostic biomarkers for HCC with reliable accuracy, sensitivity and specificity. In this review, we briefly introduce the characteristics of circRNAs and summarize the roles of circRNAs in the biological procedures of HCC. Furthermore, we provide an overview on the potential diagnostic and prognostic value of circRNAs as biomarkers for patients with HCC. Finally, we discuss future perspectives of circRNAs in cancer research.     

Development and validation of serum exosomal microRNAs as diagnostic and prognostic biomarkers for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related death worldwide. China accounts for over half of the new cases and deaths. Diagnostic imprecision and a lack of complimentary molecular biomarkers are partially responsible for this lack of progress. Herein, serum-derived exosomal microRNA (miRNA) profiling was performed on 80 patients which histologically confirmed HCC and 30 normal controls. A classification of 8 exosomal miRNAs had biologically and statistically significant differences between HCC and normal serum samples, including miR-122, miR-125b, miR-145, miR-192, miR-194, miR-29a, miR-17-5p, and miR-106a. Online algorithm showed strong independent classification accuracy (area under the curve) reached 0.535 to 0.850, separately. The significant correlation between serum exosomal miRNAs and tumor size was observed. In addition, the survival difference of HCC patients with high or low exosomal miR-106a was statistically significant using Kaplan-Meier analysis. Besides, we also measured the proliferation and invasion ability of HCC cells following exosomal miR-106a mimics or inhibitor treatment. After prediction with algorithms, mitogen-activated protein kinase and c-Jun N-terminal kinase pathways were identified associated with miR-106a’s function. In summary, differentially expressed serum exosomal miRNAs can be helpful for diagnostic and prognostic of HCC.     

Prognostic value of polarized macrophages in patients with hepatocellular carcinoma after curative resection

As the most predominant tumour‐infiltrating immune cells, tumour‐associated macrophages (TAMs) are significant for fostering tumour growth, progression and metastasis. CD68‐positive TAMs display dissimilarly polarized programmes comprising CD11c‐positive pro‐inflammatory macrophages (M1) and CD206‐positive immunosuppressive macrophages (M2). The aim of this study is to determine the prognostic significance of diametrically polarized TAMs in hepatocellular carcinoma (HCC) and their application to risk stratification of patients according to their specific prognostic values. This study included 80 consecutive patients with HCC, and we evaluated diametrically polarized functional status of macrophages by immunohistochemical staining of CD68, CD11c and CD206. Prognostic values and clinicopathologic features were assessed in these patients. High versus low CD11c‐positive TAM density (P = 0.005) and low versus high CD206‐positive TAM density (P = 0.002) were associated with better overall survival, whereas CD68‐positive TAM density had no prognostic significance (low versus high, P = 0.065). Furthermore, the presence of these positive staining macrophages did not show any prognostic significance for recurrence‐free survival (all P > 0.05). Multivariate Cox regression analysis identified CD11c‐positive and CD206‐positive TAMs as an independent prognostic factor (P < 0.001, P = 0.031, respectively). Intratumoural infiltration of diametrically polarized TAMs, a novel identified independent prognostic factor for survival in patients with HCC, could be combined with the TNM stage and the Barcelona Clinic Liver Cancer stage to improve a risk stratification system.     

Development and validation of LRP1B mutation-associated prognostic model for hepatocellular carcinoma

Purpose: To develop a lipoprotein receptor-related protein 1B (LRP1B) gene mutation-based prognostic model for hepatocellular carcinoma (HCC) patients risk prediction. Methods: The LRP1B gene mutation rate was calculated from HCC patient samples. Meanwhile, differentially expressed genes according to LRP1B mutant were screened out for prognostic model establishment. Based on this innovative model, HCC patients were categorized into high- and low-risk groups. The immune status including immune cell infiltration ratio and checkpoints have been explored in two groups. The functions of LRP1B and risk factors in the model were verified using both in vivo and in vitro experiments. Results: It could be demonstrated that LRP1B was a potential negative predictor for HCC patients prognosis with high mutation frequency. The functions of LRP1B were verified with ELISA and Quantitative Real-time PCR method based on clinic-recruited HCC participants. Eleven genes displayed significant differences according to LRP1B status, which could better predict HCC patient prognosis. The functions of these genes were examined using HCC cell line HCCLM3, suggesting they played a pivotal role in determining HCC cell proliferation and apoptosis. From the immune cell infiltration ratio analysis, there was a significant difference in the infiltration degree of seven types of immune cells and two immune checkpoints between high- and low-risk HCC patients. Conclusion: The present study hypothesized a potential prognostic biomarker and developed a novel LRP1B mutation-associated prognostic model for HCC, which provided a systematic reference for future understanding of clinical research.     

CDKN2A is a prognostic biomarker and correlated with immune infiltrates in hepatocellular carcinoma

Cyclin dependent kinase inhibitor 2A (CDKN2A) is an essential regulator of immune cell functionality, but the mechanisms whereby it drives immune infiltration in hepatocellular carcinoma (HCC) remain unclear. In the present study, we studied the association with CDKN2A expression and immune invasion with the risk of developing HCC. A totally of 2207 different genes were found between HCC and adjacent liver tissues from TCGA and GEO databases. CDKN2A was highly expressed in HCC and associated with poorer overall survival and disease-free survival. Notably, CDKN2A expression was positively correlated with infiltrating levels into purity, B cell, CD+8 T cell, CD+4 T cell, macrophage, neutrophil, and dendritic cells in HCC. CDKN2A expression showed strong correlations between diverse immune marker sets in HCC. These findings suggest that CDKN2A expression potentially contributes to regulation of tumor-associated macrophages and can be used as a prognostic biomarker for determining prognosis and immune infiltration in HCC.     

Microenvironment of a tumor-organoid system enhances hepatocellular carcinoma malignancy-related hallmarks

Organ-like microenviroment and 3-dimensional (3D) cell culture conformations have been suggested as promising approaches to mimic in a micro-scale a whole organ cellular functions and interactions present in vivo. We have used this approach to examine biologic features of hepatocellular carcinoma (HCC) cells. In this study, we demonstrate that hepatocellular carcinoma (HCC) cells, fibroblasts, endothelial cells and extracellular matrix can generate organoid-like spheroids that enhanced numerous features of human HCC observed in vivo. We show that the addition of non-parenchymal cells such as fibroblast and endothelial cells is required for spheroid formation as well as the maintenance of the tissue-like structure. Furthermore, HCC cells cultured as spheroids with non-parenchymal cells express more neo-angiogenesis-related markers (VEGFR2, VEGF, HIF-α), tumor-related inflammatory factors (CXCR4, CXCL12, TNF-α) and molecules-related to induced epithelial-mesenchymal transition (TGFβ, Vimentin, MMP9) compared with organoids containing only HCC cells.

These results demonstrate the importance of non-parenchymal cells in the cellular composition of HCC organoids. The novelty of the multicellular-based organotypic culture system strongly supports the integration of this approach in a high throughput approach to identified patient-specific HCC malignancy and accurate anti-tumor therapy screening after surgery.     

EYA4 serves as a prognostic biomarker in hepatocellular carcinoma and suppresses tumour angiogenesis and metastasis

Eye absent homolog 4 (EYA4) has been demonstrated to be down‐regulated in hepatocellular carcinoma (HCC), but its biological function and the mechanism in HCC angiogenesis and metastasis remain largely unknown. Herein, we showed that EYA4 expression was frequently low in HCC tissue samples compared with matched adjacent non‐tumourous tissues. In the analysis of 302 HCC specimens, we revealed that decreased expression of EYA4 correlated with tumour differentiation status. Univariate and multivariate analyses identified EYA4 as an independent risk factor for recurrence‐free survival (RFS) and overall survival (OS) among the 302 patients. Functional assays showed that forced expression of EYA4 suppressed HCC cell migration, invasion and capillary tube formation of endothelial cells in vitro, as well as in vivo tumour angiogenesis and metastasis in a mouse model. Furthermore, mechanism study exhibited that EYA4 could inhibit HCC angiogenesis and metastasis by inhibiting c‐JUN/VEGFA pathway. Together, we provide proof that EYA4 is a novel tumour suppressor in HCC and a new prognostic biomarker and therapeutic target in HCC.     

Vascular endothelial growth factor A is a potential prognostic biomarker and correlates with immune cell infiltration in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related deaths among cancer patients. Vascular endothelial growth factor A (VEGFA) is involved in regulating biological processes, such as angiogenesis and vascular permeability, and is very closely related to the pathogenesis of various tumours, especially vascular-rich, solid tumours. Clinical data of patients with HCC and other tumours were analysed through public databases, such as the TCGA database, Gene Expression Omnibus database, Human Protein Atlas database, STRING, Tumour Immune Estimation Resource and Kaplan–Meier Plotter. The tumour tissues and adjacent normal tissues of patients with HCC from Hunan Provincial People's Hospital were collected to verify the expression of VEGFA by immunohistochemistry, immunofluorescence, Western blotting and qPCR. VEGFA expression is elevated in multiple tumour types and correlates with the prognosis of tumour patients. VEGFA is involved in regulating the tumour microenvironment and immune cell function in tumour development. Inhibition of VEGFA reduces proliferation, invasion, and migration and promotes apoptosis in HCC cells. VEGFA is a potential predictive biomarker for the diagnosis and prognosis of HCC.     

Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302–0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299–0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.     

基于CRISPR转录激活系统构建内源性着丝粒蛋白F稳定过表达的肝细胞癌细胞模型

临床研究表明着丝粒蛋白F(centromere protein F,CENPF)与肝细胞癌(hepatocellular carcinoma,HCC)的发生相关。由于CENPF蛋白的分子量高达358 kDa,目前有关CENPF致癌机制研究使用的体内外模型主要基于CENPF表达敲低,尚缺乏将CENPF过表达以探究其与癌变因果关系的研究,CENPF过表达改变到底是“因”还是“果”仍不清楚。本研究旨在利用包括lentiMPHv2和lentiSAMv2两个载体的CRISPR/dCas9转录激活协同激活介体(synergistic activation mediator,SAM)系统构建内源性CENPF稳定过表达的细胞模型,为阐明CENPF过表达与HCC发生发展的因果关系提供有效工具。首先设计并合成能够特异性识别CENPF基因转录起始位点的单向导核糖核酸(single guide RNAs,sgRNA),并将其插入lentiSAMv2质粒中。利用慢病毒载体将lentiMPHv2质粒导入Huh-7和HCCLM3细胞株中,用潮霉素B筛选后再用慢病毒载体将连接好的携带sgRNA序列的lentiSAMv2质粒导入细胞中,并用杀稻瘟菌素S继续筛选。对2种抗生素筛选获得的Huh-7和HCCLM3细胞株样品进行CENPF mRNA和蛋白表达水平的检测,结果显示sgRNA1和sgRNA4序列均能够激活内源CENPF的表达,其中sgRNA4诱导转录效果更加明显。本研究利用CRISPR/dCas9系统成功构建内源性CENPF稳定过表达的HCC细胞模型,为研究CENPF过表达与肿瘤发生的因果关系奠定基础,并为构建大分子量蛋白过表达的细胞模型提供参考方案。     

Integrated analysis of a competing endogenous RNA network reveals key long noncoding RNAs as potential prognostic biomarkers for hepatocellular carcinoma

Growing evidence has revealed that long noncoding RNAs (lncRNAs) have an important impact on tumorigenesis and tumor progression via a mechanism involving competing endogenous RNAs (ceRNAs). However, their use in predicting the survival of a patient with hepatocellular carcinoma (HCC) remains unclear. The aim of this study was to develop a novel lncRNA expression–based risk score system to accurately predict the survival of patients with HCC. In our study, using expression profiles downloaded from The Cancer Genome Atlas database, the differentially expressed messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) were explored in patients with HCC and normal liver tissues, and then a ceRNA network constructed. A risk score system was established between lncRNA expression of the ceRNA network and overall survival (OS) or recurrence-free survival (RFS); it was further analyzed for associations with the clinical features of patients with HCC. In HCC, 473 differentially expressed lncRNAs, 63 differentially expressed miRNAs, and 1417 differentially expressed mRNAs were detected. The ceRNA network comprised 41 lncRNA nodes, 12 miRNA nodes, 24 mRNA nodes, and 172 edges. The lncRNA expression–based risk score system for OS was constructed based on six lncRNAs (MYLK-AS1, AL359878.1, PART1, TSPEAR-AS1, C10orf91, and LINC00501), while the risk score system for RFS was based on four lncRNAs (WARS2-IT1, AL359878.1, AL357060.1, and PART1). Univariate and multivariate Cox analyses showed the risk score systems for OS or RFS were significant independent factors adjusted for clinical factors. Receiver operating characteristic curve analysis showed the area under the curve for the risk score system was 0.704 for OS, and 0.71 for RFS. Our result revealed a lncRNA expression–based risk score system for OS or RFS can effectively predict the survival of patients with HCC and aid in good clinical decision-making.