Prognostic Factor For Hepatocellular Carcinoma Research Articles

Clinical Importance of Regimens in Hepatic Arterial Infusion Chemotherapy for Advanced Hepatocellular Carcinoma with Macrovascular Invasion.

Simple SummaryAlthough various molecular targeted agents have been approved, the therapeutic outcomes in hepatocellular carcinoma (HCC) with macrovascular invasion (MVI) are still unsatisfactory. Locoregional treatment using hepatic arterial infusion chemotherapy is a promising treatment for MVI-HCC. In the study, we aimed to compare the therapeutic effects of low-dose cisplatin plus 5-fluorouracil (LFP), a conventional HAIC regimen, and New FP (a fine-powder cisplatin suspended with lipiodol plus 5-fluorouracil) for MVI-HCC with preserved liver function. New FP was significantly superior to LFP in all therapeutic outcomes. New FP is a recommended HAIC regimen for the treatment of patients with MVI-HCC.Macroscopic vascular invasion (MVI) is a poor prognostic factor in hepatocellular carcinoma (HCC). Hepatic arterial infusion chemotherapy (HAIC) is a promising treatment in MVI-HCC. However, it is not clear which regimens are suitable for HAIC. In this study, we aimed to compare the therapeutic effects between New FP (a fine-powder cisplatin suspended with lipiodol plus 5-fluorouracil) and low dose FP (LFP/cisplatin plus 5-fluorouracil) in the treatment of MVI-HCC patients with Child–Pugh class A. New FP is a regimen that consists of a fine-powder cisplatin suspended with lipiodol and 5-fluorouracil. Fifty-one patients were treated with LFP, and 99 patients were New FP. We compared the therapeutic effects of LFP and New FP and assessed factors that associated with the therapeutic effects. The median survival and progression-free survival times of LFP and New FP were 16.1/24.7 and 5.4/8.8 months, respectively (p < 0.05, p < 0.05). The complete response (29%) and objective response rate (76%) of New FP were significantly higher than those of LFP (p < 0.001, p < 0.01). Factors associated with better therapeutic response were better ALBI-grade and New FP treatment choice. New FP is a more powerful regimen than LFP in HAIC for MVI-HCC. New FP represents a recommended HAIC regimen for the treatment of patients with MVI-HCC.

Downregulation of LHPP Expression Associated with AFP Acts as a Good Prognostic Factor in Human Hepatocellular Carcinoma.

Background Phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) serves as a tumor suppressor in hepatocellular carcinoma (HCC), but the correlation between the expression of LHPP and the clinical parameters of oncogenic progression is still not well defined. This study is to reveal the correlation between the expression of LHPP in HCC and their clinical parameters. Methods Immunohistochemical analysis was used to assess the correlation between the expression of LHPP and the clinical parameters of HCC. Expressions of LHPP in HCC tissues and cultured HCC cells were detected by Western blot and quantitative real-time polymerase chain reaction (qRT-PCR). LHPP, gamma-glutamyl transferase (GGT), and α-fetoprotein (AFP) expression levels in blood or HCC tissues were detected by enzyme-linked immunosorbent assay (ELISA). The Spearman rank correlation coefficient was used to evaluate the correlation of the expression of LHPP and the clinical index of HCC. Correlation of survival and expression of LHPP were analyzed using the Kaplan-Meier method and the log-rank test. Results Expressions of LHPP in HCC tissues were significantly downregulated than their paired adjacent normal tissues. A significant positive correlation was found between the cytoplasm and nuclear expression of LHPP in both HCC and their paired adjacent normal tissues. The expression of LHPP negatively correlated with the levels of GGT in the cytoplasm of adjacent tissues and with the AFP level in the nucleus of HCC cells. Relative levels of LHPP in HCC tissues were markedly lower than those of the paired adjacent normal tissues. Relative levels of LHPP in LO-2 cells were higher than those of HepG2, BEL-7404, and SMMC-7721 cell lines. The overall survival and DSF survival of patients with the high expression of LHPP were much higher than those with the low expression of LHPP in paired adjacent normal tissue. Conclusions LHPP is associated with the AFP level and acts as a good prognostic factor in HCC.

A Prognostic Autophagy-Related Gene Pair Signature and Small-Molecule Drugs for Hepatocellular Carcinoma.

Dysregulation of autophagy-related genes (ARGs) is related to the prognosis of cancers. However, the aberrant expression of ARGs signature in the prognosis of hepatocellular carcinoma (HCC) remain unclear. Using The Cancer Genome Atlas and the International Cancer Genome Consortium database, 188 common autophagy-related gene pairs (ARGPs) were identified. Through univariate, least absolute shrinkage and selection operator analysis, and multivariate Cox regression analysis, a prognostic signature of the training set was constructed on the basis of 6 ARGPs. Further analysis revealed that the ARGP based signature performed more accurately in overall survival (OS) prediction compared to other published gene signatures. In addition, a high risk of HCC was closely related to CTLA4 upregulation, LC3 downregulation, low-response to axitinib, rapamycin, temsirolimus, docetaxel, metformin, and high-response to bleomycin. Univariate Cox and multivariate Cox analysis revealed that the risk score was an independent prognostic factor for HCC. These results were internally validated in the test and TCGA sets and externally validated in the ICGC set. A nomogram, consisting of the risk score and the TNM stage, performed well when compared to an ideal nomogram. In conclusion, a 6-ARGP-based prognostic signature was identified and validated as an effective predictor of OS of patients with HCC. Furthermore, we recognized six small-molecule drugs, which may be potentially effective in treating HCC.

Use of proteomics to identify mechanisms of hepatocellular carcinoma with the CYP2D6*10 polymorphism and identification of ANGPTL6 as a new diagnostic and prognostic biomarker

BackgroundAlthough an association between the cytochrome P4502D6 (CYP2D6) *10 (100C>T) polymorphism and hepatocellular carcinoma (HCC) is known, the mechanism remains unclear. Here we aimed to explore mechanisms of CYP2D6*10 (100C>T) polymorphism conferring to HCC, and screen markers for HCC.MethodsLabel-free global proteome profiling with 34 normal livers and peritumor tissue from 61 HCC patients was performed, and angiopoietin-like protein-6 (ANGPTL6) was evaluated in 2 liver samples validation cohorts and 2 blood specimens validation cohorts.ResultsWe found a significantly decreased frequency of TT in HCC patients which reduced HCC susceptibility by 69.2% and was accompanied by lowered enzymatic activity for CYP2D6. Proteomic analysis revealed 1342 differentially expressed proteins (DEPs) that were associated with HCC and 88 DEPs were identified as 100 TT-related proteins, likely underlying the susceptibility to HCC. Twenty-two upregulated DEPs and 66 downregulated DEPs were mainly related to lipid metabolism and the extracellular matrix, respectively. High ANGPTL6 was associated with a higher risk to HCC and worse prognosis. ANGPTL6 was both an independent risk factor and an independent prognostic factor for HCC and exhibited strong potential for predicting HCC occurrence, with comparable AUC values and higher sensitivity compared with alpha-fetoprotein.ConclusionsThe TT genotype-associated decreased risk of HCC appears to be related to lowered CYP2D6 activity and altered protein expression in the tumor microenvironment, and ANGPTL6 is a promising new diagnostic and prognostic biomarker for HCC. Our findings reveal new mechanistic insights for polymorphisms related to HCC risk and provide avenues for screening for HCC.

Screening Prognosis-Related lncRNAs Based on WGCNA to Establish a New Risk Score for Predicting Prognosis in Patients with Hepatocellular Carcinoma.

Background Hepatocellular carcinoma (HCC) remains an important cause of cancer death. The molecular mechanism of hepatocarcinogenesis and prognostic factors of HCC have not been completely uncovered. Methods In this study, we screened out differentially expressed lncRNAs (DE lncRNAs), miRNAs (DE miRNAs), and mRNAs (DE mRNAs) by comparing the gene expression of HCC and normal tissue in The Cancer Genome Atlas (TCGA) database. DE mRNAs were used to perform Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Then, the miRNA and lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a competitive endogenous RNA (ceRNA) network by weighted gene coexpression network analysis (WGCNA). Moreover, univariable Cox regression and Kaplan-Meier curve analyses of DE lncRNAs and DE mRNAs were conducted. Finally, the lasso-penalized Cox regression analysis and nomogram model were used to establish a new risk scoring system and predict the prognosis of patients with liver cancer. The expression of survival-related DE lncRNAs was verified by qRT-PCR. Results A total of 1896 DEmRNAs, 330 DElncRNAs, and 76 DEmiRNAs were identified in HCC and normal tissue samples. Then, the turquoise miRNA and turquoise lncRNA/mRNA modules that were most closely related to the survival time of patients with HCC were screened to construct a ceRNA network by WGCNA. In this ceRNA network, there were 566 lncRNA-miRNA-mRNA regulatory pairs, including 30 upregulated lncRNAs, 16 downregulated miRNAs, and 75 upregulated mRNAs. Moreover, we screened out 19 lncRNAs and 14 hub mRNAs related to prognosis from this ceRNA network by univariable Cox regression and Kaplan-Meier curve analyses. Finally, a new risk scoring system was established by selecting the optimal risk lncRNAs from the 19 prognosis-related lncRNAs through lasso-penalized Cox regression analysis. In addition, we established a nomogram model consisting of independent prognostic factors to predict the survival rate of HCC patients. Finally, the correlation between the risk score and immune cell infiltration and gene set enrichment analysis were determined. Conclusions In conclusion, the results may provide potential biomarkers or therapeutic targets for HCC and the establishment of the new risk scoring system and nomogram model provides the new perspective for predicting the prognosis of HCC.

NAP1L1 Functions as a Tumor Promoter via Recruiting Hepatoma-Derived Growth Factor/c-Jun Signal in Hepatocellular Carcinoma.

NAP1L1 has been reported to be significantly involved in the carcinogenesis of hepatocellular carcinoma (HCC). Yet, its detailed molecular basis is still to be determined. Based on the analysis of The Cancer Genome Atlas (TCGA) database, NAP1L1 mRNA was found to be upregulated and predicted the poor prognosis initially. Subsequently, consistent with the prediction, the upregulated expression of NAP1L1 mRNA and protein levels was confirmed by quantitative polymerase chain reaction (qPCR), Western blot, and immunohistochemistry assays. Upregulated NAP1L1 protein positively promoted the disease progression and poor prognosis of HCC. In addition, NAP1L1 protein expression was considered as an independent prognostic factor in HCC. Inhibition of NAP1L1 expression by siRNA or shRNA pathway significantly reduced the cell proliferation and cell cycle transformation in vitro and in vivo. Mechanism analysis first showed that the function of NAP1L1 was to recruit hepatoma-derived growth factor (HDGF), an oncogene candidate widely documented in tumors. Furthermore, the latter interacted with c-Jun, a key oncogenic transcription factor that can induce the expression of cell cycle factors and thus stimulate the cell growth in HCC. Finally, transfecting HDGF or c-Jun could reverse the suppressive effects on HCC growth in NAP1L1-suppressed HCC cells. Our data indicate that NAP1L1 is a potential oncogene and acts via recruiting HDGF/c-Jun in HCC.

Lymphocyte-to-C-reactive protein ratio as a prognostic factor for hepatocellular carcinoma.

Systemic inflammation has been correlated with worse survival for some cancers. We evaluated prognostic values of various inflammatory factor combinations in patients who underwent resections for hepatocellular carcinoma (HCC). We retrospectively analysed 306 consecutive patients with HCC who underwent curative liver resections. After assessing eight combinations of inflammatory markers for predictive value for recurrence, we focused on lymphocyte-to-C-reactive protein ratio (LCR) to elucidate its associations with recurrence-free survival (RFS) and overall survival (OS) in univariate and multivariate analyses (Cox proportional hazards model). We also used immunohistochemical CD34 and CD8 staining to investigate the mechanism of LCR elevation. LCR showed the highest association with RFS in HCC patients among the compared indices. High preoperative LCR correlated with a high serum albumin concentration, small tumour size, early Barcelona Clinic Liver Cancer stage and low rates of microscopic vascular invasion and microscopic intrahepatic metastasis. Higher preoperative LCR was an independent predictor of longer RFS and OS in this cohort. High LCR patients had fewer vessels encapsulating tumour clusters, and higher intratumoural CD8+ T-cell counts than low LCR patients. Preoperative LCR is a novel and convenient prognostic marker for patients with HCC, and is associated with the tumour microenvironment immune status.

The ratio of preoperative alpha-fetoprotein level to total tumor volume as a prognostic factor of hepatocellular carcinoma after liver transplantation.

To evaluate the effect of preoperative serum alpha-fetoprotein(AFP) level to total tumor volume (TTV) ratio as a prognostic marker on predicting the tumor recurrence and overall survival time of patients with hepatocellular carcinoma (HCC) after liver transplantation.One-hundred eight patients with HCC who underwent liver transplantation in Beijing Chaoyang Hospital from April 2013 to October 2017 were studied. Divided into AFP/TTV≤2 group and AFP/TTV>2 group by the best cut-off score calculated by receiver operation characteristic curve, the clinical and pathological data of the patients in two groups were compared to explore the relationship between AFP/TTV and tumor recurrence together with the prognosis of HCC patients after liver transplantation. Risk factors of early tumor recurrence and poor prognosis of HCC in patients after liver transplantation were studied by multivariate regression analysis. Kaplan-Meier survival analysis was used to compare the tumor-free survival and overall survival between the two groups of patients.In 108 patients, 47 patients have AFP/TTV≤2 while 61 patients have AFP/TTV>2. Patients in AFP/TTV≤2 group have longer tumor-free survival time and overall survival time compared with patients in AFP/TTV>2 group. The age, total bilirubin level, serum AFP level, TTV, portal vein tumor thrombus and AFP/TTV (all P < .05) of patient with HCC are closely related to poor prognosis after liver transplantation. Multivariate regression analysis showed that have portal vein tumor thrombus (hazard ratio [HR] = 2.345, P < .05), TTV≥65.5 cm3 (HR = 2.701, P < .05) and AFP/TTV > 2 (HR = 4.624, P < .05) are independent risk factors for poor prognosis of patients with HCC after liver transplantation while TTV≥65.5 cm3 (HR = 2.451, P < .05) and AFP/TTV > 2 (HR = 4.257, P < 0.05) were independent risk factors for tumor recurrence at the same time.The tumor recurrence and the prognosis of patients with HCC after liver transplantation is affected by many factors. AFP/TTV ratio has important predictive value for the tumor recurrence and the prognosis of patients with HCC after liver transplantation. AFP/TTV>2 is an independent risk factor for both early tumor recurrence and poor prognosis of patients with HCC after liver transplantation.

Identifying Dendritic Cell-Related Genes Through a Co-Expression Network to Construct a 12-Gene Risk-Scoring Model for Predicting Hepatocellular Carcinoma Prognosis.

The prognostic prediction of hepatocellular carcinoma (HCC) is still challenging. Immune cells play a crucial role in tumor initiation, progression, and drug resistance. However, prognostic value of immune-related genes in HCC remains to be further clarified. In this study, the mRNA expression profiles and corresponding clinical information of HCC patients were downloaded from public databases. Then, we estimated the abundance of immune cells and identified the differentially infiltrated and prognostic immune cells. The weighted gene co-expression network analysis (WGCNA) was performed to identify immune-related genes in TCGA cohort and GEO cohort. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to establish a risk-scoring model in the TCGA cohort. HCC patients from the GSE14520 datasets were utilized for risk model validation. Our results found that high level of dendritic cell (DC) infiltration was associated with poor prognosis. Over half of the DC-related genes (58.2%) were robustly differentially expressed between HCC and normal specimens in the TCGA cohort. 17 differentially expressed genes (DEGs) were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. A 12-gene risk-scoring model was established to evaluate the prognosis of HCC. The high-risk group exhibits significantly lower OS rate of HCC patients than the low-risk group. The risk-scoring model shows benign predictive capacity in both GEO dataset and TCGA dataset. The 12-gene risk-scoring model may independently perform prognostic value for HCC patients. Receiver operating characteristic (ROC) curve analysis of the risk-scoring model in GEO cohort and TCGA cohort performed well in predicting OS. Taken together, the 12-gene risk-scoring model could provide prognostic and potentially predictive information for HCC. SDC3, NCF2, BTN3A3, and WARS were noticed as a novel prognostic factor for HCC.

Edge-competing Pathological Liver Vessel Segmentation with Limited Labels

The microvascular invasion (MVI) is a major prognostic factor in hepatocellular carcinoma, which is one of the malignant tumors with the highest mortality rate. The diagnosis of MVI needs discovering the vessels that contain hepatocellular carcinoma cells and counting their number in each vessel, which depends heavily on experiences of the doctor, is largely subjective and time-consuming. However, there is no algorithm as yet tailored for the MVI detection from pathological images. This paper collects the first pathological liver image dataset containing $522$ whole slide images with labels of vessels, MVI, and hepatocellular carcinoma grades. The first and essential step for the automatic diagnosis of MVI is the accurate segmentation of vessels. The unique characteristics of pathological liver images, such as super-large size, multi-scale vessel, and blurred vessel edges, make the accurate vessel segmentation challenging. Based on the collected dataset, we propose an Edge-competing Vessel Segmentation Network (EVS-Net), which contains a segmentation network and two edge segmentation discriminators. The segmentation network, combined with an edge-aware self-supervision mechanism, is devised to conduct vessel segmentation with limited labeled patches. Meanwhile, two discriminators are introduced to distinguish whether the segmented vessel and background contain residual features in an adversarial manner. In the training stage, two discriminators are devised to compete for the predicted position of edges. Exhaustive experiments demonstrate that, with only limited labeled patches, EVS-Net achieves a close performance of fully supervised methods, which provides a convenient tool for the pathological liver vessel segmentation. Code is publicly available at https://github.com/wang97zh/EVS-Net.

Gene Polymorphism of MUC15, MMP14, BRAF, and COL1A1 Is Associated with Capsule Formation in Hepatocellular Carcinoma.

Background The presence of a capsule is an important prognostic factor in hepatocellular carcinoma (HCC). Capsule formation is affected by tumor-host interaction, which may include collagen deposition and extracellular matrix (ECM) degradation. Purpose This study aimed to examine whether single-nucleotide polymorphisms (SNPs) in the genes for COL1A1 MUC15, MMP14, CD97, SMYD3, BRAF, and transforming growth factor beta 1 (TGF-β) are related to capsule formation. Methods We prospectively recruited and analyzed 185 patients with HCC with or without a capsule between 2019 and 2020. The SNPs involved were analyzed by polymerase chain reaction. Differences in the allele and genotype frequency between the cases and controls were evaluated using the chi-square test. Odds ratios and 95% confidence intervals were calculated by logistic regression analysis with adjustment for age and sex. Stratification analyses were also performed with preselected variables. Results The single-locus analysis showed that the presence of a capsule was significantly associated with five SNPs : MUC15 rs17309195 (P=0.01), rs12271124 (P= 0.02), rs10430847 (P=0.04), MMP14 rs17884816 (P=0.01), and BRAF rs74512895 (P=0.03). Adjusted logistic regression revealed that the decreased capsule formation was statistically significantly associated with BRAF rs76603725, COL1A1 rs2269336, and MUC15 rs17309195, while MMP14 rs17884816 and MUC15 rs10430847, rs2063278, and rs967490 were associated with increased capsule formation. The MUC15 block 2 haplotype was associated with increased capsule formation. Conclusions MUC15, MMP14, BRAF, and COL1A1 gene polymorphisms are associated with capsule formation in HCC. Studies involving larger samples are needed to confirm our results.

Integrated profiling identifies ITGB3BP as prognostic biomarker for hepatocellular carcinoma.

ABSTRACTHepatocellular carcinoma (HCC) is a highly malignant tumor. In this study, we sought to identify a novel biomarker for HCC by analyzing transcriptome and clinical data. The R software was used to analyze the differentially expressed genes (DEGs) in the datasets GSE74656 and GSE84598 downloaded from the Gene Expression Omnibus database, followed by a functional annotation. A total of 138 shared DEGs were screened from two datasets. They were mainly enriched in the “Metabolic pathways” pathway (Padj = 8.21E-08) and involved in the carboxylic acid metabolic process (Padj = 0.0004). The top 10 hub genes were found by protein-protein interaction analysis and were upregulated in HCC tissues compared to normal tissues in The Cancer Genome Atlas database. Survival analysis distinguished 8 hub genes CENPE, SPDL1, Hyaluronan-mediated motility receptor, Rac GTPase activating protein 1, Thyroid hormone receptor interactor 13, cytoskeleton-associated protein (CKAP) 2, CKAP5, and Integrin subunit beta 3 binding protein (ITGB3BP) were considered as prognostic hub genes. Multivariate cox regression analysis indicated that all the prognostic hub genes were independent prognostic factors for HCC. Furthermore, the receiver operating characteristic curve revealed that the 8-hub genes model had better prediction performance for overall survival compared to the T stage (p = 0.008) and significantly improved the prediction value of the T stage (p = 0.002). The Human Protein Atlas showed that the protein expression of ITGB3BP was upregulated in HCC, so the expression of ITGB3BP was further verified in our cohort. The results showed that ITGB3BP was upregulated in HCC tissues and was significantly associated with lymph node metastasis.

Identification of Potential Biomarkers From Hepatocellular Carcinoma With MT1 Deletion.

Background: Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide. Metallothioneins (MTs) are metal-binding proteins involved in multiple biological processes such as metal homeostasis and detoxification, as well as in oncogenesis. Copy number variation (CNV) plays a vital role in pathogenesis and carcinogenesis. Nevertheless, there is no study on the role of MT1 CNV in HCC. Methods: Array-based Comparative Genomic Hybridization (aCGH) analysis was performed to obtain the CNV data of 79 Guangxi HCC patients. The prognostic effect of MT1-deletion was analyzed by univariate and multivariate Cox regression analysis. The differentially expressed genes (DEGs) were screened based on The Gene Expression Omnibus database (GEO) and the Liver Hepatocellular Carcinoma of The Cancer Genome Atlas (TCGA-LIHC). Then function and pathway enrichment analysis, protein-protein interaction (PPI) and hub gene selection were applied on the DEGs. Lastly, the hub genes were validated by immunohistochemistry, tissue expression and prognostic analysis. Results: The MT1-deletion was demonstrated to affect the prognosis of HCC and can act as an independent prognostic factor. 147 common DEGs were screened. The most significant cluster of DEGs identified by Molecular Complex Detection (MCODE) indicated that the expression of four MT1s were down-regulated. MT1X and other five hub genes (TTK, BUB1, CYP3A4, NR1I2, CYP8B1) were associated with the prognosis of HCC. TTK, could affect the prognosis of HCC with MT1-deletion and non-deletion. NR1I2, CYP8B1, and BUB1 were associated with the prognosis of HCC with MT1-deletion. Conclusions: In the current study, we demonstrated that MT1-deletion can be an independent prognostic factor in HCC. We identified TTK, BUB1, NR1I2, CYP8B1 by processing microarray data, for the first time revealed the underlying function of MT1 deletion in HCC, MT1-deletion may influence the gene expression in HCC, which may be the potential biomarkers for HCC with MT1 deletion.

Identification of a five-immune gene model as an independent prognostic factor in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a common malignant tumor with a poor prognosis. We aimed to identify a new prognostic model of HCC based on differentially expressed (DE) immune genes.MethodsThe DE immune genes were identified based on an analysis of 374 cases of HCC and 50 adjacent non-tumor specimens from the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis, Lasso regression, and multivariate Cox analysis were used to construct the model based on the training group. Survival analysis and the receiver operating characteristic (ROC) curves were used to evaluate model performance. The testing group and the entire group were subsequently used for validation of the model.ResultsA five-immune gene model consisted of HSPA4, ISG20L2, NDRG1, EGF, and IL17D was identified. Based on the model, the overall survival was significantly different between the high-risk and low-risk groups (P = 7.953e-06). The AUCs for the model at 1- and 3-year were 0.849 and 0.74, respectively. The reliability of the model was confirmed using the validation groups. The risk score was identified as an independent prognostic parameter and closely related to the content of immune cells from human HCC specimens.ConclusionWe identified a five-immune gene model that can be used as an independent prognostic marker for HCC.

The Relationship Between Plexin C1 Overexpression and Survival in Hepatocellular Carcinoma: a Turkish Oncology Group (TOG) Study

Plexin C1 is a transmembrane receptor and plexin C1 overexpression might have role in carcinogenesis. Hepatocellular carcinoma (HCC) has poor prognosis because of its aggressive behavior and limited treatment options, especially in advanced stage. We recently documented that Plexin C1 was overexpressed in HCC. We aimed to evaluate the prognostic significance of Plexin C1 overexpression in HCC in the present study. Plexin C1 overexpression was evaluated immunohistochemically on paraffin-embedded blocks of the HCC patients. Plexin C1 immunohistochemical staining was scored. Plexin C1 overexpression staining intensity and prevalence were used for plexin scale staining evaluation and plexin scores were estimated according this staining scale. Plexin C1 score and its association with survival and clinicopathological features was assessed. Sixty-seven HCC patients with adequate tissue for pathological evaluation were included. Median age was 63 years with male predominance (male to female ratio was 4.75 (n 57/12). Well-differentiated HCC (53.7%) patients had higher plexin C1 overexpression (p < 0.05). Median OS was 22.1 months. Patients with lower plexin C1 score (< 12) had shorter OS (17.5 vs 30.1 months, p = 0.036). Neutrophil count, GGT, and PNR (platelet/neutrophil ratio) had prognostic significance (p = 0.047, p = 0.018, and p = 0.045). Plexin C1 overexpression is inversely correlated with grade in HCC. The patients with lower rate of Plexin C1 overexpression have worse survival outcome. It might be a prognostic factor in HCC.

High expression of microRNA-1266 in hepatocellular carcinoma is associated with poor prognosis of patients and biological cell growth.

Hepatocellular carcinoma (HCC) is a cancer with a poor prognosis and a low survival rate. Previous studies have found that microRNA-1266 (miR-1266) is associated with tumorigenesis and progression of several types of cancer, such as breast cancer and gastric cancer. The aim of the present study was to investigate the effects of miR-1266 on the clinical prognosis and biological behavior of HCC. For this purpose, reverse transcription-quantitative PCR was used to detect the expression of miR-1266 in HCC tissues and HCC cell lines. In addition, Kaplan-Meier survival analysis and Cox regression analysis were used to evaluate the prognostic value of miR-1266. Cell Counting Kit-8 (CCK-8) and Transwell assays were used to analyze the effect of miR-1266 on the biological behavior of cells. The aforementioned assays demonstrated that the examined HCC tissues had a significant upregulation of miR-1266 expression compared with normal tissues (P<0.001). The overexpression of miR-1266 was significantly associated with Tumor-Node-Metastasis stage (P=0.014). The results of the Kaplan-Meier analysis indicated that the 5-year overall survival rate of patients with high expression of miR-1266 was significantly lower compared with patients with low expression of miR-1266 (P=0.015). Cox regression analysis demonstrated that the expression level of miR-1266 could be used as an independent prognostic factor of HCC. CCK-8 and Transwell assays demonstrated that overexpression of miR-1266 promoted the proliferation, migration and invasion of HCC cells. In summary, the findings of the present study indicated that high expression of miR-1266 was positively associated with poor prognosis of patients with HCC and promoted cell proliferation, migration and invasion of HCC cells. miR-1266 may be used as a biomarker for HCC prognosis.

Development of a novel lipid metabolism-based risk score model in hepatocellular carcinoma patients

BackgroundLiver cancer is one of the most common malignancies worldwide. HCC (hepatocellular carcinoma) is the predominant pathological type of liver cancer, accounting for approximately 75–85 % of all liver cancers. Lipid metabolic reprogramming has emerged as an important feature of HCC. However, the influence of lipid metabolism-related gene expression in HCC patient prognosis remains unknown. In this study, we performed a comprehensive analysis of HCC gene expression data from TCGA (The Cancer Genome Atlas) to acquire further insight into the role of lipid metabolism-related genes in HCC patient prognosis.MethodsWe analyzed the mRNA expression profiles of 424 HCC patients from the TCGA database. GSEA(Gene Set Enrichment Analysis) was performed to identify lipid metabolism-related gene sets associated with HCC. We performed univariate Cox regression and LASSO(least absolute shrinkage and selection operator) regression analyses to identify genes with prognostic value and develop a prognostic model, which was tested in a validation cohort. We performed Kaplan-Meier survival and ROC (receiver operating characteristic) analyses to evaluate the performance of the model.ResultsWe identified three lipid metabolism-related genes (ME1, MED10, MED22) with prognostic value in HCC and used them to calculate a risk score for each HCC patient. High-risk HCC patients exhibited a significantly lower survival rate than low-risk patients. Multivariate Cox regression analysis revealed that the 3-gene signature was an independent prognostic factor in HCC. Furthermore, the signature provided a highly accurate prediction of HCC patient prognosis.ConclusionsWe identified three lipid-metabolism-related genes that are upregulated in HCC tissues and established a 3-gene signature-based risk model that can accurately predict HCC patient prognosis. Our findings support the strong links between lipid metabolism and HCC and may facilitate the development of new metabolism-targeted treatment approaches for HCC.

Clinical efficacy and prognostic factors analysis following curative hepatectomy for hepatocellular carcinoma patients with different China Liver Cancer Staging

Objective: To examine clinical efficacy and prognostic factors of hepatocellular carcinoma(HCC) patients with different China Liver Cancer Staging (CNLC) after hepatectomy. Methods: From January 2010 to December,2019,549 patients underwent surgical resection and pathologically proven HCC were retrospectively reviewed in the First Affiliated Hospital of Nanjing Medical University. There were 462 males(84.2%) and 87 females(15.8%);the median age was 57 years (range: 21-84 years). Preoperative parameters,intraoperative and postoperative conditions,and postoperative pathological examination were observed.Survival analysis was performed by Kaplan-Meier method and the Log-rank test. Factors associated with disease-free survival(DFS) and overall survival(OS) of HCC patients were identified using univariate and multivariate Cox proportional hazards regression models. Results: Among the 549 patients underedwent liver resection,200 patients(36.4%) belonged to CNLC Ⅰa,whiles 148 patients(27.0%) belonged to CNLC Ⅰb. Furthermore,there were 49 patients(8.9%) with CNLC Ⅱa,32 patients(5.8%) with CNLC Ⅱb, 101 patients(18.4%) with CNLC Ⅲa and 19 patients(3.5%) with CNLC Ⅲb.The 1-,3-,5-,10-year OS for the entire cohort was 83.8%,69.0%,54.2%,37.7%,respectively,while 1-,3-, 5-year DFS was 61.0%,44.2%,36.0%, respectively. The 1-,3-, 5-year OS and DFS for CNLC Ⅰa were 97.3%,90.6%,80.5% and 83.9%,65.0%,54.0%,respectively;The 1-, 3-, 5-years OS and DFS for CNLC Ⅰb were 87.9%,71.0%,47.7%,and 58.4%,42.3%,33.4%,respectively.The 5-year OS for CNLC Ⅱa (37.2%) and Ⅱb(44.3%) were similar to CNLC Ⅰb. The 1-, 3-, 5-year OS and DFS for CNLC Ⅲb were 35.3%,13.2%,0 and 23.5%,0 and 0,respectively. Univariate analysis showed that preoperative symptoms,AFP level,total protein level,AST level,total bilirubin level,intraoperative blood loss,intraoperative or postoperative blood transfusion,postoperative complications,tumor number and size,microvascular invasion,macrovascular invasion and tumor differentiation were prognostic factors for long-term survival(≥5 years)(all P<0.05). The multivariate analysis suggested that AST level,intraoperative blood loss,tumor number and size,macrovascular invasion and tumor differentiation were the independent prognostic factors of long-term OS (all P<0.05). Conclusions: HCC patients with different stages of CNLC have different recurrence patterns and prognosis.After strict preoperative evaluation,patients with CNLC Ⅱa-Ⅲb can also benefit from radical resection. AST level,intraoperative blood loss,tumor number,tumor size,macrovascular invasion and tumor differentiation were independent factors that affect long-term survival. This will provide an important basis for the choice of treatment and the evaluation of surgical prognosis for patients with HCC.

Identification of a Novel Metastasis-Related miRNAs-Based Signature for Predicting the Prognosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common internal malignancies worldwide and is associated with a poor prognosis. Abnormal expression of miRNAs is believed to play a role in the recurrent metastasis of HCC. However, limited studies on the role of miRNAs in HCC metastasis have been carried out. Therefore, this study is aimed at exploring the potential value of metastasis-related miRNAs (MRMs) in HCC. We retrieved MRMs were from the Human Cancer Metastasis Database. Differential miRNAs were identified for tumor samples of HCC patients and normal samples based on the TCGA database. Further, univariate and multivariate Cox regression analyses were used to screen MRMs known to be independent prognostic factors in HCC. These MRMs were then used to build a prognostic signature. All patients were classified into high-risk and low-risk groups based on the median of the signature scores. Moreover, GO and KEGG pathway enrichment analyses were performed to predict the function of these MRMs. Finally, a nomogram was constructed to predict the OS of patients at 1, 2, and 3 years. In our study, a total of seven prognostic MRMs (miR-140-3p, miR-9-5p, miR-942-5p, miR-324-3p, miR-29c-5p, miR-551a, and miR-149-5p) were identified and used for constructing the prognostic signature based on the training cohort. Patients in the low-risk HCC group showed better overall survival (OS) than those in the high-risk group. The results were validated using the validation cohort. In summary, the findings of this study provide evidence that MRMs-based prognostic signature is an independent biomarker in the prognosis of HCC patients.

Integrative Analysis of HMMR as a Potential Target of Prognosis and Therapy in Hepatocellular Carcinoma

Background: Previous work has indicated Hyaluronic acid-mediated motor receptor (HMMR) plays an important role in regulating tumor metastasis. However, few researchers address the clinical significance of HMMR and its underlying mechanisms for regulating hepatocellular carcinoma (HCC). This study focuses on the underlying effect of HMMR in the development and prognosis of HCC. Materials and Methods: In the present study, data of RNA and miRNA sequencing array were obtained from Oncomine dataset or The Cancer Genome Atlas (TCGA) dataset, the distinctive genomic patterns associated with HMMR expression and its correlation with prognosis were analysed by using R package. Gene set enrichment analysis (GSEA) were performed on genes expressed aberrantly. We also performed Reverse Transcription-polymerase Chain Reaction (RT-PCR), Immunohistochemical (IHC) staining and Western blotting analysis to evaluate the expression of HMMR in liver cancer cell lines or 12 HCC samples from The Affiliated Hospital of Southwest Medical University. Results: A total of 407 tumor tissue samples in TCGA dataset were evaluated, combined with analysis in Oncomine dataset, we found HMMR expression was increased in HCC compared to normal tissues. Higher expression of HMMR was correlated with poorer overall survival and disease-free survival outcomes. Moreover, multivariate Cox regression analysis revealed that HMMR expression was an independent risk factor for overall survival (HMMR: hazard ratio [HR] = 1.154, 95% confidence interval [CI] = 1.080-1.233, p&lt;0.001). Consistently, RT-PCR, IHC staining and Western blotting analysis further confirmed that HMMR expression was increased in HCC compared with patient-matched adjacent normal liver tissues. Notably, GSEA analysis revealed that differential gene expression in HMMR-high patients (compared with HMMRlow patients) were enriched in cell proliferation and p53 signaling pathway. Moreover, comprehensive analysis showed a strong correlation between HMMR upregulation and miRNA changes. Conclusion: The high expression of HMMR is a poor prognostic factor in HCC and might serve as a potential target of therapy in patients with HCC.