Expression and clinical significance of miR-3615 in hepatocellular carcinoma

Objective To investigate the association between microRNA-3615 (miR-3615) expression and the prognosis and clinicopathological features in patients with hepatocellular carcinoma (HCC). Methods We obtained clinicopathological and genomic data and prognostic information on HCC patients from The Cancer Genome Atlas (TCGA) database. We then analyzed differences in miR-3615 expression levels between HCC and adjacent tissues using SPSS software, and examined the relationships between miR-3615 expression levels and clinicopathological characteristics. We also explored the influence of miR-3615 expression levels on the prognosis of HCC patients using Kaplan–Meier survival curve analysis. Results Based on data for 345 HCC and 50 adjacent normal tissue samples, expression levels of miR-3615 were significantly higher in HCC tissues compared with adjacent tissues. MiR-3615 expression levels in HCC patients were negatively correlated with overall survival time and positively correlated with high TNM stage, serum Ki-67 expression level, and serum alpha-fetoprotein level. There were no significant correlations between miR-3615 expression and age, sex, and pathological grade. Conclusion MiR-3615 may be a promising new biomarker and prognostic factor for HCC.

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NDRG3 overexpression is associated with a poor prognosis in patients with hepatocellular carcinoma

Bioscience Reports ◽

10.1042/bsr20180907 ◽

2018 ◽

Vol 38 (6) ◽

Cited By ~ 1

Author(s):

Ji-sheng Jing ◽

Hongbo Li ◽

Shun-cai Wang ◽

Jiu-ming Ma ◽

La-qing Yu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Cox Regression ◽

Survival Curve ◽

Disease Free Survival ◽

Prognostic Indicator ◽

Clinicopathological Characteristics ◽

Pcr Analysis ◽

Kaplan Meier ◽

Tumor Tissues ◽

The Relationship

N-myc downstream-regulated gene 3 (NDRG3), an important member of the NDRG family, is involved in cell proliferation, differentiation, and other biological processes. The present study analyzed NDRG3 expression in hepatocellular carcinoma (HCC) and explored the relationship between expression of NDRG3 in HCC patients and their clinicopathological characteristics. We performed quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis and immunohistochemistry (IHC) analyses on HCC tissues to elucidate NDRG3 expression characteristics in HCC patients. Kaplan–Meier survival curve and Cox regression analyses were used to evaluate the prognoses of 102 patients with HCC. The results revealed that compared with non-tumor tissues, HCC tissues showed significantly higher NDRG3 expression. In addition, our analyses showed that NDRG3 expression was statistically associated with tumor size (P=0.048) and pathological grade (P=0.001). Survival analysis and Kaplan–Meier curves revealed that NDRG3 expression is an independent prognostic indicator for disease-free survival (P=0.002) and overall survival (P=0.005) in HCC patients. The data indicate that NDRG3 expression may be considered as a oncogenic biomarker and a novel predictor for HCC prognosis.

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Multi-Omic Analyses of the m5C Regulator ALYREF Reveal Its Essential Roles in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.633415 ◽

2021 ◽

Vol 11 ◽

Author(s):

Chen Xue ◽

Yalei Zhao ◽

Ganglei Li ◽

Lanjuan Li

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Immune Cell ◽

The Cancer Genome Atlas ◽

Cancer Tissue ◽

Hub Genes ◽

Specific Expression ◽

Tissue Samples ◽

Expression Levels ◽

Advanced Tumor

The ALYREF protein acts as a crucial epigenetic regulator in several cancers. However, the specific expression levels and functional roles of ALYREF in cancers are largely unknown, including for hepatocellular carcinoma (HCC). In a pan-cancer tissue analysis that included HCC, we assessed the expression of ALYREF compared to normal tissues using The Cancer Genome Atlas database. Associations between ALYREF gene expression and the clinical characteristics of HCC patient samples were assessed using the UALCAN database. Kaplan-Meier plots were performed to assess HCC patient prognosis, and the TIMER database was used to explore associations between ALYREF expression and immune-cell infiltrations. The same methods were used to assess eIF4A3 expression in HCC patient samples. In addition, ALYREF- and elF4A3-related differentially expressed genes (DEGs) were determined using LinkedOmics, associated protein functionalities were predicted for positively associated DEGs, and both the TargetScan and miRDB databases were used to predict potential upstream miRNAs for control of ALYREF and eIF4A3 expression. We found that ALYREF gene expression was dysregulated in several cancers and was significantly elevated in HCC patient tissue samples and HCC cell lines. The overexpression of ALYREF was significantly related to both advanced tumor-node-metastasis stages and poor HCC prognosis. Furthermore, we found that eIF4A3 expression was significantly correlated with ALYREF expression, and that upregulated eIF4A3 was significantly associated with poor HCC patient outcomes. In the protein-protein interaction network, we identified eight hub genes based on the positively associated DEGs in common between ALYREF and eIF4A3, and the high expression levels of these hub genes were positively associated with patient clinical outcomes. In addition, we identified miR-4666a-5p and miR-6124 as potential regulators of ALYREF and eIF4A3 expression. These findings suggest that increased ALYREF expression may function as a novel biomarker for both HCC diagnosis and prognosis predictions.

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Identification of RASSF1A Promoter Hypermethylation as a Biomarker for Hepatocellular Carcinoma

10.21203/rs.3.rs-54668/v2 ◽

2020 ◽

Author(s):

Gang Xu ◽

Xiaoxiang Zhou ◽

Jiali Xing ◽

Yao Xiao ◽

Bao Jin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Promoter Methylation ◽

Meta Analysis ◽

Promoter Hypermethylation ◽

Analysis Data ◽

Clinicopathological Characteristics ◽

The Cancer Genome Atlas ◽

Large Tumor ◽

Kaplan Meier ◽

Cancer Genome Atlas

Abstract Background: RAS association domain family protein 1A (RASSF1A) promoter hypermethylation is suggested to be linked to hepatocellular carcinoma (HCC), but the results remained controversial.Methods: We evaluated how RASSF1A promoter hypermethylation affects HCC risk and its clinicopathological characteristics through meta-analysis. Data on DNA methylation in HCC and relevant clinical data were also collected based on The Cancer Genome Atlas (TCGA) database to investigate the prognostic role of RASSF1A promoter hypermethylation in HCC.Results: Forty-four articles involving 4,777 individuals were enrolled in the pooled analyses. The RASSF1A promoter methylation rate was notably higher in the HCC cases than the non-tumor cases and healthy individuals, and was significantly related to hepatitis B virus (HBV) infection-positivity and large tumor size. Kaplan–Meier survival analysis revealed that HCC cases with RASSF1A promoter hypermethylation had worse outcomes. Receiver operating characteristic curves confirmed that RASSF1A promoter methylation may be a marker of HCC-related prognoses.Conclusions: RASSF1A promoter hypermethylation is a promising biomarker for the diagnosis of HCC from tissue and peripheral blood, and is an emerging therapeutic target against HCC.

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Prognostic Value of Phosphotyrosine Phosphatases in Hepatocellular Carcinoma

Cellular Physiology and Biochemistry ◽

10.1159/000489625 ◽

2018 ◽

Vol 46 (6) ◽

pp. 2335-2346 ◽

Cited By ~ 7

Author(s):

Guangyan Zhangyuan ◽

Yin Yin ◽

Wenjie Zhang ◽

WeiWei Yu ◽

Kangpeng Jin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Proportional Hazards ◽

Proportional Hazards Model ◽

Cox Proportional Hazards ◽

Cox Proportional Hazards Model ◽

The Cancer Genome Atlas ◽

Expression Levels ◽

Hazards Model ◽

Kaplan Meier ◽

Phosphotyrosine Phosphatases

Background/Aims: During the occurrence and progression of hepatocellular carcinoma (HCC), phosphotyrosine phosphatases (PTPs) are usually described as tumor suppressors or proto-oncogenes, and to some degree are correlated with the prognosis of HCC. Methods: A total of 321 patients from the Cancer Genome Atlas (TCGA) database and 180 patients from our validated cohort with hepatocellular carcinoma were recruited in this study. Kaplan-Meier, univariate and multivariate Cox proportional hazards model were used to evaluate the risk factors for survival. Quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) were applied to detect the expression levels of PTP genes. Results: After screening the data of TCGA, we identified five PTPs as HCC overall survival related PTP genes, among which only three (PTPN12, PTPRN, PTPN18) exhibited differential expression levels in our 180 paired HCC and adjacent tissues (P< 0.001). Further analysis revealed that expression of PTPN18 was positively, but PTPRN was negatively associated with prognosis of HCC both in TCGA cohort and our own cohort. As to PTPN12, results turned out to be opposite according to HBV status. In detail, higher expression of PTPN12 was associated with better outcome in HBV group but worse prognosis in Non-HBV group. Conclusion: Our results suggested that PTPN12, PTPRN and PTPN18 were independent prognostic factors in HCC.

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Identification of Prognostic Biomarkers and Independent Indicators Among PFDN1/2/3/4/5/6 in Liver Hepatocellular Carcinoma

10.21203/rs.3.rs-725619/v1 ◽

2021 ◽

Author(s):

Yin-Hai Dai ◽

Fuping Li ◽

Wei-Jie Kong ◽

Xue-Qin Zhang ◽

Mao Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

Human Cancer ◽

Normal Liver ◽

The Cancer Genome Atlas ◽

Prognostic Biomarkers ◽

Expression Levels ◽

Kaplan Meier ◽

Human Protein Atlas ◽

Liver Hepatocellular Carcinoma

Abstract Background: Previous studies have proved that the aberrant expressions of PFDNs (Prefoldin) family proteins were correlated with several human cancer. However, the specific functions of PFDNs in liver hepatocellular carcinoma(LIHC) remain unknown. The study aimed to identify the prognostic biomarkers and independent indicators among PFDN1/2/3/4/5/6 in liver hepatocellular carcinoma.Methods: We used these databases including Oncomine, Ualcan, GEPIA2, Human Protein Atlas, The Cancer Genome Atlas, Kaplan-Meier plotter, cBioPortal, STRI-NG and TIMER and the software of Cytoscape in our study.Results: PFDN1/2/3/4/5/6 were highly expressed in LIHC tissues. The mRNA expression levels of PFDN1/2/3/4/5/6 were relevant to tumor grades.PFDN1/3/4/5 expressions significantly changed in different cancer stages. The protein expression levels of PFDNs were higher in LIHC tissue than normal liver tissue. Moreover, High mRNA expressions of PFDN1/2/3/4 were associated with shorter OS of LIHC patients. In multivariate analysis,high expressions of PFDN1/2/4 were independently correlated with poorer OS of LIHC patients. In our findings,55% of patients with LIHC had genetic mutations on PFDNs. Besides, there were significant associations between the expressions of PFDN1/2/3/4/5 and six types of infiltrated immune cells(B cells, CD4+T cells, CD8+T cells, neutrophil, macrophage, and dendritic cells).Conclusions:PFDN1/2/3/4 were potential prognostic markers to suggest poor OS of LIHC patients. In addition, high PFDN1/2/4 expressions were independent prognostic factors in OS for LIHC patients.

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The High Expression of PTPRH Is Associated with Poor Prognosis of Human Lung Adenocarcinoma

Computational and Mathematical Methods in Medicine ◽

10.1155/2021/9932088 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Aifeng Chen ◽

Shibiao Ding ◽

Xiaoqiang Shen ◽

Xuai Lin

Keyword(s):

Lung Adenocarcinoma ◽

Roc Curve ◽

Immunohistochemical Staining ◽

Poor Prognosis ◽

Clinicopathological Characteristics ◽

The Cancer Genome Atlas ◽

Disease Stage ◽

Tissue Samples ◽

Qrt Pcr ◽

Kaplan Meier

Objective. The aim of the study is to explore the prognosis value of PTPRH in patients with lung adenocarcinoma (LUAD). Methods. Oncomine, UALCAN, and GEPIA databases were employed to examine the differential expression of PTPRH between LUAD and adjacent tissues. 100 pairs of LUAD and adjacent tissue samples were involved in this study. qRT-PCR and immunohistochemical staining were performed. Meanwhile, we analyzed The Cancer Genome Atlas (TCGA) data to investigate the correlation between PTPRH gene expression and clinicopathological characteristics. Kaplan-Meier analysis and univariate and multivariate Cox analyses were performed to estimate the relationship between PTPRH expression and LUAD prognosis. The evaluation performance was verified by drawing a ROC curve. In addition, through GSEA, the changes of PTPRH expression were analyzed by GSEA to screen out primarily affected signaling pathway. Results. Oncomine, UALCAN, and GEPIA databases showed that the mRNA expression of PTPRH in LUAD tissues was significantly higher than that in adjacent tissues. qRT-PCR and immunohistochemical staining indicated the mRNA and protein levels of PTPRH in LUAD tissues were markedly upregulated. TCGA data showed that the expression of PTPRH was significantly correlated with T stage and disease stage. Kaplan-Meier analysis showed that the patients with high PTPRH expression had a poor prognosis. Univariate and multivariate Cox analyses exhibited that PTPRH expression could act as an independent prognostic factor for LUAD. The ROC curve showed that PTPRH combined with various clinicopathological features could effectively predict the prognosis of LUAD. Finally, GSEA indicated that changes in PTPRH expression level may affect p53, VEGF, Notch, and mTOR cancer-related signaling pathways. Conclusion. Our results demonstrated that PTPRH was highly expressed in LUAD and may be closely correlated with the poor prognosis of LUAD patients.

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Identification of RASSF1A promoter hypermethylation as a biomarker for hepatocellular carcinoma

Cancer Cell International ◽

10.1186/s12935-020-01638-5 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Gang Xu ◽

Xiaoxiang Zhou ◽

Jiali Xing ◽

Yao Xiao ◽

Bao Jin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Promoter Methylation ◽

Meta Analysis ◽

Promoter Hypermethylation ◽

Analysis Data ◽

Clinicopathological Characteristics ◽

The Cancer Genome Atlas ◽

Large Tumor ◽

Kaplan Meier ◽

Cancer Genome Atlas

Abstract Background RAS association domain family protein 1A (RASSF1A) promoter hypermethylation is suggested to be linked to hepatocellular carcinoma (HCC), but the results remained controversial. Methods We evaluated how RASSF1A promoter hypermethylation affects HCC risk and its clinicopathological characteristics through meta-analysis. Data on DNA methylation in HCC and relevant clinical data were also collected based on The Cancer Genome Atlas (TCGA) database to investigate the prognostic role of RASSF1A promoter hypermethylation in HCC. Results Forty-four articles involving 4777 individuals were enrolled in the pooled analyses. The RASSF1A promoter methylation rate was notably higher in the HCC cases than the non-tumor cases and healthy individuals, and was significantly related to hepatitis B virus (HBV) infection-positivity and large tumor size. Kaplan–Meier survival analysis revealed that HCC cases with RASSF1A promoter hypermethylation had worse outcomes. Receiver operating characteristic curves confirmed that RASSF1A promoter methylation may be a marker of HCC-related prognoses. Conclusions RASSF1A promoter hypermethylation is a promising biomarker for the diagnosis of HCC from tissue and peripheral blood, and is an emerging therapeutic target against HCC.

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Identification of RASSF1A Promoter Hypermethylation as a Biomarker for Hepatocellular Carcinoma

10.21203/rs.3.rs-54668/v1 ◽

2020 ◽

Author(s):

Gang Xu ◽

Xiaoxiang Zhou ◽

Jiali Xing ◽

Yao Xiao ◽

Bao Jin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Promoter Methylation ◽

Meta Analysis ◽

Promoter Hypermethylation ◽

Analysis Data ◽

Clinicopathological Characteristics ◽

The Cancer Genome Atlas ◽

Large Tumor ◽

Kaplan Meier ◽

Cancer Genome Atlas

Abstract Background: RAS association domain family protein 1A (RASSF1A) promoter hypermethylation is suggested to be linked to hepatocellular carcinoma (HCC), but the results remained controversial. Methods: We evaluated how RASSF1A promoter hypermethylation affects HCC risk and its clinicopathological characteristics through meta-analysis. Data on DNA methylation in HCC and relevant clinical data were also collected based on The Cancer Genome Atlas (TCGA) database to investigate the prognostic role of RASSF1A promoter hypermethylation in HCC. Results: Forty-four articles involving 4,777 cases were enrolled in the pooled analyses. The RASSF1A promoter methylation rate was notably higher in the HCC cases than the non-tumor cases and healthy individuals, and was significantly related to hepatitis B virus (HBV) infection-positivity and large tumor size. Kaplan–Meier survival analysis revealed that HCC cases with RASSF1A promoter hypermethylation had worse outcomes. Receiver operating characteristic curves confirmed that RASSF1A promoter methylation may be a marker of HCC-related prognoses. Conclusions: RASSF1A promoter hypermethylation is a promising biomarker for the diagnosis of HCC from tissue and peripheral blood, and is an emerging therapeutic target against HCC.

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Possible Role of IRS-4 in the Origin of Multifocal Hepatocellular Carcinoma

Cancers ◽

10.3390/cancers13112560 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2560

Author(s):

Luis G. Guijarro ◽

Patricia Sanmartin-Salinas ◽

Eva Pérez-Cuevas ◽

M. Val Toledo-Lobo ◽

Jorge Monserrat ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Cancer ◽

Hepg2 Cells ◽

Cellular Polarity ◽

Ki 67 ◽

Tissue Samples ◽

Vitro Analysis ◽

Tumoral Cells

New evidence suggests that insulin receptor substrate 4 (IRS-4) may play an important role in the promotion of tumoral growth. In this investigation, we have evaluated the role of IRS-4 in a pilot study performed on patients with liver cancer. We used immunohistochemistry to examine IRS-4 expression in biopsies of tumoral tissue from a cohort of 31 patient suffering of hepatocellular carcinoma (HCC). We simultaneously analyzed the expression of the cancer biomarkers PCNA, Ki-67, and pH3 in the same tissue samples. The in vitro analysis was conducted by studying the behavior of HepG2 cells following IRS-4 overexpression/silencing. IRS-4 was expressed mainly in the nuclei of tumoral cells from HCC patients. In contrast, in healthy cells involved in portal triads, canaliculi, and parenchymal tissue, IRS-4 was observed in the cytosol and the membrane. Nuclear IRS-4 in the tumoral region was found in 69.9 ± 3.2%, whereas in the surrounding healthy hepatocytes, nuclear IRS-4 was rarely observed. The percentage of tumoral cells that exhibited nuclear PCNA and Ki-67 were 52.1 ± 7%, 6.1 ± 1.1% and 1.3 ± 0.2%, respectively. Furthermore, we observed a significant positive linear correlation between nuclear IRS-4 and PCNA (r = 0.989; p < 0.001). However, when we correlated the nuclear expression of IRS-4 and Ki-67, we observed a significant positive curvilinear correlation (r = 0.758; p < 0.010). This allowed us to define two populations, (IRS-4 + Ki-67 ≤ 69%) and (IRS-4 + Ki-67 > 70%). The population with lower levels of IRS-4 and Ki-67 had a higher risk of suffering from multifocal liver cancer (OR = 16.66; CI = 1.68–164.8 (95%); p < 0.05). Immunoblot analyses showed that IRS-4 in normal human liver biopsies was lower than in HepG2, Huh7, and Chang cells. Treatment of HepG2 with IGF-1 and EGF induced IRS-4 translocation to the nucleus. Regulation of IRS-4 levels via HepG2 transfection experiments revealed the protein’s role in proliferation, cell migration, and cell-collagen adhesion. Nuclear IRS-4 is increased in the tumoral region of HCC. IRS-4 and Ki-67 levels are significantly correlated with the presence of multifocal HCC. Moreover, upregulation of IRS-4 in HepG2 cells induced proliferation by a β-catenin/Rb/cyclin D mechanism, whereas downregulation of IRS-4 caused a loss in cellular polarity and in its adherence to collagen as well as a gain in migratory and invasive capacities, probably via an integrin α2 and focal adhesion cascade (FAK) mechanism.

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Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽

10.1186/s12885-021-08173-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Ping Yan ◽

Zuotian Huang ◽

Tong Mou ◽

Yunhai Luo ◽

Yanyao Liu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Malignant Tumors ◽

Expression Profiles ◽

Clinical Information ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

High Rate ◽

Competing Endogenous Rna ◽

Tissue Samples ◽

Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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