Upregulated KPNA2 promotes hepatocellular carcinoma progression and indicates prognostic significance across human cancer types

The landscape in telomere related gene prognostic signature for survival and medication treatment effectiveness prediction in hepatocellular carcinoma

OBJECTIVE

Telomeres, made of repetitive DNA sequences and shelterin complexes, which were found at the ends of chromosomes and had been extensively studied in cancer research. However, in hepatocellular carcinoma (HCC) was still relatively scarce. In this study, we investigated the correlation between telomerase-related genes (TRGs) and the prognosis and immunotherapy of HCC patients to enhance clinical outcomes.

METHODS

In this work, TRGs were gathered using TelNet, while clinical information and gene expression data for HCC patients were retrieved from the Cancer Genome Atlas (TCGA) database. A risk prediction model based on TRGs was created using COX and Lasso regression analyses, with ROC curves used to assess prognostic efficacy. Univariate and multifactorial COX regression analyses were used to determine if the risk model had an independent impact on prognosis. Nomograms were created to enhance clinical usability, and calibration curves were used to assess predictive ability at various time points. The Tumor Immune Dysfunction and Exclusion (TIDE) score was used to analyze differences in immune infiltrating cells between risk groups. The study analyzed the relationship between risk ratings and drug treatment effectiveness using data from the CellMiner database. The hub gene was identified and its relationship to prognostic markers of HCC patients was examined. The expression of hub genes in immune cell subpopulations was also investigated by single-cell data.

RESULTS

2093 TRGs were identified, with 949 showing significant differences in expression between HCC and paracancerous tissues. Seven risk genes were overexpressed in tumor tissues, leading to lower survival rates in high-risk patients. Risk model could independently predict the prognosis of HCC patients. Analysis of tumor immune infiltrating cells revealed significant differences in cell abundance between risk groups, with notable variations in immune subset enrichment between subgroups. Higher risk scores correlated with increased sensitivity to sorafenib, mitoxantrone, oxaliplatin, gemcitabine, and entinostat, while sensitivity decreased for vincristine, etc. CDCA8 was identified as a key gene in the Protein Interaction Network, while high expression associated with poorer overall survival, tumor proliferation and metastasis. The results of single-cell data analysis suggest that CDCA8 may promote the development of HCC by affecting T lymphocytes.

CONCLUSION

The TRG-based risk model could predict HCC patient prognosis and closely linked to tumor immune environment, which could offer new possibilities for clinical treatment.

Silencing KPNA2 Promotes Ferroptosis in Laryngeal Cancer by Activating the FoxO Signaling Pathway

We aim to clarify the specific role of Karyopherin α2 (KPNA2) in the progression of laryngeal cancer, a kind of malignant tumor with a poor curative effect. We performed the bioinformatic analysis to obtain the ferroptosis-related differentially expressed genes. KPNA2 was screened out. Then the CCK-8 assay, wound healing assay, and transwell assay were used to clarify the changes in the proliferation, migration, and invasion abilities of laryngeal cancer cells after silencing KPNA2. The concentrations of iron ions, glutathione, superoxide dismutase, and malondialdehyde were evaluated by the corresponding detection kits. The expression levels of cyclooxygenase 2, Acyl-CoA synthetase long-chain family member 4, glutathione peroxidase 4, forkhead box O (FoxO)1a and FoxO3a were determined by Western Blot. A total of 45 ferroptosis-related differentially expressed genes in laryngeal cancer were obtained, and KPNA2 was selected after bioinformatic analysis. In ferroptosis-induced laryngeal cancer cells, the cell viability, migration rate, invasion ability, and the expression of glutathione peroxidase 4, glutathione, and superoxide dismutase were further decreased and the expression of cyclooxygenase 2, Acyl-CoA synthetase long-chain family member 4, iron ions, and malondialdehyde were further increased after silencing KPNA2. The expression levels of FoxO1a and FoxO3a in laryngeal cancer cells were increased by silencing KPNA2. KPNA2 may be a promising therapeutic target for laryngeal cancer. Down-regulation of KPNA2 can promote ferroptosis in laryngeal cancer by stimulating the FoxO signaling pathway.

Shared and specific competing endogenous RNAs network mining in four digestive system tumors

Background

Digestive system malignancies, including esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), liver hepatocellular carcinoma (LIHC), and colon adenocarcinoma (COAD), pose significant global health challenges. Identifying shared and distinct regulatory mechanisms across these cancers can lead to improved therapies. This study aims to construct and compare competing endogenous RNA (ceRNA) networks across ESCA, STAD, LIHC, and COAD to identify RNA biomarkers that could serve as precision therapeutic targets to enhance clinical outcomes and advance personalized cancer care.

Methods

Clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to predict differentially expressed RNAs using the edgeR package. The ceRNA networks were constructed using the miRcode and ENCORI databases. Functional enrichment analysis and prognostic RNA screening were performed with ConsensusPathDB and univariate Cox regression analysis.

Results

we identified 6, 88, 55, and 41 RNA biomarkers in ESCA, STAD, LIHC, and COAD, respectively. Network analysis revealed shared and specific elements, with shared nodes enriched in cell cycle and mitotic processes. Several biomarkers, including HMGB3 and RGS16 (ESCA), COL4A1 and COL6A3 (STAD), CDCA5 and CDCA8 (LIHC), and LIMK1 and OSBPL3 (COAD), were consistent with prior studies, while novel biomarkers, such as C3P1 (ESCA), P2RY6 (STAD), and N4BP2L1 and PPP1R3B (LIHC), were discovered. Based on RNA correlation analysis, 1, 23, and 2 potential ceRNA regulatory axes were identified in STAD (PVT1/miR-490-3p/HMGA2), LIHC (DLX6-AS1/miR-139-5p/TOP2A, etc.), and COAD (STRCP1 & LINC00488/miR-142-3p/GAB1), respectively.

Conclusions

This study advances the understanding of ceRNA networks in digestive cancers, highlighting RNA biomarkers with potential as therapeutic targets for personalized treatment strategies.

Exploring casual effects and shared molecular mechanism between psoriasis and liver cancer through Mendelian randomization and comprehensive bioinformatic analyses

Psoriasis (Ps), a chronic inflammatory disease affecting approximately 2 % of the global population, has been associated with an increased risk of liver cancer in observational studies. However, their causal relationships as well as underlying shared molecular mechanisms between Ps and liver cancer remain unclear. Using bidirectional Mendelian randomization analysis, we revealed that a genetic predisposition to liver cancer increased the risk of Ps in European and East Asian populations but not the other way around. Moreover, we analyzed three transcriptomic datasets of patients with Ps and liver cancer from open-source databases. Differentially expressed genes (DEGs) and disease-specific gene co-expression module analyses revealed that cell-cycle dysregulation was the shared mechanism of Ps and liver cancer. Moreover, we identified a rank-conservative gene signature shared between these two diseases, which demonstrated significance in diagnostic and prognostic predictions. These findings provided valuable insights into the interconnections between Ps and liver cancer, which may be helpful to guide therapeutic management.

Unraveling the underlying pathogenic factors driving nonalcoholic steatohepatitis and hepatocellular carcinoma: an in-depth analysis of prognostically relevant gene signatures in hepatocellular carcinoma

BACKGROUND

Nonalcoholic steatohepatitis (NASH) is a progressive manifestation of nonalcoholic fatty liver disease (NAFLD) that can lead to fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Despite the growing knowledge of NASH and HCC, the association between the two conditions remains to be fully explored. Bioinformatics has emerged as a valuable approach for identifying disease-specific feature genes, enabling advancements in disease prediction, prevention, and personalized treatment strategies.

MATERIALS AND METHODS

In this study, we utilized CellChat, copy number karyotyping of aneuploid tumors (CopyKAT), consensus Non-negative Matrix factorization (cNMF), Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), Monocle, spatial co-localization, single sample gene set enrichment analysis (ssGSEA), Slingshot, and the Scissor algorithm to analyze the cellular and immune landscape of NASH and HCC. Through the Scissor algorithm, we identified three cell types correlating with disease phenotypic features and subsequently developed a novel clinical prediction model using univariate, LASSO, and multifactor Cox regression.

RESULTS

Our results revealed that macrophages are a significant pathological factor in the development of NASH and HCC and that the macrophage migration inhibitory factor (MIF) signaling pathway plays a crucial role in cellular crosstalk at the molecular level. We deduced three prognostic genes (YBX1, MED8, and KPNA2), demonstrating a strong diagnostic capability in both NASH and HCC.

CONCLUSION

These findings shed light on the pathological mechanisms shared between NASH and HCC, providing valuable insights for the development of novel clinical strategies.

The role of KPNA2 as a monotonically changing differentially expressed gene in the diagnosis, risk stratification, and chemotherapy sensitivity of chronic hepatitis B-liver cirrhosis-hepatocellular carcinoma

PURPOSE

Chronic hepatitis B-liver cirrhosis-hepatocellular carcinoma (CLH), commonly called the "liver cancer trilogy", is a crucial evolutionary phase in the emergence of hepatocellular carcinoma (HCC) in China. Previous studies on early diagnostic biomarkers of HCC were limited to the end-stage of HCC and did not focus on the evolutionary process of CLH.

METHODS

11 monotonically changing differentially expressed genes (MCDEGs) highly correlated with CLH were screened through bioinformatic analysis and KPNA2 was identified for further research. The serum KPNA2 expression in different CLH states was detected by Enzyme linked immunosorbent assay (ELISA). A nomogram model was constructed using univariate and multivariate Cox regression methods.

RESULTS

The single-cell RNA-seq and bulk RNA-seq revealed that KPNA2 related to immune infiltration in HCC and may participate in cell cycle pathways in HCC. The serum KPNA2 expression was monotonically upregulated in CLH and was valuable for diagnosing different CLH states. Besides, chronic hepatitis B(CHB) patients, liver cirrhosis (LC) patients, and HCC patients were classified into subgroups with distinct serum KPNA2 expressions. Accordingly, patients with different serum KPNA2 expressions displayed various clinicopathological features. The AUC value of the nomogram model was 0.959 in predicting the likelihood of developing HCC in CHB patients or LC patients. Finally, we found that KPNA2 expression was negatively correlated with the IC50 of four chemotherapeutic drugs in HCC.

CONCLUSION

KPNA2 was a novel serum biomarker for diagnosing different CLH states, monitoring the dynamic evolution of CLH, and a new therapeutic target for intervening in the progression of CLH.

Novel roles of karyopherin subunit alpha 2 in hepatocellular carcinoma

Hepatocellular carcinoma is the most common type of liver cancer and associated with a high fatality rate. This disease poses a major threat to human health worldwide. A considerable number of genetic and epigenetic factors are involved in the development of hepatocellular carcinoma. However, the molecular mechanism underlying the progression of hepatocellular carcinoma remains unclear. Karyopherin subunit alpha 2 (KPNA2), also termed importin α1, is a member of the nuclear transporter family. In recent years, KPNA2 has been gradually linked to the nuclear transport pathway for a variety of tumor-associated proteins. Furthermore, it promotes tumor development by participating in various pathophysiological processes such as cell proliferation, apoptosis, immune response, and viral infection. In hepatocellular carcinoma, it has been found that KPNA2 expression is significantly higher in liver cancer tissues versus paracancerous tissues. Moreover, it has been identified as a marker of poor prognosis and early recurrence in patients with hepatocellular carcinoma. Nevertheless, the role of KPNA2 in the development of hepatocellular carcinoma remains to be determined. This review summarizes the current knowledge on the pathogenesis and role of KPNA2 in hepatocellular carcinoma, and provides new directions and strategies for the diagnosis, treatment, and prediction of prognosis of this disease.

Estrogen-related genes influence immune cell infiltration and immunotherapy response in Hepatocellular Carcinoma

Background

Immunotherapy has been the first-line treatment option in advanced Hepatocellular Carcinoma(HCC); but now, there are no established molecular markers that can predict immunotherapy response. Estrogen has a crucial role in the development of a variety of liver illnesses, including liver fibrosis, Nonalcoholic fatty liver disease (NAFLD), and HCC. Nonetheless, the significance of estrogen-related genes in HCC immunotherapy and the underlying molecular mechanisms are not yet fully understood.

Method

In this study, we constructed a novel estrogen-related gene prognostic signature (ERGPS) by analyzing bulk RNA sequencing data from 365 HCC patients. Based on the median risk score, we divided 365 HCC patients into low- and high-risk groups. Tumor mutation burden (TMB), Microsatellite instability (MSI), T cell receptor (TCR) richness, B cell receptor (BCR) richness, single-nucleotide variants (SNV) Neoantigens, Cancer Testicular Antigens (CTA) scores, and Tumour Immune Dysfunction and Exclusion (TIDE) scores were used to evaluate the magnitude of immunotherapy response. Multiple external datasets validate the validity and robustness of the prognostic signature. Real-time quantitative polymerase chain reaction (qRT-PCR) was used to validate estrogen-related gene overexpression in HCC tissue samples.

Results

ERGPS is an independent risk factor affecting the prognosis of HCC patients and is superior to other clinical variables in predicting patient survival and immunotherapy response. Multiple independent external datasets confirmed the superior predictive efficacy of the prognostic signature. The prognostic signature was positively correlated with TMB score, MSI score, TCR richness, BCR richness, SNV Neoantigens score, CTA score, expression levels of immune checkpoint-related genes, and TIDE score. Patients with HCC in the high-risk group identified by the prognostic signature were likely to be more responsive to immunotherapy and more suitable for immunotherapy. qRT-PCR confirmed that estrogen-related genes of the construct signature were highly expressed in HCC tumor tissues.

Conclusion

Estrogen-related genes are overexpressed in HCC tissues. Our novel prognostic signature can accurately predict not only the prognosis but also the immunotherapy response of HCC patients. In the future, prognostic signatures will be a useful tool for clinicians to screen patients with HCC who are suitable for immunotherapy.

Single-cell transcriptome analysis reveals the metabolic changes and the prognostic value of malignant hepatocyte subpopulations and predict new therapeutic agents for hepatocellular carcinoma

Background

The development of HCC is often associated with extensive metabolic disturbances. Single cell RNA sequencing (scRNA-seq) provides a better understanding of cellular behavior in the context of complex tumor microenvironments by analyzing individual cell populations.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data was employed to investigate the metabolic pathways in HCC. Principal component analysis (PCA) and uniform manifold approximation and projection (UMAP) analysis were applied to identify six cell subpopulations, namely, T/NK cells, hepatocytes, macrophages, endothelial cells, fibroblasts, and B cells. The gene set enrichment analysis (GSEA) was performed to explore the existence of pathway heterogeneity across different cell subpopulations. Univariate Cox analysis was used to screen genes differentially related to The Overall Survival in TCGA-LIHC patients based on scRNA-seq and bulk RNA-seq datasets, and LASSO analysis was used to select significant predictors for incorporation into multivariate Cox regression. Connectivity Map (CMap) was applied to analysis drug sensitivity of risk models and targeting of potential compounds in high risk groups.

Results

Analysis of TCGA-LIHC survival data revealed the molecular markers associated with HCC prognosis, including MARCKSL1, SPP1, BSG, CCT3, LAGE3, KPNA2, SF3B4, GTPBP4, PON1, CFHR3, and CYP2C9. The RNA expression of 11 prognosis-related differentially expressed genes (DEGs) in normal human hepatocyte cell line MIHA and HCC cell lines HCC-LM3 and HepG2 were compared by qPCR. Higher KPNA2, LAGE3, SF3B4, CCT3 and GTPBP4 protein expression and lower CYP2C9 and PON1 protein expression in HCC tissues from Gene Expression Profiling Interactive Analysis (GEPIA) and Human Protein Atlas (HPA) databases. The results of target compound screening of risk model showed that mercaptopurine is a potential anti-HCC drug.

Conclusion

The prognostic genes associated with glucose and lipid metabolic changes in a hepatocyte subpopulation and comparison of liver malignancy cells to normal liver cells may provide insight into the metabolic characteristics of HCC and the potential prognostic biomarkers of tumor-related genes and contribute to developing new treatment strategies for individuals.

A Five-LLPS Gene Risk Score Prognostic Signature Predicts Survival in Hepatocellular Carcinoma

Background

Primary liver cancer, dominated by hepatocellular carcinoma (HCC), is one of the most common cancer types and the third leading cause of cancer death in 2020. Previous studies have shown that liquid-liquid phase separation (LLPS) plays an important role in the occurrence and development of cancer including HCC, but its influence on the patient prognosis is still unknown. It is necessary to explore the effect of LLPS genes on prognosis to accurately forecast the prognosis of HCC patients and identify relevant targeted therapeutic sites.

Methods

Using The Cancer Genome Atlas dataset and PhaSepDB dataset, we identified LLPS genes linked to the overall survival (OS) of HCC patients. We applied Least Absolute Shrinkage and Selection Operator (LASSO) Cox penalized regression analysis to choose the best genes for the risk score prognostic signature. We then analysed the validation dataset and evaluated the effectiveness of the risk score prognostic signature. Finally, we performed quantitative real-time PCR experiments to validate the genes in the prognostic signature.

Results

We identified 43 differentially expressed LLPS genes that were associated with the OS of HCC patients. Five of these genes (BMX, FYN, KPNA2, PFKFB4, and SPP1) were selected to generate a prognostic risk score signature. Patients in the low-risk group were associated with better OS than those in the high-risk group in both the training dataset and the validation dataset. We found that BMX and FYN had lower expression levels in HCC tumour tissues, whereas KPNA2, PFKFB4, and SPP1 had higher expression levels in HCC tumour tissues. The validation demonstrated that the five-LLPS gene risk score signature has the capability of predicting the OS of HCC patients.

Conclusion

Our study constructed a five-LLPS gene risk score signature that can be applied as an effective and convenient prognostic tool. These five genes might serve as potential targets for therapy and the treatment of HCC.

Diagnostic and Prognostic Profiling of Nucleocytoplasmic Shuttling Genes in Hepatocellular Carcinoma

One of the key features of eukaryotic cells is the separation of nuclear and cytoplasmic compartments by a double-layer nuclear envelope. This separation is crucial for timely regulation of gene expression, mRNA biogenesis, cell cycle, and differentiation. Since transcription takes place in the nucleus and the major part of translation in the cytoplasm, proper distribution of biomolecules between these two compartments is ensured by nucleocytoplasmic shuttling proteins - karyopherins. Karyopherins transport biomolecules through nuclear pores bidirectionally in collaboration with Ran GTPases and utilize GTP as the source of energy. Different karyopherins transport different cargo molecules that play important roles in the regulation of cell physiology. In cancer cells, this nucleocytoplasmic transport is significantly dysregulated to support increased demands for the import of cell cycle-promoting biomolecules and export of cell cycle inhibitors and mRNAs. Here, we analysed genomic, transcriptomic and proteomic data from published datasets to comprehensively profile karyopherin genes in hepatocellular carcinoma. We have found out that expression of multiple karyopherin genes is increased in hepatocellular carcinoma in comparison to the normal liver, with importin subunit α-1, exportin 2, importin subunit β-1 and importin 9 being the most over-expressed. More-over, we have found that increased expression of these genes is associated with higher neoplasm grade as well as significantly worse overall survival of liver cancer patients. Taken together, our bioinformatic data-mining analysis provides a comprehensive geno-mic and transcriptomic landscape of karyopherins in hepatocellular carcinoma and identifies potential members that could be targeted in order to develop new treatment regimens.

Seven Hub Genes Predict the Prognosis of Hepatocellular Carcinoma and the Corresponding Competitive Endogenous RNA Network

Purpose

This study was aimed at identifying hub genes and ceRNA regulatory networks linked to prognosis in hepatocellular carcinoma (HCC) and to identify possible therapeutic targets.

Methods

Differential expression analyses were performed to detect the differentially expressed genes (DEGs) in the four datasets (GSE76427, GSE6764, GSE62232, and TCGA). The intersected DEmRNAs were identified to explore biological significance by enrichment analysis. We built a competitive endogenous RNA (ceRNA) network of lncRNA-miRNA-mRNA. The mRNAs of the ceRNA network were used to perform Cox and Kaplan-Meier analyses to obtain prognosis-related genes, followed by the selection of genes with an area under the curve >0.8 to generate the random survival forest model and obtain feature genes. Furthermore, the feature genes were subjected to least absolute shrinkage and selection operator (LASSO) and univariate Cox analyses were used to identify the hub genes. Finally, the infiltration status of immune cells in the HCC samples was determined.

Results

A total of 1923 intersected DEmRNAs were identified in four datasets and involved in cell cycle and carbon metabolism. ceRNA network was created using 10 lncRNAs, 67 miRNAs, and 1,923 mRNAs. LASSO regression model was performed to identify seven hub genes, SOCS2, MYOM2, FTCD, ADAMTSL2, TMEM106C, LARS, and KPNA2. Among them, TMEM106C, LARS, and KPNA2 had a poor prognosis. KPNA2 was considered a key gene base on LASSO and Cox analyses and involved in the ceRNA network. T helper 2 cells and T helper cells showed a higher degree of infiltration in HCC.

Conclusion

The findings revealed seven hub genes implicated in HCC prognosis and immune infiltration. A corresponding ceRNA network may help reveal their potential regulatory mechanism.

Identifying a Novel Endoplasmic Reticulum-Related Prognostic Model for Hepatocellular Carcinomas

From the standpoint of the ER (endoplasmic reticulum), we were interested in identifying hub genes that impact clinical prognosis for HCC (hepatocellular carcinoma) patients and developing an ER-related prognostic model. Using TCGA-LIHC (The Cancer Genome Atlas-Liver Hepatocellular Carcinoma) and GSE14520 datasets, we conducted a series of analyses, which included differential gene screening, clinical prognostic analysis, Lasso regression, nomogram prediction, tumour clustering, gene functional enrichment, and tumour infiltration of immune cells. Following our screening for ER-related genes ( $n=1975$ ), we conducted a Lasso regression model to obtain five hub genes, KPNA2, FMO3, SPP1, KIF2C, and LPCAT1, using TCGA-LIHC as a training set. According to risk scores, HCC samples within either the TCGG-LIHC or GSE14520 cohort were categorized into high- and low-risk groups. Compared to the high-risk group of HCC patients, patients in the low-risk group had a better prognosis of OS (overall survival) or RFS (relapse-free survival). For TCGA-LIHC training set, with the factors of risk score, stage, age, and sex, we plotted a nomogram for 1-, 3-, and 5-year survival predictions. Our model demonstrated better clinical validity in both TCGA-LIHC and GSE14520 cohorts. Additionally, events related to biological enzyme activity, biological metabolic processes, or the cell cycle were associated with the prognostic risk of ER. Furthermore, two HCC prognosis-associated tumour clusters were identified by ER hub gene-based consensus clustering. Our findings indicated a link between ER prognostic signature-related high/low risk and tumour infiltration levels of several immune cells, such as “macrophages M2/M0” and “regulatory T cells (Tregs).” Overall, we developed a novel ER-related clinical prognostic model for HCC patients.

Long non-coding RNA HAGLROS facilitates tumorigenesis and progression in hepatocellular carcinoma by sponging miR-26b-5p to up-regulate karyopherin α2 (KPNA2) and inactivate p53 signaling

Hepatocellular carcinoma (HCC) is a principal histologic type of liver cancer with high mortality. Long non-coding RNAs (LncRNAs) exert a crucial role in the pathogenesis of human tumors. To date, the functions and mechanisms of lncRNA HAGLROS in HCC are rarely reported. In the current study, HAGLROS exhibited a higher level in HCC tissues and cells. HAGLROS expression was positively correlated with tumor size, TNM stage and poor clinical prognosis. Loss-of-function experiments showed that knockdown of HAGLROS significantly lowered cell proliferation, cell cycle progression, migration, invasion and epithelial to mesenchymal transition (EMT) but induced apoptosis in vitro. Consistently, tumor growth in the nude mice was effectively slowed by the depletion of HAGLROS. Mechanistically, HAGLROS could competitively bind to miR-26b-5p to prevent the suppression of miR-26b-5p on its downstream target gene Karyopherin α2 (KPNA2). Moreover, the inhibitory effects of HAGLROS knockdown on cell malignant behaviors were reversed due to the miR-26b-5p down-regulation or KPNA2 overexpression. It was interesting to note that HAGLROS inactivated p53 signaling through targeting miR-26b-5p/KPNA2. In conclusion, our results demonstrated that HAGLROS contributed to the malignant progression of HCC via serving as a sponge for miR-26b-5p to facilitate KPNA2 expression and inactivate p53 signaling. Targeting HAGLROS/miR-26b-5p/KPNA2 axis might be an alternative therapeutic strategy for HCC patients.

MicroRNA-517c Functions as a Tumor Suppressor in Hepatocellular Carcinoma via Downregulation of KPNA2 and Inhibition of PI3K/AKT Pathway

OBJECTIVE

Hepatocellular carcinoma (HCC) is a kind of solid and highly aggressive malignant tumor with poor prognosis. MicroRNA (miRNA/miR) has been confirmed to be involved in HCC development. The current study focused on the functions and mechanisms of miR-517c in HCC.

METHODS

Expressions of miR-517c and Karyopherin α2 (KPNA2) mRNA in HCC cell lines and tissue samples were examined using quantitative real-time polymerase chain reaction (qRT-PCR). Western blot was conducted for detections of epithelial-to-mesenchymal transition (EMT) and PI3K/AKT markers. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) and Transwell assays were utilized to investigate the influence of miR-517c on HCC cell proliferation, invasion, and migration. TargetScan and luciferase reporter assay were performed to search for the potential target gene of miR-517c.

RESULTS

We demonstrated that miR-517c expressions were decreased in HCC tissues and cells. Moreover, the clinical analysis showed that decreased miR-517c expressions in HCC tissues correlated with shorter overall survival and malignant clinicopathologic features of HCC patients. MTT assay showed that miR-517c upregulation prominently repressed HCC cell proliferation. In addition, miR-517c restoration could significantly suppress HCC cell invasion and migration as demonstrated by Transwell assays. We also found that miR-517c directly targeted KPNA2 and regulated the PI3K/AKT pathway and EMT, exerting prohibitory functions in HCC.

CONCLUSION

Taken together, this study stated that miR-517c inhibited HCC progression via regulating the PI3K/AKT pathway and EMT and targeting KPNA2 in HCC, providing a novel insight into HCC treatment.

A Cell Cycle Progression-Derived Gene Signature to Predict Prognosis and Therapeutic Response in Hepatocellular Carcinoma

Objective

Dysregulation of cell cycle progression (CCP) is one of the hallmarks of cancer. Here, our study is aimed at developing a CCP-derived gene signature for predicting high-risk population of hepatocellular carcinoma (HCC).

Methods

Our study retrospectively analyzed the transcriptome profiling and clinical information of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) projects. Uni- and multivariate cox regression models were conducted for identifying which hallmarks of cancer were risk factors of HCC. CCP-derived gene signature was developed with LASSO method. The predictive efficacy was verified by ROC curves and subgroup analyses. A nomogram was then generated and validated by ROC, calibration, and decisive curves. Immune cell infiltration was estimated with ssGSEA method. Potential small molecular compounds were predicted via CTRP and CMap analyses. The response to chemotherapeutic agents was evaluated based on the GDSC project.

Results

Among hallmarks of cancer, CCP was identified as a dominant risk factor for HCC prognosis. CCP-derived gene signature displayed the favorable predictive efficacy in HCC prognosis independent of other clinicopathological parameters. A nomogram was generated for optimizing risk stratification and quantifying risk evaluation. CCP-derived signature was in relation to immune cell infiltration, HLA, and immune checkpoint expression. Combining CTRP and CMap analyses, fluvastatin was identified as a promising therapeutic agent against HCC. Furthermore, CCP-derived signature might be applied for predicting the response to doxorubicin and gemcitabine.

Conclusion

Collectively, CCP-derived gene signature was a promising marker in prediction of survival outcomes and therapeutic responses for HCC patients.

Multiomics-based analyses of KPNA2 highlight its multiple potentials in hepatocellular carcinoma

Dysregulation and prognostic roles of Karyopherin α2 (KPNA2) were reported in many malignancies including hepatocellular carcinoma (HCC). A multi-omics analysis of KPNA2 is needed to gain a deeper understanding of its multilevel molecular characteristics and provide novel clues for HCC diagnosis, prognosis, and target therapy. Herein multi-omic alterations of KPNA2 were analyzed at genetic, epigenetic, transcript, and protein levels with evaluation of their relevance with clinicopathological features of HCC by integrative analyses. The significant correlations of KPNA2 expression with its gene copy number variation (CNV) and methylation status were shown through Spearman correlation analyses. With Cox regression, Kaplan-Meier survival, and receiver operating characteristic (ROC) analyses, based on the factors of KPNA2 CNV, methylation, expression, and tumor stage, risk models for HCC overall survival (OS) and disease-free survival (DFS) were constructed which could discriminate the 1-year, 3-year, and 5-year OS/DFS status effectively. With Microenvironment Cell Populations-counter (MCP-counter), the immune infiltrations of HCC samples were evaluated and their associations with KPNA2 were shown. KPNA2 expression in liver was found to be influenced by low fat diet and presented significant correlations with fatty acid metabolism and fatty acid synthase activity in HCC. KPNA2 was detected lowered in HCC patient's plasma by enzyme linked immunosorbent assay (ELISA), consistent with its translocation to nuclei of HCC cells. In conclusion, KPNA2 multilevel dysregulation in HCC and its correlations with immune infiltration and the fatty acid metabolism pathway indicated its multiple roles in HCC. The clinicopathological significance of KPNA2 was highlighted through the in-depth analyses at multilevels.

KPNA2 promotes renal cell carcinoma proliferation and metastasis via NPM

Karyopherin α2 (KPNA2), involved in nucleocytoplasmic transport, has been reported to be up‐regulated in tumorigenesis. However, comprehensive studies of KPNA2 functions in renal cell carcinoma (RCC) are still lacking. In this study, we aim to investigate the roles of KPNA2 in kidney tumour development. Our results showed that down‐regulation of KPNA2 inhibited the proliferation and invasion of kidney tumour cell cells in vitro, while the cell cycle arrest and cellular apoptosis were induced once KPNA2 was silenced. Repression of KPNA2 was proved to be efficient to repress tumorigenesis and development of kidney tumour in in nude mice. Furthermore, one related participator, NPM, was identified based on Co‐IP/MS and bioinformatics analyses. The up‐regulation of NPM attenuates the efficiency of knockdown KPNA2. These results indicated that KPNA2 may regulate NPM to play a crucial role for kidney tumour development.

KPNA2 interaction with CBX8 contributes to the development and progression of bladder cancer by mediating the PRDM1/c-FOS pathway

BACKGROUND

Bladder cancer (BCa) is a common malignancy characterized by high heterogeneity, yet the current treatment modalities are limited. The aim of the present investigation was to unravel the functional role of Karyopherin alpha 2 (KPNA2), a tumor facilitator identified in multiple malignancies, in the progression of BCa.

METHODS

BCa tissues and adjacent normal tissues were surgically resected and analyzed from patients with BCa to determine the expression profile of KPNA2 and Chromobox 8 (CBX8) by RT-qPCR, Western blot analysis and immunohistochemistry. The relationship among KPNA2, CBX8 and PR domain zinc finger protein 1 (PRDM1) was explored by co-immunoprecipitation and chromatin-immunoprecipitation. The functions of KPNA2, CBX8 and PRDM1 on BCa cell proliferation, migration and invasion were evaluated. Next, a nude mouse model of BCa was established for validating the roles of KPNA2, CBX8 and PRDM1 in vivo.

RESULTS

KPNA2 and CBX8 were highly expressed in BCa and are in association with dismal oncologic outcomes of patients with BCa. KPNA2 promoted nuclear import of CBX8. CBX8 downregulated PRDM1 by recruiting BCOR in the promoter region of PRDM1. Overexpression of KPNA2 promoted the malignant behaviors of BCa cells, which was counteracted by silencing of CBX8. Overexpressing PRDM1 attenuated the progression of BCa by inhibiting c-FOS expression. The tumor-promoting effects of KPNA2 via the PRDM1/c-FOS pathway were also validated in vivo.

CONCLUSION

Collectively, our findings attached great importance to the interplay between KPNA2 and CBX8 in BCa in mediating the development and progression of BCa, thus offering a promising candidate target for better BCa patient management.

Identification of hub genes and biological pathways in hepatocellular carcinoma by integrated bioinformatics analysis

Background

Hepatocellular carcinoma (HCC), the main type of liver cancer in human, is one of the most prevalent and deadly malignancies in the world. The present study aimed to identify hub genes and key biological pathways by integrated bioinformatics analysis.

Methods

A bioinformatics pipeline based on gene co-expression network (GCN) analysis was built to analyze the gene expression profile of HCC. Firstly, differentially expressed genes (DEGs) were identified and a GCN was constructed with Pearson correlation analysis. Then, the gene modules were identified with 3 different community detection algorithms, and the correlation analysis between gene modules and clinical indicators was performed. Moreover, we used the Search Tool for the Retrieval of Interacting Genes (STRING) database to construct a protein protein interaction (PPI) network of the key gene module, and we identified the hub genes using nine topology analysis algorithms based on this PPI network. Further, we used the Oncomine analysis, survival analysis, GEO data set and random forest algorithm to verify the important roles of hub genes in HCC. Lastly, we explored the methylation changes of hub genes using another GEO data (GSE73003).

Results

Firstly, among the expression profiles, 4,130 up-regulated genes and 471 down-regulated genes were identified. Next, the multi-level algorithm which had the highest modularity divided the GCN into nine gene modules. Also, a key gene module (m1) was identified. The biological processes of GO enrichment of m1 mainly included the processes of mitosis and meiosis and the functions of catalytic and exodeoxyribonuclease activity. Besides, these genes were enriched in the cell cycle and mitotic pathway. Furthermore, we identified 11 hub genes, MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 which played key roles in HCC. The results of multiple verification methods indicated that the 11 hub genes had highly diagnostic efficiencies to distinguish tumors from normal tissues. Lastly, the methylation changes of gene CDC20, TOP2A, TK1, FEN1 in HCC samples had statistical significance (P-value < 0.05).

Conclusion

MCM3, TRMT6, AURKA, CDC20, TOP2A, ECT2, TK1, MCM2, FEN1, NCAPD2 and KPNA2 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, the cell cycle and mitotic pathway might played vital roles in the progression of HCC.

Establishment of a Genomic-Clinicopathologic Nomogram for Predicting Early Recurrence of Hepatocellular Carcinoma After R0 Resection

BACKGROUND

A high rate of postoperative recurrence, especially early recurrence (ER) occurring within 1 year, seriously impedes patients with hepatocellular carcinoma (HCC) from achieving long-term survival. This study aimed to establish a genomic-clinicopathologic nomogram for precisely predicting ER in HCC patients after R0 resection.

METHODS

Two reliable datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected as the training and validation cohorts, respectively. The prognostic genes related to ER were screened out by univariate Cox regression analysis and differential expression analysis. The gene-based prognostic index was constructed using LASSO and Cox regression analyses, and its independent prognostic value was assessed by Kaplan-Meier and multivariate Cox analyses. Gene set enrichment analysis (GSEA) was performed to explore the biological pathways related to the prognostic index. Finally, the nomogram integrating all the independent prognostic factors was established and comprehensively evaluated by calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis.

RESULTS

Nine dysregulated and prognostic genes related to ER (ZNF131, TATDN2, TXN, DDX55, KPNA2, ZNF30, TIMELESS, SFRP1, and COLEC11) were identified (all P < 0.05). The prognostic index model based on the 9 genes was successfully constructed using the TCGA cohort and showed a certain capability to discriminate the ER group from the non-ER group (P < 0.05) and good independent prognostic value in terms of predicting poor early recurrence-free survival (P < 0.05). Eight biological pathways significantly related to ER were identified by GSEA, such as "cell cycle", "homologous recombination" and "p53 signaling pathway." The genomic-clinicopathologic nomogram integrating the 9-gene-based prognostic index and TNM stage displayed significantly higher predictive accuracy and clinical application value than that of TNM stage model both in the training and validation cohorts (all P < 0.05).

CONCLUSIONS

The novel genomic-clinicopathologic nomogram may be a convenient and powerful tool for accurately predicting ER in HCC patients after R0 resection.

KPNA2-Associated Immune Analyses Highlight the Dysregulation and Prognostic Effects of GRB2, NRAS, and Their RNA-Binding Proteins in Hepatocellular Carcinoma

Karyopherin α2 (KPNA2) was reported to be overexpressed and have unfavorable prognostic effects in many malignancies including hepatocellular carcinoma (HCC). Although its contributions to inflammatory response were reported in many studies, its specific associations with immune infiltrations and immune pathways during cancer progression were unclear. Here, we aimed to identify new markers for HCC diagnosis and prognosis through KPNA2-associated immune analyses. RNA-seq expression data of HCC datasets were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium. The gene expressions were counts per million normalized. The infiltrations of 24 kinds of immune cells in the samples were evaluated with ImmuCellAI (Immune Cell Abundance Identifier). The Spearman correlations of the immune infiltrations with KPNA2 expression were investigated, and the specific positive correlation of B-cell infiltration with KPNA2 expression in HCC tumors was identified. Fifteen genes in KEGG (Kyoto Encyclopedia of Genes and Genomes) B-cell receptor signaling pathway presented significant correlations with KPNA2 expression in HCC. Among them, GRB2 and NRAS were indicated to be independent unfavorable prognostic factors for HCC overall survival. Clinical Proteomic Tumor Analysis Consortium HCC dataset was investigated to validate the results at protein level. The upregulation and unfavorable prognostic effects of KPNA2 and GRB2 were confirmed, whereas, unlike its mRNA form, NRAS protein was presented to be downregulated and have favorable prognostic effects. Through receiver operating characteristic curve analysis, the diagnostic potential of the three proteins was shown. The RNA-binding proteins (RBPs) of KPNA2, NRAS, and GRB2, downloaded via The Encyclopedia of RNA Interactomes, were investigated for their clinical significance in HCC at protein level. An eight-RBP signature with independent prognostic value and dysregulations in HCC was identified. All the RBPs were significantly correlated with MKI67 expression and at least one of KPNA2, GRB2, and NRAS at protein level in HCC, indicating their roles in HCC progression and the regulation of the three proteins. We concluded that KPNA2, GRB2, NRAS, and their RBPs might have coordinating roles in HCC immunoregulation and progression. They might be new markers for HCC diagnosis and prognosis predication and new targets for HCC immunotherapy.

The miR-26b-5p/KPNA2 Axis Is an Important Regulator of Burkitt Lymphoma Cell Growth

The expression of several microRNAs (miRNAs) is known to be changed in Burkitt lymphoma (BL), compared to its normal counterparts. Although for some miRNAs, a role in BL was demonstrated, for most of them, their function is unclear. In this study, we aimed to identify miRNAs that control BL cell growth. Two BL cell lines were infected with lentiviral pools containing either 58 miRNA inhibitors or 44 miRNA overexpression constructs. Eighteen constructs showed significant changes in abundance over time, indicating that they affected BL growth. The screening results were validated by individual green fluorescent protein (GFP) growth competition assays for fifteen of the eighteen constructs. For functional follow-up studies, we focused on miR-26b-5p, whose overexpression inhibited BL cell growth. Argonaute 2 RNA immunoprecipitation (Ago2-IP) in two BL cell lines revealed 47 potential target genes of miR-26b-5p. Overlapping the list of putative targets with genes showing a growth repression phenotype in a genome-wide CRISPR/Cas9 knockout screen, revealed eight genes. The top-5 candidates included EZH2, COPS2, KPNA2, MRPL15, and NOL12. EZH2 is a known target of miR-26b-5p, with oncogenic properties in BL. The relevance of the latter four targets was confirmed using sgRNAs targeting these genes in individual GFP growth competition assays. Luciferase reporter assay confirmed binding of miR-26b-5p to the predicted target site for KPNA2, but not to the other genes. In summary, we identified 18 miRNAs that affected BL cell growth in a loss- or gain-of-function screening. A tumor suppressor role was confirmed for miR-26b-5p, and this effect could at least in part be attributed to KPNA2, a known regulator of OCT4, c-jun, and MYC.

Identification of hub genes in hepatocellular carcinoma using integrated bioinformatic analysis

The molecular mechanisms underlying hepatocellular carcinoma (HCC) progression remain largely undefined. Here, we identified 176 commonly upregulated genes in HCC tissues based on three Gene Expression Omnibus datasets and The Cancer Genome Atlas (TCGA) cohort. We integrated survival and methylation analyses to further obtain 12 upregulated genes for validation. These genes were overexpressed in HCC tissues at the transcription and protein levels, and increased mRNA levels were related to higher tumor grades and cancer stages. The expression of all markers was negatively associated with overall and disease-free survival in HCC patients. Most of these hub genes can promote HCC proliferation and/or metastasis. These 12 hub genes were also overexpressed and had strong prognostic value in many other cancer types. Methylation and gene copy number analyses indicated that the upregulation of these hub genes was probably due to hypomethylation or increased gene copy numbers. Further, the methylation levels of three genes, KPNA2, MCM3, and LRRC1, were associated with HCC clinical features. Moreover, the levels of most hub genes were related to immune cell infiltration in HCC microenvironments. Finally, we identified three upregulated genes (KPNA2, TARBP1, and RNASEH2A) that could comprehensively and accurately provide diagnostic and prognostic value for HCC patients.

Overexpression of Karyopherin Subunit alpha 2 (KPNA2) Predicts Unfavorable Prognosis and Promotes Bladder Cancer Tumorigenicity via the P53 Pathway

Background

We sought to investigate the expression of KPNA2 in bladder cancer (BC) and its relationship with prognosis, and to analyze the potential mechanism of KPNA2 in promoting BC progression.

Material/Methods

The RNA-seq data on BC from The Cancer Genome Atlas (TCGA) database were imported into R statistical software for differential analysis. The clinical data for patients with BC were screened and analyzed with R software. The survival curve was drawn with the Kaplan-Meier Plotter. The expression of KPNA2 in 4 human BC cell lines and a human bladder epithelial cell line was detected by quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting (WB). The proliferation of BC cells was detected with Cell Counting Kit-8 (CCK8), detection of apoptosis, and flow cytometry, and the migration and invasion of BC cells were detected through Transwell assays. WB was used to detect proteins involved in the P53 pathway.

Results

The expression of KPNA2 was higher in BC. The difference in KPNA2 expression was associated with many clinicopathological factors, and high expression of KPNA2 was associated with shorter survival time. After KPNA2 knockout, the proliferation, migration, and invasion ability decreased significantly, the cell cycle was clearly arrested in the G0/G1 phase, and the number of apoptotic cells increased. Moreover, CyclinD1, BCL2, and pro-caspase3 decreased significantly, whereas P53, P21, BAX, and cleaved-caspase3 increased significantly. The results in the overexpression group were the opposite of results in the knockdown group.

Conclusions

KPNA2 is an oncogenic factor that facilitates BC tumorigenicity through the P53 pathway.

Retracted Article: LncRNA SNHG5 regulates the cell viability and apoptosis of glioma cells by the miR-1297/KPNA2 axis

Long non-coding RNA small nucleolar RNA host gene 5 (lncRNA SNHG5) has been reported to participate in the occurrence and development of glioma. However, the function and underlying molecular mechanisms of SNHG5 in glioma remain largely unknown. The expressions of SNHG5, microRNA-1297 (miR-1297) and karyopherin subunit alpha 2 (KPNA2) in glioma tissues and cells were evaluated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) or western blot. 3-(4,5-Dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay and flow cytometry were used to detect cell viability and apoptosis, respectively. Western blot was also performed to detect the expressions of autophagy-associated proteins. The relationship among lncRNA SNHG5, miR-1297 and KPNA2 was verified by luciferase reporter assay and RNA immunoprecipitation (RIP) assay. SNHG5 and KPNA2 were over expressed, and the level of miR-1297 was down-regulated in glioma tissues and cell lines. Knockdown of SHNG5 promoted apoptosis, while suppressing cell viability and autophagy of A172 and LN340 cells. Meanwhile, SHNG5 harbored the binding sites with miR-1297, and a negative correlation between the expression of SNHG5 and miR-1297 in glioma tissues was also observed. Interestingly, silencing of miR-1297 undermined the SHNG5 depletion-mediated effect on cell viability, apoptosis, and autophagy. KPNA2 was a direct target of miR-1297, and negatively regulated by miR-1297. More importantly, gain of KPNA2 mitigated the effect of SHNG5l knockdown on glioma cells. Silencing of SNHG5 had an implication in inhibiting apoptosis and stimulating cell viability and autophagy by the miR-1297/KPNA2 axis in glioma.

Long non-coding RNA small nucleolar RNA host gene 5 (lncRNA SNHG5) has been reported to participate in the occurrence and development of glioma.

The emerging roles of KPNA2 in cancer

Karyopherin α2 (KPNA2, also known as importinα-1), a member of the nuclear transporter family, is involved in the nucleocytoplasmic transport pathway of a variety of tumor-associated proteins. Recent studies have found that KPNA2 is overexpressed in various cancers, which is associated with poor prognosis. In addition, it has been shown to promote tumor formation and progression by participating in cell differentiation, proliferation, apoptosis, immune response, and viral infection. It is indicated that KPNA2 also plays an important role in the diagnosis, treatment and prognosis of tumors. Herein, we provide an overview of the function and mechanism of KPNA2 in cancer and the prospects in the diagnosis and treatment of cancer. In the future, KPNA2 provides new ideas for the early diagnosis of malignant tumors, the development of molecularly targeted drugs, and prognosis evaluation.

Karyopherin α2-dependent import of E2F1 and TFDP1 maintains protumorigenic stathmin expression in liver cancer

Background

Members of the karyopherin superfamily serve as nuclear transport receptors/adaptor proteins and provide exchange of macromolecules between the nucleo- and cytoplasm. Emerging evidence suggests a subset of karyopherins to be dysregulated in hepatocarcinogenesis including karyopherin-α2 (KPNA2). However, the functional and regulatory role of KPNA2 in liver cancer remains incompletely understood.

Methods

Quantitative proteomics (LC-MS/MS, ~ 1750 proteins in total) was used to study changes in global protein abundance upon siRNA-mediated KPNA2 knockdown in HCC cells. Functional and mechanistic analyses included colony formation and 2D migration assays, co-immunoprecipitation (CoIP), chromatin immunoprecipitation (ChIP), qRT-PCR, immmunblotting, and subcellular fractionation. In vitro results were correlated with data derived from a murine HCC model and HCC patient samples (3 cohorts, n > 600 in total).

Results

The proteomic approach revealed the pro-tumorigenic, microtubule (MT) interacting protein stathmin (STMN1) among the most downregulated proteins upon KPNA2 depletion in HCC cells. We further observed that KPNA2 knockdown leads to reduced tumor cell migration and colony formation of HCC cells, which could be phenocopied by direct knockdown of stathmin. As the underlying regulatory mechanism, we uncovered E2F1 and TFDP1 as transport substrates of KPNA2 being retained in the cytoplasm upon KPNA2 ablation, thereby resulting in reduced STMN1 expression. Finally, murine and human HCC data indicate significant correlations of STMN1 expression with E2F1/TFPD1 and with KPNA2 expression and their association with poor prognosis in HCC patients.

Conclusion

Our data suggest that KPNA2 regulates STMN1 by import of E2F1/TFDP1 and thereby provide a novel link between nuclear transport and MT-interacting proteins in HCC with functional and prognostic significance.

Identification of the potential therapeutic target gene UBE2C in human hepatocellular carcinoma: An investigation based on GEO and TCGA databases

Hepatocellular carcinoma (HCC) ranks the third major cause of cancer-associated mortality globally. Numerous studies have attempted to elucidate the underlying mechanisms of HCC using various biomarkers. In the present study, two expression profiles datasets from Gene Expression Omnibus (GSE76427 and GSE84402) and data associated with liver cancer samples from The Cancer Genome Atlas (TCGA) were downloaded for integrated analysis. Five differentially expressed genes (DEGs) exhibiting high expression, including ubiquitin-conjugating enzyme 2C (UBE2C), topoisomerase II α, pituitary tumor transforming gene 1, glypican-3 and polycomb-repressive complex 1, were selected and considered as candidate genes. Enrichment analysis demonstrated that these genes were associated with Gene Ontology terms of cellular components and molecular functions, including regulation of apoptosis, stabilization of p53 and Anaphase Promoting Complex/Cyclosome (APC/C) (APC/C:Cdc20)-mediated degradation of Securin. The expression profiles of these genes in HCC, other human malignancies and different human HCC cell lines were validated using GSE14520, GSE3500 and TCGA data. The results confirmed the upregulation of UBE2C in tissues from patients with HCC or other human malignancies and human liver cancer cell lines, compared with the expression levels in the corresponding adjacent non-tumor tissues and cell lines, respectively. Patients with HCC who exhibited an increased messenger RNA level of UBE2C exhibited a significantly shorter survival time. The results of the present study suggest that the overexpression of UBE2C may be used as a novel prognostic biomarker of HCC.