Clinical data showed that hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths worldwide due to its frequent metastasis and lack of curative treatment . More than 580,000 new cases of liver cancer occur in Asia every year . Progressive accumulation of alterations in cancer drives genes and dysregulation of their associated signaling pathways, causing the occurrence and progression of HCC . HCC is insensitive to radiotherapy and chemotherapy, and there is no uniform standard for the optimal dose of radiotherapy . Although liver transplantation is a potential therapy for HCC, its application is limited by the liver donor supply. For targeted therapy, it can block the effect of key molecules in the formation and progression of liver cancer. Targeted drugs affect liver cancer cells more than normal cells. However, only a few drugs are currently available for patients with advanced liver cancer. Therefore, it is significant to investigate the novel key genes and major signal pathways involving in the development of HCC. To date, serum alpha-fetoprotein (AFP) and PIVKA-II (protein induced by vitamin K absence or antagonist-II) are two best used biomarker for HCC in clinical screening  - . The combination use of the both biomarkers has significantly improved HCC sensitivity detection despite that their sensitivity and specificity are far from satisfactory    . However, numerous recent studies have shown that the cut-off value of PIVKA-II and AFP, the tumor size and etiology did not have significant effects on the liver cancer heterogeneity. Therefore, it is necessary to find new genes that are useful for screening, diagnosis and monitoring of HCC.
PLK1 (Polo-like kinase 1), a serine/threonine-protein kinase that belongs to the polo-like kinase family, participates in various biological processes, including cell cycle and RNA processing  . At present, five polo-like kinsey family members (PLL1-5) have been identified in humans . Bu et al.  tested high expression of PLK1 in the HCC tissues, and showed significantly worse effect in the hematological type. Study suggested that PLK1 promotes the degradation of SUZ12 and ZNF198 by protea-some, which is a major factor in liver cancer . PLK1 phosphorylation of PTEN also caused a tumor promoting metabolic state . Moreover, PLK1 is over expressed in many cancers and serves as a significant prognostic factor in cancers, such as small-cell lung cancer, colon cancer and ovarian cancer . In addition, high expression levels of PLK1 in melanoma and breast cancer correlated well with the metastatic potential of these tumors  . PLK1 over-expression might also contribute to the deregulation of cell proliferation during oncogenesis by overcoming mitotic checkpoints .
Therefore, in order to verify the value of PLK1 in the diagnosis and treatment of HCC, it is very important to analyze the expression and significance of PLK1 in liver cancer tissues.
2. Materials and Methods
2.1. UALCAN Analysis
UALCAN (http://ualcan.path.uab.edu/analysis.html) is a web tool to profile gene expressions between tumor and non-tumor tissues and provides interactive data analyses . In this study, we utilized this online tool to analyze the expression levels of PLK1 between HCC specimen and normal tissues.
2.2. Survival Analysis
GEPIA (http://gepia.cancer-pku.cn/) is an interactive web resource and database for analyzing cancer transcriptome and patients’ survival. In this study, we utilized this online tool to analyze patients’ survival. Using GEPIA, overall survival (OS) and disease free survival (DFS) were presented and the hazards ratio was calculate based on Cox PH Model, 95% confidence interval was added as dotted line. The thresholds for high and low expression level cohorts are 50%, respectively.
2.3. Construction of the PPI Networks
The STRING database (http://string-db.org/) and Metascape (http://metascape.org/) tool was used to analyze the PPI networks. In this study, the PPI networks of the PLK1 gene was constructed using STRING and Metascape database. The non-interacting genes were excluded in order to simplify the PPI network. The top 12 genes with the highest degree of connection to the others were presented.
2.4. GO and KEGG Analysis
The STRING database (http://string-db.org/) is an online tool for high-throughput functional analysis of genes. In this study, the potential associations between the 12 core genes and PLK1 were assessed through the GO annotation analysis and KEGG pathway enrichment analysis  . P-values < 0.05 were considered as statistically significance.
2.5. Analysis of Genetic Alterations
cBioPortal (https://www.cbioportal.org/) is a database with integrated genetic data, including DNA mutations, gene amplifications and protein alterations. In our study, the cBioPortal database was used to analyze the association between genetic mutations and the development of HCC. The top 12 genes which are related to PLK1 were analyzed by using cBioPortal database. And we performed PLK1 gene mutations analysis across all tumor samples from the TCGA-HCC database.
3.1. The Expression Levels of PLK1 in HCC Patients
To verify PLK1 expression levels in HCC tissues and the value to the diagnosis and surveillance of HCC, GEPIA database was applied. As shown in Figure 1(a), the data showed that the expression level of PLK1 in the HCC group is significant higher than normal liver group (P < 0.001). Moreover, the relationship between PLK1 expression levels and HCC patients’ clinicopathological parameters were further analyzed by UALCAN databases. The result demonstrated that
Figure 1. Over-expression of PLK is associated with malignancy of HCC. (a) PLK1 expression in normal and HCC tissues from TCGA data-sets; (b) The expressions of PLK1 was partially related to patients race; (c) The high expression of PLK1 was significantly related to cancer grade; (d) The expressions of PLK1 was partially related to cancer stages. * P < 0.05, ** P < 0.01, *** P < 0.001.
expression of PLK1 was higher in Asian HCC patients than Caucasian patients (P < 0.01, Figure 1(b)). The expression of PLK1 increased from grade 1 to grade 4 of HCC, suggesting PLK1 was remarkably correlated with HCC patients’ grade (Figure 1(c)) (grade 1 vs grade 3, P < 0.01 ; grade 1 vs grade 4, P < 0.01; grade 2 vs grade 3, P < 0.05). As shown in Figure 1(d). we also found there are gradually increased expression of PLK1 from stage 1 to stage 3 but obviously declined in stage 4 (stage 1 vs stage 2, P < 0.01 and stage 1 vs stage 3, P < 0.001).
3.2. Survival Analysis of HCC Patients Based on PLK1 Expression
Here, PLK1 expression of HCC patients was divided into low-expression group and high-expression group (cutoff-high is 50%, cutoff-low is 50%). As shown in Figure 2, the overall survival (Figure 2(a)) and disease free survival (Figure 2(b)) were significant better in low PLK1 expression group than high PLK1 expression group (P < 0.001). Survival curves analysis showed that PLK1 was suitable for predicting liver cancer patients’ prognosis.
3.3. PPI Networks and GO Enrichment Analysis of PLK1
The functional interactions between proteins can provide us some information in molecular mechanism. In this study, PPI network was constructed by the Metascape database. PPI network analysis indicated that PLK1 has more interactions with other 12 proteins, including CDC20, ERCC6L, CCNB1, CCNB2,
Figure 2. Prognostic value of PLK1 in liver cancer patients. Higher expressions of PLK1 was associated with poorer OS (a) and DFS (b) in HCC patients.
KIF2C, BUB1, MAD2L1, CENPE, INCENP, CDK1, CDCA8 and NDC80 (Figure 3(a)). To predict the biological functions and signaling pathways in which PLK1 were involved in HCC, GO enrichment and KEGG pathway analyse were further performed (Figure 3(b) and Table 1). The results showed that those proteins were biologically closely associated with cell cycle, p53 signaling pathway, oocyte meiosis and progesterone-mediated oocyte maturation etc.
3.4. Specific Mutations of PLK1 Genes in HCC Patients
In order to analyze the mutations of PLK1 gene in HCC patient’s tissues, the CBioPortal database analysis was employed. As shown in Figure 4, we performed PLK1 gene mutations analysis across all tumor samples from the TCGA-HCC database (https://www.cbioportal.org/). Intriguingly, there were three specific mutations K146R, S335Afs*120 and D429H (Figure 4(a) and Figure 4(b)) in the HCC samples that were not present in any other tumor samples. These particular mutations of PLK1 in HCC patients might contribute greatly to HCC clinical diagnosis and monitoring. Moreover, the mutations between PLK1 and its interacted genes (CDC20, ERCC6L, CCNB1, CCNB2, KIF2C, BUB1, MAD2L1, CENPE, INCENP, CDK1, CDCA8 and NDC80) were analyzed through the cBioPortal dataset. The alteration statuses of 12 key genes were analyzed using TCGA HCC patients’ data of cBioPortal database. The genetic alteration of PLK1 genes was altered in 52 (13%) of 377 HCC patients (Figure 4(c)).
3.5. Prediction of Relevance Genes to PLK1
To predict the biological functions and signaling pathways in which PLK1 were involved in HCC, we found that the 12 genes were considered to be relevant genes and the scatter plots were shown in Figures 5(a)-(l).
Bioinformatics methods can provide us with gene expression levels and predict
Figure 3. PPI network and GO enrichment analysis of twelve hub genes related to PLK1. (a) PPI network and MCODE components identified in the gene lists; (b) GO enrichment analysis of the 12 PLK1 related genes.
Figure 4. (a) and (b) The particular mutations (K146R, S335Afs*120 and D429H) of PLK1 in HCC patients. (c) A visual summary of genetic alterations (data from HCC in TCGA) shows the genetic alteration of PLK1 genes which were altered in 52 (13%) of 377 HCC patients.
potential therapeutic targets. A large number of clinical data showed that the death rate of liver cancer is very high. One of the best ways to reduce mortality is to detect accurately and treat successfully. Identifying key genes associated with the development and the progression of HCC is crucial for its diagnosis and treatment.
Table 1. Significantly enriched GO terms and KEGG pathways of PLK1.
Figure 5. The plots of 12 pair-wise correlation genes. (a) PLK1 and CDK1; (b) PLK1 and BUB1; (c) PLK1 and KIF2C; (d) PLK1 and CDC20; (e) PLK1 and CCNB2; (f) PLK1 and CCNB1; (g) PLK1 and CDCA8; (h) PLK1 and ERCC6L; (i) PLK1 and NDC80; (j) PLK1 and MAD2L1; (k) PLK1 and CENPE; (l) PLK1 and INCENP.
In this study, our data showed that PLK1 expression was higher in HCC patients than that in normal tissues. PLK1 expression was remarkably correlated with HCC patients’ grade. The results demonstrated that PLK1 expression enhanced gradually from stage 1 to stage 3 but decreased in stage 4. A higher PLK1 expression resulted in a significant shorter disease free survival as well as overall survival in HCC patients, suggesting that PLK1 may play an important role in the prognosis of HCC. By mutation analysis, CBioPortal tool unveiled three specific mutations (K146R, S335Afs*120 and D429H) unique presented in the HCC samples that were not occurred in any other tumor types. These characteristic mutations of PLK1 in HCC patients might facilitate to HCC clinical diagnosis and monitoring.
To determine the probably pathogenic mechanism of PLK1 in HCC, PPI networks were further applied. The twelve interacted proteins were identified by using PPI network analysis. Go enrichment analysis suggested these genes are enriched in cell cycle and p53 signaling pathway etc. Recent study indicated that cell cycle dysregulation plays an important role in the liver tumorigenesis . It’s been reported that disruption of the cell cycle pathway can result in cell cycle arrest and has previously been related to the prognosis of human cancers . Furthermore, cell cycle arrest has been confirmed to be an effective approach in controlling tumor growth  . Boxuan Li et al.  found that PLK1 plays a crucial role in the disruption of the cell cycle pathway by dramatically induced apoptosis. Shen, L.Y. found that PLK1 could arrest cell cycle in G2/M phase and then block cell cycle pathway . High expression level of PLK1 was also identified in HCC tissues . Taken together, our novel findings suggest that PLK1 might play a crucial role in regulating the middle of cell cycle pathway.
Recently, new findings have pointed that PLK1 is able to inhibit apoptosis in a p53-dependent manner in a variety of carcinomas . Wei Sun  reported that the p53 tumor-suppressor protein is phosphorylated by PLK1, which can inhibit the proapoptotic function of p53.The inhibition of PLK1 leads to a failure to complete mitosis, eventually resulting in cell death . PLK1 could interact with the DNA binding domain of p53, thereby decreasing its stability and transcriptional activity . Thus, p53 is a major target for PLK1 controlling the growth of carcinoma cells. PLK1 is a cell cycle protein that plays multiple roles in promoting cell cycle progression. Among the many roles, the most prominent role of PLK1 is to regulate the mitotic spindle formation checkpoint at the M-phase . Robert D. Van Horn  thought that CDK1 and PLK1 are likely to act in a positive feedback activation loop for CDK1 activation through CDC25-mediated dephosphorylation during G2/M transition. CDK1 and PLK1 could form a positive feedback activation loop in human cells. Activation of CDK1 initiates the entry into mitosis and activation of PLK1. PLK1 then further feedback-activate CDK1 to promote rapid and timely entry into mitosis and coordinately regulate various aspects of mitosis, such as bipolar mitotic spindle formation and checkpoint response .
Sharon I. King et al. have demonstrated a striking association between cancer and K146R mutation of PLK1 by immunohistochemical analysis and DNA sequencing analysis of 215 primary breast tumours . Targeting PLK1 mutant at K146R site breast cancer might offer therapeutic opportunities. Although no related mutations have been reported in HCC tissues, we suggest that these particular mutations of PLK1 in HCC patients might contribute greatly to HCC clinical diagnosis and monitoring.
In summary, this study has novelly identified the elevated expression of PLK1in HCC patients when compared to that in normal tissue, and it is negatively correlated with patients’ survival time. The results from this study may push forward the mechanism underlying PLK1 progression, and provide the high prognostic value of HCC. However, further studies are needed to intensively disclose the molecular mechanism and implication of PLK1 in HCC tumorigenesis and therapy.
This work was supported by grants from the National Natural Science Foundation of China (31700736), China Scholarship Council (201908420102), Leading Talent Program of Yangtze Talent Project (to XW Wang) and the College Students Innovative Entrepreneurial Training Program in Yangtze University (2018184).
 Yi, Q., Liu, Y., Cao, M., Liu, J., Xiang, Q., et al. (2020) Transcriptional Analysis and Differentially Expressed Gene Screening of Spontaneous Liver Tumors in CBA/CaJ Mice. Gene, 725, Article ID: 144159.
 Zhang, K., Song, P., Gao, J., Li, G., Zhao, X., et al. (2014) Perspectives on a Combined Test of Multi Serum Biomarkers in China: Towards Screening for and Diagnosing Hepatocellular Carcinoma at an Earlier Stage. Drug Discoveries & Therapeutics, 8, 102-109.
 Kumazoe, M., Takai, M., Hiroi, S., Takeuchi, C., Kadomatsu, M., et al. (2017) The FOXO3/PGC-1β Signaling Axis Is Essential for Cancer Stem Cell Properties of Pancreatic Ductal Adenocarcinoma. The Journal of Biological Chemistry, 292, 10813-10823.
 Wang, P.M., Chung, N.N., Hsu, W.C., Chang, F.L., Jang, C.J., et al. (2015) Stereotactic Body Radiation Therapy in Hepatocellular Carcinoma: Optimal Treatment Strategies Based on Liver Segmentation and Functional Hepatic Reserve. Reports of Practical Oncology and Radiotherapy: Journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology, 20, 417-424.
 Zhu, J.N., Chen, G.D., Xu, J.Y. and Zhou, X. (2017) Serum AFU, 5’-NT and AFP as Biomarkers for Primary Hepatocellular Carcinoma Diagnosis. Open Medicine (Warsaw, Poland), 12, 354-358.
 Giannini, E.G., Sammito, G., Farinati, F., Ciccarese, F., Pecorelli, A., et al. (2014) Determinants of Alpha-Fetoprotein Levels in Patients with Hepatocellular Carcinoma: Implications for Its Clinical Use. Cancer, 120, 2150-2157.
 Park, H. and Park, J.Y. (2013) Clinical Significance of AFP and PIVKA-II Responses for Monitoring Treatment Outcomes and Predicting Prognosis in Patients with Hepatocellular Carcinoma. BioMed Research International, 2013, Article ID: 310427.
 Notarpaolo, A., Layese, R., Magistri, P., Gambato, M., Colledan, M., et al. (2017) Validation of the AFP Model as a Predictor of HCC Recurrence in Patients with Viral Hepatitis-Related Cirrhosis Who Had Received a Liver Transplant for HCC. Journal of Hepatology, 66, 552-559.
 Xing, H., Zheng, Y.J., Han, J., Zhang, H., Li, Z.L., et al. (2018) Protein Induced by Vitamin K Absence or Antagonist-Ii versus Alpha-Fetoprotein in the Diagnosis of Hepatocellular Carcinoma: A Systematic Review with Meta-Analysis. Hepatobiliary & Pancreatic Diseases International: HBPD INT, 17, 487-495.
 Svobodova, S., Karlikova, M., Topolcan, O., Pecen, L., Pestova, M., et al. (2018) PIVKA-II as a Potential New Biomarker for Hepatocellular Carcinoma—A Pilot Study. In Vivo (Athens, Greece), 32, 1551-1554.
 Yu, J.P., Xu, X.G., Ma, R.J., Qin, S.N., Wang, C.R., et al. (2015) Development of a Clinical Chemiluminescent Immunoassay for Serum GPC3 and Simultaneous Measurements alone with AFP and CK19 in Diagnosis of Hepatocellular Carcinoma. Journal of Clinical Laboratory Analysis, 29, 85-93.
 Abd, E.L., Gawad, I.A., Mossallam, G.I., Radwan, N.H., Elzawahry, H.M., et al. (2014) Comparing Prothrombin Induced by Vitamin K Absence-II (PIVKA-II) with the Oncofetal Proteins Glypican-3, Alpha Feto Protein and Carcinoembryonic Antigen in Diagnosing Hepatocellular Carcinoma among Egyptian Patients. Journal of the Egyptian National Cancer Institute, 26, 79-85.
 Caviglia, G.P., Ribaldone, D.G., Abate, M.L., Ciancio, A., Pellicano, R., et al. (2018) Performance of Protein Induced by Vitamin K Absence or Antagonist-II Assessed by Chemiluminescence Enzyme Immunoassay for Hepatocellular Carcinoma Detection: A Meta-Analysis. Scandinavian Journal of Gastroenterology, 53, 734-740.
 Zhang, M., Zhang, Q., Hu, Y., Xu, L., Jiang, Y., et al. (2017) miR-181a Increases FoxO1 Acetylation and Promotes Granulosa Cell Apoptosis via SIRT1 Downregulation. Cell Death & Disease, 8, e3088.
 Markant, S.L., Esparza, L.A., Sun, J., Barton, K.L., McCoig, L.M., et al. (2013) Targeting Sonic Hedgehog-Associated Medulloblastoma through Inhibition of Aurora and Polo-Like Kinases. Cancer Research, 73, 6310-6322.
 Xu, L., Zhu, Y., Shao, J., Chen, M., Yan, H., et al. (2017) Dasatinib Synergises with Irinotecan to Suppress Hepatocellular Carcinoma via Inhibiting the Protein Synthesis of PLK1. British Journal of Cancer, 116, 1027-1036.
 Zhang, H., Diab, A., Fan, H., Mani, S.K., Hullinger, R., et al. (2015) PLK1 and Hotair Accelerate Proteasomal Degradation of SUZ12 and ZNF198 during Hepatitis B Virus-Induced Liver Carcinogenesis. Cancer Research, 75, 2363-2374.
 Li, Z., Li, J., Bi, P., Lu, Y., Burcham, G., et al. (2014) PLK1 Phosphorylation of PTEN Causes a Tumor-Promoting Metabolic State. Molecular and Cellular Biology, 34, 3642-3661.
 Ahr, A., Karn, T., Solbach, C., Seiter, T., Strebhardt, K., et al. (2002) Identification of High Risk Breast-Cancer Patients by Gene Expression Profiling. Lancet (London, England), 359, 131-132.
 Kneisel, L., Strebhardt, K., Bernd, A., Wolter, M., Binder, A., et al. (2002) Expression of Polo-Like Kinase (PLK1) in Thin Melanomas: A Novel Marker of Metastatic Disease. Journal of Cutaneous Pathology, 29, 354-358.
 Tang, Z., Li, C., Kang, B., Gao, G., Li, C., et al. (2017) Gepia: A Web Server for Cancer and Normal Gene Expression Profiling and Interactive Analyses. Nucleic Acids Research, 45, W98-W102.
 Holdorf, A.D., Higgins, D.P., Hart, A.C., Boag, P.R., Pazour, G.J., et al. (2019) Caenorhabditis Eleganswormcat: An Online Tool for Annotation and Visualization of Genome-Scale Data. Genetics, 24, 287-291.
 Lv, J. and Li, L. (2019) Hub Genes and Key Pathway Identification in Colorectal Cancer Based on Bioinformatic Analysis. BioMed Research International, 2019, Article ID: 1545680.
 Li, B., Pu, K. and Wu, X. (2019) Identifying Novel Biomarkers in Hepatocellular Carcinoma by Weighted Gene Co-Expression Network Analysis. Journal of Cellular Biochemistry, 26, 79-85.
 Haupenthal, J., Bihrer, V., Korkusuz, H., Kollmar, O., Schmithals, C., et al. (2012) Reduced Efficacy of the PLK1 Inhibitor Bi 2536 on the Progression of Hepatocellular Carcinoma Due to Low Intratumoral Drug Levels. Neoplasia (New York, N.Y.), 14, 410-419.
 McKenzie, L., King, S., Marcar, L., Nicol, S., Dias, S.S., et al. (2010) P53-Dependent Repression of Polo-Like Kinase-1 (PLK1). Cell Cycle (Georgetown, Tex.), 9, 4200-4212.
 Sun, W., Su, Q., Cao, X., Shang, B., Chen, A., et al. (2014) High Expression of Polo-Like Kinase 1 Is Associated with Early Development of Hepatocellular Carcinoma. International Journal of Genomics, 2014, Article ID: 312130.
 Ando, K., Ozaki, T., Yamamoto, H., Furuya, K., Hosoda, M., et al. (2004) Polo-Like Kinase 1 (PLK1) Inhibits P53 Function by Physical Interaction and Phosphorylation. The Journal of Biological Chemistry, 279, 25549-25561.
 Bouhlal, H., Ouled-Haddou, H., Debuysscher, V., Singh, A.R., Ossart, C., et al. (2016) RB/PLK1-Dependent Induced Pathway by Slamf3 Expression Inhibits Mitosis and Control Hepatocarcinoma Cell Proliferation. Oncotarget, 7, 9832-9843.
 VanHorn, R.D., Chu, S., Fan, L., Yin, T., Du, J., et al. (2010) Cdk1 Activity Is Required for Mitotic Activation of Aurora a during G2/M Transition of Human Cells. The Journal of Biological Chemistry, 285, 21849-21857.
 Singleton, M.R., Wentzell, L.M., Liu, Y., West, S.C. and Wigley, D.B. (2002) Structure of the Single-Strand Annealing Domain of Human RAD52 Protein. Proceedings of the National Academy of Sciences of the United States of America, 99, 13492-13497.
 King, S.I., Purdie, C.A., Bray, S.E., Quinlan, P.R., Jordan, L.B., et al. (2012) Immunohistochemical Detection of Polo-Like Kinase-1 (PLK1) in Primary Breast Cancer Is Associated with Tp53 Mutation and Poor Clinical Outcome. Breast Cancer Research: BCR, 14, R40.