The Novel Action of miR-193b-3p/CDK1 Signaling in HCC Proliferation and Migration: A Study Based on Bioinformatic Analysis and Experimental Investigation

Hepatocellular carcinoma (HCC) is a common human malignancy with high mortality and dismal prognosis. A growing number of novel targets underlying HCC pathophysiology have been detected using microarray high throughput screening platforms. This study carried out bioinformatics analysis to explore underlying biomarkers in HCC and assessed the potential action of the miR-193b-3p/CDK1 signaling pathway in HCC progression. A total of 241 common differentially expressed genes (DEGs) were screened from GSE33294, GSE104310, and GSE144269. Functional analysis results implicated that DEGs are significantly associated with “cell cycle,” “cell division,” and “proliferation.” The protein–protein interaction network analysis extracted ten hub genes from common DEGs. Ten hub genes were significantly overexpression in HCC tissues. Kaplan–Meier survival analysis revealed that 10 hub genes were linked with a poorer prognosis in HCC patients. Functional assays showed that CDK1 knockdown repressed HCC cell proliferation and migration. Luciferase reporter assay showed that miR-193b-3p could target CDK1 3′ untranslated region, and miR-193b-3p negatively modulated CDK1. Enforced CDK1 expression attenuated miR-193b-3p-modulated suppressive actions on HCC cell proliferation and migration. To summarize, we performed a comprehensive bioinformatics analysis and identified 10 hub genes linked to the prognosis in HCC patients. Functional analysis revealed that CDK1, negatively regulated by miR-193b-3p, may act as an oncogene to promote HCC cell proliferation and migration and may predict poor prognosis of HCC patients. However, the role of CDK1/miR-193b-3p may still require further investigation.


Introduction
Hepatocellular carcinoma (HCC) is a common human malignancy with high mortality and dismal prognosis [1,2]. Studies have found that viral hepatitis infection is a risk factor contributing to HCC development [3][4][5][6]. Early-stage HCC patients often have a 5-year overall survival (OS) rate of about 30%, whereas for the patients with distant metastases, the rate drops to around 5% [7,8]. For the treatment of HCC, surgical resection is the primary therapeutic option for HCC at its early stages, whereas patients with advancedstage HCC often were unsuitable for surgical resection. So far, though significant improvements have been made in targeted therapy in the clinical aspects, the OS of patients with HCC remains poor due to the insufficient understanding of molecular mechanisms underlying HCC pathophysiology [7,8]. Therefore, it is necessary to understand its underlying mechanisms to design valuable and effective strategies.
Recently, genome-wide studies using microarray high throughput technology have significantly advanced our understating of the genetic landscape and driver pathways contributing to the HCC development [9][10][11][12][13][14]. Chen et al. conducted a tissue microarray analysis and identified a correlation between ALKBH5 and HCC progression [15]. Hamdane et al. proposed that the increased risk of HCC is affected by epigenetic alterations [16]. Lu et al. performed the long noncoding RNA (lncRNA) and mRNA profiling using RNA sequencing and found that lncRNA TSPAN12 acted as a potential microvascular invasion-related biomarker in HCC [17]. Huang and co-workers performed the integrated analysis of RAN-Seq data of HCC. They identified the intrinsic gene expression pattern of HCC, which provides a novel perspective to understanding the heterogeneity of pathogenesis in the HCC tumorigenesis [18]. Thus, more studies may be performed on microarray datasets to reveal novel potential targets related to HCC pathophysiology.
MicroRNA (miRNA) belongs to a class of small noncoding RNA with 21-30 nucleotides in length [19,20]. miRNA can negatively regulate target genes by binding to the 3 ′ untranslated region (UTR) of the mRNAs [19]. Due to this mechanism, miRNAs have been found to regulate the HCC pathophysiology via distinct mechanisms [21]. Komoll et al. showed that miR-342-3p acted as a potent tumor suppressor in HCC [22]. Zhou et al. demonstrated that the miR-28-5p-interleukin-34-macrophage feedback loop could regulate the HCC metastasis [23]. Bhattacharya et al. found that serum miR-30e and miR-223 could act as novel noninvasive biomarkers for HCC [24]. Recently, studies also demonstrated that upregulation of miR-520c-3p via hepatitis B virus enhanced HCC migration and invasion by the PTEN/AKT/NF-κB axis [25]. Therefore, further understanding the involvement of miRNAs in HCC progression is of great importance for developing novel therapies.
This study utilized the Gene Expression Omnibus (GEO) datasets (GSE33294, GSE104310, and GSE144269) to extract differentially expressed genes (DEGs) in the liver tissues between HCC and non-tumor groups. Overlapping DEGs among GSE33294, GSE104310, and GSE144269 were utilized for functional analysis and protein-protein interaction (PPI) network establishment. Identified hub genes were further subjected to survival analysis of patients with HCC. Besides, the biological functions of CDK1 (one hub gene) were examined by experimental assays, and its regulatory miRNA was also determined. The present study may advance our understanding of HCC progression and prognosis.

DEGs
Extractions. Gene expression sets in GSE33294, GSE104310, and GSE144269 were extracted using Geo RNAseq experiments Interactive Navigator (GREIN), an online pipeline for analyzing the GEO datasets uniformly. The DEGs were selected as false discovery rate <0.05, −2 > log (fold change) > 2. Common DEGs among GSE33294, GSE104310, and GSE144269 were collected for subsequent evaluation.
2.3. Functional Analysis of DEGs. The g:Profiler tool [26] was utilized to carry out Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and miRNA pathway enrichment analysis. GO enrichment analysis field included biological processes, cellular components, and molecular function [26]. The KEGG was utilized to understand relevant pathways [26].
2.4. PPI Network Establishment. Interactive details of DEGs were evaluated by the STRING tool. Subsequently, Cytoscape (version 3.6.1; https://cytoscape.org/) was utilized to establish the PPI network of DEGs. The submodules from the PPI network were extracted using CytoHubba and Molecular Complex Detection (MCODE) applications.

Hub Gene Expression Analysis. The Gene Expression
Profiling Interactive Analysis (GEPIA) database (a newly developed interactive web server for analyzing the RNA sequencing expression data of 9,736 tumors and 8,587 normal samples from the TCGA and the GTEx projects, using a standard processing pipeline) [27] was utilized to explore 10 hub genes expression, and P < 0:05 was statistically significant. Protein levels of relevant hub genes were evaluated using Human Protein Atlas database.
2.6. Survival Analysis. OS and disease-free survival (DFS) of HCC patients were assessed by GEPIA [27]. Kaplan-Meier curves were plotted using the data from 369 HCC patients. P < 0:05 was statistically significant.
2.7. Cell Lines and Cell Culture. LO2, HCC-LM3, SMMC7221, and HEK293T cells were purchased from the Chinese Academy of Sciences (Shanghai, China). Cells were cultured in the Dulbecco's modified eagle medium (Sigma, St. Louis, USA) supplemented with 10% fetal bovine serum (Sigma) and were maintained in a humidified atmosphere with 5% CO 2 at 37°C.
2.9. RNA Isolation and RT-qPCR. RNA extraction from respective cells was carried out TRIzol (TaKaRa, Dalian China). The purity and concentration of the extracted RNA were determined using the spectrophotometer (Sigma). One microgram RNA was transcribed into cDNA using Prime-Script 1st strand cDNA Synthesis Kit (TaKaRa). Real-time PCR was carried out utilizing One Step PrimeScript™ RT-PCR Kit (TaKaRa) with ABI7900 (Applied Biosystems, Foster City, USA). Glyceraldehyde-3-phosphate dehydrogenase was selected for reference control of CDK1, and 2 International Journal of Genomics    International Journal of Genomics   Table S1. 2.11. Bromodeoxyuridine (BrdU) Assay. BrdU staining assay was utilized to measure the proliferative potential of respective cells with corresponding interventions. Briefly, cells after different interventions were subjected to BrdU (10 μg/ml; Sigma-Aldrich) and BrdU incubation for 30 minutes. After rinsing with phosphate-buffered saline, cells were fixed in 4% paraformaldehyde for 20 minutes. Subsequently, cells were probed with the primary antibody against BrdU (1 : 200; Abcam, Cambridge, MA, USA) for 1 hour, followed by probing with Alexa FluorR ® 594conjugated secondary antibody. The 4 ′ ,6-diamidino-2-phenylindole (DAPI) (300 nM) was used for nuclear staining. The number of BrdU + cells was determined using a fluorescent microscope.
2.12. TdT-UTP Nick End Labeling Assay. TdT-UTP nick-end labeling (TUNEL) assay was carried out with the one-step TUNEL kit (Elabscience, Wuhan, China) according to the manufacturer's instructions. Briefly, corresponding cells with different interventions were fixed onto poly-(L-lysine)-coated slides with 4% paraformaldehyde. Cells were permeabilized with 0.1% Triton X-100 followed by incubation in 50 ml TUNEL reaction mixture for 1 hour at 37°C in the dark. Next, DAPI was added and incubated for 2 minutes at room temperature for the staining of the nucleus. Cells exhibiting green fluorescence were defined as TUNEL-positive, apoptotic cells.
2.14. Wound Healing Assay. A wound healing assay was utilized to measure HCC cell migratory potential. Briefly, HCC cells after different treatments were seeded onto six-well plates. After cells grew to about 80% confluence, a wound was generated utilizing a sterile pipette tip to scratch the cellular monolayer. Wound healing was evaluated for 24 hours. Wound width was measured at 0 and 24 hours, respectively. The wound closure was calculated as follows: (width of the wound at 0 hour − width of the wound at 24 hours)/width of the wound at 0 hour.

The Expression and Survival
Analysis of Hub Genes in HCC. Ten hub genes in control and HCC tissues were

CDK1 Silence Attenuates HCC Cell Proliferation and
Migration. CDK1 has the highest score as a hub gene based on the CytoHubba analysis, so CDK1 was chosen for further in vitro functional studies. As shown in Figure 9(a), CDK1 was up-regulated in the SMMC7721 and HCC-LM3 cells compared with that in LO2. Furthermore, the downregulation of CDK1 was achieved by treating HCC cells with CDK1 siRNA. CDK1 siRNA transfection repressed CDK1 expression (Figures 9(b) and 9(c)). The CCK-8 and BrdU assays showed that CDK1 knockdown reduced the HCC cell viability and proliferation (Figures 9(d), 9(e), 9(f), and 9(g)).

CDK1 Overexpression Attenuated miR-193b-3p-Mediated
Effects on the HCC Cell Proliferation and Migration. The expression of miR-193b-3p in the LO2, SMMC7721, and HCC-LM3 cells was evaluated by qRT-PCR, and the expression level of miR-193b-3p was significantly downregulated in the SMMC7721 and HCC-LM3 cells when compared with LO2 cells (Figure 11(a)). The functional experiments showed that miR-193b-3p overexpression sig-nificantly repressed cell viability, cell proliferation, and migration but increased the number of apoptotic cells and enhanced the caspase-3/-7 activity of SMMC7721 cells, which was significantly reversed by the enforced expression of CDK1 (Figures 11(b), 11(c), 11(d), 11(e), 11(f), and 11(g)).

Discussion
HCC patient survival is poor owing to insufficient diagnostic and effective strategy HCC [1]. Using microarray high throughput screening platforms, a growing number of novel targets underlying HCC pathophysiology have been identified [12]. This analyzed GSE33294, GSE104310, and GSE144269 datasets and found 241 common DEGs. Functional analysis revealed essential pathways of DEGs. Ten hub genes from DEGs were detected from the PPI network. TGCA database analysis showed that the high expression of ten hub genes was closely linked to a worse prognosis for HCC patients. Functional assays indicated that CDK1 knockdown repressed the HCC cell proliferation and migration; CDK1 was negatively modulated by miR-193b-3p and  Recently, many GEO microarray datasets have been explored to retrieve novel targets associated with the HCC progression. In the GSE33294, researchers utilized large-scale transcriptomic analysis and revealed the differentially expressed ADARs in HCC [29]. In GSE144296, Candia et al. described molecular features of Mongolian HCC patients using whole-exome and transcriptomic analysis and proposed novel mechanisms of hepatocarcinogenesis in the Mongolians [30]. In the present study, we extracted common DEGs from the above datasets and detected 241 common DEGs, and functional analysis revealed that these common DEGs were mainly classified into pathways associated with cell proliferation and division.
We identified 10 highly connective hub genes based on the PPI network results. Based on the GEPIA tool analysis, ten hub genes were overexpressed in HCC tissues. High expression of these hub genes was linked with poor prognosis of HCC patients. Previous studies have demonstrated that the role of CDK1, CDC20, BUB1, BUB1B, CCNA2, TOP2A, KIF2C, KIF20A, CCNB1, and CCNB2 has been explored in HCC to some extent [31][32][33][34]. Among the ten hub genes, we selected CDK1 for further investigation, due to the highest score in the PPI network based on the CytoHubba. Our study found that CDK1 silence impaired HCC cell proliferation and migration, which was consistent with previous studies [31,32,34]. Studies also showed that the block of CKD1 could attenuate in vivo tumor growth of HCC cells [35]. Furthermore, to further decipher the regulatory action of CDK1 in HCC cell progression, we found that miR-193b-3p targeted most of the common DEGs including CDK1. Thus, we further confirmed the link between miR-193b-3p and CDK1 3 ′ UTR by bioinformatic prediction and luciferase reporter assay. CDK1 was negatively modulated by miR-193b-3p, and enforced CKD1 expression attenuated the miR-193b-3p-mediated suppressive actions on HCC cell proliferation and migration. Tumor-suppressive action of miR-193b-3p has been examined in various types of cancers [36][37][38][39][40]. miR-193b-3p could target various downstream targets, such as MORC4 [40], CCND1 [41], ETS1 [42], MYB [43], and so on. In the in vivo studies, miR-193b-3p exerted suppressive effects on the tumor growth of HCC cells in the nude mice [44]. In the clinical aspect, Wang et al. demonstrated that miR-193b-3p was downregulated in the HCC tissues by analyzing the Cancer Genome Atlas database [45]; Xu et al. demonstrated the down-regulation of miR-139b-3p in most of the HCC tissues compared to the matching non-tumoural liver tissues [44]. However, in our study, we demonstrated that miR-193b-3p targeted CDK1 3′UTR and subsequently repressed the expression of CDK1 in HCC cells. The above evidence suggested the novel miR-193b-3p/CDK1 signaling pathway in modulating the HCC progression.
There are several limitations existing in our work. First, the correlation between miR-193b-3p and CDK1 was only examined in the in vitro studies, and further studies should confirm the in vitro findings using the clinical samples from HCC patients. Second, the predicted upstream circular RNAs and long non-coding RNAs that may affect miR-193b-3p expression should be confirmed by mechanistic studies.
To summarize, we performed a comprehensive bioinformatics analysis and identified 10 hub genes linked to the prognosis of HCC patients. Functional analysis revealed the novel functional action of miR-193b-3p/CDK1 signaling in HCC pathophysiology.

16
International Journal of Genomics

Data Availability
Data supporting this research article are available from the corresponding author or first author on reasonable request.

Conflicts of Interest
The author(s) declare(s) that they have no conflicts of interest.

Authors' Contributions
All authors made substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; took part in drafting the article or revising it critically for important intellectual content; agreed to submit to the current journal; gave final approval of the version to be published; and agreed to be accountable for all aspects of the work.