Differential expression and function prediction of miRNAs in Hepatocellular carcinoma based on bioinformatics

Cheng-Zhou Pa, Shan-Min Wu

Department of Hepatobiliary Surgery, Renmin Hospital of Wuhan University, wuhan 430060, China

Keywords:

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1. Introduction

Hepatocellular carcinoma (HCC) is the third most common cause of cancer death globally, with the major risk factors being chronic Hepatitis C virus (HCV) and/or Hepatitis B virus (HBV) infection, heavy alcohol consumption, diabetes, and non-alcoholic fatty liver disease [1]. According to the guidelines for the diagnosis and treatment of primary liver cancer (2019 edition), HCC is the fourth most common malignant tumor and the second leading cause of death in China. MicroRNA (miRNA) is a kind of non-coding small RNA with a length of about 20 nucleotides, which plays an important role in the occurrence, development and prognosis of various types of malignant tumors such as liver cancer, colorectal cancer, lung cancer and breast cancer [2]. miRNA can be involved in cell cycle regulation, cell differentiation and regulation as tumor suppressor or oncogene, and its expression imbalance is causeeffect related to the occurrence of carcinogenesis [3].Due to the difficulty in early diagnosis and high postoperative recurrence rate, HCC has a high mortality rate. Therefore, the exploration of differentially expressed miRNAs in HCC is conducive to further improving the understanding of the disease and the level of diagnosis and treatment. In this study, miRNA from HCC samples and adjacent liver tissue samples from GEO database were retrieved for differential analysis, and the differentially expressed miRNA of both samples was screened for functional enrichment analysis, and transcription factors were predicted, providing new ideas for early diagnosis and late intervention of HCC.

2. Materials and methods

2.1 Data sources

GEO database (https:// www.ncbi.nlm.nih.gov/geo) is a genomic data repository created and maintained by the national center for biotechnology information (NCBI), with the largest and most comprehensive public source of gene expression data available today. "Hepatocellular carcinoma" was used as the key word for retrieval, and the detection type was "non-coding RNA profiling by array", to define the species and obtain the dataset GSE108724. This data set is from zhongshan hospital of fudan university, and contains 7 pairs of liver cancer tissues and their corresponding samples of adjacent liver tissues. Download agilent-070156 Human miRNA platform and matrix data files.

2.2 Data collection and differential expression analysis

The data set GSE108724 was sorted by using platform files and sample annotation information, and was divided into two groups: normal liver tissue and liver cancer tissue. Using R (v 3.6.0) to extract gene set data through limma packet, differential expression was screened using | log fold change | >2 and P<0.05 as the filtering condition, and differential miRNA was visualized in combination with pheatmap packet to draw volcano map and heatmap.

2.3 Transcription factor prediction and functional enrichment analysis

FunRich (v 3.1.3) is an independent software tool for functional enrichment and interaction network analysis of genes and proteins. FunRich software was used to screen out differential miRNAs for transcription factor prediction. Differential miRNA signaling pathway analysis and Gene Ontology (GO) enrichment analysis were performed. GO enrichment analysis included Biological Process, Cellular Component and Molecular function. The enrichment of transcription factors and pathways of miRNA showed the first 20 positions according to the P value and was visualized. Meanwhile, the GO enrichment analysis used ImageGP (www.ehbio.com/ImageGP) to draw the bubble map.

3. Results

3.1 Differential miRNA expression

In the dataset GSE108724, a total of 2,549 miRNAs were included, and a total of 37 miRNAs were screened with different expressions (Figure 1A). In HCC, the up-regulated miRNAs were miR-3188, miR-18a-5p, miR-1181, miR-221-3p, miR-532-3p, miR-222-3p, miR-96-5p, miR-362-5p, miR-18b-5p, miR-502-3p, miR-500a-3p, miR-4651, miR-196b-5p, miR-362-3p, miR-6516-3p; The downregulated miRNAs were miR-10a-5p, miR-4324, miR-199a-3p, miR-139-3p, miR-6769b-5p, miR-338-3p, miR-3616-3p, miR-7152-5p, miR-378a-5p, miR-7845-5p, miR-8089, miR-6793-5p, miR-200a-3p, miR-3912-5p, miR-557, miR-6515-5p, miR-199a-5p, miR-378d, miR-6757-5p, miR-486-5p, miR-214-3p, miR-375 (Figure 1B).

Fig 1 A. Volcano of miRNA expression in HCC and normal liver tissues B. Heatmap of differential miRNA in HCC and normal liver tissues

3.2 Prediction of transcription factors

FunRich software was used to predict the transcription factors of 37 miRNAs with different expressions, and a total of 201 transcription factors were obtained. The 20 transcription factors with the greatest differences were EGR1, POU2F1, SP1, NKX6-1, MEF2A, FOXA1, SP4, NFIC, RREB1, ARID3A, HOXA5, HNF4A, HOXD8, RORA, LHX3, POU3F2, FOXJ2, POU5F1, NKX2-1, SOX1 (Figure 2).

Fig 2 Prediction of transcription factor

3.3 Signal path analysis and GO enrichment analysis

Analysis of signaling pathways revealed that different miRNAs may play a role through Glypican, Nectin adhesion, Thrombin/proteaseactivated receptor (PAR), The epidermal growth factor receptor (EGFR), IGF-1, γ-IFN, Plasma membrane estrogen receptor signaling pathways play a role,and differential miRNAs is associated with VEGF, VEGFR, PDGF, Hepatocyte Growth Factor Receptor (c-Met), Syndecan-1, IL5, protease-activated receptor 1 (PAR-1), Protein serine/threonine kinase, Syndecan mediated signaling events (figure 3). GO enrichment analysis showed that differential miRNAs were found to be mainly located in the Nucleus and Cytoplasm, It has molecular functions such as Protein serine/threonine kinase activity, Receptor signaling complex scaffold activity, Transcription regulator activity and Transcription factor activity, Involved in Nucleic acid metabolism and Signal transduction and Cell communication (figure 4).

Fig 3 Pathways of differential miRNA

Fig 4 Biological function of differential miRNA

4. Discussion

miRNAs are small non-coding molecules known to regulate over 60% of human gene expression, mainly by interacting with the 3 'non-coding region of mRNA to form RNA-induced silencing complexes that lead to translation inhibition or degradation of target genes to regulate gene expression. Studies have shown that[4-7], Differential miRNA plays an important role in regulating the proliferation, apoptosis, invasion and migration of HCC cells, One miRNA also regulates multiple target genes, Up-regulated miR-532-3p promotes the migration and proliferation of HCC cells by targeting PTPRT, KIFC1, etc. It is worth noting that Yusuke Yamamoto used miRNAs microarray analysis of 345 cases of HCC, 46 cases of chronic hepatitis, 93 cases of cirrhosis of the liver and 1033 healthy people and found in the serum of miRNAs can be used as biomarkers of accurate detection of HCC, because of its diagnostic accuracy in Ⅰ stage also can maintain, may be a method of accurate early detection of HCC[8] . In the future, the 37 differential miRNAs screened out from HCC could be further explored in clinical work as early detection biomarkers.

miRNA and transcription factors are the two largest trans-acting factors, which are important regulatory factors for gene expression regulation. They are closely related in the regulatory network of gene expression, play a regulatory role in coordination, and fine-regulate gene expression, playing an important role in cell differentiation and animal growth and development. POU2F1 regulated by AKT pathway promotes the migration and invasion ability of tumor cells by Epithelial-mesenchymal transition (EMT), RREB1 integrates TGF-β and RAS signals to drive EMT [9, 10]. Transcription factors FOXA1 and FOXJ2, a member of the forkheadbox (FOX) protein family, can bind to non-transcriptional chromosomes, change their structure, and improve the transcription of other transcription initiation factors to regulate the expression of downstream genes [11, 12]. Sp1 is involved in the transcriptional regulation of VEGF in tumor cells under hypoxic conditions[13]. Changes in the expression levels of EGR1, HOXA5, SOX1, LHX3 and HNF4A can affect the proliferation, apoptosis and invasion ability of tumors [14-18]. The remaining transcription factors involved in various biological behaviors such as cell proliferation, differentiation, apoptosis and metastasis need to be further verified and clarified in the experimental studies on co-regulation of miRNA.

The analysis results of signaling pathways showed that the enrichment of differential miRNA was related to PDGF, VEGF, VEGFR-mediated signaling events, suggesting that the expression imbalance of miRNA also had an important impact on angiogenesis. The VEGF/VEGFR2 signaling pathway is involved in the proliferation of new endothelial cells around tumors and is the most important rate-limiting step of physiologic and pathological angiogenesis[19]. At the same time, differential miRNAs are also involved in the regulation of cell proliferation, differentiation, adhesion and migration. EGF, PDGF, VEGF, IGF-1 and other receptors have Receptor tyrosine kinase (RTKs) activity, which plays a key role in cancer metastasis [20].

Different miRNAs are mainly located in the Nucleus and Cytoplasm. Protein serine/threonine kinase is the most important class of kinases regulating intracellular phosphorylation and covalent modification, and cyclin-dependent kinase (CDK) is one of the driving forces of cell cycle, which will lead to the occurrence of tumor once the normal cell cycle is disturbed[21]. In the treatment of HCC, surgery remains an important means of long-term survival for HCC patients. The first-line drug sorafenib, often used to treat patients with advanced HCC, is a small molecule multi-tyrosine kinase inhibitor that improves survival, but most patients eventually develop resistance to sorafenib[22]. Studies have shown that[23], miR-378a can not only inhibit the proliferation and invasion of HCC and hepatoblastoma cell lines, but also enhance the sensitivity of tumor cells to sorafenib by targeting VEGFR, PDGFR-β and Raf-1 protooncogene.

In conclusion, differential miRNAs play an important role in many physiological and pathological processes including cell proliferation, differentiation, apoptosis, tumorigenesis and signal transduction of HCC. With the development of miRNA research techniques and further studies on the signaling pathways, epigenetic regulation and pathogenesis in HCC, it has been confirmed that some differentially expressed serum miRNA can be used as potential biomarkers for the early diagnosis of HCC, and restoring the physiological level of miRNA may be a new strategy for the treatment of HCC. Continuous improvement of gene expression regulatory pathways and molecularly targeted drugs can improve the resistance of HCC patients to sorafenib, which is of great value and significance for improving the clinical efficacy of HCC.