Screening and evaluation of key genes in contributing to pathogenesis of hepatic fibrosis based on microarray data

Hepatic fibrosis (HF), a common health issues worldwide, usually progresses to liver cirrhosis, primary liver cancer and then results in death [1‐3]. Despite the impact of HF, it is regretful about note that an optimal treatment has yet to be identified. The good news is that advances in molecular biotechnology and high-throughput technology have positioned us on the frontier of understanding the possible molecular mechanism of HF at the gene and protein levels [4‐6]. However, a comprehensive understanding of the pathogenesis underlying HF still remains to be elucidated, due to its complexity, especially the complicated regulatory mechanisms of gene expression. Hence, understanding the underlying pathophysiology of HF, and the screening of molecular markers in the development of therapeutic targets remains critical.

More and more evidence has indicated that, rather than being transcriptional noise, lots of non-coding RNAs (ncRNAs) can affect the expression levels of target genes [7, 8]. Long non-coding RNAs (lncRNAs), one of a ncRNAs, which play critical roles in transcription, splicing and translation [9]. However, up to now, compared with mRNAs, the function of lncRNAs has not been well annotated [10, 11]. Therefore, to research the roles of lncRNAs by studying the related to targeting genes such as mRNAs, whose functions have been known, have been certificated an efficient way in many kinds of diseases [12‐14].

In the current study, we used microarray data to identify novel HF-related lncRNAs and mRNAs. Furthermore, bioinformatics technologies, such as Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, protein–protein interaction (PPI) network and weighted gene co-expression network analysis (WGCNA), were applied to analyze the differentially expressed lncRNAs (DELs) and mRNAs (DEMs). The findings may provide in-depth molecular insight into the pathophysiology of HF.

Hepatic fibrosis, a reversible lesion, is a common progresses for acute or chronic liver diseases to liver cirrhosis, which is irreversible [21‐24]. Therefore, it is crucial to explore the comprehensive mechanisms of HF to reverse its progress promptly. Over the past several years, as novel regulators in the cellular and biological processes, lncRNAs have attracted much close attention [25‐27]. However, as previously mentioned, the number of meaningful key lncRNAs identified in HF tissues is still not sufficient.

In this study, we screened 254 DELs, which consisted of 107 up- and 147 down-regulated lncRNAs. Meanwhile, 472 DEMs were examined, which consisted of 308 up- and 164 down-regulated mRNAs. Furthermore, to investigate the functions of HF-related genes, we annotated these genes into GO and KEGG pathway analysis, we found that the DE genes were remarkably enriched in the GO terms involving TGF-β signaling pathway, ECM-receptor interaction, PPAR signaling pathway, etc. It is well known that activated hepatic stellate cells (HSCs) are famous for their role in liver fibrosis. Several studies have shown TGF-β plays a critical role in HSCs activation, and the TGF-β signaling pathway could be a potential therapeutic target for HF [28‐30]. This classic signaling pathway is activated by TGF-β binding to its receptors located on the cell membrane. The downstream proteins, namely Smad2 and Smad3, are activated by phosphorylation, which further promotes the transcription of genes encoding ECM components, then accelerates the development of liver fibrosis [31]. Similarly, KEGG analysis revealed that the DE genes were mainly enriched in the metabolic process, which were closely related to previous studies. For example, our previous studies indicated that dysregulations of cytochrome P450, sphingolipid, glucose and water electrolyte, fatty acid, amino acid and energy metabolism might be involved in the pathogenesis of HF in rats [32, 33].

The WGCNA is a bioinformatics technology for describing the correlation patterns among genes across microarray samples. It is a powerful systems analysis technology that focuses on the coherent function of gene network modules, which aims at identifying higher-order relationships among gene products [34]. WGCNA analysis of lncRNAs and mRNAs has been successfully utilized to screen functionally enriched modules involved in complex diseases [35‐37]. Via WGCNA, two lncRNA-mRNA weighted co-expression sub-networks were identified, which included 24 key lncRNAs and 40 mRNAs.

Although several LncRNAs that could affect hepatic fibrosis were already reported including lnc LFAR1 [15], p21 [38], MALAT1 [39], MEG3 [40] and so on. However, the functional characterization of the 24 key lncRNAs is still in its infancy. To infer potential function of LncRNAs, according to ceRNA theory, we studied the related to mRNAs, whose functions have been annotated. For example, lnc Gm38888, NONMMUT006555, NONMMUT074618 were screened out and could interact with Col6a1 in the blue module. It is worth noting that Col6a1, the main component of HF identified in our study, is a type VI collagen gene which has been widely reported to be closely associated with HF. Accumulation of type VI collagen may lead to the distorted architecture and functional damage to the liver in HF [41, 42]. Moreover, KEGG analysis showed that Col6a1 is enriched in ECM-receptor interaction, which has been reported to play a key role in HF, as discussed above.

For the turquoise module, lnc Gm39636, Gm26618, NONMMUT015498, etc., which interact with Itga8. In particular, Itga8 is a specific cell surface marker of mesothelial cell (MC)-derived HSCs and MCs. Itga8⁺ (MCs) is the maintain phenotype of hepatoblasts in liver development and myofibroblasts increase the expression of Itga8 during liver injury [43]. Recently research suggested that MCs played important roles in liver development, fibrosis, and regeneration [44]. KEGG analysis showed Itga8 is enriched in the pathways of ECM-receptor interaction, FA and PI3K-Akt signaling pathway, which have been demonstrated to be closely related with HF.

In summary, HF was a complicated process with some lncRNAs, mRNAs involved, which were the key genes in contributing to pathogenesis of HF. This study revealed crucial information on the molecular mechanisms of HF and laid a foundation for subsequent gene validation and functional studies, which could contribute to the development of novel diagnostic markers and provide new therapeutic targets for the clinical treatment of HF. However, there were still some limitations in this study. Firstly, the key genes need to be verified in liver tissue specimens of liver fibrosis by RT-PCR. Secondly, further experiments are required to validate their effects and mechanisms in HF. The last but not least, the homology of the key genes needs to be validated for using as potential biomarkers and therapeutic targets in clinical applications.