Identification of hub genes and pathways in cholangiocarcinoma by coexpression analysis

Cholangiocarcinoma (CCA) is the most common biliary tract malignancy and the second most prevalent primary hepatic malignancy after hepatocellular carcinoma (HCC) [1]. CCA combined with HCC was reported to be the third leading cause of cancer-related deaths in China in 2015 [2]. Moreover, despite having a lower CCA incidence rate, the age-adjusted incidence rates of CCA have increased in the United States and Western Europe during the last several decades [3]. At present, the commonly used treatment approaches for CCA include surgical resection, chemotherapy, molecularly targeted therapies and liver transplantation [4, 5]. However, the 5-year overall survival rate of CCA is still dismal, especially in advanced CCA [6]. In addition, the current serum biomarkers used for CCA diagnosis are not sensitive or accurate, and there is a lack of knowledge about CCA development, progression and prognosis [7, 8, 9]. Consequently, a better understanding of the molecular mechanisms of CCA tumorigenesis and progression is critical and may provide new insight into CCA therapy.

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In recent years, gene expression analysis based on high-throughput platforms has been widely used for detecting significant expression changes in thousands of genes and identifying promising biomarkers for the diagnosis and therapy of cancers [10]. Some studies have found many differentially expressed genes (DEGs) that play critical roles in CCA development, progression and prognosis and could be regarded as potential diagnostic and therapeutic targets. Betesh et al. [11] identified fucosylated Fetuin-A as an effective serum marker in the surveillance of people at risk of developing of CCA. Through multiplexed mutational profiling, Zhu et al. [12] demonstrated that KRAS and IDH1 were the most common mutations noted in intrahepatic cholangiocarcinoma (ICC) and were associated with the clinicopathological features of ICC. Weighted gene coexpression network analysis (WGCNA) is a powerful tool that can be used in data exploration or to find modules containing highly correlated genes. It has been widely used for finding hub genes in many malignancies. For instance, Tang et al. [13] used WGCNA and identified five core genes, the dysregulation of which was closely associated with the progression and prognosis of breast cancer. In this study, to further understand the molecular mechanisms of CCA development, progression and prognosis, we used WGCNA to explore modules related to clinical characteristics.

3. Results

CCA is the most common biliary malignancy arising from the epithelial lining of the bile duct [26]. Due to its silent clinical characteristics, difficulties in early diagnosis and limited therapeutic approaches, the prognosis of CCA is still dismal [6]. The detection of the disease at an early stage is crucial for patients to receive surgical resection, which is regarded as the single curative treatment. Nevertheless, the diagnosis of CCA is still challenging because of the lack of specific biomarkers in serum and/or biopsy samples and imaging methods [27, 28, 29]. Consequently, the identification of novel diagnostic and therapeutic biomarkers of patients with CCA is an important future direction. Recent advances in high-throughput technologies, including gene chips and mass-spectrometric techniques [30, 31], provide novel insight into the molecular understanding of CCA that can increase the identification of potential biomarkers for clinical use.

In the present study, a CCA-related dataset, GSE 89748, encompassing the molecular and clinical data of 72 cholangiocarcinoma samples, was downloaded from the NCBI GEO database. Using WGCNA, a coexpression network complex was constructed using 6274 genes, and 25 modules were screened. Among them, three modules, cyan, light cyan and red, were closely associated with histology and were regarded as modules containing hub genes. Subsequently, 20 candidates were discovered in both the coexpression and PPI networks, 13 of which were found to be related to the prognosis of CCA, and 10 genes, LIMA1, HDAC1, ITGA3, ACTR3, GSK3B, ITGA2, THOC2, PTGES3, HEATR1 and ILF2 were finally identified as real hub genes dysregulated in CCA samples and were associated with CCA prognosis.

HDAC1, also known as histone deacetylase 1, belongs to the class I histone deacetylases, which also contain HDAC2, 3 and 8 [31]. HDAC1 located in the nucleus, as an epigenetic factor, could antagonize the acetylation status of histone and nonhistone proteins [33]. It was reported that HDAC1 was dysregulated in various types of malignancies. In patients with breast cancer, Tang et al. [34]. discovered that the mRNA level of HDAC1 was overexpressed in tumour tissues. In addition, they also found that HDAC1 could activate Snail/IL-8 signalling and promote the proliferation and migration of cancer cells. In lung cancer patients, a recent meta-analysis revealed that the dysregulation of HDAC1 was related to poorer differentiation grade, which is commonly regarded as a reflection of poor prognosis in cancer [33]. Moreover, the relationship between the dysregulation of HDAC1 and dismal prognosis of lung cancer was also proven in this study. In liver cancer, Ser et al. [35] found that HDAC1 was overexpressed in HCC samples, and in addition to a higher number of cancer-specific deaths, its dysregulation was also related to poor differentiation grade, multiple lesions and satellite nodules. Several studies have focused on the role of HDAC1 in CCA prognosis. In a study of thirsty-five patients, Morine et al. [36] found that the overexpression of HDAC1 was associated with various malignant tumour characteristics, including higher tumour stage, vascular invasion and lymph node metastasis. They also proved that the dysregulation of HDAC1 was related to shorter disease-free survival and overall survival. In a recent study, Zhou et al. [37] discovered that the histone deacetylase inhibitor HC toxin could suppress the proliferation and migration of CCA cells in vivo and could thus be a potential candidate for CCA chemotherapeutic drugs. Undoubtedly, HDAC1 seems to be a crucial biomarker in CCA development and progression, and further studies should be conducted to reveal the related mechanisms.

Integrin alpha 2 (ITGA2) and Integrin alpha 3 (ITGA3) are both members of the integrin family of proteins, serving as cell surface adhesion proteins, and they play crucial roles in cell-cell interactions and developmental and pathological processes [38]. Both genes are aberrantly expressed in various cancers and are associated with poor prognosis of cancers [39, 40, 41, 42, 43]. For instance, in pancreatic cancer, the dysregulation of ITGA3 was discovered to be associated with poorer histological grades, later tumour stages, and shorter disease-free survival and overall survival [43]. To reveal the related mechanisms, Gong et al. [44] demonstrated that the overexpression of UCA1-ITGA2 could promote the proliferation, migration and invasion of pancreatic cancer cells. In a recent study, Ren et al. [45] proved that via the activation of the STAT3 signalling pathway, ITGA2 could upregulate PD-L1 expression and thus promote cancer cell proliferation and migration, which might provide a new insight into immune therapy for cancer. In CCA patients, ITGA3 was found to be overexpressed in CCA samples and was related to many malignant clinical traits, including tumour size, stage and lymph node metastasis [46]. In an in vitro experiment, although negatively related to CCA cell migration and invasion, Huang et al. [46] proved that ITGA3 could promote CCA cell proliferation by regulating the G1 phase of cell cycle progression. Considering the crucial roles of ITGA2 and ITGA3 in cancer development and progression, it is clear that they could be potential diagnostic biomarkers and therapeutic targets for CCA, and further explorations should be performed.

The dysregulation of the remaining core genes has also been discovered to be associated with cancer development, progression or poor prognosis. LIMA1, also known as EPLIN, is an actin-related molecule that is dysregulated in various cancers via adherens junction [47] and post-translational modifications [48], LIMA1 can influence cancer cell proliferation and invasion, which increases the metastatic probability of tumours [49]. GSK3B is a serine/threonine kinase that participates in various processes, including metabolism, neurological diseases and oncogenesis [50]. Recent studies proved that GSK3B plays two core roles in cancer development and progression: i) induction of NF- κ B activation; and ii) prevention of EMT pathways [51]. THOC2 was proven to be an oncogene in melanoma and was associated with the poor prognosis of these patients; it could promote tumour cell proliferation and migration via the cAMP signalling pathway [52]. HEATR1 was found to play a crucial role in ribosome biogenesis, and the dysregulation of HEATR1 could cause impaired ribosome biosynthesis and lead to the activation of the p53-dependent cell cycle checkpoint, which might be associated with the genesis of cancer [53]. In pancreatic ductal adenocarcinoma ILF2 was found to regulate cancer cell proliferation and promote tumorigenesis by regulating cyclin members such as cyclin E and G1 cyclin [54].

In the GO analysis, protein binding was the pathway in which the genes in the three modules were mainly enriched. This result was consistent with the related functions of the hub genes, including LIMA1, GSK3B ITGA2 and ITGA3. Furthermore, in the KEGG analysis, the majority of the genes in the three modules were enriched in signal transduction, metabolism-related pathways, post-transduction modification and gene expression, which suggested that the genes were closely related to the mitotic cell cycle process. Cell cycle dysregulation has been demonstrated to be associated with the development and progression of various types of cancers, including CCA [55, 56]. Chen et al. [57] demonstrated that the downregulation of KLHL21 could alter the P21/P27/Cyclin E1 protein, trigger G0/G1 cell cycle arrest and prevent CCA cell migration and invasion by restraining the activation of the Erk signalling pathway, which might be a novel therapeutic target. In addition, several studies have shown that many drugs, such as telmisartan and cryptotanshinone, could induce cell cycle arrest and apoptosis in CCA and are potential therapeutic agents for CCA [58, 59]. Clearly, more attention should be paied to these cell cycle-related pathways and genes to explore the mechanism of CCA development and progression and CCA treatment.

There are still several limitations in this study. First, although a relatively large number of CCA samples were analysed, and an external TCGA dataset was used to validate the expression and diagnostic efficacy of the hub genes, more studies with larger samples sizes are needed to validate the findings of this study. Second, although the immunohistochemistry results of the hub genes were evaluated in this study, they were based only on the information from an online database. Consequently, further experiments should be performed to validate the results in this study and to reveal the mechanisms of these hub genes in CCA progression and prognosis.

In summary, by using coexpression analysis and a series of other bioinformatics approaches, we identified 10 real hub genes, LIMA1, HDAC1, ITGA3, ACTR3, GSK3B, ITGA2, THOC2, PTGES3, HEATR1 and ILF2, involved in the development, progression and prognosis of CCA. Cell cycle-related pathways such as signal transduction, metabolism related pathways, post-transduction modification and gene expression, were enriched in the hub genes. These study results enrich our understanding of CCA development and progression and may help us improve CCA therapy.