Patients with cirrhosis are at risk of a variety of complex diseases like ascites, esophageal or gastric varices, hepatic encephalopathy, and hepatocellular carcinoma [28]. Cirrhosis is the most important risk factor for the development of HCC and about 80% of HCC cases are caused by liver cirrhosis.
One of the effective methods in the management of HCC on a cirrhotic background is to understand the molecular mechanisms underlying the transition level of cirrhosis to HCC. Studies show genetic factors affect the development of HCC from cirrhosis. Therefore, it is important to understand how HCC develops from cirrhosis to decipher factors involved in cell malignancy. Noticeably, identifying these factors is crucial for screening and molecular targeted therapy for cancer. HCC development is closely linked to cirrhosis, an inflammatory liver disease, in which normal liver tissue is replaced by scar tissue and reconstructive nodes after prolonged damage caused by various causes such as hepatitis B or C viruses [29].
Like many other cancers, HCC develops slowly after the progressive accumulation of alterations in genetic and epigenetic factors, therefore, to decipher novel strategies for the treatment of HCC, the molecular networks and pathways need to be further investigated.
At first glance, it seems that enough studies have been done on HCC, however, there is an urgent need for further research on this subject especially given the path we took in this study. The used algorithms and methods for this study are valuable and efficient due to their lower cost and earlier efficiency. Because of using experimental evidence algorithms, we could access important and key genes along this path with greater confidence and a lower probability of error [30].
As studies have shown, one advantage of compiling large numbers of high throughput data is that the results of different studies can be compared directly [31]. In this study, we had an effort to find a set of cancer-associated genes in HCC on a cirrhotic background using a comprehensive data analysis and systems biological viewpoint. Regarding the analysis of three datasets, we found totally 427 common DEGs in HCC derived from cirrhotic tissues. Then we analyzed the association of patients' overall survival rate for each acquired common DEG and we found a list of 231 molecular signatures which could be considered as prognostic markers for HCC patients. In other words, common DEGs were filtered to identify a list of prognostic markers for HCC on a cirrhotic background whose expression changes reduce the overall survival rate of HCC patients (Fig. 2).
Moreover, using experimental evidence we constructed a GRN consist of 231 genes as molecular signatures and 29 DETFs which affect the expression level of the molecular signatures in HCC. After analyzing the constructed GRN, we found 9 DETFs as the key regulators for the molecular signatures. The DETFs by the names of TCF4, RUNX1, HINFP, KDM2B, MAF, and JUN are down-regulated and NR5A2, NFYA, and AR are up-regulated in HCC (Table 2). This approach shows these 9 transcription factors as one of the most important elements to control the expression levels of genes that are associated with patients' survival rate in HCC on a cirrhotic background which could be considered as targets for molecular target therapies in this type of cancer. The impact of some of these transcription factors has been previously reported in cancer progression and tumorigenesis. The transcription factor TCF4 causes the epithelial to mesenchymal transition and enhances the cancer cell invasion [32]. RUNX1 is a member of the RUNX family which plays important role in the development of cancer and tumorigenesis [33, 34]. KDM2B roles in the alteration of the gene expression as a histone lysine demethylase by epigenetics changes. KDM2B increases cancer cell proliferation and enhances cellular migration by affecting the migration-associated genes [35]. NFYA is reported to be up-regulated in HCC, breast, lung and other types of cancers [36]. The value of NR5A2 as a key regulator for colorectal cancer metastasis was studied [37]. Besides, it was shown that NR5A2 expression level is up-regulated in glioma. Also, the expression level of NR5A2 is considered a poor prognostic factor in glioma patients. In addition, this factor plays a role in cell proliferation, migration, and invasion in malignant glioblastoma cells [38]. We previously showed that the nuclear receptor AR is an important factor for breast cancer development and progression [22]. The value of AR has been shown in HCC as a useful molecule in the molecular targeted therapy for hard-to-treat cancers [39].
In addition, we found protein interaction networks based on experimental evidence that convey some important information about cellular pathways and developing effective therapies for the treatment of cancer (Fig. 4). Proteins are vital components that act as molecular machines, sensors, transporters, and structural elements, with interactions between proteins, being key to their function [40]. In this study, PPI network analysis showed that CDC20 plays as a hub node. CDC20 (Cell division cycle 20) is known as a key element that is remarkably suppressed by p53 introduction and is up-regulated in a wide variety of human cancer tissues. CDC20 is known as a potential cancer therapeutic target that is negatively regulated by p53. We also found JUN and CTTNB1 (Catenin beta 1), both of which play pivotal roles in a variety of cancers, as hub genes in PPI network. The products of the Jun family genes are essential components of the activating protein-1 transcription factor complexes that are critically important in the control of cell growth, differentiation, and neoplastic transformation. It should be noted that JUN plays a crucial role in signal transduction pathways and is involved in cell division, motility, adhesion, and survival in both normal and cancer cells [41], and affects the expression of catenin beta 1 in gastroenteropancreatic endocrine tumors[42].
With regards to the pathway enrichment analysis, we found linoleic acid metabolism, chemical carcinogenesis, and cell cycle as the most significant pathways for HCC patients' molecular signatures. The linoleic acid pathway regulates many physiological processes, then, its metabolic pathway is vital for metabolisms in cancer cells. According to the previous studies, defects in this pathway have been observed in HCC patients, therefore, our results confirm the previous ones [43, 44]. Besides, pathways involved with chemical carcinogenesis and cell cycle are associated with cancer development. Also, according to the results from the GO analysis, we found cytoplasmic, extracellular region, and vesicle as cellular components associated with HCC on cirrhotic tissue molecular signatures. In addition, GO analysis at the level of molecular function showed the value of some binding functions such as tetrapyrrole, collagen, and heme-binding proteins (Fig. 5).
In conclusion, the validation of these findings is valuable in clinical and pathological research in HCC patients. In the present study, we proposed a comprehensive transcriptome data analysis to find a set of molecular signatures associated with the transition between HCC and cirrhotic tissue. Then we constructed a GRN to highlight the possible regulatory mechanism of these DEGs by DETFs. In addition, we used systems biology approaches to find PPI network, pathways and GO associated with the acquired molecular signatures. The results of this study suggested some key elements that could be used as potential prognostic markers and/or therapeutic targets in cirrhotic and HCC patients to prevent malignancy.