The present study was carried out as an effort to identify new potential biomarkers for better understanding of liver cancer treatment. In spite of various researches over the years in the area of novel chemotherapeutic agent discovery, no effective medications have been developed to date for HCC treatment. Sorafenib (FDA approved, antiangiogenic agent) has the ability to increase the overall survival among all the available treatment available . Sorafenib combination therapy can give better result than other individual chemotherapeutic medication . We have evaluated efficacy of pullulan coated tablets having combination of sorafenib and silibinin in 1:1 ratio. The result indicated that histopathological changes in the liver tissue with the formulation treated group have a significant improvement in the hepatocytes and exhibit less disarrangement and degeneration of hepatocytes with no adenoma as compared to the diseased group. This improvement may be exhibited the antiangiogenic ability of silibinin to decrease intracellular ROS. Additionally proliferation of normal hepatic cell was observed to be enhanced in sorafenib-silibinin formulation treated group, which suggested that increased liver regeneration can assist to protect normal hepatocytes against tumorigenic growth. In accordance to our finding we have observed similar results in silymarin pre and post treated animal model of HCC [19, 20]. The result of biochemical analysis signifies that serum ALT, AST and ALP level were notably decreased with sorafenib-silibinin formulation. Antioxidant parameters like GSH content, MDA level and catalase activity were significantly improved with both of formulation treatment due to free radical scavenge; hence prevent the hepatocellular damage caused by DEN and 2AAF. In support of our finding, Mesallamy et al reported similar result, which revelled synergistic effect of silymarin treatment against DEN induced HCC model . This promising finding suggests that molecular targeting drugs may be effective against HCC. Molecular characterization of liver cancer can also provide a personalised molecular targeted therapy. Systemic drugs can alter the expression of numerous proteins in HCC patients, and the accuracy of their expression profiles can be measured through various proteomic tools [21, 22].
In our investigation, we used 2D gel electrophoresis to perform protein profiling for determination of differentially expressed spots after treatment. Gel imaging was used for protein spot detection and quantification, later we have identified a total of 11 differentially expressed proteins with MALD-TOF-MS. Bioinformatics analysis of these biological factors is used to identify genes that are helpful in treatment. As a result, it is critical to investigate biomarkers and related regulatory pathways that influence the development and treatment of HCC. According to gene annotation analysis of biological processes on the DAVID tool, the majority of the identified proteins were associated with positive regulation of multicellular organismal processes, phosphate metabolic processes, regulation of molecular function, protein phosphorylation, and negative regulation of cellular processes. It has previously been reported that the previous mentioned processes were linked to the progression of HCC . The PPI network complex was created, and 141 nodes with 1520 edges were observed. The MCODE plug-in screened the PPI network complex to identify the modules with the highest significant score. Later, the CytoHubba plug-in was used to filter the top ten hub genes in each module complex with the highest degrees of betweenness. Finally, functional enrichment analysis and the top ten hub gene list revealed the significance of three query proteins (HRas, RRas, and FOS.) in the protein network. The steps outlined above were taken to validate pharmacodynamic biomarkers in the context of sorafenib-silibinin treatment. The association of these candidate markers (HRas, RRas, and FOS) specific to HCC progression was validated by survival analysis using GEIPA.
The most important role of H-Ras is the proliferation induced by Raf-MEK-ERK kinase and PI3K/Akt dependent pathway which support cell survival in tumor cells . In accordance with the previous reports, we have also observed a significant increase in H-Ras levels in diseased conditions due to the enhanced proliferation of tumorigenic animal models. According to the survival analysis of HRas, a high level of HRas expression is associated with a low survival rate in HCC patients (Fig. 4F and F’). However, formulation treatment group showed significant reduction in its level. The drug-gene analysis on the STITCH database also validated that sorafenib-silibinin combination inhibits various kinase-related pathways as well as other signalling pathways, and found to interact with HRas via the VEGFA (vascular endothelial growth factor A) protein (Fig. 5), which is a marker candidate in hepatocarcinogenesis . Our findings suggested that HRas interacts directly with KDR (a VEGFA cell-surface receptor) and Raf1. Previous research found that silibinin as well as sorafenib inhibited phosphorylation of KDR and activation of RAF1 in HCC cell lines, indicating anti-metastasis properties of both compounds [26–28]. Therefore, as a pharmacodynamic biomarker, HRas expression could indeed be used to predict the efficacy of this combination treatment.
Ras proteins switch between active GTP-bound and inactive GDP-bound states, acting as signalling switchers . RRas levels are closely associated with metastasis, ErbB related pathway and have critical role in RRAS criteria in predicting HCC recurrence [30, 31]. In line with previous reports, we found a significant increase in R-Ras levels in diseased conditions as a result of the increased cell survival in diseased group animal. To back up our findings, we ran an over-all survival analysis of RRas gene, which also indicates that over expressed RRas have been found in HCC patients Fig. 4G and G’). The formulation treatment group, on the other hand, showed a significant reduction in its level. The STITCH database revealed that RRas has direct interactions with PIK3CA (Phosphoinositide-3-kinase catalytic subunit alpha) and Raf1 (Fig. 5), which are candidate proteins for proliferation and invasion of HCC [32, 33]. Recent studies that both sorafenib and silibinin represented were found to inhibit ErbB (Ras/Raf/MEK/ERK and, PI3K/Akt/mTOR) family pathway . Similarly, RRas has a direct link with NRP1 (neuropilin 1, a membrane-bound receptor) (Fig. 5), which was found to interact with VEGFs and other proangiogenic heparin-binding cytokines and can be inhibited by sorafenib . As a result, RRas could also serve as a pharmacodynamic biomarker for sorafenib:silibinin combination therapy.
The role of c-Fos (also known as FOS) in HCC development is evident. C-Fos appears to be important for cell migration tumor cell proliferation in human HCC cell lines, according to research [36, 37]. Recent report also suggested that FOS expression was linked to Hepatitis B Virus (HBV) infection, alpha-fetoprotein (AFP) levels, and macrovascular invasion. In association with our research, we discovered that FOS was over expressed in disease liver tissue, though its expression was reduced after combination treatment due to the antiproliferative and antiangiogenic effects of sorafenib and silibinin. We conducted a survival analysis and boxplot on GEIPA to support our finding, which stated that higher expression is associated with a low survival rate in HCC patients Fig. 4H and H’). A Kaplan–Meier analysis by Hu et al. also observed that patients with higher FOS expression had significantly shorter median overall survival (OS) than patients with lower FOS expression in HCC patients. . Drug- gene interaction on STITCH also validated that FOS has various indirect interaction with sorafenib and silibinin through number of proteins like HRAS, VEGFA, JUN (jun proto-oncogene) and PIK3CA (Fig. 5) which are key regulatory factors in hepatocarcinogenesis.
Concurrent with these findings, the current study demonstrated that decreased HRas, RRas, and FOS expression levels could be used to predict therapeutic intervention in HCC model.