In vitro and In vivo Based Multi-Target Therapy and Prognostic Bio-modeling inLiver Cancer

Introduction: Hepatocellular Carcinoma, being 3rd most aggressive malignancy with complex multifactorial etiologies become a major public health issue worldwide. The critical and unknown molecular environment raised multiple challenges for oncologists, which is resulting in poor earlier detection with unsatisfactory treatment options in patients. Methods: This study determined the cancer regulatory networks and interaction mechanism of five distinctive genes (CTNNB1TTN, TERT, ALB, OBSCN) in HCC by using comprehensive statistical-based machine learning and system biology approaches. This work implemented redundancy analysis of genes by CRISPRCas9 and RNAi technique, accompanied by identification of transcription factors, kinases, and intermediate proteins associated with key genes. Network Pharmacology with molecular docking and dynamics simulation followed by in-vitro verification is used to evaluate anti-cancer drug activity against TERT. Results: The results declared a high frequency of genetic alteration in genes at the allelic level with enrichment in several oncogenic signaling pathways, including stem cell proliferation and transferase activity, etc. Among key genes, TERT is being analyzed for drug discovery in HCC. The molecular docking studies of TERT with ambrisentan revealed high binding energy, which was further investigated by molecular dynamics studies and ADMET evaluation. An in vitro wet lab experiment (MTT assay) is designed to determine the cytotoxicity of the drug in the HepG2 cell line discussion: With higher recurrence and metastasis HCC remains deadliest threat to public health. Despite of incredible inventions and high throughput technologies, this cancer claims the lives of 832,000 people annually [24]. With a wide range of genetic and cellular characteristics it is difficult for oncologist to find ideal treatment outcomes. The drug response and acquired resistance against LIHC is unpredictable with the current guidelines regarding mutation patterns and molecular biomarkers [25].In order to understand best pharmacological targets, this study implicated five genes (CTNNB1,TTN, TERT, ALB, and OBSCN) out of a gene panel of around 250 analyzed from 45 research publications in various aspects of HCC tumorigenesis. These five genes have been identified by numerous research as possible indicators of LIHC; however, holistic understanding of their genetic mechanism is still undefined. In our research, CTNNB1, TERT shows over expression while TTN, ALB and OBSCN shows lower expression when compared with normal liver tissue samples. We found higher mRNA pattern expression of key genes at stage II and III which show aggressive initial tumor progression into invasive carcinoma. The over-expression of genes in African-American ethnic groups aged 21–40, 41–60, and 61–80 years were noticed that emphasizes its ability to regulate development at any stage of life (Fig 1).Cancer can result from the interplay of correlated genes [26]. Current study illustrated TCAP, WRAP53, NHP2, SLCO1B3, SLCO1B1, SLCO1A2, SLC10A1, LEF1, PINX1, SMG6, CTNNA1, CTNNBIP1, ACTN2, LRRFIP1, LCAT, SMG5, ABCC3, CALM1, TCF7L2, and DKC1 were highly correlated with key genes based on physical interaction, co-expression and protein domain similarity (Fig 2). Furthermore, mutational frequency ranging from 13 to 34% elucidated from 2113 samples from 4 LIHC studies that indicate therapeutic eligibility of key genes. The genetic plot of CTNNB1 and TTN shows missense and splice mutation. TERT have amplification and promoter mutation while ALB and OBSCN shows splice and truncating mutation (Fig 3).In the current work, protein signaling cascades retrieved genes with higher nodes and edges that can promotes carcinogenesis. Then MCODE plugin module in the Cytoscape program was used to generate clustering networks.The findings revealed that module 1 with CTNNB1 and TERT had the highest score, followed by module 2 with TTN (4.286) and module 3 with OBSN (3) score. However, none of the modules contained ALB (Fig 5). According to previous studies, CTNNB1 is recognized to play a critical role in the cell cycle and signal transduction pathway like Wnt/β-catenin a process that promote metastasis and progression of cancer [27].In our study we find Kaplan Meier plots of high expressed CTNNB1 with hazardous ratio (HR) = 1.31 and log-rank P-value = 0.11 with poor overall survival. Similarly, TERT gene which can induce carcinogenic process like angiogenesis, inflammatory factors, cell senescence and vascularization is find over-expressed with worst overall survival [28]. TTN gene on the other hand is involved in muscle elastic protein and immune response defects in its regulation become cause of various malignancies [29]. Moreover, OBSCN a metastasis suppressor is found lower expressed gene in current study with poor prognostic value.Its dysregulation is associated with PI3K/AKT pathway that can promote oncogenic effect [30]. Finally ALB a serum albumin protein with lower expression is related with poorer therapeutic outcomes in various cancers [31]. This study systematically determined muscle stretch, telomere maintenance and RNA templated DNA biosyntetic as enriched biological processes (Fig 5). While enriched molecular functions were chaperone binding, RNA directed DNA polymerase activity and transferase activity.The Cellular components are myofibril, RNA directed RNA polymerase complex, and sarcomere. KEGG pathways linked with our genes are Hippo signaling pathway, Adherens junction, Human papilloma virus infection and signaling pathways for pluripotency of stem cells (Fig 5). The hallmarks of cancer like telomerase is part of every cancer irrespective of its type.Numerous studies demonstrate that cancer cells evade replication restrictions and prevent telomere shortening by preserving telomere length. This makes it possible for cancer cells that express telomerase to divide endlessly, which is one of the characteristics of cancer