Abstract
The mechanisms leading to the development and progression of hepatocellular carcinoma (HCC) are complicated and regulated genetically and epigenetically. The recent advancement in high-throughput sequencing has facilitated investigations into the role of genetic and epigenetic regulations in hepatocarcinogenesis. Therefore, we used systems biology and big database mining to construct genetic and epigenetic networks (GENs) using the information about mRNA, miRNA, and methylation profiles of HCC patients. Our approach involves analyzing gene regulatory networks (GRNs), protein-protein networks (PPINs), and epigenetic networks at different stages of hepatocarcinogenesis. The core GENs, influencing each stage of HCC, were extracted via principal network projection (PNP). The pathways during different stages of HCC were compared. We observed that extracellular signals were further transduced to transcription factors (TFs), resulting in the aberrant regulation of their target genes, in turn inducing mechanisms that are responsible for HCC progression, including cell proliferation, anti-apoptosis, aberrant cell cycle, cell survival, and metastasis. We also selected potential multiple drugs specific to prominent epigenetic network markers of each stage of HCC: lestaurtinib, dinaciclib, and perifosine against the NTRK2, MYC, and AKT1 markers influencing HCC progression from stage I to stage II; celecoxib, axitinib, and vinblastine against the DDIT3, PDGFB, and JUN markers influencing HCC progression from stage II to stage III; and atiprimod, celastrol, and bortezomib against STAT3, IL1B, and NFKB1 markers influencing HCC progression from stage III to stage IV.
Highlights
Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the third leading cause of cancerrelated deaths worldwide [1]
In order to validate the real gene regulatory networks (GRNs) by applying the model in (1), simultaneous measurement of gene expression and DNA methylation profiles in each tissue sample were required, we only validated the protein-protein networks (PPINs) of the real genetic and epigenetic networks (GENs) in HCC stage I, II, and III using the validation set
By applying principal network projection (PNP) to the real PPINs identified by the validation set in HCC stage I, II, and III, the projection distance in the PPINs identified by using validation set was highly correlated with the results in this study in HCC stage I (R2 = 0.909), II (R2 = 0.928), and III (R2 = 0.902) (Figure S5)
Summary
Hepatocellular carcinoma (HCC) is the fifth most common type of cancer and the third leading cause of cancerrelated deaths worldwide [1]. Understanding the molecular mechanism involved in the development and progression of HCC is imperative for the development of more efficacious therapeutic strategies, given that the worldwide incidence of HCC, a type of cancer with a poor 5-year survival rate (at the late stage) and high rate of recurrence (after surgical resection) [2], stands at over one million. The development and progression of HCC is a long-term multistep process, comprising chronic liver injury, necro-inflammation and regeneration, small cell dysplasia, and the appearance of low- and high-grade dysplastic nodules [3, 4]. HCC is recognized as a genetic and epigenetic disease; that is, both genetic and epigenetic components are believed to be involved in all stages of liver carcinogenesis [7]
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