![]() Based on differential geneĮxpression analysis, subclass prediction, and pathway analysis, GSE64041 using HCC samples and matched control samples to establishĪ molecular classification of human HCC. Makowska et al ( 16) developed the gene expression file Such as intrinsic pathway and pathways participating in cell cycleĪdvances, the key mechanism underlying HCC remains to be furtherĮlucidated to screen promising biomarkers and potential targets forīioinformatics approaches are effective for Such as growth factor receptors, pathways involved in apoptosis TheĬandidate pathways include pathways involved in signal transduction HCC have been proven to be efficient for HCC treatment. Serve as a targets for HCC therapy ( 14). Proliferation and increase apoptosis, suggesting that DNMT1 may Methyltransferase 1 (DNMT1) knockdown can inhibit HCC cell Silencing of GPC-3 can inhibit the proliferation of HCC cells In addition, it is revealed that theĮxpression level of glypican 3 (GPC-3) in liver tissues can be used To have the value for the detection of primary HCC ( 11). Methylated GSH-sulphur-transferase P1 in serum can be used for theīesides, methylation status of plasma P16 gene has been indicated Investigate promising biomarkers and therapeutic targets for theĭiagnosis and treatment of HCC. Molecular mechanism underlying HCC, many efforts have been made to What's more, signaling pathways suchĪs retinoblastoma pathways, Ras/MAPK pathway and Wnt/β-catenin TFs are found to play important role in the invasion and metastasis Metalloproteinase (MMP)2 and MMP9, and TFs like hypoxia inducible Such as cyclin-dependent kinases and TFs such as E2F transcriptionįactors (E2Fs) are involved in cell cycle ( 5, 6).Īnother hallmark of cancer cells is metastasis. Like all the other cancers, cells of HCC lost Transcription factors (TFs) associated with HCC development haveīeen revealed. Molecular targeted therapies of the disease. Researches of HCC have thrown light on molecular diagnosis and In the past decades, efforts on molecular mechanism Therapies for HCC should be taken into consideration. Investigation of safe and accurate diagnosis methods and effective Great improvements in HCC treatments have been achieved, further Resection and liver transplantation, the prognosis of these Pain, fatigue, weight loss, and obstructive syndromes includingĪll of HCC patients qualifying surgical treatments including tumor Have a high risk in liver cirrhosis and other symptoms such as Prevalent cancers worldwide, causing the third most death of Hepatocellular carcinoma (HCC) is one of the most In addition, FOXM1, TCF7L1, E2F4 and SIN3A were revealed to be key TFs associated with HCC. ‘Cell division’ and ‘cell cycle’ were indicated to act as key GO terms and Kyoto Encyclopedia of Genes and Genomes pathways in HCC. TOP2A, ITGA2, PLK1 and CDK1 may be key genes involved in HCC development. Finally, 4 TFs including forkhead box M1 (FOXM1), E2F transcription factor 4 (E2F4), SIN3 transcription regulator family member A (SIN3A) and transcription factor 7 like 1 (TCF7L1) were obtained through integrated network analysis. TOP2A, cyclin dependent kinase 1 (CDK1) and polo like kinase 1 (PLK1) were revealed to be hub nodes in the sub‑network. Topoisomerase (DNA) IIα (TOP2A) and integrin subunit α2 (ITGA2) were hub nodes in the PPI network. In addition, functional enrichment analysis for DEGs in the sub‑network revealed ‘cell division’ and ‘cell cycle’ as key Gene Ontology (GO) terms and pathways. A total of 378 DEGs were obtained, including 101 upregulated and 277 downregulated DEGs. ![]() Then functional enrichment analyses, protein‑protein interaction (PPI) network, sub‑network and integrated transcription factor (TF)‑microRNA (miRNA)‑target network analyses were performed for these DEGs. Differentially expressed genes (DEGs) between HCC and control groups were identified. ![]() The microarray dataset GSE64041 was downloaded from the Gene Expression Omnibus database, which included 60 tumor liver samples and 60 matched control samples. The purpose of the present study was to investigate the underlying molecular mechanism of hepatocellular carcinoma (HCC) using bioinformatics approaches. ![]()
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