Dataset Information

Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.

ABSTRACT: Background: Drug repurposing is a strategy that complements the conventional approach of developing new drugs. Hepatocellular carcinoma (HCC) is a highly prevalent type of liver cancer, necessitating an in-depth understanding of the underlying molecular alterations for improved treatment. Methods: We searched for a vast array of microarray experiments in addition to RNA-seq data. Through rigorous filtering processes, we have identified highly representative differentially expressed genes (DEGs) between tumor and non-tumor liver tissues and identified a distinct class of possible new candidate drugs. Results: Functional enrichment analysis revealed distinct biological processes associated with metal ions, including zinc, cadmium, and copper, potentially implicating chronic metal ion exposure in tumorigenesis. Conversely, up-regulated genes are associated with mitotic events and kinase activities, aligning with the relevance of kinases in HCC. To unravel the regulatory networks governing these DEGs, we employed topological analysis methods, identifying 25 hub genes and their regulatory transcription factors. In the pursuit of potential therapeutic options, we explored drug repurposing strategies based on computational approaches, analyzing their potential to reverse the expression patterns of key genes, including AURKA, CCNB1, CDK1, RRM2, and TOP2A. Potential therapeutic chemicals are alvocidib, AT-7519, kenpaullone, PHA-793887, JNJ-7706621, danusertibe, doxorubicin and analogues, mitoxantrone, podofilox, teniposide, and amonafide. Conclusion: This multi-omic study offers a comprehensive view of DEGs in HCC, shedding light on potential therapeutic targets and drug repurposing opportunities.

SUBMITTER: Caputo WL

PROVIDER: S-EPMC10705715 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.

Caputo Wesley Ladeira WL de Souza Milena Cremer MC Basso Caroline Rodrigues CR Pedrosa Valber de Albuquerque VA Seiva Fábio Rodrigues Ferreira FRF

Cancers 20231130 23

<b>Background</b>: Drug repurposing is a strategy that complements the conventional approach of developing new drugs. Hepatocellular carcinoma (HCC) is a highly prevalent type of liver cancer, necessitating an in-depth understanding of the underlying molecular alterations for improved treatment. <b>Methods</b>: We searched for a vast array of microarray experiments in addition to RNA-seq data. Through rigorous filtering processes, we have identified highly representative differentially expressed ...[more]

PMID: 38067357

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Project description:Background: Methylation plays a significant role in the etiology and pathogenesis of hepatocellular carcinoma (HCC). The aim of the present study is to identify aberrantly methylated-diferentially expressed genes (DEGs) and dysregulated pathways associated with the development of HCC through integrated analysis of gene expression and methylation microarray. Method: Aberrantly methylated-DEGs were identified from gene expression microarrays (GSE62232, GSE74656) and gene methylation microarrays (GSE44909, GSE57958). Functional enrichment and pathway enrichment analyses were performed through the database of DAVID. Protein-protein interaction (PPI) network was established by STRING and visualized in Cytoscape. Subsequently, overall survival (OS) analysis of hub genes was performed by OncoLnc. Finally, we validated the expression level of CDCA5 by quantitative real-time PCR (qRT-PCR) and western blotting, and performed Immunohistochemical experiments utilizing a tissue microarray. Cell growth assay and flow cytometry were behaved to explore the function of CDCA5. Results: Aberrantly methylated-DEGs were enriched in biological process, molecular function, cellular component and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Among them, cell cycle was enriched most frequently, and some terms associated with cancer were enriched, such as p53 signaling pathway, pathways in cancers, PI3K-Akt signaling pathway and AMPK signaling pathway. After survival analysis and validation in TCGA database including methylation and gene expression status, 12 hub genes were identified. Furthermore, the expression level of new gene CDCA5 was validated in HCC cell lines and hepatic normal cell lines through qRT-PCR and western blotting. In additional, immunohistochemistry experiments revealed higher CDCA5 protein expression from HCC tumor tissues compared with paracancer tissues by tissue microarray. Finally, through loss of function, we demonstrated that CDCA5 promoted proliferation by regulating the cell cycle. Conclusions: In summary, the present study implied possible aberrantly methylated-differentially expressed genes and dysregulated pathways in HCC by bioinformatics analysis and experiments, which could be helpful in understanding the molecular mechanisms underlying the development and progression of HCC. Hub genes including CDC20, AURKB, BIRC5, RRM2, MCM2, PTTG1, CDKN2A, NEK2, CENPF, RACGAP1, GNA14 and especially the new gene CDCA5 may serve as biomarkers for diagnosis, treatment and prognosis of HCC.

Project description:BackgroundExosomes are involved in cell-to-cell communication, neovascularization, cancer metastasis, and drug resistance, which all play an important role in the occurrence and progression of hepatocellular carcinoma (HCC). Because there are few mechanistic studies about the function of exosomes in HCC, the goals of this study were to identify exosome-related genes in HCC, to establish a reliable prognostic model for HCC, and to explore underlying mechanisms.MethodsThe exoRBase and The Cancer Genome Atlas (TCGA) databases were used to analyze differentially expressed genes (DEGs). Cox regression and least absolute shrinkage and selection operator analyses were used to identify DEGs closely related to the overall survival of patients with HCC. An exosome-related prognostic model was then constructed in TCGA and validated in the International Cancer Genome Consortium database. A nomogram was developed to predict survival. CIBERSORT was used to estimate the abundance of different types of immune cells. Immunotherapy-related DEGs were used to predict the effect of immunotherapy.ResultsForty-eight exosome-related DEGs were obtained; of them, five [exportin 1 (XPO1), lysosomal thiol reductase (IFI30), F-box protein 16 (FBXO16), calmodulin 1 (CALM1), MORC family CW-type zinc finger 3 (MORC3)] were selected to construct a predictive model. Patients with HCC were then divided into low- and high-risk groups using the best cut-off value, as determined by the X-tile software. Prognosis was significantly poorer in the high-risk than in the low-risk group (P=0.009; hazard ratio =2.65). Features related to exosomes were found to positively regulate immune response. Further analysis showed a higher risk score was associated with higher expression of immune checkpoint molecules, including programmed death ligand 1 (PD-L1), programmed death ligand 2 (PD-L2), T cell Ig and ITIM domain (TIGIT), and indoleamine-2,3-dioxygenase 1 (IDO1).ConclusionsThis study has identified a novel signature based on exosome-related genes that has potential as a prognostic biomarker for HCC. Our research provides an immunological perspective for the development of precision treatment for HCC.

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Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.

Publications

Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.

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