Identification of hub genes and candidate drugs in hepatocellular carcinoma by integrated bioinformatics analysis

Global Gene Expression Profiling and Bioinformatics Analysis Reveal Downregulated Biomarkers as Potential Indicators for Hepatocellular Carcinoma

Objective: The study aimed to elucidate the significance of CLEC4G, CAMK2β, SLC22A1, CBFA2T3, and STAB2 in the prognosis of hepatocellular carcinoma (HCC) patients and their associated molecular biological characteristics. Additionally, the research sought to identify new potential biomarkers with therapeutic and diagnostic relevance for clinical applications. Methods and Materials: We utilized a publicly available high throughput phosphoproteomics and proteomics data set of HCC to focus on the analysis of 12 downregulated phosphoproteins in HCC. Our approach integrates bioinformatic analysis with pathway analysis, encompassing gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the construction of a protein-protein interaction (PPI) network. Results: In total, we quantified 11547 phosphorylation sites associated with 4043 phosphoproteins from a cohort of 159 HCC patients. Within this extensive data set, our specific focus was on 19 phosphorylation sites displaying significant downregulation (log2 FC ≤ -2 with p-values < 0.0001). Remarkably, our investigation revealed distinct pathways exhibiting differential regulation across multiple dimensions, including the genomic, transcriptomic, proteomic, and phosphoproteomic levels. These pathways encompass a wide range of critical cellular processes, including cellular component organization, cell cycle control, signaling pathways, transcriptional and translational control, and metabolism. Furthermore, our bioinformatics analysis unveiled noteworthy insights into the subcellular localizations, biological processes, and molecular functions associated with these proteins and phosphoproteins. Within the context of the PPI network, we identified 12 key genes CLEC4G, STAB2, ADH1A, ADH1B, CAMK2B, ADH4, CHGB, PYGL, ADH1C, AKAP12, CBFA2T3, and SLC22A1 as the top highly interconnected hub genes. Conclusions: The findings related to CLEC4G, ADH1B, SLC22A1, CAMK2β, CBFA2T3, and STAB2 indicate their reduced expression in HCC, which is associated with an unfavorable prognosis. Furthermore, the results of KEGG and GO pathway analyses suggest that these genes may impact liver cancer by engaging various targets and pathways, ultimately promoting the progression of hepatocellular carcinoma. These results underscore the significant potential of CLEC4G, ADH1B, SLC22A1, CAMK2β, CBFA2T3, and STAB2 as key contributors to HCC development and advancement. This insight holds promise for identifying therapeutic targets and charting research avenues to enhance our understanding of the intricate molecular mechanisms underlying hepatocellular carcinoma.

Olmutinib Reverses Thioacetamide-Induced Cell Cycle Gene Alterations in Mice Liver and Kidney Tissues, While Wheat Germ Treatment Exhibits Limited Efficacy at Gene Level

Background and Objectives: TAA is potent hepatic/renal toxicant. Conversely, WGO is a potent dietary supplement with impressive antioxidant properties. Olmutinib is an apoptotic chemotherapy drug that does not harm the liver or kidney. This study investigated the impact of olmutinib and wheat germ oil (WGO) on Thioacetamide (TAA)-induced gene alterations in mice liver and kidney tissues. Materials and Methods: Adult male C57BL/6 mice were exposed to 0.3% TAA in drinking water for 14 days, followed by the oral administration of olmutinib (30 mg/kg) and WGO (1400 mg/kg) for 5 consecutive days. Treatment groups included the following: groups I (control), II (TAA-exposed), III (TAA + olmutinib), IV (TAA + WGO), and V (TAA + olmutinib + WGO). Results: The findings revealed that TAA exposure increased MKi67 and CDKN3 gene expression in liver and kidney tissues. Olmutinib treatment effectively reversed these TAA-induced effects, significantly restoring MKi67 and CDKN3 gene expression. WGO also reversed MKi67 effects in the liver but exhibited limited efficacy in reversing CDKN3 gene alterations induced by TAA exposures in both the liver and kidney. TAA exposure showed the tissue-specific expression of TP53, with decreased expression in the liver and increased expression in the kidney. Olmutinib effectively reversed these tissue-specific alterations in TP53 expression. While WGO treatment alone could not reverse the gene alterations induced by TAA exposure, the co-administration of olmutinib and WGO exhibited a remarkable potentiation of therapeutic effects in both the liver and kidney. The gene interaction analysis revealed 77.4% of physical interactions and co-localization between MKi67, CDKN3, and TP53 expressions. Protein-protein interaction networks also demonstrated physical interactions between MKi67, TP53, and CDKN3, forming complexes or signaling cascades. Conclusions: It was predicted that the increased expression of the MKi67 gene by TAA leads to the increase in TP53, which negatively regulates the cell cycle via increased CDKN3 expression in kidneys and the restoration of TP53 levels in the liver. These findings contribute to our understanding of the effects of olmutinib and WGO on TAA-induced gene expression changes and highlight their contrasting effects based on cell cycle alterations.

Screening of ferroptosis-related genes in sepsis-induced liver failure and analysis of immune correlation

Purpose

Sepsis-induced liver failure is a kind of liver injury with a high mortality, and ferroptosis plays a key role in this disease. Our research aims to screen ferroptosis-related genes in sepsis-induced liver failure as targeted therapy for patients with liver failure.

Methods

Using the limma software, we analyzed the differentially expressed genes (DEGs) in the GSE60088 dataset downloaded from the Gene Expression Omnibus (GEO) database. Clusterprofiler was applied for enrichment analysis of DEGs enrichment function. Then, the ferroptosis-related genes of the mice in the FerrDb database were crossed with DEGs. Sepsis mice model were prepared by cecal ligation and perforation (CLP). ALT and AST in the serum of mice were measured using detection kit. The pathological changes of the liver tissues in mice were observed by hematoxylin-eosin (H & E) staining. We detected the apoptosis of mice liver tissues using TUNEL. The expression of Hmox1, Epas1, Sirt1, Slc3a2, Jun, Plin2 and Zfp36 were detected by qRT-PCR.

Results

DEGs analysis showed 136 up-regulated and 45 down-regulated DEGs. Meanwhile, we found that the up-regulated DEGs were enriched in pathways including the cytokine biosynthesis process while the down-regulated DEGs were enriched in pathways such as organic hydroxy compound metabolic process. In this study, seven genes (Hmox1, Epas1, Sirt1, Slc3a2, Jun, Plin2 and Zfp36) were obtained through the intersection of FerrDb database and DEGs. However, immune infiltration analysis revealed that ferroptosis-related genes may promote the development of liver failure through B cells and natural killer (NK) cells. Finally, it was confirmed by the construction of septic liver failure mice model that ferroptosis-related genes of Hmox1, Slc3a2, Jun and Zfp36 were significantly correlated with liver failure and were highly expressed.

Conclusion

The identification of ferroptosis-related genes Hmox1, Slc3a2, Jun and Zfp36 in the present study contribute to our understanding of the molecular mechanism of sepsis-induced liver failure, and provide candidate targets for the diagnosis and treatment of the disease.

Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis

Glioblastoma (GBM) is the most devastating and frequent type of primary brain tumor with high morbidity and mortality. Despite the use of surgical resection followed by radio- and chemotherapy as standard therapy, the progression of GBM remains dismal with a median overall survival of <15 months. GBM embodies a populace of cancer stem cells (GSCs) that is associated with tumor initiation, invasion, therapeutic resistance, and post-treatment reoccurrence. However, understanding the potential mechanisms of stemness and their candidate biomarkers remains limited. Hence in this investigation, we aimed to illuminate potential candidate hub genes and key pathways associated with the pathogenesis of GSC in the development of GBM. The integrated analysis discovered differentially expressed genes (DEGs) between the brain cancer tissues (GBM and GSC) and normal brain tissues. Multiple approaches, including gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were employed to functionally annotate the DEGs and visualize them through the R program. The significant hub genes were identified through the protein-protein interaction network, Venn diagram analysis, and survival analysis. We observed that the upregulated DEGs were prominently involved in the ECM-receptor interaction pathway. The downregulated genes were mainly associated with the axon guidance pathway. Five significant hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) were screened out through multiple analyses. GO and KEGG analyses of hub genes uncovered that these genes were primarily enriched in disease-associated pathways such as the inhibition of apoptosis and the DNA damage repair mechanism, activation of the cell cycle, EMT (epithelial-mesenchymal transition), hormone AR (androgen receptor), hormone ER (estrogen receptor), PI3K/AKT (phosphatidylinositol 3-kinase and AKT), RTK (receptor tyrosine kinase), and TSC/mTOR (tuberous sclerosis complex and mammalian target of rapamycin). Consequently, the epigenetic regulatory network disclosed that hub genes played a vital role in the progression of GBM. Finally, candidate drugs were predicted that can be used as possible drugs to treat GBM patients. Overall, our investigation offered five hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) that could be used as precise diagnostic and prognostic candidate biomarkers of GBM and might be used as personalized therapeutic targets to obstruct gliomagenesis.