ObjectiveTo screen differential expression of genes in hepatocellular carcinoma (HCC) by bioinformatics method, and analyze its clinical significance and its possible molecular mechanism in HCC.MethodsThe HCC gene expression profile GSE101728 was picked out to analyze the differential expression genes. The hub genes were identified by STRING and Cytoscape. GO and KEGG analysis were carried out by using DAVID and PPI network were constructed by STRING. The relationship among the hub genes were analyzed by using GEPIA.ResultsA total of 1 082 DEGs were captured (354 up-regulated genes and 728 down-regulated genes). Meantime, 10 hub genes ［cyclin dependent kinase 1 (CDK1), cyclin B1 (CCNB1), cyclin A2 (CCNA2), polo-like kinase 1 (PLK1), laser kinase B (AURKB), cyclin of cell division 20 (CDC20), centromere protein A (CENPA), mitotic arrest defective protein 2 (MAD2L1), cyclin B2 (CCNB2), and kinesin family 2C (KIF2C)］ were identified, and its expression and clinical significance were verified by GEPIA. GO and KEGG analysis showed 10 hub genes were mainly enriched in cell division and cell cycle. Expressions of AURKB, CCNB1, and MAD2L1 were obviously positively correlated (P<0.05).ConclusionThis study analyzes the hub genes in the development of HCC by bioinformatics methods and provides valuable information for further research on the mechanism of HCC.
Objective To explore the aberrantly expressed genes in hepatocellular carcinoma (HCC) and their relationship with prognosis of HCC through bioinformatics analysis. Methods Five datasets related to HCC were selected from the GeneExpression Omnibus database to explore differentially expressed genes (DEGs), followed by further gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The co-upregulated genes CNIH4 and TOMM40 were selected to explore the differences in their expressions in HCC tissues and normal tissues, and to explore the relationship between their expressions and the 5-year survival of patients by using TCGA database. Tissues and paraneoplastic tissues of eight cases of HCC who underwent surgery at the Guangdong Second Provincial General Hospital were collected to verify the expression differences of CNIH4 and TOMM40L mRNA. Results A total of 25 up-regulated genes and 21 down-regulated genes were identified in this study. The results of GO analysis and KEGG analysis indicated that DEGs were mainly related to catabolism, cell division, DNA replication and repair. The results of TCGA database analysis showed that the expression of up-regulated genes CNIH4 mRNA and TOMM40L mRNA were up-regulated in HCC tissues as compared with normal tissues (P<0.05) and that the 5-year survival of patients in the high expression group was worse than that in the low expression group (P<0.05). The results of clinical samples showed that CNIH4 mRNA and TOMM40L mRNA were up-regulated in HCC tissues as compared with paraneoplastic tissues. Conclusion CNIH4 and TOMM40L genes are up-regulated in HCC tissues, and their high expressions are associated with poor prognosis, and may be potential biomarkers and prognostic indicators for HCC.
Objective To explore key genes and mechanisms of depression aggravating Crohn disease. Methods In March 2023, the Public Health Genomics and Precision Health Knowledge Base and Gene Expression Omnibus database were used to identify the overlapping differentially expressed genes between Crohn disease and depression and the key genes were screened by Metascape, STRING, Cytoscape, and protein interaction network analysis. The Gene Expression Omnibus database was used to analyze the correlations between key genes and clinical pathologies such as Crohn Disease Endoscopic Index of Severity and intestinal microvilli length. Results There were 137 overlapping differentially expressed genes between Crohn disease and depression, and 25 key genes were further screened out. Among them, CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A genes were significantly correlated with multiple clinical parameters. The functions of PROK2 and PROK2-related genes were mainly enriched in neutrophil and granulocyte migration, neutrophil and granulocyte chemotaxis, etc. Conclusions There are 25 key genes, especially CREB1, FKBP5, MAPT, NTSR1, OXTR, PROK2, POMC, HTR2B, and PPARGC1A, that possibly contribute to the establishment and deterioration of Crohn disease caused by depressive disorder. Among these genes, PROK2 showes the possibility of regulating immune cell (neutrophils and CD8+ T cells) infiltration.
ObjectiveTo investigate the relation between disulfidptosis-related genes (DRGs) and prognosis or immunotherapy response of patients with pancreatic cancer (PC). MethodsThe transcriptome data, somatic mutation data, and corresponding clinical information of the patients with PC in The Cancer Genome Atlas (TCGA) were downloaded. The DRGs mutated in the PC were screened out from the 15 known DRGs. The DRGs subtypes were identified by consensus clustering algorithm, and then the relation between the identified DRGs subtypes and the prognosis of patients with PC, immune cell infiltration or functional enrichment pathway was analyzed. Further, a risk score was calculated according to the DRGs gene expression level, and the patients were categorized into high-risk and low-risk groups based on the mean value of the risk score. The risk score and overall survival of the patients with high-risk and low-risk were compared. Finally, the relation between the risk score and (or) tumor mutation burden (TMB) and the prognosis of patients with PC was assessed. ResultsThe transcriptome data and corresponding clinical information of the 177 patients with PC were downloaded from TCGA, including 161 patients with somatic mutation data. A total of 10 mutated DRGs were screened out. Two DRGs subtypes were identified, namely subtype A and subtype B. The overall survival of PC patients with subtype A was better than that of patients with subtype B (χ2=8.316, P=0.003). The abundance of immune cell infiltration in the PC patients with subtype A was higher and mainly enriched in the metabolic and conduction related pathways as compaired with the patients with subtype B. The mean risk score of 177 patients with PC was 1.921, including 157 cases in the high-risk group and 20 cases in the low-risk group. The risk score of patients with subtype B was higher than that of patients with subtype A (t=14.031, P<0.001). The overall survival of the low-risk group was better than that of the high-risk group (χ2=17.058, P<0.001), and the TMB value of the PC patients with high-risk was higher than that of the PC patients with low-risk (t=5.642, P=0.014). The mean TMB of 161 patients with somatic mutation data was 2.767, including 128 cases in the high-TMB group and 33 cases in the low-TMB group. The overall survival of patients in the high-TMB group was worse than that of patients in the low-TMB group (χ2=7.425, P=0.006). ConclusionDRGs are closely related to the prognosis and immunotherapy response of patients with PC, and targeted treatment of DRGs might potentially provide a new idea for the diagnosis and treatment of PC.
ObjectiveTo investigate the expression and biological function of centromere protein F (CENPF) in non-small cell lung cancer (NSCLC) and the association with prognosis.MethodsThrough retrieving and analyzing the bioinformatics data such as Oncomine database, Human Protein Atlas (HPA), Kaplan-Meier Plotter, STRING and DAVID database, the expression of CENPF in both normal tissues and cancer tissues of lung cancer patients was identified, and the protein interaction network analysis, functional annotation and pathway analysis of CENPF with its associated genes were carried out.ResultsCENPF was overexpressed in lung adenocarcinoma tissues, but not in normal tissues. The median overall survival (OS) of NSCLC patients with low expression of CENPF was significantly longer than that of patients with high expression of CENPF. Further sub-analysis showed that low expression group from lung adenocarcinoma patients had longer median disease-free survival and OS compared with high expression group patients. CENPF and its associated hub genes mainly affected the protein K11-linked ubiquitination in biological process, anaphase-promoting complex (APC) in cell composition, ATP binding in molecular function, and cell cycle in KEGG pathway.ConclusionCENPF is regulated in tumorigenesis and progression of NSCLC, and its protein expression level has the value of early diagnosis and prognosis evaluation in lung adenocarcinoma. It is suggested that CENPF gene can be a potential target for molecular targeted therapy of NSCLC.
ObjectiveTo construct a prognostic model of esophageal squamous cell carcinoma (ESCC) based on immune checkpoint-related genes and explore the potential relationship between these genes and the tumor microenvironment (TME). Methods The transcriptome sequencing data and clinical information of immune checkpoint genes of samples from GSE53625 in GEO database were collected. The difference of gene expression between ESCC and normal paracancerous tissues was evaluated, and the drug sensitivity of differentially expressed genes in ESCC was analyzed. We then constructed a risk model based on survival-related genes and explored the prognostic characteristics, enriched pathway, immune checkpoints, immune score, immune cell infiltration, and potentially sensitive drugs of different risk groups. ResultsA total of 358 samples from 179 patients were enrolled, including 179 ESCC samples and 179 corresponding paracancerous tissues. There were 33 males and 146 females, including 80 patients≤60 years and 99 patients>60 years. 39 immune checkpoint genes were differentially expressed in ESCC, including 14 low expression genes and 25 high expression genes. Drug sensitivity analysis of 8 highly expressed genes (TNFRSF8, CTLA4, TNFRSF4, CD276, TNFSF4, IDO1, CD80, TNFRSF18) showed that many compounds were sensitive to these immunotherapy targets. A risk model based on three prognostic genes (NRP1, ICOSLG, HHLA2) was constructed by the least absolute shrinkage and selection operator analysis. It was found that the overall survival time of the high-risk group was significantly lower than that of the low-risk group (P<0.001). Similar results were obtained in different ESCC subtypes. The risk score based on the immune checkpoint gene was identified as an independent prognostic factor for ESCC. Different risk groups had unique enriched pathways, immune cell infiltration, TME, and sensitive drugs. Conclusion A prognostic model based on immune checkpoint gene is established, which can accurately stratify ESCC and provide potential sensitive drugs for ESCC with different risks, thus providing a possibility for personalized treatment of ESCC.
Objective To explore the key genes, pathways and immune cell infiltration of bicuspid aortic valve (BAV) with ascending aortic dilation by bioinformatics analysis. Methods The data set GSE83675 was downloaded from the Gene Expression Omnibus database (up to May 12th, 2022). Differentially expressed genes (DEGs) were analyzed and gene set enrichment analysis (GSEA) was conducted using R language. STRING database and Cytoscape software were used to construct protein-protein interaction (PPI) network and identify hub genes. The proportion of immune cells infiltration was calculated by CIBERSORT deconvolution algorithm. Results There were 199 DEGs identified, including 19 up-regulated DEGs and 180 down-regulated DEGs. GSEA showed that the main enrichment pathways were cytokine-cytokine receptor interaction, pathways in cancer, regulation of actin cytoskeleton, chemokine signaling pathway and mitogen-activated protein kinase signaling pathway. Ten hub genes (EGFR, RIMS3, DLGAP2, RAPH1, CCNB3, CD3E, PIK3R5, TP73, PAK3, and AGAP2) were identified in PPI network. CIBERSORT analysis showed that activated natural killer cells were significantly higher in dilated aorta with BAV. Conclusions These identified key genes and pathways provide new insights into BAV aortopathy. Activated natural killer cells may participate in the dilation of ascending aorta with BAV.
Objective To analyze the relationship between the expression of carbonic anhydrase 3 (CA3) in breast cancer tissues, its prognostic potential and the number of immune cells by a variety of online databases. Methods GEPIA2.0 and TIMER databases were used to analyze the difference of CA3 mRNA expression in breast cancer tissues. Bc-GenExMinerv4.7 database was used to analyze the difference of CA3 mRNA expression in breast cancer subcategories. Kaplan-Meier plotter, Bc-GenExMinerv4.7 and PrognoScan databases were used to analyze the effect of CA3 mRNA expression levels on prognosis of patient. LinkedOmics database was used to analyze of the biological behavior involved in CA3 co-expressed genes. TIMER database was used to analyze the relationship between CA3 mRNA expression and immune cells infiltration in breast cancer tissues. Results The expression of CA3 mRNA in breast cancer tissues was lower than that in normal breast tissues (P<0.05), and the expression levels of CA3 mRNA were higher in ER negative (P<0.05), PR negative (P<0.05), HER2 negative (P<0.05) and no lymphatic metastasis (P<0.05). In addition, the expression level of CA3 in breast cancer patients with high Ki67 expression was lower (P<0.05) and closely related to SBR and NPI grade (P<0.05). Breast cancer patients with low expression of CA3 mRNA had lower overall survivall, recurrence free survival, and disease free survival ( P<0.05). Ten of the top 50 positively correlated co-expressed genes screened out had low risk ratio (P<0.05), and 11 of the top 50 negatively correlated co-expressed genes screened out had high risk ratio (P<0.05). The expression of CA3 mRNA was positively correlated with CD4+ T cells and CD8+ T cells in breast cancer tissues (rs=0.175, P<0.001; rs=0.137, P<0.001), and negatively correlated with T cell failure markers LAG3, TIM-3 and PVRL2 (rs=–0.100, P<0.01; rs=–0.143, P<0.001; rs=–0.082, P<0.05). Conclusions The low expression of CA3 mRNA in breast cancer tissues is correlated with the occurrence, development and prognosis of breast cancer. CA3 can be used as a potential independent prognostic marker for breast cancer and may be related to immune infiltration.
Objective To explore depression-related biomarkers and potential therapeutic drugs in order to alleviate depression symptoms and improve patients’ quality of life. Methods From November 2022 to January 2024, gene expression profiles of depression patients and healthy volunteers were downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed to identify differentially expressed genes. Enrichment analysis of these genes was conducted, followed by the construction of a protein-protein interaction network. Finally, Cytoscape software with the Cytohubba plugin was used to identify potential key genes, and drug prediction was performed. Results Through differential expression analysis, a total of 110 differentially expressed genes (74 upregulated and 36 downregulated) were identified. Protein-protein interaction network identified 10 key genes, and differential expression analysis showed that 8 of these genes (CPA3, HDC, IL3RA, ENPP3, PTGDR2, VTN, SPP1, and SERPINE1) exhibited significant differences in expression levels between healthy volunteers and patients with depression (P<0.05). Enrichment analysis revealed that the upregulated genes were significantly enriched in pathways related to circadian rhythm, niacin and nicotinamide metabolism, and pyrimidine metabolism, while the downregulated genes were primarily enriched in extracellular matrix-receptor interaction and interleukin-17 signaling pathways. Six overlapping verification genes (SALL2, AKAP12, GCSAML, CPA3, FCRL3, and MS4A3) were obtained across two datasets using the Wayn diagram. Single-cell sequencing analysis indicated that these genes were significantly expressed in astrocytes and neurons. Mendelian randomization analysis suggested that the FCRL3 gene might play a critical role in the development of depression. Drug prediction analysis revealed several potential antidepressant agents, such as cefotiam, harmol, lincomycin, and ribavirin. Conclusions Circadian rhythm, nicotinate and nicotinamide metabolism, and pyrimidine metabolism pathways may represent potential pathogenic mechanisms in depression. Harmol may be a potential therapeutic drug for the treatment of depression.
Objective To analyze the pathways, biomarkers and diagnostic genes of systemic sclerosis associated interstitial lung disease (SSc-ILD) using bioinformatics. Methods SSc-ILD related gene data sets from April to June 2023 were downloaded from the Gene Expression Omnibus database for differential analysis and enrichment analyses including gene ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis, disease ontology analysis, and gene set enrichment analysis. Least absolute shrinkage and selection operator regression and support vector machine algorithms were applied to screen and take the intersection to get the diagnostic genes and validate the results. Disease-related data were analyzed by immune cell infiltration. Results A total of 178 differential genes were obtained, and enrichment analyses showed that they were related to 5 signaling pathways and associated with 3 diseases. The diagnostic genes screened were TNFAIP3, ID3, and NT5DC2, and immune cell infiltration showed that the diagnostic genes were associated with plasma cells, resting mast cells, activated natural killer cells, macrophage M1 and M2, resting dendritic cells, and activated dendritic cells. Conclusion The screened diagnostic genes and immune cells may be involved in the development of SSc-ILD.