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.
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.
The purpose of this paper is to present the research on the molecular biological characteristics of proto-oncogene pim-2 and to analyze the related mechanism. Proto-oncogene pim-2 was studied and analyzed by the bioinformatics method and technology. With an online server, the chromosomal localization of pim-2 gene was analyzed, and the exon, open reading frame, CpG island and miRNAs complementary fragments and the like were predicted. With bioinformatics software, the physicochemical property of transcription protein of proto-oncogene pim-2 and various modification sites of protein sequence, such as ubiquitination and glycosylation, were predicted, the antigenic index was calculated, and the spatial structural was modeled. The research findings showed that the proto-oncogene pim-2 comprised six exons, the CDS (coding sequence) transcribed a section of peptide chain including 311 amino acids, a gene promoter has a CpG island, and the 3'UTR region contains an miRNA gene. The molecular weight of the Pim-2 protein was 34, 188.47, the isoelectric point was 5.78, the instability index was 45.87, and the extinction coefficient was 279nm. A plurality of covalent modification sites, two ubiquitination sites, four glycosylation sites, an SUMO sumoylation site, a nitrosation site, two palmitoylation sites and sixteen regions with higher antigenic index were distributed in the protein sequence. This research showed that the related regions and modification sites distributed on the sequence of proto-oncogene pim-2 were closely related to the carcinogenic effect thereof.
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 explore the role and clinical significance of cell-cycle dependent kinase 1 (CDK1) and its upstream and downstream molecules in the development of malignant peripheral nerve sheath tumor (MPNST) through the analysis of clinical tissue samples. Methods A total of 56 tumor samples from MPNST patients (“Tianjin” dataset) who underwent surgical resection, confirmed by histology and pathology between September 2011 and March 2020, along with 17 normal tissue samples, were selected as the research subjects. MPNST-related hub genes were identified through transcriptome sequencing, bioinformatics analysis, immunohistochemistry staining, and survival analysis, and their expression levels and prognostic associations were analyzed. Results Transcriptome sequencing and bioinformatics analysis revealed that upregulated genes in MPNST were predominantly enriched in cell cycle-related pathways, with CDK1 occupying a central position among all differentially expressed genes. Further differential analysis demonstrated that CDK1 mRNA expression in sarcoma tissues was significantly higher than in normal tissues [based on searching the cancer genome atlas (TCGA) dataset, P<0.05]. In MPNST tissues, CDK1 mRNA expression was not only significantly higher than in normal tissues (based on Tianjin, GSE141438 datasets, P<0.05), but also significantly higher than in neurofibromatosis (NF) and plexiform neurofibromas (PNF) (based on GSE66743 and GSE145064 datasets, P<0.05). Immunohistochemical staining results indicated that the expression rate of CDK1 protein in MPNST tissues was 40.31%. Survival analysis results demonstrated that CDK1 expression was associated with poor prognosis. The survival time of MPNST patients with high CDK1 mRNA expression was significantly lower than that of the low expression group (P<0.05), and the overall survival trend of patients with positive CDK1 protein expression was worse than that of patients with negative CDK1 expression. Additionally, differential analysis of CDK family genes (CDK1-8) revealed that only CDK1 was significantly upregulated in MPNST, NF, and PNF. Conclusion Increased expression of CDK1 is associated with poor prognosis in MPNST patients. Compared to other CDK family members, CDK1 exhibits a unique expression pattern, suggesting its potential as a therapeutic target for MPNST.
Objective A series of bioinformatics methods were used to identify ferroptosis related biomarkers in lupus nephritis (LN). Methods We retrieved sequencing data of GSE112943 from the GEO (Gene Expression Omnibus) database and screened LN differentially expressed genes. We searched for ferroptosis-related gene (FRG) through FerrDb database, and screened LN-FRG. We conducted enrichment analysis on the LN-FRGs using David online bioinformatics database and screened the core LN-FRG using cytoHubba. We used external data sets to verify the core LN-FRGs, constructed competing endogenous RNA networks, and conducted molecular docking analysis. Results A total of 37 LN-FRGs were selected through screening. These genes are mainly enriched in inflammation, immune regulation and ferroptosis related signaling pathways. Through the cytoHubba and external dataset validation, the key core LN-FRG of ATF3 (activating transcription factor 3) was ultimately identified, and its expression was significantly increased in LN (P<0.05). Molecular docking analysis showed that ATF3 was closely bound to SLC7A11 and NRF2, and may participate in the occurrence and development of LN through the microRNA-27-ATF3 regulation axis. Conclusion The pivotal gene ATF3 may participate in the inflammation and immune injury of LN through ferroptosis.
ObjectiveTo explore the significance of mesenchymal epithelial transition factor (MET) as a clinical prognostic evaluation index for patients with pancreatic cancer based on bioinformatics analysis.MethodsThe GSE28735 and GSE62452 gene chips from GEO database were downloaded and the difference of MET gene expression between cancer and adjacent cancerous tissues were analyzed by bioinformatics. We downloaded pancreatic cancer gene chip from TCGA database to analyze the correlation between MET gene expression and clinicopathological features of pancreatic cancer patients and prognosis risk. Finally, the possible molecular mechanism of MET involved in pancreatic carcinogenesis was analyzed by GO and KEGG enrichment analysis.ResultsThe expression level of MET gene in pancreatic cancer tissues was significantly higher than that in adjacent cancerous tissues (P<0.001). The overall survival and disease-free survival of pancreatic cancer patients in the high MET gene expression group were lower than those in the low expression group (P<0.001). The expression level of MET gene was related to the age of pancreatic cancer patients, T stage, and histological grading of tumors (P<0.05), and high MET gene expression, age >65 years, and N1 stage were independent risk factors affecting the prognosis of pancreatic cancer patients. KEGG enrichment analysis showed that MET was mainly related to PI3K/AKT signaling pathway, FAK signaling pathway, and cancer transcription dysregulation and so on.ConclusionMET may be a valuable tumor marker for pancreatic cancer and can predict the poor prognosis of patients with pancreatic cancer.
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.
To screen new tuberculosis diagnostic antigens and vaccine candidates, we predicted the epitopes of Mycobacterium tuberculosis latent infection-associated protein Rv2004c by means of bioinformatics. The homology between Rv2004c protein and human protein sequences was analyzed with BLAST method. The second structures, hydrophilicity, antigenicity, flexibility and surface probability of the protein were analyzed to predict B cell epitopes and T cell epitopes by Protean software of DNAStar software package. The Th epitopes were predicted by RANKPEP and SYFPEITHI supermotif method, the CTL epitopes were predicted by means of combination analyses of SYFPEITHI supermotif method, BIMAS quantitative motif method and NetCTL prediction method. The peptide sequences with higher scores were chosen as the candidate epitopes. Blast analysis showed that Rv2004c protein had low homology with human protein. This protein had abundant secondary structures through analysis of DNAStar software, the peptide segments with high index of hydrophilicity, antigenicity, surface probability and flexibility were widely distributed and were consistent with segments having beta turn or irregular coil. Ten candidates of B cell epitopes were predicted. The Th epitopes of Rv2004c protein were located after the 200th amino acid. Of 37 Th cell epitopes predicted, there were more epitopes of HLA-DRB1*0401 and HLA-DRB1*0701 phenotypes, and the MHC restrictive types of some Th cell epitopes exist cross overlap. Of 10 CTL epitopes predicted, there were more number and higher score of HLA-A2 restricted epitopes. Therefore Mycobacterium tuberculosis Rv2004c protein is a protein antigen with T cell and B cell epitopes, and is expected to be a new target protein candidate for tuberculosis diagnosis and vaccine.
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.