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.
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.
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.
ObjectiveTo investigate the role of Peptidase domain containing associated with muscle regeneration 1 (PAMR1) in the proliferation, migration, and prognosis of hepatocellular carcinoma (HCC) through cellular experiments and clinical sample validation. Methods① Bioinformatics analysis was performed on datasets from the GEO public database to identify and screen for key genes, ultimately selecting PAMR1 for further study. Findings were validated using data from the TCGA database and six primary HCC surgical specimens prospectively obtained from the Army Characteristic Medical Center of Army Medical University from February 2024 to June 2024. ② PAMR1-overexpressing cell lines were established using HCC cell lines Huh7 and Lm3. Cells were transfected with either the recombinant plasmid pcDNA3.1(+)-PAMR1 as overexpression group or the empty vector pcDNA3.1(+) as negative control group. The effects of PAMR1 on HCC cell proliferation and migration were assessed using the Cell Counting Kit-8 (CCK-8) assay and wound healing assay, respectively. ③ Pathological specimens and clinical data were retrospectively collected from 61 patients with primary HCC who underwent surgical resection at the Army Characteristic Medical Center of Army Medical University between May 2019 and April 2020. The impact of PAMR1 expression on disease-free survival was evaluated. Results① PAMR1 was identified as a candidate gene through GEO database screening and was found to be downregulated in HCC tissues based on both TCGA data and the six HCC surgical specimens. ② The CCK-8 assay revealed that cell proliferation was significantly inhibited in the PAMR1 overexpression group compared to the negative control group (P<0.05). Similarly, the wound healing assay demonstrated reduced migratory capability in PAMR1 overexpression group (P<0.05). ③ Multivariate cox proportional hazards regression analysis of patient data indicated that high PAMR1 expression serves as an independent protective factor for disease-free survival in HCC (HR= 0.335, P=0.026). ConclusionPAMR1 serves as a crucial gene in HCC, high PAMR1 expression can significantly suppressing tumor cell proliferation and migration and indicates a favorable prognosis.
ObjectiveTo explore the clinical significance and possible potential mechanism of hepatocellular carcinoma through the screening of key genes in hepatocellular carcinoma.MethodsHepatocellular carcinoma gene chip was obtained from GEO database, differentially expressed genes (DEGs) were screened by GEO2R online tools and Venn map, GO analysis and KEGG pathway analysis were performed in DAVID database, core genes were screened by STRING and Cytscape software, core genes were analyzed in Kaplan-Meier Plotter for survival analysis, and expression was analyzed by GEPIA database. The core genes related to prognosis and highly expressed in hepatocellular carcinoma were analyzed by Metascape online tool for function and pathway enrichment analysis. Finally, the key genes were verified in hepatocellular carcinoma and paracancerous tissues.ResultsA total of 94 DEGs were screened from three gene chips GSE14520, GSE60502, and GSE102079, obtained from GEO. After the selected DEGs was analyzed by GO function analysis, KEGG pathway enrichment analysis, STRING and Cytscape software by DAVID, 19 core DEGs were screened. After 19 core DEGs were analyzed by Kaplan-Meier Plotter website, 9 genes [ribonucleotide reductase M2 (RRM2), polycomb repressive complex 1 (PRC1), topoisomerase Ⅱ alpha (TOP2A), aurora kinase A (AURKA), nucleolar spindle-associated protein 1 (NUSAP1), Rac-GTPase activating protein 1 (RACGAP1), abnormal spindle-like microcephaly-associated (ASPM), cyclin dependent kinase 1 (CDK1) and GINS complex subunit 1 (GINS1)] were found to be associated with the prognosis of hepatocellular carcinoma. The expressions of these 9 genes were analyzed by GEPIA, and the results showed that all 9 genes were highly expressed in hepatocellular carcinoma tissues. The functions and pathways of 9 highly expressed genes were analyzed by metascape website. Finally, RRM2 was selected for verification in hepatocellular carcinoma tissues and adjacent tissues, and it was found that the staining score of RRM2 in hepatocellular carcinoma tissues was (10.9±1.5) points, which was significantly higher than its staining score in adjacent tissues [(4.5±1.2) points], P<0.001.ConclusionThe nine genes identified by bioinformatics analysis may be the key genes in the occurrence and development of hepatocellular carcinoma, which can provide reference for further study on the pathogenesis, diagnosis and treatment of hepatocellular carcinoma.
Objective To detect the expression and clinical significance of POLD1 gene in non-small cell lung cancer (NSCLC) via bioinformatics method. Methods The expression difference of POLD1 in NSCLC tissue and normal lung tissue was investigated by TIMER database. UALCAN database was used to further verify different expression of POLD1 as well as the relationship between POLD1 expression and clinicopathological characteristics of NSCLC. The correlation between POLD1 gene and prognosis of NSCLC patients was detected by GEPIA and TIMER database. cBioPortal database was used to analyze frequencies of POLD1 gene mutation. POLD1-related protein-protein interaction network was constructed by STRING database. The relationship between POLD1 and immune infiltration was based on TISIDB database. Results The expression of POLD1 gene in lung adenocarcinoma and lung squamous cell carcinoma was significantly higher than that in normal lung tissue. In lung adenocarcinoma, patients with lower POLD1 level showed better prognosis. 1.2% of lung adenocarcinoma patients and 1.8% of lung squamous cell carcinoma patients carried mutated POLD1 gene, mainly missense mutations. POLD1 may interact with POLD2, POLD3, POLD4, POLE, RPA1, PCNA, MSH6, MSH2 and FEN1. The biological processes include DNA replication, mismatch repair, etc. Besides, the expression of POLD1 in NSCLC was correlated with the number of different immune cells. Conclusions The POLD1 gene is highly expressed in NSCLC patients, and negatively related with survival prognosis in patients of lung adenocarcinoma. POLD1 gene may be a potential diagnostic target and prognostic marker in NSCLC.
ObjectiveTo explore the functional heterogeneity of T lymphocytes in various organs after SARS-CoV-2 infection. Methods Using the public database GEO data (GSE171668, GSE159812, GSE159556, GSE167747) and the analysis method of single-cell technology, the functional differences of T lymphocytes in various organs of patients after infection with SARS-CoV-2 were analyzed. Results Through single-cell data extraction of 16 livers, 19 hearts,2 spleens, 6 brains, 58 lungs, 21 kidneys and 5 pancreases from SARS-CoV-2 infected patients, invasion genes were relatively highly expressed in T lymphocytes of the lung and pancreas. The lung had a special ability to express the interferon signaling pathway, while the expression of other organs was relatively low; at the same time, the T lymphocytes of the lung also highly expressed fatty acid binding sites. Conclusion After SARS-CoV-2 infection, compared with other organs, the lung has a special interferon-activated signaling pathway and fatty acid binding site.
Objective To investigate the relationship between miR-3187-5p in peripheral blood and pericardial drainage after coronary artery bypass grafting (CABG) and postoperative atrial fibrillation (POAF). Methods Patients who underwent CABG in the Heart Center of Beijing Chao-Yang Hospital from March to May 2022 were enrolled. Peripheral blood and pericardial drainage were collected at 0 h after surgery (immediate time for patients to return to ICU from operating room) to detect miR-3187-5p, and perioperative confounding factors were also collected. The miR-3187-5p was measured by quantitative real-time PCR and its regulated target genes were analyzed by bioinformatics. Results A total of 15 patients were enrolled, including 9 males and 6 females with an average age of 65.6±8.2 years. The incidence rate of POAF was 40.0%. miR-3187-5p in pericardial drainage at 0 h after surgery was an independent predictor for POAF. A total of 1 642 target genes of miR-3187-5p were predicted. GO function enrichment analysis and KEGG signal pathway enrichment analysis showed that target genes of miR-3187-5p were enriched in TGF-β, MAPK, Wnt and other classical collagen metabolic signal pathways, which might activate collagen metabolism by negatively regulating SMAD6 and other inhibitors of the pathways. Conclusion This study is the first to find that miR-3187-5p in pericardial drainage at 0 h after surgery is a potential, novel, and predictive factor for POAF, which may be related to the regulation of myocardial fibrosis signal pathways like TGF-β, MAPK and Wnt pathways, promoting the early collagen metabolism imbalance after CABG, increasing the collagen deposition in the atrium, and then promoting the early structural reconstruction after CABG and leading to the occurrence of POAF. The result provides a research basis for the accurate prediction and prevention of clinical POAF.
Objective To identify immune-related genes critical to asthma pathogenesis and construct a clinically applicable diagnostic model based on immune-gene signatures. Methods We first intersected 1639 immune-related genes (IRGs) with differentially expressed genes (DEGs) from the discovery dataset (GSE43696, n=128) to obtain differentially expressed IRGs (DE-IRGs). Expression stability was confirmed in the independent validation dataset GSE64913 (n=62). Least absolute shrinkage and selection operator (LASSO) regression and support-vector-machine (SVM) recursive feature elimination were applied to rank genes, followed by overlap with key modules identified by weighted gene co-expression network analysis (WGCNA). A logistic-regression diagnostic model was constructed using the optimal gene set, and its functional landscape was interrogated by gene-set enrichment analysis (GSEA). Finally, the model and the selected genes were cross-validated in ten transcriptomic cohorts encompassing eight distinct asthma phenotypes (total n=1137) and in lung tissue from an ovalbumin (OVA)-induced murine asthma model. Results A total of 38 DE-IRGs were identified. Among them, cholecystokinin (CCK), cellular retinol binding protein 2 (CRABP2) and C-X-C motif chemokine ligand 6 (CXCL6) were involved in immune-related processes and signaling pathways, which were of great significance in the diagnosis of asthma. The logistic regression diagnostic model based on three genes has shown good universality in various asthma samples. These three genes have also been verified to a certain extent in the lung tissues of OVA mice. Conclusion Integrative bioinformatics and in vivo validation establish CCK, CRABP2, and CXCL6 as a compact, biologically grounded immune-gene signature for asthma diagnosis and mechanistic investigation.
ObjectiveTo investigate differentially expressed genes (DEGs) and potential molecular mechanisms between hepatitis C-related hepatocellular carcinoma (HCV-HCC) and hepatitis B-related HCC (HBV-HCC). MethodsThe data of HCV-HCC and HBV-HCC gene expressions were downloaded and integrated from the public gene expression database, and the limma package was used to investigate the DEGs between the HCV-HCC and HBV-HCC samples. The gene set enrichment analysis (GSEA) was used to explore the differences in suppressed or activated gene sets between the HCV-HCC and HBV-HCC samples, and the MCODE was used to explore the key molecular modules, and then the potential biological processes and molecular pathways of the key molecular modules were analyzed. The effect of key genes on survival of the HCC patients was analyzed by the Kaplan-Meier-Plotter database.ResultsIn this study, 119 HBV-HCC samples and 163 HCV-HCC samples were obtained, and the 199 DEGs were screened out. Compared with HBV-HCC, the activated gene sets of HCV-HCC were mainly enriched in the gene sets of inflammation, complement, up-regulation of genes in response to interferon, up-regulation of genes in response to KRAS, genes regulated by the nuclear factor- κB-tumor necrosis factor pathway, and apoptosis. However, the cell cycle-related gene sets were obviously suppressed. Eight key molecular modules enriched by DEGs were found, which included 18 key genes (IFI27, DDX60, MX1, IRF9, OAS3, OAS1, RSAD2, GBP4, HERC6, ISG15, IFIT1, CMPK2, EPSTI1, IFI44, IFI44L, HERC5, IFITM1, CXCL10). GO analysis showed that the biological process was mainly concentrated in the body response related to virus infection, the molecular component was mainly in the host cells, and the molecular function was mainly enriched in the biological combination. KEGG analysis showed that the key genes were mainly involved in the molecular signaling pathway related to virus infection. The survival analysis showed that the 9 key genes (CXCL10, HERC6, DDX60, IFITM1, IFI27, GBP4, IFI44L, IFI44, MX1) were closely related to better prognosis of patients with HCC (HR<1, P<0.05). ConclusionsThere is an essential difference between HBV-HCC and HCV-HCC. Occurrence of HCV-HCC is mainly related to virus infection and immune response induced by the virus. Therefore, for HCV infection, active antiviral treatment is necessary for avoiding hepatitis turning into chronic viral infection and preventing or blocking HCV infection converting to HCC.