Bioinformatics analysis of the prognosis and biological significance of VCAN in gastric cancer.
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ABSTRACT:
SUBMITTER: Huang XY
PROVIDER: S-EPMC8127546 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundGastric cancer (GC) is one of the common gastrointestinal malignancy worldwide and exhibits a poor prognosis. Increasing studies have indicated that microRNAs play critical roles in the cancer progression and have shown great potential as useful biomarkers. The search for potential diagnostic and prognostic biomarkers of gastric cancer (GC) with integrated bioinformatics analyses has been undertaken in previous studies.MethodsIn this study, the robust rank aggregation (RRA) method was used to perform an integrated analysis of differentially expressed miRNAs (DEMs) from five microarray datasets in the Gene Expression Omnibus (GEO) database to find robust biomarkers for GC. Ultimately, seven miRNAs were filtered from fourteen primary miRNAs using the validation set of The Cancer Genome Atlas (TCGA) database. Based on these results, diagnostic and survival analyses were performed, and logistic regression and Cox regression were used to determine the clinicopathological characteristics of the DEM expression and overall survival.ResultsNine eligible miRNA datasets related to GC were selected from the GEO database for integrated analysis in this study. Diagnostic analysis implied that these miRNAs could be regarded as promising candidate diagnostic biomarkers in GC tissues, but whether the results of the tissue analysis are consistent with those of peripheral blood analysis requires further validation. The logistic regression indicated that the ectopic expression of these DEMs was relevant to the histological type, anatomical region, and pathological grade of GC. However, the survival and Cox regression analyses suggested that the poor prognosis of GC patients was not strongly dependent on the ectopic expression of the seven miRNAs, but rather, a poor prognosis was associated with age, metastasis, and histological grade.ConclusionsBased on the results presented in this study it can be concluded that these miRNAs (miR-455-3p, miR-135b-5p, let-7a-3p, miR-195-5p, miR-204-5p, miR-149-5p, and miR-143-3p) might be potential biomarkers for the early diagnosis of GC patients, but this finding should be regarded with caution. A large-scale, prospective, and multicenter cohort study should be performed.
| S-EPMC8246217 | biostudies-literature
Project description:Gastric cancer (GC) is one of the most common malignancies of the digestive system. In diffuse‑type GC, differentiation is relatively poor, and the probability of distant metastasis and lymph node metastasis is high, resulting in poor clinical prognosis. The purpose of this study was to identify specific genes that can predict the prognosis of different types of GC. Differentially expressed genes (DEGs) were screened in the GSE62254 dataset obtained from the Gene Expression Omnibus using the 'limma' and 'survival' R packages. A total of 355 survival‑related DEGs were selected according to specific screening criteria, of which 293 were associated with diffuse‑type GC and 62 with intestinal‑type GC. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for functional annotation and pathway enrichment analysis of DEGs. Using protein‑protein interaction networks and Cytoscape software, three hub genes were identified in diffuse‑type GC‑associated DEGs, including angiotensinogen (AGT), C‑X‑C motif chemokine ligand 12 (CXCL12) and adrenoceptor β2 (ADRB2). Immunohistochemical staining and reverse transcription‑quantitative PCR revealed that the expression levels of the three genes in diffuse‑type GC samples were upregulated compared with in intestinal‑type GC samples. Kaplan Meier analysis indicated that a higher expression levels of these three hub genes were associated with a poorer prognosis of diffuse‑type GC. In summary, the present findings suggested that AGT, CXCL12 and ADRB2 might contribute to the progression of diffuse‑type GC, and could serve as potential biomarkers or therapeutic targets for this disease.
| S-EPMC7809905 | biostudies-literature
Project description:BackgroundAlternative splicing (AS) is an important mechanism for regulating gene expression and proteome diversity. Tumor-alternative splicing can reveal a large class of new splicing-associated potential new antigens that may affect the immune response and can be used for immunotherapy.MethodsThe RNA-seq transcriptome data and clinical information of stomach adenocarcinoma (STAD) cohort were downloaded from The Cancer Genome Atlas (TCGA) database data portal, and data of splicing events were obtained from the SpliceSeq database. Predicting genes were validated by Asian cancer research group (ACRG) cohort and Oncomine database. RT-qPCR was used to analysis the expression of ECT2 in STAD.ResultsA total of 32,166 AS events were identified, among which 2,042 AS events were significantly associated with patients survival. Biological pathway analysis indicated that these genes play an important role in regulating gastric cancer-related processes such as GTPase activity and PI3K-Akt signaling pathway. Next, we derived a risk signature, using alternate acceptor, that is an independent prognostic marker. Moreover, high ECT2 expression was associated with poorer prognosis in STAD. Multivariate survival analysis demonstrated that high ECT2 expression was an independent risk factor for overall survival. Gene set enrichment analysis revealed that high ECT2 expression was enriched for hallmarks of malignant tumors. The ACRG cohort and Oncomine also showed that high ECT2 expression was associated with poorer prognosis in gastric cancer patients. Finally, RT-qPCR showed ECT2 expression was higher in STAD compared to the normal tissues.ConclusionThis study excavated the alternative splicing events in gastric cancer, and found ECT2 might be a biomarkers for diagnosis and prognosis.
| S-EPMC7527772 | biostudies-literature
Project description:Background:Ranking fourth in the world in tumor incidence and second in cancer-related death worldwide, gastric cancer (GC) is one of the major malignant tumors, and has a very complicated pathogenesis. In the present study, we aimed to identify new biomarkers to predict the survival rate of GC patients. Methods:The differentially expressed genes (DEGs) between GC tissues and normal stomach tissues were obtained by using GEO2R, and overlapped DEGs were acquired with Venn diagrams. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted with R software. Then, the protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape. Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression differences of hub genes in gastric adenocarcinoma tissues and normal tissues. Overall survival (OS) of hub genes was calculated by Kaplan-Meier plotter. Results:There were a total of 128 consistently expressed genes in the two datasets: 85 upregulated genes were enriched in extra-cellular matrix (ECM)-receptor interaction, protein digestion and absorption, focal adhesion, gastric acid secretion, mineral absorption, systemic lupus erythematosus, amoebiasis, and PI3K-Akt signaling pathway, and 43 downregulated genes were enriched in palate development, blood coagulation, positive regulation of transcription from RNA polymerase II promoter, axonogenesis, receptor internalization, negative regulation of transcription from RNA polymerase II promoter, and in no significant signaling pathways. From the PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 27 upregulated genes were selected. Furthermore, to analyze the OS among these genes, Kaplan-Meier analysis was conducted, and 25 genes were associated with remarkably worse survival. For validation in GEPIA, 11 of 25 genes were discovered to be highly expressed in GC tissues compared to normal OS tissues. Furthermore, in the re-analysis of the Database for Annotation, Visualization and Integrated Discovery (DAVID), three genes [G2/miotic-specific cyclin B1 (CCNB1), polo-like kinases 1 (PLK1), and pituitary tumor-transforming gene-1 (PTTG1)] were markedly enriched in the cell cycle pathway, particulary the G1-G1/S phase. Conclusions:Three remarkably upregulated DEGs with poor prognosis in GC were identified and may serve as new prognostic biomarkers and targets in GC therapy.
| S-EPMC7396774 | biostudies-literature
Project description:BackgroundGastric cancer (GC) is one of the most common cancers of the digestive tract, with the fifth-highest incidence and third highest mortality rate in the world.MethodsIn this study, the Kaplan-Meier Plotter database was used to analyze the correlation between the expression of the glutathione peroxidase (GPX) family and the clinical prognosis of gastric cancer (GC). The prognostic value of increased GPX family mRNA expression in GC patients in different clinical stages, with different differentiation degrees, in different genders and human epidermal growth factor receptor-2 (HER2) status, and treated with different therapeutic regimens was also studied.ResultsThe results showed that with the increase of GPX1 and GPX2 mRNA low expression levels, the overall survival (OS) of gastric cancer patients was longer. However, when the high expression levels of GPX3, GPX5 and GPX6 mRNA increased, gastric cancer patients presented good OS, while the increase of GPX4 mRNA expression level had no significant correlation with OS in gastric cancer patients.ConclusionThe results of this study are expected to provide a reliable basis for the clinical treatment of GC and lay a foundation for the development of a novel GC treatment approach.
| S-EPMC9830173 | biostudies-literature
Project description:Background and aimCyclins have been reported to be overexpressed with poor prognosis in several human cancers. However, limited numbers of studies evaluated the expressions and prognostic roles of cyclins in gastric cancer (GC). We aim to evaluate the expressions and prognostic roles of cyclins. Also, further efforts were made to explore biological function of the differentially expressed cyclins.MethodsCyclins expressions were analyzed by Oncomine and The Cancer Genome Atlas datasets, and the prognostic roles of cyclins in GC patients were investigated by the Kaplan-Meier Plotter database. Then, a comprehensive PubMed literature search was performed to identify expression and prognosis of cyclins in GC. Biological functions of the differentially expressed cyclins were explored through Enrich R platform, and KEGG and transcription factor were analyzed.ResultsThe expression levels of CCNA2 (cyclin A2), CCNB1 (cyclin B1), CCNB2 (cyclin B2), and CCNE1 (cyclin E1) mRNAs were identified to be significantly higher in GC tissues than in normal tissues in both Oncomine and The Cancer Genome Atlas datasets. High expressions of CCNA2, CCNB1, and CCNB2 mRNAs were identified to be related with poor overall survival in Kaplan-Meier Plotter dataset. Evidence from clinical studies showed that CCNB1 was related with overall survival in GC patients. Cyclins were associated with several biological pathways, including cell cycle, p53 signaling pathway, FoxO signaling pathway, viral carcinogenesis, and AMPK signaling pathway. Enrichment analysis also showed that cyclins interacted with some certain transcription factors, such as FOXM1, SIN3A, NFYA, and E2F4.ConclusionBased on our results, high expressions of cyclins were related with poor prognosis in GC patients. The above information might be useful for better understanding the clinical and biological roles of cyclins mRNA and guiding individualized treatments for GC patients.
| S-EPMC6186297 | biostudies-literature
Project description:IntroductionGastric cancer is one of the most common cancers in the world. This study aimed to identify genes, biomarkers, and metabolic pathways affecting gastric cancer using bioinformatic analysis and meta-analysis.MethodsDatasets containing gene expression profiles of tumor lesions and adjacent non-tumor mucosa samples were downloaded. Common differentially expressed genes between data sets were selected to identify hub genes and further analysis. Gene Expression Profiling and Interactive Analyses (GEPIA) and the Kaplan-Meier method were used to further validate the expression level of genes and plot the overall survivalcurve, respectively.Results and disscussionKEGG pathway analysis showed that the most important pathway was enriched in ECM-receptor interaction. Hub genes includingCOL1A2, FN1, BGN, THBS2, COL5A2, COL6A3, SPARC and COL12A1 wereidentified. The top interactive miRNAs including miR-29a-3p, miR-101-3p,miR-183-5p, and miR-15a-5p targeted the most hub genes. The survival chart showed an increase in mortality in patients with gastric cancer, which shows the importance of the role of these genes in the development of the disease and can be considered candidate genes in the prevention and early diagnosis of gastric cancer.
| S-EPMC10288990 | biostudies-literature
Project description:BackgroundLarge numbers of studies have identified that procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) family members play important roles in tumorigenesis and tumor progression in various cancers. However, the expression pattern, clinical value and function of PLOD family have yet to be analyzed systematically and comprehensively in bladder urothelial carcinoma (BLCA).MethodsWe investigated the transcriptional levels, genetic alteration, biological function, immune cell infiltration, data on survival of PLODs in patients with BLCA based on UALCAN, the Cancer Genome Atlas (TCGA) database, Gene Expression Profiling Interactive Analysis (GEPIA), TIMER, STRING, cBioPortal and GSCALite databases. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software using the Cluster Profiler Bioconductor package. Protein-protein interaction (PPI) network was established by STRING and visualized by using R version (3.6.3) software. Survival analysis was performed using the packages "survminer".ResultsThe mRNA and protein expression patterns of PLOD family members were noticeably increased in BLC compared with normal tissue. The mRNA expression levels of PLOD1-2 genes were significantly correlated with histological subtypes and PLOD1 was significantly correlated with pathological stage. Furthermore, the high expression levels of PLOD1-2 were remarkably associated with poor overall survival (OS) in BLCA patients, meanwhile high expression levels of PLOD1 and PLOD3 were markedly associated with poor progression-free interval (PFI). In co-expression gene analysis, 50 genes were primarily associated with the differentially expressed PLODs in BLCA. Functional enrichment analysis revealed that protein hydroxylation, collagen fibril organization, and lysine degradation were key biological functions of PLODs in BLCA. Moreover, PLOD family genes were identified as being associated with the activities of tumor-infiltrating immune cells and closely associated with immune responses in BLCA.ConclusionPLOD family members might serve as potential therapeutic targets and prognostic markers for BLCA patients' survival.
| S-EPMC9975538 | biostudies-literature
Project description:Background Gastric cancer (GC) is one of the most common malignant diseases worldwide, the incidence and mortality for GC is still high, thus it is urgently important to identify the effective and reliable biomarkers to evaluate GC and the underlying molecular events. Methods The study integrated four Gene Expression Omnibus (GEO) profile datasets and The Cancer Genome Atlas (TCGA) dataset to screen differentially expressed genes (DEGs), screened key genes by performing the Kaplan-Meier analysis, univariate and multivariate-cox analysis. Further analysis were performed to evaluate and validate the prognostic value of the key genes based on TCGA database and online websites. In addition, mechanism analysis of the key genes was performed thought biological processes and KEGG pathway analysis. Results In the study, 192 DEGs (92 up-regulated and 100 down-regulated) were identified from the GEO and TCGA datasets. Next, gene ontology (GO) for DEGs focused primarily on cell adhesion, extracellular region and extracellular matrix structural constituent. Then four significant key genes were screened by performed the Kaplan-Meier analysis, univariate and multivariate-cox analysis. By using Kaplan-Meier plotter and OncoLnc, the expression level was associated with a worse prognosis. In addition, the area under curve (AUC) for time-dependent receiver operating characteristic (ROC) indicated a moderate diagnostic value. Furthermore, the expression of collagen triple helix repeat containing 1 (CTHRC1), serpin family E member 1 (SERPINE1), Versican (VCAN) was associated with tumor size, Uroplakin 1B (UPK1B) expression was associated with distant metastasis. Finally, multiple biological processes and signaling pathway associated with key genes revealed the underlying mechanism in GC. Conclusions Taken together, CTHRC1, SERPINE1, VCAN, UPK1B were novel potential prognostic molecular markers for GC, which acted as oncogene to promote the development of GC.
| S-EPMC8798080 | biostudies-literature
Project description:Collagen type X alpha 1 (COL10A1) is a member of the collagen family and the main matrix component. However, COL10A1 expression and prognosis relationship remains unclear in gastric cancer (GC). Through the analysis of database of Oncomine, the Cancer Genome Atlas (TCGA) as well as the Gene Expression Omnibus (GEO), in contrast to the tissue of normal gastric, COL10A1 in gastric cancer, had been upregulated. The high expression of COL10A1 was obviously related to T stage (P = 0.025) and lymph node metastasis (P = 0.025). It has been illustrated by the analysis of logistic regression that COL10A1's heightened expression in gastric cancer had been essentially linked with pathological stage, tumor differentiation, and T classification. The Kaplan-Meier curve in the Kaplan-Meier plotter database (P = 0.0371) and GSE84437 (P = 0.002) indicate that patients with high COL10A1 expression possess poor prognosis, specifically GC patients with lymph node metastasis have it. TCGA's Multivariate analysis (P = 0.025) and GSE84437 dataset (P = 0.034) show that high expression COL10A1 is a key independent predictor of poor overall survival. Searching KEGG pathway enrichment by GSEA, the results suggested that 29 pathways were enriched. qRT-PCR technique was used for verification of the COL10A1's high expression in gastric cancer in contrast to the normal gastric tissues. In conclusion, COL10A1 is of great importance in predicting the survival rate of GC patients.
| S-EPMC8291830 | biostudies-literature