Dataset Information

Comprehensive analysis reveals CTHRC1, SERPINE1, VCAN and UPK1B as the novel prognostic markers in gastric cancer

ABSTRACT:

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.

SUBMITTER: Zhu Z

PROVIDER: S-EPMC8798080 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:PurposeThe serine protease inhibitor clade E member 1 (SERPINE1) has been studied as a potential biomarker in a variety of cancers, but poorly studied in gastric cancer (GC). The purpose of this study was to explore the prognostic value of SERPINE1 in GC and primarily analyze its functions.MethodsWe analyzed the the prognostic value of SERPINE1 and studied the relationship with clinicopathologic biomarkers in gastric cancer. The expression of SERPINE1 was analyzed by GEO and TCGA databases. Moreover, we validated the results by immunohistochemistry. Next, the correlation analysis between SERPINE1 and the cuproptosis-related genes was analyzed by the "Spearman" method. CIBERSORT and TIMER algorithms were used to analyze the correlation of SERPINE1 with immune infiltration. Furthermore, GO and KEGG gene enrichment analyses were used to study the functions and pathways that SERPINE1 might be involved in. Then, drug sensitivity analysis was performed using CellMiner database. Finally, a cuproptosis-immune-related prognostic model was constructed using genes related to immune and cuproptosis, and verified against external datasets.ResultsSERPINE1 was up-regulated in gastric cancer tissues, which tends toward poor prognosis. Using immunohistochemistry experiment, the expression and prognostic value of SERPINE1 were verified. Then, we found that SERPINE1 was negatively correlated with cuproptosis-related genes FDX1, LIAS, LIPT1, and PDHA1. On the contrary, SERPINE1 was positively correlated with APOE. This indicates the effect of SERPINE1 on the cuproptosis process. Furthermore, by conducting immune-related analyses, it was revealed that SERPINE1 may promote the inhibitory immune microenvironment. The infiltration level of resting NK cells, neutrophils, activated mast cells, and macrophages M2 was positively correlated with SERPINE1. However, B cell memory and plasma cells were negatively correlated with SERPINE1. Functional analysis showed that SERPINE1 was closely related to angiogenesis, apoptosis, and ECM degradation. The KEGG pathway analysis showed that SERPINE1 may be associated with P53, Pi3k/Akt, TGF-β, and other signaling pathways. Drug sensitivity analysis showed that SERPINE1 could be also seen as a potential treatment target. The risk model based on SERPINE1 co-expression genes could better predict the survival of GC patients than SERPINE1 alone. We also verified the prognostic value of the risk score by GEO external datasets.ConclusionSERPINE1 is highly expressed in gastric cancer and related to poor prognosis. SERPINE1 may regulate cuproptosis and the immune microenvironment by a series of pathways. Therefore, SERPINE1 as a prognostic biomarker and potential therapeutic target deserves further study.

Project description:Gastric cancer (GC) is one of the most common malignancies worldwide. To the best of our knowledge, no biomarkers have been widely accepted for the early diagnosis and prognostic prediction of GC. This study aimed to identify potential novel prognostic biomarkers for GC. The dataset GSE29272, which originates from the public database Gene Expression Omnibus, was employed in the present study. The online tool GEO2R was used to calculate the differentially expressed genes (DEGs) in GSE29272 between tumour tissues and adjacent tissues. CytoHubba and MCODE plugins of Cytoscape software were used to obtain hub genes and modules of DEGs. The online tools Database for Annotation, Visualisation and Integrated Discovery and Search Tool for the Retrieval of Interacting Genes were employed to conduct Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and to construct protein-protein interaction networks. A total of 117 DEGs were extracted from GSE29272. In addition, 15 hub genes and seven modules were identified in the 117 DEGs. The enrichment analysis revealed that they were mainly enriched in GO biological process and cellular component domains, and the 'ECM-receptor interaction', 'focal adhesion', 'metabolism of xenobiotics by cytochrome P450' and 'drug metabolism' pathways. The hub genes asporin (ASPN), collagen type I α1 chain (COL1A1), fibronectin 1 (FN1), versican (VCAN) and mucin 5AC (MUC5AC) were demonstrated to have prognostic value for patients with GC. The ASPN and VCAN genes were significantly associated with overall survival and disease-free survival (log-rank P=0.025, 0.038, 0.0014 and 0.015, respectively). COL1A1 and FN1 were significantly associated with overall survival (log-rank P=0.013 and 0.05, respectively), and MUC5AC was significantly associated with disease-free survival (log-rank P=0.027). Results from the present study suggested that ASPN, COL1A1, FN1, VCAN and MUC5AC may represent novel prognostic biomarkers for GC.