Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics Analysis.
ABSTRACT: Background and Objective: Despite striking advances in multimodality management, gastric cancer (GC) remains the third cause of cancer mortality globally and identifying novel diagnostic and prognostic biomarkers is urgently demanded. The study aimed to identify potential key genes associated with the pathogenesis and prognosis of GC. Methods: Differentially expressed genes between GC and normal gastric tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Key genes related to the pathogenesis and prognosis of GC were identified by employing protein-protein interaction network and Cox proportional hazards model analyses. Results: We identified nine hub genes (TOP2A, COL1A1, COL1A2, NDC80, COL3A1, CDKN3, CEP55, TPX2, and TIMP1) which might be tightly correlated with the pathogenesis of GC. A prognostic gene signature consisted of CST2, AADAC, SERPINE1, COL8A1, SMPD3, ASPN, ITGBL1, MAP7D2, and PLEKHS1 was constructed with a good performance in predicting overall survivals. Conclusion: The findings of this study would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of GC.
Project description:Integrin, beta-like 1 (ITGBL1), a ?-integrin-related extracellular matrix protein, was found more commonly up-regulated in gastric cancer (GC) by screening and analyzing Gene Expression Omnibus (GEO) and Oncomine databases, reminding us to explore its prognostic significance in GC. In our current study, we observed that ITGBL1 expression was significantly up-regulated in GC compared with normal controls in clinical specimens. In addition, elevated ITGBL1 expression was positively correlated with patients' tumor-node-metastasis (TNM) stage and distant metastasis. Kaplan-Meier analysis indicated that high ITGBL1 expression was significantly associated with shorter survival times in GC patients. Multivariate Cox regression analysis confirmed ITGBL1 expression as an independent prognostic factor in GC. Gene set enrichment analysis (GSEA) of multiple GEO datasets revealed a close relationship between ITGBL1 expression and the KRAS/epithelial-mesenchymal transition (EMT) signaling pathway. In conclusion, these data provide evidences that ITGBL1 is a potential predictor and may be involved in cancer cell invasion and metastasis via inducing EMT, and the ITGBL1-related pathways may represent a novel therapeutic strategy for treatment of GC.
Project description:<h4>Purpose</h4>Gastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients.<h4>Materials and methods</h4>We investigated the differential gene expression between GC and normal tissues of GSE66229. Univariate, multivariate and Lasso Cox regression analyses were conducted to establish a four-gene-related prognostic model based on the risk score. The risk score was based on a linear combination of the expression levels of individual genes multiplied by their multivariate Cox regression coefficients. Validation of the prognostic model was conducted using The Cancer Genome Atlas (TCGA) database. A nomogram containing clinical characteristics and the prognostic model was established to predict the prognosis of Asian GC patients.<h4>Results</h4>Four genes (RBPMS2, RGN, PLEKHS1, and CT83) were selected to establish the prognostic model, and it was validated in the TCGA Asian cohort. Receiver operating characteristic analysis confirmed the sensitivity and specificity of the prognostic model. Based on the prognostic model, a nomogram containing clinical characteristics and the prognostic model was established, and Harrell's concordance index of the nomogram for evaluating the overall survival significantly higher than the model only focuses on the pathologic stage (0.74 vs. 0.64, p < 0.001).<h4>Conclusion</h4>The four-gene-related prognostic model and the nomogram based on it are reliable tools for predicting the overall survival of Asian GC patients.
Project description:BACKGROUND Gastric carcinoma (GC) is one of the most aggressive primary digestive cancers. It has unsatisfactory therapeutic outcomes and is difficult to diagnose early. AIM To identify prognostic biomarkers for GC patients using comprehensive bioinformatics analyses. METHODS Differentially expressed genes (DEGs) were screened using gene expression data from The Cancer Genome Atlas and Gene Expression Omnibus databases for GC. Overlapping DEGs were analyzed using univariate and multivariate Cox regression analyses. A risk score model was then constructed and its prognostic value was validated utilizing an independent Gene Expression Omnibus dataset (GSE15459). Multiple databases were used to analyze each gene in the risk score model. High-risk score-associated pathways and therapeutic small molecule drugs were analyzed and predicted, respectively. RESULTS A total of 95 overlapping DEGs were found and a nine-gene signature (COL8A1, CTHRC1, COL5A2, AADAC, MAMDC2, SERPINE1, MAOA, COL1A2, and FNDC1) was constructed for the GC prognosis prediction. Receiver operating characteristic curve performance in the training dataset (The Cancer Genome Atlas-stomach adenocarcinoma) and validation dataset (GSE15459) demonstrated a robust prognostic value of the risk score model. Multiple database analyses for each gene provided evidence to further understand the nine-gene signature. Gene set enrichment analysis showed that the high-risk group was enriched in multiple cancer-related pathways. Moreover, several new small molecule drugs for potential treatment of GC were identified. CONCLUSION The nine-gene signature-derived risk score allows to predict GC prognosis and might prove useful for guiding therapeutic strategies for GC patients.
Project description:Epigenetic silencing of tumor suppressor genes contributes to the pathogenesis of hepatocellular carcinoma (HCC). To identify clinically relevant tumor suppressor genes silenced by DNA methylation in HCC, we integrated DNA methylation data from human primary HCC samples with data on up-regulation of gene expression after epigenetic unmasking.We performed genome-wide methylation analysis of 71 human HCC samples using the Illumina HumanBeadchip27K array; data were combined with those from microarray analysis of gene re-expression in 4 liver cancer cell lines after their exposure to reagents that reverse DNA methylation (epigenetic unmasking).Based on DNA methylation in primary HCC and gene re-expression in cell lines after epigenetic unmasking, we identified 13 candidate tumor suppressor genes. Subsequent validation led us to focus on functionally characterizing 2 candidates, sphingomyelin phosphodiesterase 3 (SMPD3) and neurofilament, heavy polypeptide (NEFH), which we found to behave as tumor suppressor genes in HCC. Overexpression of SMPD3 and NEFH by stable transfection of inducible constructs into an HCC cell line reduced cell proliferation by 50% and 20%, respectively (SMPD3, P = .003 and NEFH, P = .003). Conversely, knocking down expression of these genes with small hairpin RNA promoted cell invasion and migration in vitro (SMPD3, P = .0001 and NEFH, P = .022), and increased their ability to form tumors after subcutaneous injection or orthotopic transplantation into mice, confirming their role as tumor suppressor genes in HCC. Low levels of SMPD3 were associated with early recurrence of HCC after curative surgery in an independent patient cohort (P = .001; hazard ratio = 3.22; 95% confidence interval: 1.6-6.5 in multivariate analysis).Integrative genomic analysis identified SMPD3 and NEFH as tumor suppressor genes in HCC. We provide evidence that SMPD3 is a potent tumor suppressor gene that could affect tumor aggressiveness; a reduced level of SMPD3 is an independent prognostic factor for early recurrence of HCC.
Project description:Promoter mutations of pleckstrin homology domain-containing S1 (PLEKHS1) are frequent in several cancer types. To evaluate the DNA mutations, the mRNA expression and prognostic value of PLEKHS1 was evaluated in bladder cancer. We investigated DNA mutations and mRNA expression of PLEKHS1 in a first series of 154 bladder tumors [71 non-muscle-invasive bladder cancer (NMIBC) and 83 muscle-invasive bladder cancers (MIBC)] from patients who underwent transurethral bladder resection or radical cystectomy between 2001 and 2006, and 20 normal bladder samples. Results were then validated in a second series of 181 bladder tumors (91 NMIBC and 90 MIBC). All patients have signed an informed consent form. DNA mutations were analysed by high-resolution melt analysis and sanger sequencing. The mRNA expression was measured by real-time reverse-transcriptase quantitative PCR. The results of the molecular analysis were compared with survival data. PLEKHS1 mutations occurred in 25.0 and 32.2% of NMIBC and MIBC, respectively in the first series. These results were confirmed in the second series (33.0 and 37.8% of NMIBC and MIBC, respectively). In MIBC, DNA mutations were significantly more frequent with the basal than non-basal phenotype (61.5 vs. 27.1%; P=0.0025). The PLEKHS1 mRNA level was increased in 22.5 and 27.7% of NMIBC and MIBC tumors but was not associated with DNA mutations. In NMIBC, PLEKHS1 mRNA overexpression was significantly associated with progression to muscle-invasive disease (P=0.0069) and remained an independent prognostic factor on multivariate analysis (P=0.034). DNA mutations of PLEKHS1 occurred in one-third of bladder tumors and was frequent in the basal MIBC phenotype. PLEKHS1 mRNA overexpression may be an independent prognostic factor of progression-free survival in NMIBC.
Project description:Purpose: Gastric cancer (GC) is a primary cause of cancer-associated mortality worldwide. N6-methyladenosine (m6A) is one of the most common RNA modifications that involves in the progression of numerous cancers. However, the expression status and function of m6A-related genes in gastric cancer is still not well understood. The current study is aimed to investigate the expression status and determinate prognostic value of m6A-related genes in gastric cancer. Methods: m6A-asssociated gene expression was evaluated via analyzing the expression data of GC patients from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The protein expression levels of m6A-associated molecules were further validated by immunohistochemical (IHC) staining data from GC tissue microarray (TMA) cohort and Human Protein Atlas (HPA) database. Kaplan-Meier analysis was performed to assess the prognostic value of m6A-associated genes in gastric cancer. Risk score model was established by lasso COX regression analysis and its prognostic predicted efficiency was assessed by the receiver-operator characteristic (ROC) curve. Cox regression analyses were used for exploring risk factors related to GC patient prognosis. Results: Most of m6A-related genes were upregulated at both mRNA and protein levels in gastric cancer tissues compared with that in normal gastric tissues. The expression levels of m6A-related genes were associated with clinicopathological features including race, age and TNM stage. High expression of WTAP and FTO predicted poor prognosis of GC patients. Survival analysis demonstrated that patients with high-risk scores had worse overall survival (OS) and ROC curves suggested the prediction performance for gastric patients. Moreover, Cox regression analyses indicated that m6A risk model score was a prognostic factor for OS and FTO upregulation might be a potential independent prognostic factor for recurrence-free survival (RFS) in gastric cancer patients. Conclusion: m6A-related genes were dysregulated in GC and were closely associated with prognosis of GC patients. FTO might serve as a novel prognostic biomarker for gastric cancer, while the m6A-related risk score might be informative for risk assessment and prognostic stratification.
Project description:The replication protein A (RPA)1-4 family are single-stranded DNA-binding proteins that are essential components of DNA replication, repair and recombination, and cell cycle regulation. The present study aimed to evaluate the prognostic value of the RPA family members in patients with gastric cancer (GC), using datasets retrieved from the Oncomine public database. Datasets were retrieved for the purpose of comparing the RPA expression levels between GC and normal tissues. Additionally, Kaplan-Meier analysis was used to compare the overall survival (OS) times of GC patients that expressed different levels of RPA proteins. RPA1, 2, and 3 expression levels were all significantly upregulated in gastric intestinal-type, diffuse gastric, and gastric mixed adenocarcinomas, compared with those in normal mucosal tissues. Moreover, high mRNA expression levels of RPA3 and 4 predicted poorer OS times in all GCs, as well as patients with human epidermal growth factor receptor 2-negative and -positive GC. The high-risk group, separated by RPA signature, showed a poorer outcome than the low-risk group. RPA3 was the most strongly correlated with CD4+ T-cell levels. In conclusion, RPAs are novel prognostic indicators in GC, and can also predict the features of immunological diseases. Future experimental investigation into the roles of RPAs concerning the pathogenesis and development of GC may provide a novel biomarker or therapeutic target, improving the prognosis of patients with GC.
Project description:Purpose:To explore the role of FKBP prolyl isomerase 10 (FKBP10) protein in the progression of gastric cancer. Methods:Four independent gastric cancer databases (GSE27342, GSE29272, GSE54129 and TCGA-STAD) were used to identify differentially expressed genes (DEGs). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was used to identify the abnormally active pathways in patients with gastric cancer. Univariate Cox regression analysis was used to identify genes with stable prognostic value in gastric cancer patients based on three independent gastric cancer databases (GSE15459, GSE62254, TCGA-STAD). Gene set enrichment analysis (GSEA) was used to explore the possible pathways related to FKBP10. The reverse transcription-polymerase chain reaction (RT-PCR) was employed to determine the expression of FKBP10 mRNA in the HGC-27 and MKN-7 cell lines. Adhesion assay was used to detect changes in cell adhesion ability. FKBP10, ITGA1, ITGA2, ITGA5, ITGAV, ITGA6, P- AKT 473, P- AKT 308, AKT, and ?-actin were evaluated by Western blot (WB). Results:We first performed differential expression genes (DEGs) screening of four independent GC databases (GSE27342, GSE29272, GSE54129 and TCGA-STAD). Eighty-nine genes showed consistent up-regulation in GC, the results of pathway analysis showed that they were related to "Focal adhesion". The prognostic value of these 89 genes was tested in three independent GC databases GSE15459, GSE62254 and TCGA-STAD cohort. Finally, 12 genes, in which the expression of FKBP10 was prominently increased in patients with lymph node metastasis (LNM), showed stable prognostic value. The following gene set enrichment analysis (GSEA) also showed that FKBP10 is mainly involved in cell adhesion process, while adhesion experiments confirmed that cell adhesion was down-regulated after silencing FKBP10 in GC cells, and adhesion-related molecules integrin ?V and ?6 were down-regulated. Conclusion:FKBP10 may be used as a marker for lymph node metastasis of GC and could be used as a potential target for future treatment of GC.
Project description:Objectives: The aims of this study were to compare the expression of fibronectin type III domain containing 1 (FNDC1) in gastric cancer (GC) and normal gastric tissue, to explore the prognostic significance of FNDC1 expression in patients with gastric adenocarcinoma, and to analyze FNDC1-related signaling pathways. Methods: The expression level of FNDC1 was initially predicted using the Oncomine and Cancer Genome Atlas databases. A Kaplan-Meier plotter database was mined to examine the clinical prognostic significance of FNDC1 mRNA in patients with GC. Subsequently, immunohistochemistry was used to measure FNDC1 protein expression levels in tissue from 90 cases of GC and paired adjacent normal tissue. Kaplan-Meier univariate and Cox multivariate survival analyses were used to determine the prognostic role of FNDC1 expression. Results: Bioinformatic data indicated that FNDC1 mRNA expression levels were significantly highly expressed in GC compared with normal gastric tissue (all P < 0.05), and patients with GC with high FNDC1 mRNA expression levels had remarkably lower overall survival (all P < 0.01). Immunohistochemical results revealed that expression levels of FNDC1 protein were significantly increased in GC compared with normal gastric tissue (P < 0.001). Additionally, Kaplan-Meier univariate and Cox multivariate survival analyses indicated that increased expression of FNDC1 was an independent predictor of poor prognosis in patients with GC (all P < 0.05). Conclusions: FNDC1 was highly expressed in GC, and high expression of FNDC1 was an independent predictor of poor prognosis in patients with GC. FNDC1 co-expressed genes were largely enriched in extracellular matrix-receptor interactions, which are closely related to tumor metastasis.
Project description:BACKGROUND:Gastric cancer (GC) is the most prevailing digestive tract malignant tumor worldwide with high mortality and recurrence rates. However, its potential molecular mechanism and prognostic biomarkers are still not fully understood. We aim to screen novel prognostic biomarkers related to GC prognosis using comprehensive bioinformatic tools. METHODS:Four gene expression microarray data were downloaded from the Gene Expression Omnibus (GEO) database (GSE26942, GSE33335, GSE63089, and GSE79973). Differentially expressed genes (DEGs) between gastric carcinoma and normal gastric tissue samples were identified by an integrated bioinformatic analysis. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using statistical software R. STRING and Cytoscape software were employed to construct protein-protein interaction (PPI) networks. Hub genes with a high score of connectivity identified from the PPI network were identified. Prognostic values of hub genes were evaluated in GSE15459 dataset. Hub genes related to GC overall survival were further validated in GEPIA (Gene Expression Profiling Interactive Analysis) online tool. RESULTS:A total of 12 upregulated DEGs and 59 downregulated DEGs were identified when the 4 microarray data overlapped. Among them, 10 hub genes with a high score of connectivity were identified. High expression of ghrelin and obestatin prepropeptide (GHRL), BGN, TIMP metallopeptidase inhibitor 1, thrombospondin 2, secreted phosphoprotein 1, and low expression of CHGA were associated with a poor overall survival of gastric cancer (all log rank P?<?.05). After validation in GEPIA database, only GHRL was confirmed associated with a poor overall survival of gastric cancer (log rank P?=?.04). CONCLUSIONS:GHRL could be used as a novel biomarker for the prediction of a poor overall survival of gastric cancer, and could be a novel therapeutic target for gastric cancer treatment. However, future experimental studies are still required to validate these findings.