Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE15460 | GEO | 2009/10/06
SECONDARY ACCESSION(S): PRJNA115897
REPOSITORIES: GEO
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Project description:Many solid cancers are known to exhibit a high degree of heterogeneity in their deregulation of different oncogenic pathways. We sought to identify major oncogenic pathways in gastric cancer (GC) with significant relationships to patient survival. Using gene expression signatures, we devised an in silico strategy to map patterns of oncogenic pathway activation in 301 primary gastric cancers, the second highest cause of global cancer mortality. We identified three oncogenic pathways (proliferation/stem cell, NF-kappaB, and Wnt/beta-catenin) deregulated in the majority (>70%) of gastric cancers. We functionally validated these pathway predictions in a panel of gastric cancer cell lines. Patient stratification by oncogenic pathway combinations showed reproducible and significant survival differences in multiple cohorts, suggesting that pathway interactions may play an important role in influencing disease behavior. Individual GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Predicting pathway activity by expression signatures thus permits the study of multiple cancer-related pathways interacting simultaneously in primary cancers, at a scale not currently achievable by other platforms.
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Project description:Oncogenic Pathway Combinations Predict Clinical Prognosis in Gastric Cancer
| PRJNA115897 | ENA
Project description:Nucleotide excision repair (NER) is a versatile system that repairs various DNA damage. Polymorphisms of core NER genes could change NER ability and affect gastric cancer (GC) prognosis. We systematically analyzed the association between 43 SNPs of ten key NER pathway genes (ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, ERCC6, ERCC8, XPA, XPC, and DDB2) and overall survival (OS) of 373 GC patients in Chinese. Genotyping was performed by Sequenom MassARRAY platform. We found for the first time that carriers of ERCC2 rs50871 GG genotype demonstrated significantly increased hazards of death than GT/TT individuals (HR=2.55, P=0.002); ERCC6 rs1917799 heterozygote GT were associated with significantly shorter OS than wild-type TT (adjusted HR=1.68, P=0.048); patients with DDB2 rs3781619 GG genotype suffered higher hazards of death compared with AG/AA carriers (adjusted HR=2.30, P=0.003). Patients with ERCC1 rs3212961 AA/AC genotype exhibited longer OS than CC genotype (adjusted HR=0.63, P=0.028); ERCC5 rs2094258 AA/AG genotype revealed significantly favorable OS compared with GG genotype (adjusted HR=0.65, P=0.033); DDB2 rs830083 CG genotype could increase OS compared with GG genotype (adjusted HR=0.61, P=0.042). Furthermore, patients simultaneously carrying two "hazard" genotypes exhibited even significantly worse survival with HR of 3.75, 3.76 and 6.30, respectively. Similarly, combination of "favorable" genotypes predicted better prognosis with HR of 0.56, 0.49 and 0.33, respectively. In conclusion, ERCC2 rs50871 G/T, ERCC6 rs1917799 G/T, DDB2 rs3781619 A/G polymorphisms could predict shorter OS while ERCC1 rs3212961 A/C, ERCC5 rs2094258 A/G, DDB2 rs830083 C/G polymorphisms could predict longer OS of GC, which might serve as promising biomarkers for GC prognosis.
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Project description:AimsIdentification of miRNA signature to predict the prognosis of gastric cancer (GC) patients by integrating bioinformatics and experimental validation.MethodsThe miRNA expression profile and clinical data of GC were collected. The univariable and LASSO-Cox regression were used to construct the risk signature. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model.ResultsA 3-miRNA prognostic signature was constructed, which included hsa-miR-126-3p, hsa-miR-143-5p, and hsa-miR-1275. A nomogram, including the prognostic signature to predict the overall survival, was established, and internal validation in the The Cancer Genome Atlas (TCGA) cohort was performed. We found that compared with the traditional pathological stage, the nomogram was the best at predicting the prognosis.ConclusionsThe predictive model and the nomogram will enable patients with GC to be more accurately managed in clinical practice.
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Project description:This SuperSeries is composed of the SubSeries listed below.
2023-12-19 | GSE248183 | GEO
Project description:Procollagen-lysine, 2-oxoglutarate 5-dioxygenases (PLODs) are a set of enzymes involved in the hydroxylation of lysine and stabilization of collagen by crosslinks. Previous studies have highlighted that overexpressing PLOD genes were related to the progression, migration and progression of different human cancers. However, the diverse expression patterns and prognostic values of PLOD genes remain to be elucidated in gastric cancer (GC). In this study, we mined the expression and survival data in GC patients through ONCOMINE, UALCAN and Kaplan-Meier Plotter database. STRING portal couple with DAVID was used to establish a functional protein interaction network of PLOD family genes and analyze the GO and KEGG enriched pathways. Differential gene expression correlated with PLOD family genes was identified with LinkedOmics. We found that PLOD1, 2 and 3 were up-regulated in GC patients compared with normal tissues. High expression levels of PLOD1 and PLOD3 were associated with shorter overall survival (OS), first progression (FP) and post progression survival (PPS) while high expression level of PLOD2 was only associated with shorter FP in all GC patients. Specifically, only high PLOD2 expression had significant correlation with shorter OS, FP and PPS in the diffuse type GC patients. Furthermore, combinatorial use of expressions of all PLOD genes was a superior prognostic indicator for GC patients. Pathway analysis confirmed that PLOD family genes mainly participate in regulating the collagen metabolism and extracellular matrix constitution, and the cellular adaptor protein SHC1, which helps to transduce an extracellular signal into an intracellular signal, could be the regulatory module mediating PLOD's effect on GC. Therefore, we propose that individual PLOD genes or PLOD family genes as a whole could be potential prognostic biomarkers for GC.
| S-EPMC6930397 | biostudies-literature
Project description:Gastric cancer (GC) has a high incidence and mortality rate. If discovered late, GC tends to have a poor prognosis. Improvements in the prognostic accuracy of GC through combined analysis of multiple relevant genes and clinical factors may solve this problem. In the present study, GSE62254 (including 300 GC tissues), obtained from the Gene Expression Omnibus database, was used as a training set, and the mRNA?sequencing data of GC (including 384 GC tissues) downloaded from the Cancer Genome Atlas database served as a validation set. Based on the t?test and Wilcoxon test, the significantly differentially expressed genes (DEGs) were obtained by screening the intersecting DEGs. The prognosis-associated genes and clinical factors were identified using Cox regression analysis in the R survival package. The optimal prognosis?associated pathways were examined using the Cox?proportional hazards (Cox?PH) model in the R penalized package. Finally, risk prediction models were constructed and validated using the Cox?PH model and the Kaplan?Meier method, respectively. There were a total of 382 significant DEGs, including 268 upregulated genes and 114 downregulated genes. A total of 50 prognosis?associated genes were identified, 16 optimal prognosis?associated pathways (including mitochondrial pathway and the tyrosine?protein kinase JAK?signal transducer and activator of transcription signaling pathway, which involve caspase 7, phosphoinositide?3?kinase regulatory subunit 3, peroxisome proliferator?activated receptor ? and collagen triple helix repeat containing 1) and four prognosis?associated clinical factors [including Pathologic_N, Pathologic_stage, mutL homolog 1 (MLH1) mutation and recurrence]. The pathway? and clinical?factor?based risk prediction model exhibited marked prognostic accuracy. The clinical?factor?based risk prediction model with improved P?values for prognosis prediction may be superior to the pathway?based risk prediction model in predicting the prognosis of GC patients.
| S-EPMC5928624 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-04-17 | E-GEOD-66229 | biostudies-arrayexpress
Project description:Gastric cancer (GC) is a highly molecular heterogeneous tumor with unfavorable outcomes. The Notch signaling pathway is an important regulator of immune cell differentiation and has been associated with autoimmune disorders, the development of tumors, and immunomodulation caused by tumors. In this study, by developing a gene signature based on genes relevant to the Notch pathway, we could improve our ability to predict the outcome of patients with GC. From the TCGA database, RNA sequencing data of GC tumors and associated normal tissues were obtained. Microarray data were collected from GEO datasets. The Molecular Signature Database (MSigDB) was accessed in order to retrieve sets of human Notch pathway-related genes (NPRGs). The LASSO analysis performed on the TCGA cohort was used to generate a multigene signature based on prognostic NPRGs. In order to validate the gene signature, the GEO cohort was utilized. Using the CIBERSORT method, we were able to determine the amounts of immune cell infiltration in the GC. In this study, a total of 21 differentially expressed NPRGs were obtained between GC specimens and nontumor specimens. The construction of a prognostic prediction model for patients with GC involved the identification and selection of three different NPRGs. According to the appropriate cutoff value, the patients with GC were divided into two groups: those with a low risk and those with a high risk. The time-dependent ROC curves demonstrated that the new model had satisfactory performance when it came to prognostic prediction. Multivariate assays confirmed that the risk score was an independent marker that may be used to predict the outcome of GC. In addition, the generated nomogram demonstrated a high level of predictive usefulness. Moreover, the scores of immunological infiltration of the majority of immune cells were distinctly different between the two groups, and the low-risk group responded to immunotherapy in a significantly greater degree. According to the results of a functional enrichment study of candidate genes, there are multiple pathways and processes associated with cancer. Taken together, a new gene model associated with the Notch pathway may be utilized for the purpose of predicting the prognosis of GC. One potential method of treatment for GC is to focus on NPRGs.
| S-EPMC9889149 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-10-01 | E-GEOD-49052 | biostudies-arrayexpress