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:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-10-01 | E-GEOD-49052 | biostudies-arrayexpress
Project description:Objective: Mammalian target of rapamycin complex 1 (mTORC1) plays an important role in maintaining proper cellular functions in gastric cancer (GC). Previous studies demonstrated genetic variants within mTORC1 genes were associated with GC risk. However, no studies reported the associations between genetic variants within mTORC1 genes and GC prognosis. Herein, we firstly assessed the associations of genetic variants of mTORC1 genes with overall survival (OS) of GC in Chinese populations. Methods: We genotyped eight single nucleotide polymorphisms (SNPs) in mTORC1 genes (i.e., rs2536 T>C and rs1883965 G>A for mTOR, rs3160 T>C and rs26865 A>G for MLST8, rs3751934 C>A, rs1062935 T>C, rs3751932 T>C and rs12602885 G>A for RPTOR) by the TaqMan method in 197 Chinese GC patients who had surgical resection in Xinhua Hospital. We conducted Kaplan-Meier survival plots and Cox hazards regression analysis to explore the associations of these SNPs with OS. Results: The single-locus analysis indicated that RPTOR rs1062935 T>C was associated with an increased risk of poor GC prognosis (CC vs. TT/TC: adjusted Hazard ratio (HR) = 1.71, 95% confidence interval (CI) = 1.04-2.82). The combined analysis of all eight SNPs showed that patients with more than three risk genotypes significantly increased risk of death (adjusted HR = 2.44, 95% CI = 1.30-4.58), when compared to those with three or less risk genotypes. Conclusions: Our findings indicated that genetic variants within mTORC1 genes may predict GC prognosis in Chinese populations. The results need to be validated in future studies with larger sample sizes.
| S-EPMC5929090 | biostudies-literature