Transcriptome profiling for Korean Diffuse Gastric cancers
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ABSTRACT:
PROVIDER: EGAS00001001859 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:The incidence of diffuse gastric cancers (DGC) remains steadily high, but relatively small numbers of DGCs have been evaluated with whole exome sequencing (WES). Clinicopathological features of DGC vary according to age, but the molecular basis for these variations is unclear. To identify genomic alteration in this unique subset of gastric cancers, whole exome and SNP6 analyses were performed using frozen cancer tissue. The same analyses were also performed using blood of the same patients.
| EGAS00001001711 | EGA
Project description:Gastric cancer is a leading cause of death from cancer globally. Gastric cancer is classified into intestinal, diffuse and indeterminate subtypes based on histology according to the Laurén classification. The intestinal and diffuse subtypes, although different in histology, demographics and outcomes, are still treated in the same fashion. This study was designed to discover proteomic signatures of diffuse and intestinal subtypes. Mass spectrometry-based proteomics using tandem mass tags (TMT)-based multiplexed analysis was used to identify proteins in tumor tissues from patients with diffuse or intestinal gastric cancer with adjacent normal tissue control. A total of 7,804 or 5,166 proteins were identified from intestinal or diffuse subtype, respectively. This quantitative mass spectrometric analysis defined a proteomic signature of differential expression across the two subtypes, which included gremlin1 (GREM1), bcl-2-associated athanogene 2 (BAG2), olfactomedin 4 (OLFM4), thyroid hormone receptor interacting protein 6 (TRIP6) and melanoma-associated antigen 9 (MAGE-A9) proteins. Although GREM1, BAG2, OLFM4, TRIP6 and MAGE-A9 have all been previously implicated in tumor progression and metastasis, they have not been linked to intestinal or diffuse subtypes of gastric cancer. Using immunohistochemical labelling of a tissue microarray comprising of 132 cases of gastric cancer, we validated the proteomic signature obtained by mass spectrometry in the discovery cohort. Our findings should help investigate the pathogenesis of these gastric cancer subtypes and potentially lead to strategies for early diagnosis and treatment.
2022-02-17 | PXD026279 | Pride
Project description:To identify transcriptome profile in this unique subset of gastric cancers, RNA-seq analyses were performed using frozen cancer tissue. Adjacent normal tissue of the same patients were used in differently expressed gene selection and fusion gene prediction.
| EGAD00001002187 | EGA
Project description:We performed the expression RNA-seq experiments for mRNA of gastric cancer tissue. Most of gastric cancers (GCs) are accompanied by Helicobacter pylori (HP) infection. However, a very limited fraction lacks any signs of HP infection and exhibits early-stage diffuse (ED) phenotype. Although previous genomic cohorts have identified multiple driver mutations for gastric cancers including diffuse-type histology, any driver event of GC without HP has not been elucidated. The present study aims to explore the molecular mechanism with comprehensive genomic and transcriptomic analyses by comparing EDGC with and without HP. EDGCs were classified as HP-negative based on the following criteria: 1) no antibiotic eradication history, 2) no atrophic appearance by endoscopy, 3) no atrophic appearance by histology, 4) negativity in two or more tests such as rapid urease, urease breath, serum antibody, stool antigen and serum pepsinogen tests. DNAs and RNAs were extracted from EDGCs with over 10 mm in diameter to secure sufficient amount of cancer tissues. Laser-capture microdissection was then used to reduce contamination of normal cells for further molecular assays. For transcriptome analyses, we conducted RNA-seq of 2 HP-positive and 4 HP-negative fresh frozen EDGCs obtained endoscopically
2022-03-25 | GSE129219 | GEO
Project description:To identify the specific genes for intestinal-type and diffuse-type gastric cancers. We selected 18 intestinal-type gastric cancers and 12 diffuse-type gastric cancers showing typical characteristics on the form of cell growth (clustered or scattered) and the degree of differentiation (well/moderate or poor), and performed microarray analysis for obtaining genome-wide mRNA expression profiles.
2014-12-25 | E-GEOD-47007 | biostudies-arrayexpress
Project description:Human primary gastric cancer tissue SAGE libraries. Profile of the genes expressed in well and poorly differentiated gastric cancer, early and advanced gastric cancer, scirrhous type gastric cancer, and lymph node metastasis determined through SAGE. Keywords = gastric cancer, histology, early gastric cancer, advanced gastric cancer, lymph node metastasis, scirrhous type gastric cancer Keywords: other
2003-07-21 | GSE545 | GEO
Project description:To identify the specific genes for intestinal-type and diffuse-type gastric cancers.
2014-12-25 | GSE47007 | GEO
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. KaplanâMeier analysis with peritoneal relapse free survival showed a significant difference between âgood signature groupâ and âpoor signature groupâ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.
2010-05-23 | E-GEOD-15081 | biostudies-arrayexpress
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan–Meier analysis with peritoneal relapse free survival showed a significant difference between ‘good signature group’ and ‘poor signature group’ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers.
2009-03-04 | GSE15081 | GEO
Project description:Gene expression profiling of apparently normal gastric tissue (obtained from patients undergoing gastric surgery for Non-gastric cancers), paired normals (obtained from the same stomach as the gastric cancer but confirmed by frozen section not to harbour any tumour cells) and gastric cancer, with an intent to identify genes involved in the malignant transformation of normal gastric mucosa and to identify genes which can be used as biomarkers for early diagnosis and potential targets for treatment Identification of novel prognostic markers using microarray gene expression studies. Keywords: Patient tissue samples Two-dye experiments using Universal control RNA (Stratagene) and RNA from tissues. Biological replicates: Apparently Normal = 5; Paired Normal = 20; Gastric cancers = 24. One replicate per array.
2010-11-30 | E-GEOD-17154 | biostudies-arrayexpress