Expression data from gastric cancer
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE193606 | GEO | 2022/01/14
REPOSITORIES: GEO
Similar Datasets
Project description:Gastric cancer (GC) is associated with high mortality rates and an unfavorable prognosis at advanced stages. In addition, there are no effective methods for diagnosing gastric cancer at an early stage or for predicting the outcome for the purpose of selecting patient-specific treatment options. Therefore, it is important to investigate new methods for GC diagnosis. We designed a custom microarray of gastric cancer. The customized microarray contained 1042 canceration and prognosis related genes identical to the probes on the Agilent microarray. DNA microarray profilling analysis was performed on gastric cancer tissues and premalignant tissues (20 samples per group).
2014-03-01 | E-MTAB-1881 | biostudies-arrayexpress
Project description:Gastric cancer is one of the most lethal malignancies with high mortality and gastric cancer-specific biomarker is need due to the lack of specific method for early screening, diagnosis, and prognosis of the patients with gastric cancer. Ascites is known for an important source for conducing biomarker discovery because it contains the secreted proteins from malignant cells, growth factors, and cytokines. In this study, we have conducted a comprehensive proteome study using ascites of patients with inflammatory diseases and gastric cancer. In the discovery stage, we have identified 2761 ascites-specific proteins, where 234 proteins were quantitated using the label free quantitation method, the normalized spectral abundance factor (NSAF); 152 and 82 proteins showed up and down-regulated pattern, respectively. Our ascites proteome can be used as baseline data for the discovery of novel biomarkers of the gastric cancer.
2018-04-16 | PXD002213 | Pride
Project description:Gastric cancer is still one of the most common causes of cancer-related death worldwide, which is mainly attributable to late diagnosis and poor treatment options. Infection with H. pylori, different environmental factors and genetic alterations are known to influence the risk of developing gastric tumors. However, the molecular mechanisms involved in gastric carcinogenesis are still not fully understood, making it difficult to design targeted therapeutic approaches. Aberrant expression of the specific gastric differentiation marker Sox2 (sry-related HMG box 2) has been observed in stomach cancer. However, the role of Sox2 in gastric tumors has not been well established to date. To elucidate the role of Sox2 in gastric tumorigenesis, Sox2 transcriptional activity was blocked in AZ521 cells. Interestingly, inhibition of Sox2 reduced cell proliferation and migration, increased apoptosis and induced changes in cell cycle. Blocking of Sox2 also reduced the tumorigenic potential of AZ521 cells in vivo. In addition, correlation of Sox2 expression and proliferation was observed in a subset of human gastric tumours. Finally, target genes of Sox2 were for the first time identified by RNA microarray in gastric cancer cells. Taken together, the results presented here indicate that Sox2 controls several aspects related to gastric cancer development and progression by regulating the expression of members of important signalling pathways. These findings could provide new therapeutic options for a subset of gastric cancers exhibiting Sox2 deregulation. Inducible dnSox2 in AZ521 cells, 4 timepoints with/without induction.
2013-12-31 | E-GEOD-42937 | biostudies-arrayexpress
Project description:Timely diagnosis of gastric adenocarcinoma (GAC) can effectively prevent the deterioration of the disease and significantly improve the survival rate of patients. Currently, tumor markers used in clinical practice cannot meet the needs of patients, and it is urgent to develop biomarkers with high sensitivity and specificity to guide clinical diagnosis. In this study, serum samples from 33 patients with GAC and 19 healthy persons were collected. EVs were extracted by ultracentrifugation and EV protein expression profiles were obtained by DIA quantitative mass spectrometry. Multi-group differential protein expression analysis showed that 23 intersecting proteins had the same expression trend, among which 15 EV proteins were chosen as candidate biomarkers for GAC diagnosis. Afterward, a subset of 2 to 6 proteins was randomly selected as features for logistic regression modeling. To verify the diagnostic performance of these models, serums from a new cohort of 12 patients with gastric cancer and 18 healthy controls were collected, and the EV protein were quantified using the same method. We finally found a panel consisting of six proteins that performed the best as classifier. We also tried to discover biomarkers for diagnosis of advanced stage in GAC, and the results showed a three-protein panel had the best classification performance. In conclusion, we identified new protein biomarker panels from serum EVs for early diagnosis of gastric cancer that worth further validation.
2023-03-11 | PXD027535 | Pride
Project description:Gastric cancer is one of the most common causes of cancer-related death worldwide, and the molecular mechanisms involved in gastric carcinogenesis are still not fully understood. To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 111 human gastric cancer tissues and 21 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. These results provide not only a new molecular basis for understanding biological properties of gastric cancer, but also useful resources for future development of therapeutic targets and diagnostic markers for gastric cancer.
2017-01-15 | GSE54129 | GEO
Project description:miRNA expression profiles in the progression of the gastric cancer According to the development of intestinal gastric cancer(GC), the normal gastric mucosa gradually evolves into gastric cancer through CSG(Chronic superficial gastritis), CAG(Chronic atrophic gastritis), IM (intestinal metaplasia) and Dys(Dysplasia). H. pylori is the main risk factor for GC, but the mechanism is still unclear. In this study, we indentified the miRNA, lncRNAs and mRNAs expression profiles in GC progression, analyzed the fuctions and pathways and investigated the relationship between non coding RNAs and H. pylori infection. Our study provided new ideas for the study of the pathogenesis of GC and a basis for the early diagnosis and treatment of GC and precancerous lesions.
2023-12-17 | GSE163747 | GEO
Project description:The paper "Metabolomic Machine Learning Predictor for Diagnosis and Prognosis of Gastric Cancer" addresses the need for non-invasive diagnostic tools for gastric cancer (GC). Traditional methods like endoscopy are invasive and expensive. The authors conducted a targeted metabolomics analysis of 702 plasma samples to develop machine learning models for GC diagnosis and prognosis. The diagnostic model, using 10 metabolites, achieved a sensitivity of 0.905, outperforming conventional protein marker-based methods. The prognostic model effectively stratified patients into risk groups, surpassing traditional clinical models.
I have successfully reproduced the diagnosis model from the paper. This machine learning-based system differentiates GC patients from non-GC controls using metabolomics data from plasma samples analyzed by liquid chromatography-mass spectrometry (LC-MS). The model focuses on 10 metabolites, including succinate, uridine, lactate, and serotonin. Employing LASSO regression and a random forest classifier, the model achieved an AUROC of 0.967, with a sensitivity of 0.854 and specificity of 0.926. This model significantly outperforms traditional diagnostic methods and underscores the potential of integrating machine learning with metabolomics for early GC detection and treatment.
2024-07-23 | MODEL2407230001 | BioModels
Project description:Gastric cancer is still one of the most common causes of cancer-related death worldwide, which is mainly attributable to late diagnosis and poor treatment options. Infection with H. pylori, different environmental factors and genetic alterations are known to influence the risk of developing gastric tumors. However, the molecular mechanisms involved in gastric carcinogenesis are still not fully understood, making it difficult to design targeted therapeutic approaches. Aberrant expression of the specific gastric differentiation marker Sox2 (sry-related HMG box 2) has been observed in stomach cancer. However, the role of Sox2 in gastric tumors has not been well established to date. To elucidate the role of Sox2 in gastric tumorigenesis, Sox2 transcriptional activity was blocked in AZ521 cells. Interestingly, inhibition of Sox2 reduced cell proliferation and migration, increased apoptosis and induced changes in cell cycle. Blocking of Sox2 also reduced the tumorigenic potential of AZ521 cells in vivo. In addition, correlation of Sox2 expression and proliferation was observed in a subset of human gastric tumours. Finally, target genes of Sox2 were for the first time identified by RNA microarray in gastric cancer cells. Taken together, the results presented here indicate that Sox2 controls several aspects related to gastric cancer development and progression by regulating the expression of members of important signalling pathways. These findings could provide new therapeutic options for a subset of gastric cancers exhibiting Sox2 deregulation.
2013-12-31 | GSE42937 | GEO
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 investigate miRNA expression profiles between gastric cancers plasma and healthy controls plasma,screening the microRNAs that can serve as plasma biomarkers for the early diagnosis of gastric cancer by miRNA array.
2016-09-13 | GSE86822 | GEO