Identification of cell-free DNA in gastric cancer patient
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ABSTRACT:
PROVIDER: PRJNA427805 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:cfDNA (Cell-free DNA) was extracted from serum exosome of gastric cancer patient. We analyzed cfDNA by aCGH (array comparative genomic hybridization).
2018-03-31 | GSE108602 | GEO
Project description:Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-xpression-based clustering of a large collection of gastric adenocarcinomas from Singaporean patients [GSE34942 and GSE15459]. We developed and validated a classifier for the three subtypes in Australian patient cohort. Profiling of 70 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from Peter MacCallum Cancer Center, Australia; the Research Ethics Review Committee; and signed patient informed consent.
2012-07-04 | E-GEOD-35809 | biostudies-arrayexpress
Project description:Genome-wide mRNA expression profiles of 70 primary gastric tumors from the Australian patient cohort. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-xpression-based clustering of a large collection of gastric adenocarcinomas from Singaporean patients [GSE34942 and GSE15459]. We developed and validated a classifier for the three subtypes in Australian patient cohort.
2012-07-05 | GSE35809 | GEO
Project description:Genome-wide mRNA expression profiles of 56 primary gastric tumors from the Singapore patient cohort, batch B. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-expression-based clustering of a large collection of gastric adenocarcinomas (with GSE15459) from Singaporean patients. Profiling of 56 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from the National Cancer Centre, Singapore; the Research Ethics Review Committee; and signed patient informed consent.
2014-09-05 | E-GEOD-34942 | biostudies-arrayexpress
Project description:Genome-wide mRNA expression profiles of 56 primary gastric tumors from the Singapore patient cohort, batch B. Like many cancers, gastric adenocarcinomas (gastric cancers) show considerable heterogeneity between patients. Thus, there is intense interest in using gene expression profiles to discover subtypes of gastric cancers with particular biological properties or therapeutic vulnerabilities. Identification of such subtypes could generate insights into the mechanisms of cancer progression or lay the foundation for personalized treatments. Here we report a robust gene-expression-based clustering of a large collection of gastric adenocarcinomas (with GSE15459) from Singaporean patients.
2014-09-05 | GSE34942 | GEO
Project description:To investigate the differences of STAT3-mediated DNA methylation in gastric cancer patient samples, genome wide DNA methylation profiling for STAT3-positive/negative patient samples
2023-12-05 | GSE162731 | GEO
Project description:Helicobacter pylori strain:gastric mucosa of a patient with gastric ulcer | isolate:gastric mucosa of a patient with gastric ulcer Genome sequencing
| PRJNA973247 | ENA
Project description:Unbiased de-novo identification of biomarkers for H.pylori associated gastric cancer; Microarrays, representing 242 seroreactive H.pylori proteins, were generated by spotting of the respective gene constructs and cell-free on-chip expression. Antibody levels to these proteins were measured by application of sera from non-cardia gastric cancer patients and their matched controls. Possible new biomarkers, associated with gastric cancer, were evaluated by unadjusted conditional regression.
2020-09-14 | E-MTAB-9534 | biostudies-arrayexpress
Project description:Genome-wide mRNA expression profiles of 200 primary gastric tumors from the Singapore patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Experiment Overall Design: Profiling of 200 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Array. All tumors were collected with approvals from the National Cancer Centre, Singapore; the Research Ethics Review Committee; and signed patient informed consent.
2009-04-10 | E-GEOD-15459 | biostudies-arrayexpress
Project description:Background: Gastric cancer (GC) remains the third leading cause of cancer death worldwide due to the absence of sensitive and specific biomarkers for its early detection. 5-hydroxymethylcytosine (5hmC)-enriched gene profiles and regions show tissue-specific and tumor specific, and cell-free DNA (cfDNA) 5hmC modification feature sequencing provides a robust tool for gastric cancer detection.Methods: A matched case‒control study design with 50 gastric cancer patients and 50 controls was performed to sequence the 5hmC modification of cfDNA. Significantly differential 5hmC modification genes were identified to construct a gastric cancer diagnostic model. The data set from Gene Expression Omnibus consisted of 61 gastric cancer patients, 90 healthy individuals and 22 benign gastric disease controls was used as an external testing set to test the robustness of the diagnostic model. Results: The vast majority of 5hmC peaks were distributed in the gene body, accounting for more than 90% of the total 5hmC peaks in both the GC and control groups. The diagnostic model was developed based on five different 5hmC modification genes, FBXL7, PDE3A, TPO, SNTG2 and SXBP5. The model could clearly distinguish gastric cancer patients from controls in the training (AUC=0.95, sensitivity=88.6%, specificity=94.3%), validation (AUC=0.87, sensitivity=73.3%, specificity=93.3%) and testing (AUC=0.90, sensitivity=81.9%, specificity=90.2%) sets. The predicted risk scores of the controls were significantly lower than those of GC patients in our own data (P<0.001) or GEO external testing data (P<0.001), but no significant difference was observed between different TNM stage groups (P=0.09 and 0.66). Furthermore, the risk scores of healthy and benign gastric disease controls in the testing set were also not different (P=0.10). Conclusions: The characteristics of 5hmC in cfDNA are specific to GC patients, and the diagnostic model constructed by the 5hmC features of five genes could effectively identify GC patients.
2024-12-30 | GSE246110 | GEO