Homo sapiens
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: E-GEOD-35809E-GEOD-34942E-GEOD-51704E-GEOD-51706E-GEOD-51704
PROVIDER: PRJNA152559 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Gastric cancer subtyping (Singapore Patient Cohort, batch B)
| PRJNA150983 | ENA
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 | ArrayExpress
Project description:Gastric Cancer Project '08 (Singapore Patient Cohort)
| PRJNA122965 | ENA
Project description:Primary Gastric Cancer Expression Profiles (UK Patient Cohort)
| PRJNA122979 | ENA
Project description:Genome wide mRNA expression profiling of 94 gastric tumours derived from Australian based cohort was performed. . From this data we identified a cluster of co-expressed genes termed the stromal response cluster which almost perfectly differentiates tumor from its non-malignant gastric tissue and hence can be regarded as a highly tumor-specific gene expression signature. We show that these genes are consistently co-expressed across a range of independent gastric datasets as well as other cancer types suggesting a conserved functional role in cancer. Profiling of 94 primary gastric tumors on Affymetrix GeneChip Human Genome U133 Plus 2.0 Arrays. All tumors were collected with approvals from Peter MacCallum Cancer Center, Australia; the Research Ethics Review Committee; and signed informed patient consent.
2014-04-01 | E-GEOD-51105 | ArrayExpress
Project description:Gastric cancers comprise molecularly heterogeneous diseases; four molecular subtypes were identified in the cancer genome atlas (TCGA) study, with implications in patient management. In our efforts to devise a clinically feasible means of subtyping, we devised an algorithm based on histology and five stains available in most academic pathology laboratories. This algorithm was used to subtype our cohort of 107 gastric cancer patients from a single institution (St. Michael's Hospital, Toronto, Canada), which was divided into 3 cases of EBV-positive, 23 of MSI, 27 of GS and 54 of CIN tumours. 87% of the tumours with diffuse histology were classified as GS subtype, which was notable for younger age. Examining for characteristic molecular features, aberrant p53 immunostaining was seen most frequently in the CIN subtype (43% in CIN vs. 6% in others), whereas ARID1A loss was rarely seen (6% vs. 35% in others). HER2 overexpression was seen exclusively in CIN tumours (17% of CIN tumours). PD-L1 positivity was seen predominantly in the EBV and MSI tumours. As with the TCGA study, no survival differences were seen between the subtypes. A similar strategy was employed to approximate the Asian Cancer Research Group (ACRG) molecular subtyping, with the addition of p53 IHC to the algorithm. We observed rates of ARID1A loss and HER2 overexpression that were comparable to the ACRG study. In summary, our algorithm allowed for clinically feasible means of subtyping gastric carcinoma that recapitulated the key molecular features reported in the large scale studies.
2019-01-01 | S-EPMC6886787 | BioStudies
Project description:The continuous characterization of genome-wide diversity in population and case-cohort samples, allied to the development of new algorithms, are shedding light on host ancestry impact and selection events on various infectious diseases. Especially interesting are the long-standing associations between humans and certain bacteria, such as the case of <i>Helicobacter pylori</i>, which could have been strong drivers of adaptation leading to coevolution. Some evidence on admixed gastric cancer cohorts have been suggested as supporting <i>Homo</i>-<i>Helicobacter</i> coevolution, but reliable experimental data that control both the bacterium and the host ancestries are lacking. Here, we conducted the first in vitro coinfection assays with dual human- and bacterium-matched and -mismatched ancestries, in African and European backgrounds, to evaluate the genome wide gene expression host response to <i>H. pylori</i>. Our results showed that: (1) the host response to <i>H. pylori</i> infection was greatly shaped by the human ancestry, with variability on innate immune system and metabolism; (2) African human ancestry showed signs of coevolution with <i>H. pylori</i> while European ancestry appeared to be maladapted; and (3) mismatched ancestry did not seem to be an important differentiator of gene expression at the initial stages of infection as assayed here.
2021-01-01 | S-EPMC7912213 | BioStudies
Project description:Objectives:A better understanding of antitumor immunity will help predict the prognosis of gastric cancer patients and tailor the appropriate therapies in each patient. Therefore, we propose a novel immunological classification of gastric cancer. Methods:We performed whole-exome sequencing (WES), RNA-Seq and flow cytometry in 29 gastric cancer patients who received surgery. The TCGA data set of 323 gastric cancer patients and RNA-Seq data of 45 patients who received pembrolizumab (Kim et al. Nat Med 2018; 24: 1449-1458) were also analysed. Results:Immunogram analysis of cancer-immunity interaction of gastric cancer revealed immune signatures of four main types, designated Hot1, Hot2, Intermediate and Cold. Immunologically hot tumors displayed a dysfunctional T-cell signature, while cold tumors had an exclusion signature. Ex vivo tumor-infiltrating lymphocyte analysis documented T-cell dysfunction with the expression of checkpoint molecules and impaired cytokine production. The T-cell function was more profoundly damaged in Hot1 than Hot2 tumors. Patients in Hot2 subtypes had better survival in our cohort and TCGA cohort. Although these immunological subtypes overlapped to some degree with the molecular subtypes in the TCGA, intratumoral immune responses cannot be predicted solely based on histological or molecular subtyping of gastric cancer. Molecular and immunological classifications complement each other to predict the responses to anti-PD-1 therapy and have the potential to be a biomarker for the treatment of gastric cancer. Conclusion:The immunological classification of gastric cancer resulted in four subtypes. Hot tumors were further divided into two subtypes, between which the functional status of T cells was different.
2020-01-01 | S-EPMC7568758 | BioStudies
Project description:This SuperSeries is composed of the following subset Series:; GSE15455: GEMINI (Gastric Encyclopedia of Molecular Interactions and Nodes for Intervention) Phases A-C; GSE15456: Primary Gastric Cancer Expression Profiles (UK Patient Cohort); GSE15459: Gastric Cancer Project '08 (Singapore Patient Cohort); GSE15537: GEMINI (Gastric Encyclopedia of Molecular Interactions and Nodes for Intervention) Phases A-C, normal skin fibroblasts Experiment Overall Design: Refer to individual Series
2009-04-10 | E-GEOD-15460 | ArrayExpress
Project description:We investigated the evidence of recent positive selection in the human phototransduction system at single nucleotide polymorphism (SNP) and gene level.SNP genotyping data from the International HapMap Project for European, Eastern Asian, and African populations was used to discover differences in haplotype length and allele frequency between these populations. Numeric selection metrics were computed for each SNP and aggregated into gene-level metrics to measure evidence of recent positive selection. The level of recent positive selection in phototransduction genes was evaluated and compared to a set of genes shown previously to be under recent selection, and a set of highly conserved genes as positive and negative controls, respectively.Six of 20 phototransduction genes evaluated had gene-level selection metrics above the 90th percentile: RGS9, GNB1, RHO, PDE6G, GNAT1, and SLC24A1. The selection signal across these genes was found to be of similar magnitude to the positive control genes and much greater than the negative control genes.There is evidence for selective pressure in the genes involved in retinal phototransduction, and traces of this selective pressure can be demonstrated using SNP-level and gene-level metrics of allelic variation. We hypothesize that the selective pressure on these genes was related to their role in low light vision and retinal adaptation to ambient light changes. Uncovering the underlying genetics of evolutionary adaptations in phototransduction not only allows greater understanding of vision and visual diseases, but also the development of patient-specific diagnostic and intervention strategies.
2013-01-01 | S-EPMC3743458 | BioStudies