Gene expression data of ovarian cancer from Singapore
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE69207 | GEO | 2016/01/10
SECONDARY ACCESSION(S): PRJNA284886
REPOSITORIES: GEO
Similar Datasets
Project description:A collection of 100 ovarian cancer sample gene expression data from Singapore. Frozen archival epithelial ovarian cancer tumors samples from Department of Obstetrics & Gynecology, National University of Singapore dated from 2006 to 2014 were collected and subjected to microarray analysis.
2016-01-10 | E-GEOD-69207 | biostudies-arrayexpress
Project description:A collection of ascites and ovarian cancer gene expression data from Singapore.
2019-03-26 | GSE94598 | 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:Gene expression data of ovarian clear cell carcinoma from Singapore
| PRJNA531946 | ENA
Project description:Ovarian clear cell carcinoma (OCCC) is an epithelial ovarian cancer (EOC) histology having distinct pathology, biology, and molecular footprints. OCCC is chemo-resistant and has the worst stage-adjusted prognosis amongst EOC. Yet, treatment for OCCC patients is no different than other EOC. As OCCC incidence rate has significantly increase in recent decades, it is critical to find OCCC-tailored therapeutic. However, majority of EOC gene expression molecular subtypes (GEMS) studies for personalized medicine focused on the high grade serous histology, and studies in OCCC GEMS were of small sample size. Using more than 200 OCCC gene expression profiles, we identified two OCCC subtypes: EpiCC—epithelial-like, early stage, good prognosis, relative higher rate of gene mutations in SWI/SNF complex; and MesCC—mesenchymal-like, late stage, and poor prognosis. The differential prognosis between EpiCC and MesCC could be observed as early as stage IC. Genetic, copy number and transcriptome profiling showed that both EpiCC and MesCC carried OCCC-associated aberrations. The EpiCC and MesCC are reproducible in validation cohorts and OCCC cell lines. Cell lines assays showed that MesCC is more proliferative and more anoikis resistant than EpiCC. Both EpiCC and MesCC are resistant to cisplatin. Applying the OCCC subtypes to TCGA 534 renal clear cell carcinoma indicated interoperability of the subtyping scheme, and revealed preferential response of EpiCC to sorafenib, and MesCC to bevacizumab. The EpiCC and MesCC classification shows promise in prognostication utility especially for stage IC OCCC patients, and warrants further investigation for subtype-tailored treatment regimen.
2020-01-08 | GSE129617 | GEO
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients. Gene expression was measured for 32 ovarian cancer cell lines using the GeneChip Human Exon 1.0 ST Array (Affymetrix). Morphological subtypes were assigned based on cell morphology, size, growth pattern and proliferation rate during culturing of the cell lines.
2014-09-18 | E-GEOD-53418 | biostudies-arrayexpress
Project description:Purpose: Investigate cellular heterogeneity in a fresh human ovarian cancer tissue sample Methods: Enzymatic digestion of fresh tissue sample collected from the operating room to produce single cell suspension. Cells were labelled with fluorescent antibodies to CD3, CD14, CD19, CD20, CD56 and FACS sorted to remove immune cells. The negative population was used for sequencing. Single cells were processed using the Fluidigm C1 Chip to generate barcoded cDNA for each cell. Amplifed cDNA was sequenced using an Illumina HiSeq 2500 machine. Results: Single cell RNA sequence data was obtained for 92 cells and a "bulk" sample of 1000 cells. 26 cells were removed from analysis due to quality control standards. The remaining 66 cells and the bulk sample were analyzed. Conclusion: Single cell RNA sequence analysis reveals heterogeneity in gene expression in cells harvested from a high grade ovarian serous cancer
2018-12-07 | GSE123476 | GEO
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients.
2014-09-18 | GSE53418 | GEO