OCaMIR a non-invasive early diagnostic test for ovarian cancer: A multi-cohort retrospective and prospective analysis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE127873 | GEO | 2020/03/06
REPOSITORIES: GEO
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Project description:<p>Ovarian cancer (OC) causes high mortality in women because of ineffective biomarkers for early diagnosis. Here, we perform metabolomics analysis on an initial training set of uterine fluid from 96 gynecological patients. A seven-metabolite-marker panel consisting of vanillylmandelic acid, norepinephrine, phenylalanine, beta-alanine, tyrosine, 12-S-hydroxy-5,8,10-heptadecatrienoic acid and crithmumdiol is established for detecting early-stage OC. The panel is further validated in an independent sample set from 123 patients, discriminating early OC from controls with an area under the curve (AUC) of 0.957 (95% confidence interval [CI], 0.894-1.000). Interestingly, we find elevated norepinephrine and decreased vanillylmandelic acid in most OC cells, resulting from excess 4-hydroxyestradiol that antagonizes the catabolism of norepinephrine by catechol-O-methyltransferase. Moreover, exposure to 4-hydroxyestradiol induces cellular DNA damage and genomic instability that could lead to tumorigenesis. Thus, this study not only reveals metabolic features in uterine fluid of gynecological patients but also establishes a noninvasive approach for the early diagnosis of OC. </p>
2023-03-06 | MTBLS4861 | MetaboLights
Project description:Ovarian cancer is a deadly gynecological malignancy for which novel biomarkers and therapeutic targets are imperative for improving survival. To investigate the role of histone H1 in ovarian cancer cells, we overexpress a histone H1 variant, H1.3, in the OVCAR-3 epithelial ovarian cancer cell line. RNA was extracted from OV-3/H1.3(H) cells (OVCAR-3 with overexpression of H1.3) and control cells of OVCAR-3 transfected with vectors without H1.3. The microarray chip used was human Affymetrix ST1.0 array. Gene expression changes caused by overexpression of H1.3 in OVCAR-3 cells were identified. Affymetrix Human Exon 1.0 ST array was used to identify the changes in transcriptome of OVCAR-3 caused by overexpression of H1.3
2014-10-31 | E-GEOD-61692 | biostudies-arrayexpress
Project description:Ovarian cancer is a deadly gynecological malignancy for which novel biomarkers and therapeutic targets are imperative for improving survival. To investigate the role of histone H1 in ovarian cancer cells, we overexpress a histone H1 variant, H1.3, in the OVCAR-3 epithelial ovarian cancer cell line. RNA was extracted from OV-3/H1.3(H) cells (OVCAR-3 with overexpression of H1.3) and control cells of OVCAR-3 transfected with vectors without H1.3. The microarray chip used was human Affymetrix ST1.0 array. Gene expression changes caused by overexpression of H1.3 in OVCAR-3 cells were identified.
2014-10-31 | GSE61692 | GEO
Project description:Ovarian cancer (OC) is the most lethal gynecological carcinoma because of the lack of early diagnostic markers and effective drug targets. Discovery of new therapeutic targets in OC to improve the treatment outcome is urgently needed. Patients with recurrent EOC after initial therapy have few treatment options that greatly compromises their quality of life and life expectancy. Discovery of new therapeutic targets in EOC to improve the treatment outcome is urgently needed. Proteomic analysis is one of the approaches to identify therapeutic targets in OC.
2019-09-09 | PXD013811 | Pride
Project description:Ovarian cancer is the leading cause of death in gynecological diseases, and has been considered as one of the most fatal cancers due to lack of reliable detection strategy in the early stage. Therefore the capability to detect the morbidity initiation with an sensitive and effective approach is one of the most desirable goals for curing ovarian cancer. In this study, we used microarray technology for salivary mRNA biomarkers discovery, and evaluated the performance and translational utilities of discovered markers from a clinical study using an independent sample cohort . We used microarrays to profile and compare the gene expressions between ovairan cancer patient and matched controls, and identified seven down-regulated genes after the validation study. To find salivary transcriptomic biomarkers for ovarian cancer, salivary transcriptomes in 11 ovarian cancer patients and 11 matched controls were profiled using Affymetrix HG-U133-Plus-2.0 array, and followed by t-test and fold-change analyses. The biomarker candidates selected from the microarray results were subjected to clinical validation using an independent sample cohort by RT-qPCR. The prediction power of biomarkers was analyzed by logistic regression approach
2011-05-12 | E-GEOD-29220 | biostudies-arrayexpress
Project description:Ovarian cancer (OC) is still the most fatal gynecological cancer due to late diagnosis when peritoneal metastasis has already occurred. OC progression requires lipid nutrients that are either synthesized endogenously in the cancer cells or imported from the surrounding host tissue. Accordingly, blockade of lipid synthesis has been shown to be a powerful strategy against OC. However, direct evidence of the role of lipid import and transport for OC growth is still largely missing. Therefore, we exposed OC cells to inhibitors of lipid uptake and transport proteins, which are typically overexpressed in OC. Our data reveal that pharmacological inhibition of these lipid handling proteins caused drug-specific, dose- and time-dependent decline of lipid-uptake, which was associated with cell growth reduction, cell cycle arrest and apoptosis indicating that OC cells are exquisitely sensitive to lipid deficiency. This dependency provides the rationale for the development of novel lipid-antimetabolic strategies against OC.
2022-12-05 | GSE212702 | GEO
Project description:The identification of prognostic biomarkers is a priority for patients suffering from high-grade serous ovarian cancer (SOC), which accounts for >70% of ovarian cancer (OC) deaths. Meanwhile borderline ovarian cancer (BOC) is a low malignancy tumor and usually patients undergo surgery with low probabilities of recurrence. However, SOC remains the most lethal neoplasm due to the lack of biomarkers for early diagnosis and prognosis. In this regard BORIS (CTCFL), a CTCF paralog, is a promising cancer biomarker that is overexpressed and controls transcription in several cancer types, mainly in OC. Studies suggest that BORIS has an important function in OC by altering gene expression, but the effect and extent to which BORIS influences transcription in OC from a genome-wide perspective is unclear. Here we sought to identify BORIS target genes in an OC cell line (OVCAR3) with potential biomarker use in OC tumor samples. To achieve this, we performed in vitro knockout (KO) and knockdown (KD) experiments of BORIS in OVCAR3 cell line followed by expression microarrays and bioinformatics network enrichment analysis to identify relevant BORIS target genes.
2019-07-31 | GSE130163 | GEO
Project description:OCaMIR a non-invasive early diagnostic test for ovarian cancer: A multi-cohort retrospective and prospective analysis
| PRJNA525672 | ENA
Project description:Ovarian cancer (OC) is the one of the most common gynecological tumors with high morbidity and mortality. Alterations in serum N-glycosylation have been observed in many diseases, and specific N-glycans of serum could be used for disease diagnosis or prognosis. However, the association between serum N-glycome profiles and OC progression remains unclear. Herein, high-throughput mass spectrometry was applied to characterize serum N-glycome profile in individuals with healthy controls, benign neoplasm and different stages of OC patients. It was observed that high-mannosylation, neutral bisection and agalactosylation of serum glycoproteins were uniformly increased in the initiation and development of OC, but sialylation was substantially changed on an opposite trend. Additionally, agalactosylation, high-mannosylation and sialylation gained at least moderately accurate merit for diagnosis of both OC and benign neoplasm. Notably, serum N-glycome profile could accurately discriminate OC patients from benign cohorts, with a comparable or even higher diagnostic score compared with CA125 and HE4. Furthermore, bioinformatics verified the differential expression of glycogens in OC progression. Significantly, strong correlations were found between CA 125 and high-mannosylation, galactosylation and sialylation. These findings demonstrated the great potential of serum N-glycome for OC diagnosis and precancerous lesion prediction, paving a new way for OC screening and monitoring.
2023-11-24 | PXD040959 | Pride
Project description:High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer (OC), and lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there is no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem-mass spectrometry on depleted serum samples from 26 HGSOC cases and 24 healthy controls (HCs) to discover potential HGSOC diagnostic biomarkers. A total of 1,847 proteins were identified across all samples, among which 116 proteins showed differential expressions between HGSOC patients and HCs. Network modeling showed activations of coagulation and complement cascades, platelet activation and aggregation, NET formation, TLR4, IGF, and TGF-β signaling, and suppression of lipoprotein assembly and FcγR activation in HGSOC. Based on the network model, we prioritized 28 biomarker candidates, and validated 18 of them using targeted MS assays in an independent cohort. Predictive modeling showed a sensitivity of 1 and specificity of 0.91 in the validation cohort. Finally, in vitro functional assays on four potential biomarkers (FGA, VWF, ARHGDIB, and SERPINF2) suggested that they may play an important role in cancer cell proliferation and migration in HGSOC.
2022-08-11 | PXD033169 | Pride