Serum microRNA analysis of primary ovarian cancer patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE79943 | GEO | 2017/03/19
SECONDARY ACCESSION(S): PRJNA317470
REPOSITORIES: GEO
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Project description:Background: This study aimed to screen the signaling axis of epigenetic modification in serum exosomes of ovarian cancer patients based on sequencing technology and raw signal analysis, perform an in-depth study of the potential mechanism of action of ovarian cancer, predict potential therapeutic targets and perform a survival prognosis analysis of potential targets Methods: Serum exosomes from three ovarian cancer patients were selected as the experimental group, and serum exosomes from three uterine fibroid patients were selected as the control group. The whole transcriptomes of serum exosomes were used to obtain differentially expressed lncRNAs and mRNAs in ovarian cancer. The miRcode database and miRNA target gene prediction website were used to predict the target genes. Cytoscape software was used to draw a ceRNA network model of epigenetic modification of ovarian cancer serum exosomes, and R language was used for GO and KEGG enrichment analyses of the target genes. Finally, the TCGA website was used to download clinical and expression data related to ovarian cancer, and the common potential target genes obtained in the previous period were analyzed for survival. Results: A total of 117 differentially expressed lncRNAs and 513 differentially expressed mRNAs (P < 0.05, |log2 FC|≥ 1.0) were obtained by combining sequencing data and raw signal analysis, and 841 predicted target genes were reciprocally mapped by combining the miRcode database and the miRNA target gene prediction website, resulting in 11 potential target genes related to ovarian cancer (FGFR3, BMPR1B, TRIM29, FBN2, PAPPA, CCDC58, IGSF3, FBXO10, GPAM, HOXA10, LHFPL4). Survival prognosis analysis of the above 11 target genes revealed that the survival curve was statistically significant (P < 0.05) for HOXA10-only genes but not for the other genes. Through enrichment analysis, we found that the above target genes were mainly involved in biological processes such as regulation of transmembrane receptor protein kinase activity, structural molecule activity with elasticity, transforming growth factor-activated receptor activity, and GABA receptor binding, and were mainly enriched in metabolism pathways regulating stem cell pluripotency, bladder cancer, glycerolipid metabolism, central carbon metabolism of cancer, and resistance to EGFR tyrosine kinase inhibitors. Conclusions: The serum exosomal DIO3OS-hsa-miR-27a-3p-HOXA10 epigenetic modification signaling axis affects ovarian cancer development and disease survival prognosis by targeting transcriptional dysregulation pathways in cancer.
2022-06-20 | GSE194238 | GEO
Project description:Serum samples were obtained from patients with ovarian cancer (OC; n=64) and noncancerous control (n=4) for microarray. We found that four miRNAs were significantly high-expression level in OC relative to the controls.
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Project description:Serum starvation induces quiescence in ovarian cancer
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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.
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Project description:Global microRNA expression profiling of serum were collected using Agilent miRNA microarrays (G4471A Human, Amadid 29297, Sanger 14) carrying 887 individual human miRNA probes. Two different sources of RNA were analyzed: serum from healthy controls (N=5) and patients with ovarian carcinoma (CA, n=5)
2014-02-05 | GSE48485 | GEO
Project description:Global microRNA expression profiling of serum were collected using Agilent miRNA microarrays (G4471A Human, Amadid 29297, Sanger 14) carrying 887 individual human miRNA probes. Two different sources of RNA were analyzed: serum from healthy controls (N=5) and patients with ovarian carcinoma (CA, n=5) Two conditions (CA, N), each condition is represented by 5 biological replicates
2014-02-05 | E-GEOD-48485 | biostudies-arrayexpress
Project description:We aimed to discover and validate a panel of serum biomarkers for high grade serous ovarian cancer (HGSOC) using our lectin-magnetic bead array-coupled proteomics platform. Serum from age-matched women with HGSOC, benign tumours or healthy controls were analysed in discovery (UKCTOCS, n=30 and UKOPS, n=30) and validation (Australian Ovarian Cancer Study, n=95) cohorts using shotgun and targeted proteomics, respectively. A 7-lectin discovery screen shortlisted 60 candidate proteins and 3 lectins for validation, which revealed elevated levels of AAL, SNA or STL-binding FIBB, CO9, ITIH3, HPT, A1AT, AACT in HGSOC, while IBP3, A2MG, PON1, CHLE and ALS were reduced. Multimarker panels were developed using generalized regression with lasso estimation and leave-one-out cross-validation. The best performing panel comprised of 13 peptides from Solanum Tuberosum lectin (STL)-binding proteins with 96.3% area under the receiver operating curve, 97.7% specificity and 78.6% sensitivity for distinguishing HGSOC from benign and healthy groups. The peptides robust in cross-validations were from IBP3, KNG1, CO9, THRB, HPTR, HPT, FINC, FA10, GELS. The validated serum biomarkers show promise for early detection of HGSOC and should be further evaluated.
2023-10-24 | PXD032299 | Pride
Project description:Diagnosis of ovarian cancer at an early stage is the most important determinant of survival. Thus, there is a clear need for novel biomarkers to improve diagnostic and prognostics that may better inform on therapeutic strategies. We have conducted a discovery study using label-free quantitative mass spectrometry (LFQ) to identify potential biomarker candidates in urine from individual ovarian cancer patients. LFQ analyses identified 4394 proteins (16397 peptides) in urine samples (n=20), 23 of which were significantly elevated in the malignant patient group compared to patients with benign disease. To validate these changes, we used Parallel Reaction Monitoring (PRM) to investigate their abundance in an independent cohort (n=20) of patient urine samples. Seven of the ten proteins were significantly enriched in the ovarian cancer patient samples; amongst these were established ovarian cancer markers WFDC2 (HE4) and Mesothelin (MSLN), validating our approach. This is the first application of a LFQ-PRM workflow to identify and validate ovarian cancer-specific biomarkers in urine samples.
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Project description:A serum miRNA combination could be a powerful classifier for the detEsophageal Cancertion of patients with ovarian cancer.
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