Repertoire of miRNAs in epithelial ovarian cancer determined by next generation sequencing of small RNA cDNA libraries
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE15190 | GEO | 2009/03/12
SECONDARY ACCESSION(S): PRJNA116407
REPOSITORIES: GEO
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Project description:Background: MicroRNAs (miRNAs) are small regulatory RNAs that are implicated in cancer pathogenesis and have recently shown promise as blood-based biomarkers for cancer detection. Epithelial ovarian cancer is a deadly disease for which improved outcomes could be achieved by successful early detection and enhanced understanding of molecular pathogenesis that leads to improved therapies. A critical step toward these goals is to establish a comprehensive view of miRNAs expressed in epithelial ovarian cancer tissues as well as in normal ovarian surface epithelial cells. Methodology: We used massively parallel pyrosequencing (i.e., M-bM-^@M-^\454 sequencingM-bM-^@M-^]) to discover and characterize novel and known miRNAs expressed in primary cultures of normal human ovarian surface epithelium (HOSE) and in tissue from three of the most common histotypes of ovarian cancer. Deep sequencing of small RNA cDNA libraries derived from normal HOSE and ovarian cancer samples yielded a total of 738,710 high-quality sequence reads, generating comprehensive digital profiles of miRNA expression. Expression profiles for 498 previously annotated miRNAs were delineated and we discovered six novel miRNAs and 39 candidate miRNAs. A set of 124 miRNAs was differentially expressed in normal versus cancer samples and 38 miRNAs were differentially expressed across histologic subtypes of ovarian cancer. Taqman qRT-PCR performed on a subset of miRNAs confirmed results of the sequencing-based study.
2009-03-12 | E-GEOD-15190 | biostudies-arrayexpress
Project description:The paper describes a model on the detection of cancer based on cancer and immune biomarkers.
Created by COPASI 4.25 (Build 207)
This model is described in the article:
Improving cancer detection through combinations of cancer and immune biomarkers: a modelling approach
Raluca Eftimie and and Esraa Hassanein
J Transl Med (2018) 16:73
Abstract:
Background: Early cancer diagnosis is one of the most important challenges of cancer research, since in many can- cers it can lead to cure for patients with early stage diseases. For epithelial ovarian cancer (which is the leading cause of death among gynaecologic malignancies) the classical detection approach is based on measurements of CA-125 biomarker. However, the poor sensitivity and specificity of this biomarker impacts the detection of early-stage cancers.
Methods: Here we use a computational approach to investigate the effect of combining multiple biomarkers for ovarian cancer (e.g., CA-125 and IL-7), to improve early cancer detection.
Results: We show that this combined biomarkers approach could lead indeed to earlier cancer detection. However, the immune response (which influences the level of secreted IL-7 biomarker) plays an important role in improving and/or delaying cancer detection. Moreover, the detection level of IL-7 immune biomarker could be in a range that would not allow to distinguish between a healthy state and a cancerous state. In this case, the construction of solu- tion diagrams in the space generated by the IL-7 and CA-125 biomarkers could allow us predict the long-term evolu- tion of cancer biomarkers, thus allowing us to make predictions on cancer detection times.
Conclusions: Combining cancer and immune biomarkers could improve cancer detection times, and any predic- tions that could be made (at least through the use of CA-125/IL-7 biomarkers) are patient specific.
Keywords: Ovarian cancer, Mathematical model, CA-125 biomarker, IL-7 biomarker, Cancer detection times
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2019-07-09 | BIOMD0000000741 | BioModels
Project description:Most (70%) epithelial ovarian cancers (EOCs) are diagnosed late. Non-invasive biomarkers that facilitate disease detection and predict outcome are needed. The microRNAs (miRNAs) represent a new class of biomarkers. This study was to identify and validate plasma miRNAs as biomarkers in EOC. We evaluated plasma samples of 360 EOC patients and 200 healthy controls from two institutions. All samples were grouped into screening, training and validation sets. We scanned the circulating plasma miRNAs by TaqMan low-density array in the screening set and identified/validated miRNA markers by real-time polymerase chain reaction assay in the training set. Receiver operating characteristic and logistic regression analyses established the diagnostic miRNA panel, which were confirmed in the validationsets. We found higher plasma miR-205 and lower let-7f expression in cases than in controls. MiR-205 and let-7f together provided high diagnostic accuracy for EOC, especially in patients with stage I disease. The combination of these two miRNAs and carbohydrate antigen-125 (CA-125) further improved the accuracy of detection. MiR-483-5p expression was elevated in stages III and IV compared with in stages I and II, which was consistent with its expression pattern in tumor tissues. Furthermore, lower levels of let-7f were predictive of poor prognosis in EOC patients. Our findings indicate that plasma miR-205 and let-7f are biomarkers for ovarian cancer detection that complement CA-125; let-7f may be predictive of ovarian cancer prognosis.
2013-08-30 | GSE50472 | GEO
Project description:Despite a considerable literature concerning the molecular pathogenesis of pituitary tumors, the mechanisms of pituitary tumors development and progression remain unknown. Four SAGE cDNA libraries were constructed using a pool of mRNA obtained from five GH-, two ACTH-secreting, and four non secreting pituitary tumors (NS), and three normal pituitaries from patients who had accidental death, using I-SAGE kit (Invitrogen). The aim of this study was to evaluate the differential gene expression profile by SAGE genes in different subtypes of pituitary tumors to contribute for understanding of pituitary tumorigenesis.
2014-04-10 | GSE37153 | GEO
Project description:Ovarian cancer is a nearly uniform lethal disease and its highly aggressive metastatic phenotype portends a poor prognosis. Lack of a well-controlled, relevant experimental model has been a major obstacle to identifying key molecules causing metastasis. Here we describe the creation of a new isogenic model of spontaneous human ovarian cancer metastasis exhibiting opposite phenotypes - highly metastatic (HM) and non-metastatic (NM) - both in vitro and in vivo. HM was unique in its ability to metastasize consistently to the peritoneum, mimicking the major dissemination route of human ovarian cancer. In contrast, NM failed to form detectable metastases although it was equally tumorigenic. Using comparative label-free quantitative LC-MS/MS, we identified b-catenin which we demonstrated for the first time a direct role in the pathogenesis of ovarian cancer metastasis. Our studies also revealed a previously unrecognized role of b-catenin in the downregulation of multiple microRNAs (miRNAs) through attenuating miRNA biogenesis by targeting Dicer, a key component of the microRNA processing machinery. One such downregulated miRNAs was miR-29s involved in epithelial-to-mesenchymal transition and subsequent stem cell traits. Silencing b-catenin or overexpressing Dicer or miR-29 mimics in HM significantly reduced the ability of these cells to migrate. B-catenin knockdown cells also failed to metastasize in an orthotopic model of ovarian cancer. Meta-analysis revealed an increase in CTNNB1 and a decrease in DICER1 expression levels in the high-risk group. These results uncover b-catenin as a critical player in promoting ovarian cancer aggressiveness and a new mechanism linking between b-catenin and miRNA downregulation underlying this process.
2017-07-03 | PXD006327 | Pride
Project description:Despite a considerable literature concerning the molecular pathogenesis of pituitary tumors, the mechanisms of pituitary tumors development and progression remain unknown. Four SAGE cDNA libraries were constructed using a pool of mRNA obtained from five GH-, two ACTH-secreting, and four non secreting pituitary tumors (NS), and three normal pituitaries from patients who had accidental death, using I-SAGE kit (Invitrogen). The aim of this study was to evaluate the differential gene expression profile by SAGE genes in different subtypes of pituitary tumors to contribute for understanding of pituitary tumorigenesis. Comparative analysis of gene expression profiles in subtypes of pituitary tumores.
2014-04-10 | E-GEOD-37153 | biostudies-arrayexpress
Project description:Ovarian cancer is the most lethal malignancy in the United States. In the year 2012, there will be an estimated 22,280 new cases and 15,500 deaths from ovarian cancer in the country (Siegel et al., 2012). While studies on ovarian cancer pathogenesis were mainly focused on the epithelial component of the tumor, understanding in the role of cancer associated fibroblasts (CAFs) in ovarian cancer progression is limited. We hypothesized that comparing the gene expression profiles of different components from laser capture microdissected ovarian tissue will allow us to identify an ovarian CAFs specific gene signature which accounts for the supportive role of CAFs in ovarian cancer progression. In this study, gene expression profiling was completed for 31 cancer stroma samples and 32 samples of epithelial component from high grade serous ovarian cancer patients. 8 microdissected normal ovarian stroma and 6 normal human ovarian surface epithelium (HOSE) samples were also included in the study. By comparing the expression data from cancer stroma against that from normal stroma, cancer cells and HOSE, we identified a set of differential expressed genes in ovarian CAFs which showed correlation with cancer patient survival. Further study on these genes can reveal their roles in ovarian cancer progression and pathogenesis. Ultimately, ovarian CAFs specified genes identified in this study may aid in the classification and enhancement of patient outcome. Transcriptome profiling analyses were performed on 31 laser microdissected cancer associated stroma samples, 32 epithelial tumor samples from high grade serous ovarian cancer patients, 8 microdissected normal ovarian stroma samples and 6 ovarian surface epthelium (HOSE) samples using the Affymetrix human genome U133 Plus 2.0 microarray.
2014-09-11 | E-GEOD-40595 | biostudies-arrayexpress
Project description:The Urine RNA from 5 ovarian cancer and 5 healthy control were analyzed with the Human miRNA Microarray and then validated with a quantitative reverse-transcription PCR assay with 29 individual samples, 20 benign gynecological disease and 26 age/sex-matched healthy control. This study determines the clinical value of urine miRNAs as biomarker for epithelial ovarian cancer. Results: The miRNA microarray results demonstrate that the original 38 were identified that were significantly differentially expression in epithelial ovarian cancer compared with healthy control (P<0.01). A total of 1 miRNA was up-regulated in ovarian cancer, while 37 miRNA were down-regulated. the urine RNA from 5 ovarian cancer and 5 healthy women were analysised with Human mirRNA microarry
2015-06-17 | E-GEOD-58517 | biostudies-arrayexpress
Project description:Owing to the lack of effective screening tools and early detection biomarkers, ovarian cancer (OC) still remains as a deadly disease with highest mortality among other gynecological cancers. So far there have been no attempts to discover biomarkers using early stage OC patients. MicroRNAs (miRNAs) have been recognized as great tool to develop non-invasive biomarkers in various cancers including ovarian cancer.
2020-03-06 | GSE127873 | GEO
Project description: Not available
| S-EPMC2668797 | biostudies-literature