MiRNAs in ovarian cancer: A systems approach (MAS5, plier, GCRMA)
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE27431 | GEO | 2011/07/29
SECONDARY ACCESSION(S): PRJNA137223
REPOSITORIES: GEO
Similar Datasets
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. Previous studies have shown that miRNAs inhibit the translation and facilitate the degradation of their targeted mRNAs making them attractive candidates for use in cancer therapy. However, the potential clinical utility of miRNAs in cancer therapy rests heavily upon our ability to understand and accurately predict the consequences of fluctuations in levels of miRNAs within the context of complex tumor cells. To evaluate the predictive power of current models, levels of miRNAs and their targeted messenger RNAs (mRNAs) were measured in laser captured micro-dissected (LCM) ovarian cancer epithelial cells (CEPI) and compared with levels present in ovarian surface epithelial cells (OSE). We found that the predicted inverse correlation between changes in levels of miRNAs and levels of their mRNA targets held for only ~6-11% of predicted target mRNAs. Our results underscore the complexities of miRNA-mediated regulation in vivo and caution against the widespread clinical application of miRNAs and miRNA inhibitors until the basis of these complexities is more fully understood. mRNAs were collected from 3 miR-7 treated, 2 miR-128 treated , and 3 negative control miRNA treated HEY ovarian cancer cell samples. The mRNA expression pattern was compared between the miR-7 treated cells and the negative control treated cells, and separately between the miR-128 treated cells and the negative control treated cells using the Affymetrix U133 Plus 2.0 3' expression array.
2011-07-28 | E-GEOD-27431 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci. mRNAs were collected from three laser captured microdissected ovarian cancer epithelial (CEPI) samples. The mRNA expression pattern was compared with five healthy ovarian surface epithelia samples as controls using the Affymetrix U133 Plus 2.0 3' expression array.
2011-07-28 | E-GEOD-23391 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci. miRNAs were collected from three laser captured microdissected ovarian cancer epithelial (CEPI) samples. The miRNA expression pattern was compared with three healthy ovarian surface epithelia samples as controls using a custom-manufactured Affymetrix GeneChip® array.
2011-07-28 | E-GEOD-23383 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci.
2011-07-29 | GSE23391 | GEO
Project description:MicroRNAs (miRNAs) are short (~22 nucleotides) regulatory RNAs that can modulate gene expression and are aberrantly expressed in many diseases including cancer. We report the results of a systems analysis of miRNA regulation in ovarian cancer. We found that 33 miRNAs are up-regulated and 9 down-regulated in CEPI relative to OSE (p<0.01, ≥2 fold change). Of these, 12 were previously annotated miRNAs (Sanger miRBase) of which 9 are up-regulated and 3 are down-regulated in CEPI relative to OSE. Current models predict that changes in levels of miRNAs will be inversely correlated with changes in the levels of targeted mRNAs due to miRNA regulation. This predicted inverse correlation held for only ~9% of predicted target mRNAs. Computational analyses indicate the unexpected low inverse correlation may be at least partially explained by variation in the number of miRNA binding sites within the 3’ UTRs of targeted mRNAs and by miRNA-mediated changes in levels of transcription factors that can exert overriding trans-regulatory controls on target loci.
2011-07-29 | GSE23383 | GEO
Project description:RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of 18 serous ovarian cancer patients (Cepi). For 7 of these patients, a matched set of surrounding cancer stroma (CS) was also collected. For controls, surface ovarian epithelial cells (OSE) were isolated from the normal (non-cancerous) ovaries of 12 individuals including matched sets of samples of OSE and normal stroma (NS) from 8 of these patients. Unsupervised hierarchical clustering of the microarray data resulted in the expected separation between the OSE and Cepi samples. Consistent with models of stromal activation, we also observed significant separation between the NS and CS samples. Unexpectedly, the CS samples sub-divided into two distinct groups. Analysis of expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples are consistent with the hypothesis that the two CS sub-groups differ significantly in their relative propensities to support tumor growth.The results indicate the existence of distinct categories of ovarian cancer stroma and suggest that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development. Gene expression analysis of 8 normal stroma (NS) and 8 matched normal ovarian surface epithelium (OSE) from 12 individuals, along with 7 cancer stroma and 7 matched cancer epithelium from 18 additional ovarian cancer patients
2012-06-13 | E-GEOD-38666 | biostudies-arrayexpress
Project description:RNA microarray profiling of 45 tissue samples was carried out using the Affymetrix (U133) gene expression platform. Laser capture microdissection (LCM) was employed to isolate cancer cells from the tumors of 18 serous ovarian cancer patients (Cepi). For 7 of these patients, a matched set of surrounding cancer stroma (CS) was also collected. For controls, surface ovarian epithelial cells (OSE) were isolated from the normal (non-cancerous) ovaries of 12 individuals including matched sets of samples of OSE and normal stroma (NS) from 8 of these patients. Unsupervised hierarchical clustering of the microarray data resulted in the expected separation between the OSE and Cepi samples. Consistent with models of stromal activation, we also observed significant separation between the NS and CS samples. Unexpectedly, the CS samples sub-divided into two distinct groups. Analysis of expression patterns of genes encoding signaling molecules and compatible receptors in the CS and Cepi samples are consistent with the hypothesis that the two CS sub-groups differ significantly in their relative propensities to support tumor growth.The results indicate the existence of distinct categories of ovarian cancer stroma and suggest that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development.
2012-06-14 | GSE38666 | GEO
Project description:Background: The aim of this study was to identify differentially expressed miRNAs in high-grade serous ovarian carcinoma (HGSC), clear cell ovarian carcinoma (CCC) and ovarian surface epithelium (OSE). Selected miRNAs were evaluated for association with clinical parameters including survival, and miRNA/mRNA interactions were mapped. Results: Differentially expressed miRNAs between HGSC, CCC and OSE were identified, of which 18 were validated (p<0.01) using RT-qPCR in an extended cohort. Compared with OSE, miR-205-5p was the most overexpressed miRNA in HGSC. miR-200 family members and miR-182-5p were the most overexpressed in HGSC and CCC compared with OSE, whereas miR-383 was the most underexpressed. miR-509-3-5p, miR-509-5p, miR-509-3p and miR-510 were among the strongest differentiators between HGSC and CCC, all being significantly overexpressed in CCC compared with HGSC. High miR-200c-3p expression was associated with poor progression-free (p=0.031) and overall (p=0.026) survival in HGSC. Interacting miRNAs and mRNA targets, including those of a TP53-related pathway presented previously, were identified in HGSC. Conclusions: Several miRNAs are overexpressed in HGSC and CCC compared with OSE, including the miR-200 family, among which miR-200c-3p is associated with survival in HGSC. A set of miRNAs differentiates CCC from HGSC, of which miR-509-3-5p and miR-509-5p are the strongest classifiers. Several interactions between miRNAs and mRNAs in HGSC were mapped. Methods: Differences in miRNA expression between HGSC, CCC and OSE scrapings were analyzed by global miRNA expression profiling (Affymetrix GeneChip miRNA 2.0 Arrays, n=30), validated by RT-qPCR (n=63), and evaluated for associations with clinical parameters. For HGSC, differentially expressed miRNAs were linked to differentially expressed mRNAs identified previously (GSE36668).
2014-02-13 | E-GEOD-47841 | biostudies-arrayexpress
Project description:Background: The aim of this study was to identify differentially expressed miRNAs in high-grade serous ovarian carcinoma (HGSC), clear cell ovarian carcinoma (CCC) and ovarian surface epithelium (OSE). Selected miRNAs were evaluated for association with clinical parameters including survival, and miRNA/mRNA interactions were mapped. Results: Differentially expressed miRNAs between HGSC, CCC and OSE were identified, of which 18 were validated (p<0.01) using RT-qPCR in an extended cohort. Compared with OSE, miR-205-5p was the most overexpressed miRNA in HGSC. miR-200 family members and miR-182-5p were the most overexpressed in HGSC and CCC compared with OSE, whereas miR-383 was the most underexpressed. miR-509-3-5p, miR-509-5p, miR-509-3p and miR-510 were among the strongest differentiators between HGSC and CCC, all being significantly overexpressed in CCC compared with HGSC. High miR-200c-3p expression was associated with poor progression-free (p=0.031) and overall (p=0.026) survival in HGSC. Interacting miRNAs and mRNA targets, including those of a TP53-related pathway presented previously, were identified in HGSC. Conclusions: Several miRNAs are overexpressed in HGSC and CCC compared with OSE, including the miR-200 family, among which miR-200c-3p is associated with survival in HGSC. A set of miRNAs differentiates CCC from HGSC, of which miR-509-3-5p and miR-509-5p are the strongest classifiers. Several interactions between miRNAs and mRNAs in HGSC were mapped.
2014-02-13 | GSE47841 | GEO
Project description:In a mouse model of ovarian cancer, we have established that prolonged exposure to 17β-estradiol (E2) accelerates tumour onset and increases the incidence of morphologically dysplastic ovarian surface epithelium (OSE). OSE cell proliferation and morphology are tightly regulated by the asymmetrical distribution of polarity proteins that provide positional cues for surface localization and growth inhibition. We hypothesized that E2 causes OSE dysplasia by inhibiting a tumour suppressor gene called Disabled-2 (Dab2). Dab2 is critical in mediating the polarized distribution of cell surface proteins and is highly expressed in normal OSE, but is absent in the majority of ovarian cancers. In this study, Dab2 is shown to be suppressed by E2 and we investigated the possibility that this occurs through E2 up-regulation of microRNAs. microRNA microarray analysis comparing control vs. E2 treated mouse ovarian cancer cells (MASE) was used to identify candidate miRNAs that have a seeding sequence capable of targeting the 3-prime untranslated region (3’UTR) of both human and mouse Dab2 transcript.
2017-11-30 | GSE98391 | GEO