Expression of miRNAs in ovarian cancer recurrence
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ABSTRACT:
PROVIDER: PRJNA558993 | ENA |
REPOSITORIES: ENA
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Project description:Recurrence is the major cause of treatment failure in patients with ovarian cancer. The purpose of this study is to identify novel miRNAs contributing to ovarian cancer recurrence.
2019-08-15 | GSE135469 | GEO
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Project description:This SuperSeries is composed of the following subset Series: GSE23383: miRNAs in ovarian cancer: A systems approach (miRNA data) GSE23391: miRNAs in ovarian cancer: A systems approach (mRNA data) GSE27431: miRNAs in ovarian cancer: A systems approach (MAS5, plier, GCRMA) Refer to individual Series
2011-07-28 | E-GEOD-23392 | biostudies-arrayexpress
Project description:Cancer stem cells can self-renew, proliferate into differentiated cells, or enter a quiescent state and are regarded to cause chemoresistance and recurrence. Fresh tumor cells from three ovarian cancer patients were cultured to isolated spheroid-forming cells (SFC; cancer stem-like cells). The miRNAs that exhibited significant differential expression between SFCs and adherent cells were identified using miRNAs microarrays.
2019-09-06 | GSE136925 | GEO
Project description:Cancer stem cells can self-renew, proliferate into differentiated cells, or enter a quiescent state and are regarded to cause chemoresistance and recurrence. Fresh tumor cells from three ovarian cancer patients were cultured to isolated spheroid-forming cells (SFC; cancer stem-like cells). The miRNAs that exhibited significant differential expression between SFCs and adherent cells were identified using miRNAs microarrays.
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Project description:Analysis of extracellular vesicles (Evs) miRNAs in ovarian cancer
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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. 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. 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