Analysis of miRNA profiles in mucinous ovarian cancer cells that silenced PRKRA.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE119845 | GEO | 2019/01/01
REPOSITORIES: GEO
Similar Datasets
Project description:Analysis of miRNA profiles in mucinous ovarian cancer cells that silenced PRKRA.
| PRJNA490447 | ENA
Project description:Gene expression profile of 8 mucinous borderline ovarian tumors and 9 mucinous ovarian carcinomas. Frozen tumor samples were laser-capture microdissected for their epithelial component. RNA was extracted. Gene expression profiling was completed using Affymetrix U133 Plus 2.0 oligonucleotide microarrays.
2018-06-28 | E-MTAB-6844 | biostudies-arrayexpress
Project description:Introduction: Mucinous tumors are the second most common form of epithelial ovarian tumor, yet the cell of origin for this histological sub-type remains undetermined. While these tumors are thought to arise through a stepwise progression from benign cystadenoma to borderline tumor to invasive carcinoma, few studies have attempted to comprehensively characterize the genetic changes specific to this subtype or its precursors. Methods: To explore the spectrum of genomic alterations common to mucinous tumors we performed high resolution genome-wide copy number analysis, mutation screening by Sanger sequencing and immunohistochemistry on a series of primary ovarian mucinous cystadenomas (n=20) and borderline tumors (n=22). Results: Integration of copy number data, targeted mutation screening of RAS/RAF pathway members and immunohistochemistry reveals that p16 loss and RAS/RAF pathway alterations are highly recurrent events that occur early during mucinous tumor development. The frequency of concurrence of these events was observed in 40% of benign cystadenomas and 68% of borderline tumors. Conclusions: This study is the largest and highest resolution analysis of mucinous benign and borderline tumors performed to date and provides strong support for these lesions being precursors of primary ovarian mucinous adenocarcinoma. The high level of uniformity in the molecular events underlying the pathogenesis of mucinous ovarian tumors provides an opportunity for treatments targeting specific mutations and pathways. Copy number data was generated for 42 mucinous ovarian tumours (20 benign, 22 borderline). Epithelial and stromal DNA from the tumours and matched-normal lymphocyte DNA were all analysed. Processed/normalized data for the germline DNA samples are not provided because they themselves are normalised to a diploid copy number, making all the probe values 2, which is not informative.
2012-08-26 | E-GEOD-39076 | biostudies-arrayexpress
Project description:Introduction: Mucinous tumors are the second most common form of epithelial ovarian tumor, yet the cell of origin for this histological sub-type remains undetermined. While these tumors are thought to arise through a stepwise progression from benign cystadenoma to borderline tumor to invasive carcinoma, few studies have attempted to comprehensively characterize the genetic changes specific to this subtype or its precursors. Methods: To explore the spectrum of genomic alterations common to mucinous tumors we performed high resolution genome-wide copy number analysis, mutation screening by Sanger sequencing and immunohistochemistry on a series of primary ovarian mucinous cystadenomas (n=20) and borderline tumors (n=22). Results: Integration of copy number data, targeted mutation screening of RAS/RAF pathway members and immunohistochemistry reveals that p16 loss and RAS/RAF pathway alterations are highly recurrent events that occur early during mucinous tumor development. The frequency of concurrence of these events was observed in 40% of benign cystadenomas and 68% of borderline tumors. Conclusions: This study is the largest and highest resolution analysis of mucinous benign and borderline tumors performed to date and provides strong support for these lesions being precursors of primary ovarian mucinous adenocarcinoma. The high level of uniformity in the molecular events underlying the pathogenesis of mucinous ovarian tumors provides an opportunity for treatments targeting specific mutations and pathways.
2012-08-26 | GSE39076 | GEO
Project description:Advanced stage MOC have poor chemotherapy response and prognosis and biomarkers to help with Stage I adjuvant treatment are lacking. In addition, differentiating primary mucinous ovarian carcinoma (MOC) from gastrointestinal (GI) metastases to the ovary is challenging due to phenotypic similarities. Clinicopathological and gene expression data were analysed to identify prognostic and diagnostic features.
2022-08-26 | GSE203611 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors.
2012-10-25 | E-GEOD-30274 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors. Data was pre-processed and normalized with Hapmap JPT using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30283 | biostudies-arrayexpress
Project description:Mucus is associated with poor prognosis of colorectal cancer, but its mechanism remains unclear. The aim of this study was to reveal the key proteins in mucinous colorectal cancer. In this study, high-resolution liquid chromatography tandem mass spectrometry (LC-MS / MS) combined with quantitative 6-plex tandem mass mass tag labeling was used to profile protein changes in the left and right sides of mucinous and non-mucinous colorectal cancer tissues. A total of 7432 proteins were identified and analyzed.
2020-11-28 | PXD022802 | iProX
Project description:Epithelial ovarian cancer (EOC) are a heterogeneous collection of malignancies, each with their own developmental origins, clinical behavior and molecular profile. With less than 5% of EOC cases, mucinous ovarian carcinoma is a rare form with a poor prognosis with a 5-year survival of 11% for advanced stages (III/IV). Clinically, due to the large size and heterogeneity of mu-cinous tumors, Malignant forms are difficult to distinguish from Borderline (15%) and benign (80%) forms with a better prognosis. Improving their diagnosis is therefore a challenge with regard to the risk of under-treating a malignant form or of unnecessarily undertaking radical surgical excision. The involvement of microRNAs (miRNAs) in cancer and their potential as biomarkers of diagnosis are becoming increasingly recognized. In this study, miRNA expres-sion profiling generates using FFPE patient samples followed by qRT-PCR validation allows to identify 10 down-regulated and 5 up-regulated miRNAs between Malignant and Borderline tumors. To overcome issues linked to data normalization and to improve the accuracy of the results, a ratio analysis combining up-regulated and down-regulated miRNAs was used. Alt-hough 21/50 miRNA expression ratio were significantly different between Malignant and Bor-derline tumor samples, any ratio could perfectly discriminate the two groups. However, a combination of 14 miRNAs expression ratio (double ratio) showed high discriminatory poten-tial, with 100% of accuracy in distinguishing Malignant and Borderline ovarian tumors, and suggests that miRNAs may hold significant clinical potential as a diagnostic tool. Epithelial ovarian cancer (EOC) are a heterogeneous collection of malignancies, each with their own developmental origins, clinical behavior and molecular profile. With less than 5% of EOC cases, mucinous ovarian carcinoma is a rare form with a poor prognosis with a 5-year survival of 11% for advanced stages (III/IV). Clinically, due to the large size and heterogeneity of mu-cinous tumors, Malignant forms are difficult to distinguish from Borderline (15%) and benign (80%) forms with a better prognosis. Improving their diagnosis is therefore a challenge with regard to the risk of under-treating a malignant form or of unnecessarily undertaking radical surgical excision. The involvement of microRNAs (miRNAs) in cancer and their potential as biomarkers of diagnosis are becoming increasingly recognized. In this study, miRNA expres-sion profiling generates using FFPE patient samples followed by qRT-PCR validation allows to identify 10 down-regulated and 5 up-regulated miRNAs between Malignant and Borderline tumors. To overcome issues linked to data normalization and to improve the accuracy of the results, a ratio analysis combining up-regulated and down-regulated miRNAs was used. Alt-hough 21/50 miRNA expression ratio were significantly different between Malignant and Bor-derline tumor samples, any ratio could perfectly discriminate the two groups. However, a combination of 14 miRNAs expression ratio (double ratio) showed high discriminatory poten-tial, with 100% of accuracy in distinguishing Malignant and Borderline ovarian tumors, and suggests that miRNAs may hold significant clinical potential as a diagnostic tool.
2023-10-19 | GSE245725 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 42 archived frozen tumor samples collected from Department of Obstetrics and Gynecology, Tri-Service General Hospital, Taiwan, containing 8 clear cell, 3 mucinous, and 31 serous.
2012-10-25 | E-GEOD-30284 | biostudies-arrayexpress