MiRNA expression profile of non-epithelial ovarian tumors
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE98536 | GEO | 2017/09/01
SECONDARY ACCESSION(S): PRJNA385387
REPOSITORIES: GEO
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Project description:Comparison of miRNA expression profiles in malignant germ cell tumors compared to non-malignant control group. Use of bioinformatic algorithm Sylamer to interrogate mRNA expression profiles from malignant germ cell tumors for enrichment or depletion of binding sites for differentially expressed miRNAs. Use of Gene Ontology (GO) analysis to demonstrate functional significance of differentially expressed miRNAs in malignant germ cell tumors. mRNA profiling: Analyzed global mRNA expresion profiles from 21 pediatric samples (17 malignant germ cell tumors, 1 benign germ cell tumor and 3 gonadal controls) using Sylamer (van Dongen et al, Nature Methods 2008, PMID 18978784) to study functional significance of differentially expressed miRNAs in malignant germ cell tumors. 16 of these files previously published - Palmer et al, Cancer Research 2008, PMID 18519683; GEO Accession Number GSE10615. Similarly, re-analyzed published global mRNA expresion profiles from 25 adult samples (20 malignant germ cell tumors and 5 testis controls) using Sylamer (van Dongen et al, Nature Methods 2008, PMID 18978784) to study functional significance of differentially expressed miRNAs in malignant germ cell tumors. These files previously published - Korkola at al, Cancer Research 2006, PMID 16424014; GEO Accession Number GSE3218. miRNA profiling: Analyzed global miRNA expression files from 48 samples including 32 pediatric gonadal and extragonadal germ cell tumors, 2 adult testicular seminomas, 8 gonadal and developmental control samples and 6 germ cell tumor cell lines. Re-analyzed published data (TaqMan MicroRNA Assays) from study of miRNA expression in adult gonadal germ cell tumors (Gillis et al, J Pathol 2007, PMID 17893849) and compared with pediatric findings. Re-analyzed data linked below as supplementary file.
2010-03-14 | E-GEOD-18155 | biostudies-arrayexpress
Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as M-bM-^@M-^\C-signaturesM-bM-^@M-^]) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers. Total RNA obtained from serous ovarian adenocarcinomas, adenomas and borderline tumors. Gene expression profiling using Illumina's HT12 v4 bead arrays. Application of ovarian cancer molecular subtypes and intrinsic breast cancer subtypes using nearest centroid classification. KRAS and BRAF mutation analyses in the malignant and borderline tumors.
2014-08-15 | E-GEOD-57477 | biostudies-arrayexpress
Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as “C-signatures”) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers.
2014-08-15 | GSE57477 | GEO
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:The Homeobox (HOX) family of genes encodes transcription factors involved in basic developmental processes, most notably during embryogenesis. A possible HOX gene link between development and oncogenesis has recently been described. Dysregulation of HOX genes may be an early event in malignant transformation likely to induce antibody response and thus provide a potential marker for early diagnosis of cancer. Ovarian cancer is characterized by poor early detection and serves as an excellent model system to develop potential markers for early diagnosis. In this study we begin to characterize HOX gene expression in malignant tumors of the ovary and analyze the potential role of HOX genes as biomarkers for early detection of ovarian cancer. Microarray analysis of mRNA from human ovarian tissues was performed on 65 samples of normal, benign, borderline malignant and malignant ovarian tissue. These samples were analyzed using the Affymetrix Human Genome Focus GeneChip (HG-Focus) microarray to distinguish the differential pattern of mRNA expression between the four types of samples. Real-time reverse transcription PCR was utilized to confirm up-regulation of HOX genes as determined by microarray analysis. Our results demonstrate multiple HOX genes to be up-regulated in ovarian cancer. We have shown stepped increase in HOX expression comparing normal, benign neoplastic, and malignant human ovarian tissue samples. This suggests dysregulation of HOX genes may be an early event in malignant transformation and warrants additional studies to validate HOX gene products as potential markers for early detection of ovarian cancer. Experiment Overall Design: 67 samples were analyzed. 4 groupings based on pathology (normal, benign, borderline malignant, malignant). An average of normal samples was used as controls. Cell lines were used as ovarian cancer control samples.
2008-10-17 | E-GEOD-4122 | biostudies-arrayexpress
Project description:Background - The malignant potential of serous ovarian tumors, the most common ovarian tumor subtype, varies from benign to low malignant potential (LMP) tumors to frankly invasive cancers. Given the uncertainty about the relationship between these different forms, we compared their patterns of gene expression. Methods - Expression profiling was carried out on samples of 7 benign, 7 LMP and 28 invasive (moderate and poorly differentiated) serous tumors and surface epithelium of four normal whole ovaries using oligonucleotide microarrays representing over 21,000 genes. Results - We identified 311 transcripts that distinguished invasive from benign tumors, and 20 transcripts that were significantly differentially expressed between invasive and LMP tumors at p < 0.01 (with multiple testing correction). Five genes that were differentially expressed between invasive and either benign or normal tissues were validated by real time PCR in an independent panel of 46 serous tumors (4 benign, 7 LMP, 35 invasive). Overexpression of SLPI and WNT7A and down-regulation of C6orf31, PDGFRA and GLTSCR2 were measured in invasive and LMP compared with benign and normal tissues. Over-expression of WNT7A in an ovarian cancer cell line led to increased migration and invasive capacity. Conclusions - These results highlight several genes that may play an important role across the spectrum of serous ovarian tumorigenesis.
2009-07-28 | GSE17308 | GEO
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:Comparison of miRNA expression profiles in malignant germ cell tumors compared to non-malignant control group. Use of bioinformatic algorithm Sylamer to interrogate mRNA expression profiles from malignant germ cell tumors for enrichment or depletion of binding sites for differentially expressed miRNAs. Use of Gene Ontology (GO) analysis to demonstrate functional significance of differentially expressed miRNAs in malignant germ cell tumors.
2010-03-15 | GSE18155 | GEO
Project description:A data set of normal epithelium, serous ovarian surface epithelial-stromal tumors (benign and type II malignancies), stroma distal to tumor, and stroma adjacent to tumor (50 samples total). Additional cel files are included which represent replicate sampling from patients, and cel files that failed quality control but may be bioinformatically interesting. Additional replicate or failed cel files were not included in the final analysis (and so these samples were not included in the matrix). Background: Ovarian cancer is the most lethal gynecologic cancer in the United States. If caught in early stages, patient survival rate can reach 94%, when diagnosed at late stages survival rates drop to 28%. Correct diagnosis depends on the presence of definite symptoms: while ~90% of diagnosed ovarian cancers have symptoms, they tend to be unfocused and subacute. A definitive and early molecular signature of disease is thus desired. To further progress towards this goal, we present an Affymetrix™ human exon array data set measuring ovarian tumor expression, assembled using best practices. Method: Samples were collected from patients with benign and malignant (type II) serous ovarian surface epithelial-stromal tumors. Normal epithelium, tumor, stroma adjacent to tumor, and distal stroma were selected based on histopathology, and isolated using laser capture microdissection. Nugen products were used to perform random-primed mRNA amplification procedures (for full transcript capture) before hybridization to Affymetrix exon chips. Tumor expression and paracrine signaling was assessed using GC-RMA and a two-way Model I ANOVA. Single enrichment ontological analysis and gene network construction were performed to guide inferences about biological context. Results: In total, across 50 microarrays, ~270 million measurements were obtained. Based on comparisons to known ovarian cancer properties as established in molecular genetics literature, the initial analysis presented emphasizes data quality. Major trends between sample classes included: apical surface and tight junction activity, mitotic activity, benign tumor suppression, epithelial-mesenchymal transitioning, tumor oncogene activity, and paracrine signaling. A list of differentially expressed transcripts has been produced to enable rapid comparisons with published biomarker lists, but it is expected that detailed alternative transcript analysis will refine these predictions. Conclusions: A data set of 50 arrays, from carefully dissected serous ovarian surface epithelial-stromal tumors, has been produced, from which high quality measurements were obtained. While relatively small in number, this represents an important addition to the community pool of ovarian tumor samples, and the chosen platform enables bridging between 3' expression and exome sequencing data sets. This represents a significant contribution to the ovarian cancer genetics community. A total of 50 human ovary samples were used in analysis: 23 tissue samples laser capture microdissected from an ovary with a benign serous tumor (specifically 4 normal epithelium samples, 5 tumor samples, 6 stroma samples adjacent to the tumor, and 8 stroma samples distal of the tumor), and 27 tissue samples laser capture microdissected from an ovary with a malignant serous tumor (specifically 5 normal epithelium samples, 8 tumor samples, 7 stroma samples adjacent to the tumor, and 7 stroma samples distal of the tumor). Additional cel files were provided which, although were used in the quality control of the data set, were not used in the final experimental analysis. 8 replicates are included as cel files (1 from each cohort previously listed). 14 cel files were also included which failed quality control. Although the replicate and failed cel files were not used in the final analysis, they may still be interesting in other research.
2011-05-11 | E-GEOD-29156 | biostudies-arrayexpress
Project description:Serous borderline tumours (SBOT) are a challenging group of ovarian tumours positioned between benign and malignant disease. We have profiled the DNA methylomes of 12 low grade serous carcinoma (LGSC), 19 SBOT and 16 benign serous tumours (BST) across 27,578 CpG sites to further characterise the epigenomic relationship between these subtypes of ovarian tumours. Unsupervised hierarchical clustering of DNA methylation levels showed that LGSC differ distinctly from BST, however, not from SBOT. Gene ontology analysis of genes showing differential methylation at linked CpG sites between LGSC and BST revealed significant enrichment of gene groups associated with cell adhesion, cell-cell signalling and the extracellular region consistent with a more invasive phenotype of LGSC as compared to BST. Consensus clustering highlighted differences between SBOT methylomes and returned subgroups with malignant-like or benign-like methylation profiles. Furthermore, a two loci DNA methylation signature can distinguish between these SBOT subgroups with benign-like and malignant-like methylation characteristics. Our findings indicate striking similarities between SBOT and LGSC methylomes which supports a common origin and the view that LGSC may arise from SBOT. A subgroup of SBOT can be classified into tumours with a benign-like or a malignant-like methylation profile which may help in identifying tumours more likely to progress into LGSC. Array-based methylation profiling was performed using the Infinium HumanMethylation27 BeadChip in 12 low grade serous carcinoma, 19 serous borderline tumours and 16 benign serous tumours. The reproducibility of the Infinium HumanMethylation27 BeadChips was evaluated using four biological replicates of the high grade serous ovarian cancer cell line PEO1. Differential methylation cutoff was estimated from four biological replicates by bootstrap resampling and set at Δβ ≥ 0.25 corresponding to a FDR ≤ 0.09.
2012-12-31 | E-GEOD-40105 | biostudies-arrayexpress