Genomics analysis of mucinous tumours of the ovary and related neoplasms
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PROVIDER: EGAS00001003545 | EGA |
REPOSITORIES: EGA
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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: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:Background There is a lack of tools for identifying the site of origin in mucinous cancer. This study aimed to evaluate the performance of a transcriptome-based classifier for identifying the site of origin in mucinous cancer. Methods Transcriptomic data of 1,878 non-mucinous and 82 mucinous cancer specimens, with 7 sites of origin, namely, the uterine cervix (CESC), colon (COAD), pancreas (PAAD), stomach (STAD), uterine endometrium (UCEC), uterine carcinosarcoma (UCS), and ovary (OV), obtained from The Cancer Genome Atlas, were used as the training and validation sets, respectively. Transcriptomic data of 14 mucinous cancer specimens from a tissue archive were used as the test set. For identifying the site of origin, a set of 100 differentially expressed genes for each site of origin was selected. After removing multiple iterations of the same gene, 626 genes were chosen, and their RNA expression profiles, at each site of origin, were used to train the deep neural network classifier. The performance of the classifier was estimated using the training, validation, and test sets. Results The accuracy of the model in the training set was 0.977, while that in the validation set was 0.939 (77/82). In the test set, the model showed an accuracy of 0.857 (12/14). t-SNE analysis revealed that samples in the test set were part of the clusters obtained for the training set. Conclusion Although limited by small sample size, we showed that a transcriptome-based classifier could correctly identify the site of origin of mucinous cancer.
2020-12-15 | GSE163126 | GEO
Project description:MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with premalignant lesions. We wished to identify miRNA expression profiles in pancreatic cystic tumors with low malignant potential (serous microcystic adenomas) and high malignant potential (mucinous cystadenoma and intraductal papillary mucinous neoplasm (IPMN)) and compare these to PDAC and carcinoma-ex-IPMN (CEI).
2011-05-18 | GSE29352 | GEO
Project description:MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with premalignant lesions. We wished to identify miRNA expression profiles in pancreatic cystic tumors with low malignant potential (serous microcystic adenomas) and high malignant potential (mucinous cystadenoma and intraductal papillary mucinous neoplasm (IPMN)) and compare these to PDAC and carcinoma-ex-IPMN (CEI). n= 20 samples Benign Pancreatic Cystic Tumour (n=7 Microcystic, n= 6 Mucinous, n= 7 IPMN) were compared with n= 9 samples of carcinoma ex IPMN and n= 14 samples of pancreatic cancer (adenocarcinoma) for known homo sapiens miRNAs (mirbase 13).
2011-05-18 | E-GEOD-29352 | biostudies-arrayexpress
Project description:Intraductal papillary mucinous neoplasm (IPMN) is a benign tumor that grows within the pancreatic ducts characterized by the production of thick mucinous fluid by surrounding tumor cells. IPMN is the most important precursor lesion for pancreatic cancer that is the fourth most common cause of cancer deaths. Differentiating between low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive intraductal papillary mucinous neoplasms (IPMNs) remains a diagnostic challenge with current biomarkers, necessitating the development of novel biomarkers that can distinguish IPMN malignancy. We investigated differentially expressed proteins among pancreatic cyst fluids consisted of LGD, HGD, and invasive IPMN patients by using our novel proteomic strategy, and finally we discovered pancreatic cyst fluid protein marker candidates that can predict the malignant potential of IPMNs.
2018-05-01 | PXD008302 | Pride
Project description:Circulating epithelial cells (CECs) were purified using a microfluidic device from healthy donors, patients bearing intraductal papillary mucinous neoplasms, or pancreatic ductal adenocarcinoma and their transcriptomes were sequenced.
2017-11-01 | GSE103152 | GEO
Project description:Gene expression profile of laser-capture microdissected epithelium component of 6 mucinous cystic neoplasms of the pancreas were included in the study. The expression arrays were generated with Affymetrix HU133A gene chips (18,462 genes/EST transcripts).
2018-06-28 | E-MTAB-6853 | biostudies-arrayexpress
Project description:In this study, to obtain a complete registry of genetic lesions in MDS and to identify novel therapeutic targets, we performed SNP array analysis and whole exome analysis for novel mutations using high-throughput sequencing technologies. In whole exome analysis, paired CD3-positive T cells were used as a normal control. By comparing sequences in tumors and paired T cells, 268 non-synonymous somatic mutations were confirmed with an overall true positive rate of 53.9 %, including 206 missense, 25 nonsense, and 10 splice site mutations, and 27 frameshift-causing insertions/deletions (indels). The mutations of the known gene targets, however, accounted for only 12.3 % of all detected mutations (N = 33), and the remaining 235 mutations involved previously unreported genes. Combined with the genomic copy number profile obtained by SNP array karyotyping, this array of somatic mutations provided a landscape of myelodysplasia genomes. Copy number analysis of Affymetrix 250K SNP arrays was performed for 29 MDS or related neoplasms and paired 29 germline samples.
2011-09-11 | E-GEOD-31174 | biostudies-arrayexpress
Project description:In this study, to obtain a complete registry of genetic lesions in MDS and to identify novel therapeutic targets, we performed SNP array analysis and whole exome analysis for novel mutations using high-throughput sequencing technologies. In whole exome analysis, paired CD3-positive T cells were used as a normal control. By comparing sequences in tumors and paired T cells, 268 non-synonymous somatic mutations were confirmed with an overall true positive rate of 53.9 %, including 206 missense, 25 nonsense, and 10 splice site mutations, and 27 frameshift-causing insertions/deletions (indels). The mutations of the known gene targets, however, accounted for only 12.3 % of all detected mutations (N = 33), and the remaining 235 mutations involved previously unreported genes. Combined with the genomic copy number profile obtained by SNP array karyotyping, this array of somatic mutations provided a landscape of myelodysplasia genomes.
2011-09-12 | GSE31174 | GEO