Expression Data from Ovarian Surface Kinome
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Solange Mongoue
PROVIDER: E-GEOD-15578 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:The human kinome is incolved in multiple function in the life cycle of cells, and ther differntial expression in cacner suggests that protein kinases play an important role in tumor progression and proliferation. To delineate pathways that may be important for neoplastic change in women at high risk for ovarian cancer, we compared the expression signature of surface kinases in normal ovarian surface epithelium with ovarian epithelium from patients at high risk, and epithelial ovarian cancer using Affymetrix expresion array HG U133Plus2.
2009-04-07 | GSE15578 | GEO
Project description:The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We provide a bioinformatic analysis of copy number variation and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We individually examined the copy number variation and DNA methylation for 44 primary ovarian cancer samples and 7 ovarian normal samples using our MOMA-ROMA technology and Affymetrix expression data as well as 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with significantly altered copy number and correlated changes in expression. We identify changes in DNA methylation and expression for all amplified and deleted genes. We predicted 615 potential oncogenes and tumor suppressors candidates by integrating these multiple genomic and epigenetic data types. Expression data accompaniment to CSHL ROMA and MOMA3 human ovarian analysis. Correlation of expression to Methylation and Copy Number Variation in ovarian cancer.
2011-10-16 | E-GEOD-27943 | biostudies-arrayexpress
Project description:Integration of several ovarian cancer datasets to identify a reproducible predictors of survival Four microarray datasets from different institutions were reprocessed in a uniform manner, into a single training dataset. Survival analysis was performed and a validation cohort (61 patients from 3 institutions) was profiled using a custom array to confirm the prognostic value of the predictors. The four datasets were obtained from the following reports: Spentzos D, Levine DA, Ramoni MF, et al. Gene expression signature with independent prognostic significance in epithelial ovarian cancer. J Clin Oncol 2004;22:4700-10 Bild AH, Yao G, Chang JT, et al. Oncogenic pathway signatures in human cancers as a guide to targeted therapies. Nature 2006;439:353-7 Marquez RT, Baggerly KA, Patterson AP, et al. Patterns of gene expression in different histotypes of epithelial ovarian cancer correlate with those in normal fallopian tube, endometrium, and colon. Clin Cancer Res 2005;11:6116-26 Zhang L, Volinia S, Bonome T, et al. Genomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer. Proc Natl Acad Sci U S A 2008;105:7004-9 61 samples
2011-06-15 | E-GEOD-19161 | biostudies-arrayexpress
Project description:A gene expression profile of BRCAness was defined in publicly available expression data of 61 patients with epithelial ovarian cancer (34 patients with BRCA-1 or BRCA-2 mutations and 27 patients with sporadic disease). This dataset is publicly available at http://jnci.oxfordjournals.org/cgi/content/full/94/13/990/DC1 The BRCAness profile was correlated with outcome in 70 patients with epithelial ovarian cancer and known outcome data. Correlation with outcome
2010-07-11 | E-GEOD-19829 | biostudies-arrayexpress
Project description:We evaluated the genome-wide mRNA expression profiles in lymphoblastoid cell lines of familial ovarian cancer patients and controls Comparing the mRNA expression data of 74 ovarian cancer cases with 47 healthy controls. Genotype information of the 7 risk alleles is linked to the bottom of the Series record.
2013-06-06 | E-GEOD-37582 | biostudies-arrayexpress
Project description:Epidemiological studies have shown that the regular use of non-steroidal anti-inflammatory (NSAIDs) drugs is associated with a reduced risk of various cancers. In addition, in vitro and experiments in mouse models have demonstrated that NSAIDs decrease tumor initiation and/or progression of several cancers. However, there are limited preclinical studies investigating the effects of NSAIDs in ovarian cancer. Here, we have studied the effects of two NSAIDs, diclofenac and indomethacin, in ovarian cancer cell lines and in a xenograft mouse model. Diclofenac and indomethacin treatment decreased cell growth by inducing cell cycle arrest and apoptosis. In addition, diclofenac and indomethacin reduced tumor volume in a xenograft model of ovarian cancer. To identify possible molecular pathways mediating the effects of NSAID treatment in ovarian cancer, we performed microarray analysis of ovarian cancer cells treated with indomethacin or diclofenac. Interestingly, several of the genes found downregulated following diclofenac or indomethacin treatment are transcriptional target genes of E2F1. E2F1 was downregulated at the mRNA and protein level upon treatment with diclofenac and indomethacin, and overexpression of E2F1 rescued cells from the growth inhibitory effects of diclofenac and indomethacin. In conclusion, NSAIDs diclofenac and indomethacin exert an anti-proliferative effect in ovarian cancer in vitro and in vivo and the effects of NSAIDs may be mediated, in part, by downregulation of E2F1. The serous ovarian adenocarcinoma cell lines HEY, OVCAR5 and UCI-101 were grown in culture then seeded in 60 mm dishes and treated for 24 hours with 300 mM diclofenac, indomethacin or no treatment (Control). RNA was isolated and one sample from each group was labeled and hybridized to Illumina Sentrix bead arrays.
2014-06-20 | E-GEOD-45052 | biostudies-arrayexpress
Project description:PURPOSE: We investigated whether tumor tissue obtained at diagnosis expresses a specific gene profile that is predictive of findings at second-look surgery in patients with epithelial ovarian cancer (EOC). PATIENTS AND METHODS: Tumor tissue obtained at the time of diagnosis was profiled with oligonucleotide microarrays. Class prediction analysis was performed in a training set of 24 patients who had undergone a second-look procedure. The resultant predictive signature was then tested on an independent validation set comprised of 36 patients. RESULTS: A 93-gene signature referred to as the Chemotherapy Response Profile (CRP) was identified through its association with pathologic complete response. When applied to a separate validation set, the CRP distinguished between patients with unfavorable versus favorable overall survival (median 41 months v not yet reached, respectively, log-rank P = .007), with a median follow-up of 52 months. The signature maintained independent prognostic value in multivariate analysis, controlling for other known prognostic factors such as age, stage, grade, and debulking status. There was no genetic overlap between the CRP and our previously described Ovarian Cancer Prognostic Profile (OCPP), which demonstrated similar prognostic value. The combination of the CRP and OCPP yielded better prognostic discrimination then either profile alone. Genes present in the CRP include BAX, a proapoptotic protein previously associated with chemotherapy response in ovarian cancer. CONCLUSION: Identification of a gene expression profile based on pathologic response in EOC provides independent prognostic information and offers potential insights into the mechanism of drug resistance. Efforts to identify a more tailored profile using selected genes from both the CRP and OCPP are underway. keyword(s): Correlation with outcome All microarray experiments were performed at the BIDMC Genomics Center. Ovarian cancer samples were collected at the time of primary debulking surgery and frozen at 80°C. Tumor samples were pulverized in liquid nitrogen and homogenized in Trizol solution, followed by RNA isolation, probe labeling, and Affymetrix GeneChip hybridization using standard manufacturer protocols. The dChip algorithm was used for data normalization and for generating gene expression signal values. Two outlier arrays as identified by the dChip software were excluded from further analysis.
2011-08-11 | E-GEOD-31245 | biostudies-arrayexpress
Project description:To date, a variety of studies have employed gene expression profiling to classify ovarian carcinomas in clinically relevant subtypes. These studies provided valuable first clues to molecular changes in ovarian cancer that might be exploited in new treatment strategies. However, most studies were of relatively limited size and the number of overlapping genes in the identified profiles was minimal. Although identification of gene expression profiles associated with clinically relevant subtypes in ovarian cancer is important, knowledge is now emerging rapidly on how genes interact in pathways, networks and complexes; this allows us to unravel those cellular pathways determining the biological behavior of ovarian cancer, that might be successfully targeted with drugs. The aim of our study was: 1) To develop a gene expression profile associated with overall survival in advanced stage serous ovarian cancer, 2) to assess the association of pathways and transcription factors with overall survival, and 3) to validate our identified profile and pathways/transcription factors in an independent set of ovarian cancers. According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. A continuous predictor of overall survival was built taking into account well-known issues in microarray analysis, such as multiple testing and overfitting. A functional class scoring analysis was utilized to assess pathways/transcription factors for their association with overall survival. The prognostic value of genes that constitute our overall survival profile was validated on a fully independent, publicly available data set of 118 well-defined primary serous ovarian cancers. Furthermore, functional class scoring analysis was also performed on this independent data set to assess the similarities with results from our own data set. An 86-gene overall survival profile discriminated between patients with unfavorable and favorable prognosis (median survival, 19 vs. 41 months, respectively; permutation p-value of log-rank statistic = 0.015) and maintained its independent prognostic value in multivariate analysis. Genes that comprised the overall survival profile were also able to discriminate between the two risk groups in the independent data set. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival of which 16 and 12 respectively were confirmed in the independent dataset. Our study provides new clues to genes, pathways and transcription factors which contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies. Keywords: Oncology/Gynecological Cancers, Genetics and Genomics/Cancer Genetics, Genetics and Genomics/Gene Expression, Genetics and Genomics/Genomics According to a randomized design, profiling of 157 advanced stage serous ovarian cancers was performed in duplicate using ~35K 70-mer oligonucleotide microarrays. Two randomly selected samples were hybridized together on the arrays for intensity-based instead of ratio-based analysis of the microarray data.
2008-12-10 | E-GEOD-13876 | biostudies-arrayexpress
Project description:To determine the global changes in hypothalamic gene expression that may occur at the time of female puberty in this species, animals were euthanized at three different stages, juvenile (25-days of age), early puberty (30-35 days of age) and on the day of the first proestrus (32-37 days of age). According to criteria previously established (Ojeda,S.R.; Urbanski,H.F. Puberty in the rat pp.363-409. The Physiology of Reproduction, 2nd Edition, Vol 2. Edited by Knobil,E.; Neill,J.D. Raven Press, 1994), 25-day-old animals are in the mid- juvenile phase of prepubertal development (JUV). At this time, the vagina is not yet patent and the uterine weight is 60Â mg or less, with no accumulation of intrauterine fluid. Older rats showing a closed vagina, accumulation of intrauterine fluid and an uterine weight less that 180 mg are considered to be in the early proestrous (EP) phase of puberty. Finally, rats still exhibiting a closed vagina, but showing a uterus ballooned with fluid and a uterine weight of at least 200Â mg are considered to be in late proestrus (LP), i.e., the phase of puberty when the first preovulatory surge of LHRH and gonadotropins takes place. The first ovulation occurs the following day. All animals were sacrificed between 1600-1700 h, and the medial basal hypothalamus (MBH) was immediately dissected, as previously described (Rogers,L.C.; Junier,M-P.; Farmer,S.R.; Ojeda,S.R. A sex-related difference in the developmental expression of class II -tubulin messenger RNA in rat hypothalamus. Mol.Cell.Neurosci., 2: 130-138, 1991) and stored in RNAlater according to manufacturerâs instructions. Experiment Overall Design: Affymetrix arrays were used to detect global changes in gene expression in the hypothalamus of normal sexual development of the female rat.
2008-06-16 | E-GEOD-8310 | biostudies-arrayexpress
Project description:Recurrent disease emerges in the majority of patients with ovarian cancer (OVCA). Adoptive T-cell therapies with T-cell receptors (TCRs) targeting tumor-associated antigens (TAAs) are considered promising solutions for less-immunogenic ‘cold’ ovarian tumors. In order to treat a broader patient population, more TCRs targeting peptides derived from different TAAs binding in various HLA class I molecules are essential. By performing a differential gene expression analysis using mRNA-seq datasets, PRAME, CTCFL and CLDN6 were selected as strictly tumor-specific TAAs, with high expression in ovarian cancer and at least 20-fold lower expression in all healthy tissues of risk. In primary OVCA patient samples and cell lines we confirmed expression and identified naturally expressed TAA-derived peptides in the HLA class I ligandome. Subsequently, high-avidity T-cell clones recognizing these peptides were isolated from the allo-HLA T-cell repertoire of healthy individuals. Three PRAME TCRs and one CTCFL TCR of the most promising T-cell clones were sequenced, and transferred to CD8+ T cells. The PRAME TCR-T cells demonstrated potent and specific antitumor reactivity in vitro and in vivo. The CTCFL TCR-T cells efficiently recognized primary patient-derived OVCA cells, and OVCA cell lines treated with demethylating agent 5-aza-2′-deoxycytidine (DAC). The identified PRAME and CTCFL TCRs are promising candidates for the treatment of patients with ovarian cancer, and are an essential addition to the currently used HLA-A*02:01 restricted PRAME TCRs. Our selection of differentially expressed genes, naturally expressed TAA peptides and potent TCRs can improve and broaden the use of T-cell therapies for patients with ovarian cancer or other PRAME or CTCFL expressing cancers.
2023-03-10 | PXD040651 | Pride