44-gene panel
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB75542 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR13069300.fastq.gz | Fastqsanger.gz | |||
| ERR13069300_1.fastq.gz | Fastqsanger.gz | |||
| ERR13069300_2.fastq.gz | Fastqsanger.gz | |||
| ERR13069400.fastq.gz | Fastqsanger.gz | |||
| ERR13069400_1.fastq.gz | Fastqsanger.gz |
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Project description:An Analysis of Genetic Polymorphisms in 76 Genes Related to the Development of Ovarian Tumors of Different Aggressiveness
| PRJEB75531 | ENA
Project description:Heredity is a major risk factor for ovarian cancer, but many families escape detection. Refined diagnosis of ovarian cancers linked to the breast and ovarian cancer (HBOC) syndrome and the hereditary nonpolyposis colorectal cancer (HNPCC) syndrome would allow cancer prevention in high risk families. In order to delineate genetic profiles of hereditary ovarian cancer, we applied genome wide array comparative genomic hybridization to 24 sporadic tumors, 12 HBOC associated tumors (BRCA1 mutations) and eight HNPCC associated tumors (mismatch repair gene mutations). Unsupervised cluster analysis identified two distinctive clusters related to genetic complexity. Most sporadic and HBOC associated tumors had complex genetic profiles with multiple gains and losses with an average of 41% of the genome altered, whereas mismatch repair defective tumors had stable genetic profiles, with an average of 18% of the genome altered. Losses of 4q34, 13q12-q32 and 19p13 were overrepresented in the HBOC subset, gains of chromosomes 17 and 19 characterized the HNPCC tumors and gains of 20q11 were more common in the sporadic tumors. The genetic distinction between HBOC and HNPCC associated ovarian cancer suggests that genetic profiles can be applied for refined classification of hereditary cases and reflects tumor development along different genetic pathways.
2011-04-27 | GSE28850 | GEO
Project description:Abstract: CRNDE is an oncogene expressed as a long non-coding RNA. However, our team previously reported that the CRNDE gene also encodes a micropeptide, CRNDEP. The amino acid sequence of CRNDEP has recently been revealed by other researchers, too. This study aimed to investigate genetic alterations within the CRNDEP-coding region of the CRNDE gene, methylation profiling of this gene, and CRNDEP expression analysis. All investigations were performed on clinical material from patients with ovarian tumors of diverse aggressiveness. We found that CRNDEP levels were significantly elevated in highly aggressive tumors compared to benign neoplasms. Consistently, a high level of this micropeptide was a negative, independent, prognostic, and predictive factor in high-grade ovarian cancer (hgOvCa) patients. The cancer-promoting role of CRNDE(P), shown in our recent study, was also supported by genetic and epigenetic results obtained herein, revealing no CRNDEP-disrupting mutations in any clinical sample. Moreover, in borderline ovarian tumors (BOTS), but not in ovarian cancers, the presence of a single nucleotide polymorphism in CRNDE, rs115515594, significantly increased the risk of recurrence. Consistently, in BOTS only, the same genetic variant was highly overrepresented compared to healthy individuals. We also discovered that hypomethylation of CRNDE is associated with increased aggressiveness of ovarian tumors. Accordingly, hypomethylation of this gene’s promoter/first exon correlated with hgOvCa resistance to chemotherapy, but only in specimens with accumulation of the TP53 tumor suppressor protein. Taken together, these results contribute to a better understanding of the role of CRNDE(P) in tumorigenesis and potentially may lead to improvements in screening, diagnosis, and treatment of ovarian neoplasms.
2024-07-27 | GSE262765 | GEO
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients. Gene expression was measured for 32 ovarian cancer cell lines using the GeneChip Human Exon 1.0 ST Array (Affymetrix). Morphological subtypes were assigned based on cell morphology, size, growth pattern and proliferation rate during culturing of the cell lines.
2014-09-18 | E-GEOD-53418 | biostudies-arrayexpress
Project description:Epithelial ovarian cancer is a very heterogeneous disease and remains the most lethal gynaecological malignancy in the Western world. Rational therapeutic approaches need to account for interpatient and intratumoral heterogeneity in treatment design. Detailed characterization of in vitro models representing the different histological and molecular subtypes is therefore imperative. Strikingly, from ~100 available ovarian cancer cell lines the origin and which subtype they represent is largely unknown. We have extensively and uniformly characterized 39 ovarian cancer cell lines (with mRNA/microRNA expression, exon sequencing, dose response curves for clinically relevant therapeutics) and obtained all available information on the clinical features and tissue of origin of the original ovarian cancer to refine the putative histological subtypes. From 39 ovarian cell lines, 14 were assigned as high-grade serous, four serous-type, one low-grade serous and 20 non-serous type. Three morphological subtypes (21 Epithelial, 7 Round, 12 Spindle) were identified that showed distinct biological and molecular characteristics, including overexpression of cell movement and migration-associated genes for the Spindle subtype. Clinical validation showed a clear association of the spindle-like tumors with metastasis, advanced stage, suboptimal debulking and poor prognosis. In addition, the morphological subtypes associated with the molecular C1-6 subtypes identified by Tothill et al. [1], Spindle clustered with C1-stromal subtype, Round with C5-mesenchymal and Epithelial with C4 subtype. We provide a uniformly generated data resource for 39 ovarian cancer cell lines, the ovarian cancer cell line panel (OCCP). This should be the basis for selecting models to develop subtype specific treatment approaches, which is very much needed to prolong the survival of ovarian cancer patients.
2014-09-18 | GSE53418 | GEO
Project description:Plasma was collected from 251 participants, including patients with EOC (n = 97), borderline ovarian tumors (n = 38), benign ovarian tumors (n = 54), and healthy controls (n = 62). Proteomic and metabolomic profiling was performed. A machine learning model was trained on a training cohort (34 EOC patients and 62 non-OC individuals [borderline, benign, and healthy controls]) to distinguish EOC from other groups. The model was validated in two independent cohorts: validation cohort 1 (n = 25) and validation cohort 2 (n = 130) using targeted proteomics and untargeted metabolomics.
2025-07-31 | PXD066792 |
Project description:Understanding the regulatory landscape of the human genome is a central question in complex trait genetics. Most single nucleotide polymorphisms (SNPs) associated with cancer risk lie in non protein-coding regions, implicating regulatory DNA elements as functional targets of susceptibility variants. Here, we describe genome-wide annotation of regions of open chromatin and histone modification in fallopian tube and ovarian surface epithelial cells (FTSECs, OSECs), the debated cellular origins of high-grade serous ovarian cancers (HGSOCs), and in endometriosis epithelial cells (EECs), the likely precursor of clear cell ovarian carcinomas (CCOCs). The regulatory architecture of these cell types was compared to normal human mammary epithelial cells (HMECs) and LNCaP prostate cancer cells. We observed similar positional patterns of global enhancer signatures across the three different ovarian cancer precursor cell types, and evidence of tissues specific regulatory signatures to non-gynecological cell types. We found significant enrichment for risk-associated SNPs intersecting regulatory biofeatures at 17 known HGSOC susceptibility loci in FTSECs (P=3.8x10-30) OSECs (P=2.4x10-23) and HMECs (P=6.7x10-15) but not for EECs (P=0.45) or LNCaP cells (P=0.88). Hierarchical clustering of risk SNPs conditioned on the six different cell types indicates FTSECs and OSECs are highly related (96% of samples using multi-scale bootstrapping) indicating both cell types may be precursors of HGSOC. These data represent the first description of regulatory catalogues of normal precursor cells for different ovarian cancer subtypes, and provide unique insights into the tissue specific regulatory variation with respect to the likely functional targets germline genetic susceptibility variants for ovarian cancer FAIRE-Seq and ChIP-Seq of 2 different histone modifications in 5 cell types.
2015-04-22 | E-GEOD-68104 | biostudies-arrayexpress
Project description:Purpose: Increasing genomics-based evidence suggests that synchronous endometrial and ovarian cancer (SEOC) represents clonally related primary and metastatic tumors. A systematic analysis of the global protein landscape of SEOCs, heretofore lacking, could reveal functional and disease-specific consequences of known genetic alterations, the directionality of metastasis, and accurate histological markers to distinguish SEOCs from single-site tumors. Experimental Design: We performed a systematic proteogenomic analysis of 29 patients diagnosed with SEOC at three international gynecologic oncology treatment centers (Chicago, Vancouver, Tübingen). For direct comparison to single-site tumors, we included 9 patients with single-site endometrioid ovarian and 26 patients with single-site endometrial endometrioid cancer. For all 64 patients, we performed sequencing of a 275-gene cancer panel combined with compartment-resolved mass spectrometry (MS) based proteomics of consecutive tissue sections to compare global (6,000+ proteins), tumor, and stromal proteomes. Results: DNA-based panel sequencing confirmed that most SEOCs are clonally related, suggesting primary and metastatic disease. These findings were further substantiated on the global proteome level, uncovering pronounced differences between SEOCs and single tumors and underscoring the importance of the stromal proteome in defining and identifying SEOCs. Our integrated proteogenomic approach confirmed that SEOCs more closely resemble endometrial endometrioid than endometrioid ovarian cancers. Conclusions: The integrated proteogenomic data show that SEOCs are distinguishable from endometrial endometrioid or endometrioid ovarian cancers. Based on their proteogenomic similarity to endometrial endometrioid cancers, we conclude that most synchronous endometrial and ovarian cancers represent primary endometrial endometrioid cancers that have metastasized to the ovary.
2025-03-11 | PXD059172 | Pride
Project description:Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I, II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
2018-10-04 | GSE101108 | GEO
Project description:Ovarian cancer is the most lethal gynecological malignancy in the western world. Despite recent efforts to characterize ovarian cancer using molecular profiling, few targeted treatment options are currently available. Here, we examined genetic variants, fusion transcripts, SNP genotyping, and gene expression patterns for early-stage (I, II) ovarian carcinomas (n=96) in relation to clinicopathological characteristics and clinical outcome, thereby identifying novel genetic features of ovarian carcinomas. Furthermore, mutation frequencies of specific genetic variants and/or their gene expression patterns were associated with histotype and overall survival, e.g. SLC28A2 (mucinous ovarian carcinoma histotype), ARCN1 (low expression in 0-2 year survival group), and tumor suppressor MTUS1 (mutation status and overall survival). The long non-coding RNA MALAT1 was identified as a highly promiscuous fusion transcript in ovarian carcinoma. Moreover, gene expression deregulation for 23 genes was associated with tumor aggressiveness. Taken together, the novel biomarkers identified here may improve ovarian carcinoma subclassification and patient stratification according to histotype and overall survival.
2018-10-04 | GSE101107 | GEO