Single cell RNA sequencing of human high-grade serous ovarian cancer (HGSC) cells and human immortalized fallopian tube epitheilal (FTE) cells
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE150864 | GEO | 2020/06/15
REPOSITORIES: GEO
Shared Molecules
Only show the datasets with similarity scores above: 0.5
Threshold
0.5
Similar Datasets
Project description:The cell and tissue of origin of high grade serous ovarian cancer (HGSC) is controversial. While the disease was traditionally assumed to arise from the ovarian surface epithelium (OSE), recent work supports an alternative model implicating the fallopian tube fimbriae epithelium (FTE). We used comparative DNA methylome analyses as a means to test these two competing models, hypothesizing that the HGSC methylome should more closely resemble its tissue of origin. Using two separate analysis methods, analysis within distinct genomic contexts, and validation studies using large-scale publically available HGSC methylome data, we consistently observed that the DNA methylome of HGSC more closely resembles FTE than OSE. These data support the FTE origin model, and suggest DNA methylome analysis as a useful approach to examine cell/tissue lineage origin in cancer. HGSC is the most common and lethal form of epithelial ovarian cancer (EOC). Two distinct tissues have been hypothesized as the tissue of origin of HGSC: OSE and FTE. We hypothesized that the DNA methylome of HGSC would more closely resemble the methylome of its tissue of origin. To test this, we profiled HGSC (n=10), OSE (n=7), and FTE (n=7) primary fresh-frozen tissues, and analyzed DNA methylome using Illumina 450K arrays (n=24) and Agilent Sure Select methyl-seq (n=7). We compared methylomes using statistical analyses of differentially methylated CpG sites (DMC) and differentially methylated regions (DMR), and methylation within a variety of different genomic contexts, including CpG island shores. We also analyzed methylation specifically at Homeobox (HOX) genes, due to their role in tissue specification. We used publically available HGSC methylome data (n=628) to provide additional comparison with FTE and OSE and potential validation. This analysis revealed that HGSC and FTE methylomes were significantly and consistently more highly conserved than were HGSC and OSE. Pearson correlations and hierarchal clustering of genes, promoters, CpG islands, CpG island shores, and HOX genes all revealed the increased relatedness of HGSC and FTE methylomes. In addition, two different large data sets of publically-available HGSC methylome data confirmed these relationships. In summary, our findings support the FTE origin model for HGSC, the most common and deadly EOC subtype. Due to its tissue-specificity and biochemical stability, interrogation of the DNA methylome appears to be a valuable approach to examine cell/tissue lineage in cancer.
2016-05-10 | GSE81227 | GEO
Project description:The cell and tissue of origin of high grade serous ovarian cancer (HGSC) is controversial. While the disease was traditionally assumed to arise from the ovarian surface epithelium (OSE), recent work supports an alternative model implicating the fallopian tube fimbriae epithelium (FTE). We used comparative DNA methylome analyses as a means to test these two competing models, hypothesizing that the HGSC methylome should more closely resemble its tissue of origin. Using two separate analysis methods, analysis within distinct genomic contexts, and validation studies using large-scale publically available HGSC methylome data, we consistently observed that the DNA methylome of HGSC more closely resembles FTE than OSE. These data support the FTE origin model, and suggest DNA methylome analysis as a useful approach to examine cell/tissue lineage origin in cancer. HGSC is the most common and lethal form of epithelial ovarian cancer (EOC). Two distinct tissues have been hypothesized as the tissue of origin of HGSC: OSE and FTE. We hypothesized that the DNA methylome of HGSC would more closely resemble the methylome of its tissue of origin. To test this, we profiled HGSC (n=10), OSE (n=7), and FTE (n=7) primary fresh-frozen tissues, and analyzed DNA methylome using Illumina 450K arrays (n=24) and Agilent Sure Select methyl-seq (n=7). We compared methylomes using statistical analyses of differentially methylated CpG sites (DMC) and differentially methylated regions (DMR), and methylation within a variety of different genomic contexts, including CpG island shores. We also analyzed methylation specifically at Homeobox (HOX) genes, due to their role in tissue specification. We used publically available HGSC methylome data (n=628) to provide additional comparison with FTE and OSE and potential validation. This analysis revealed that HGSC and FTE methylomes were significantly and consistently more highly conserved than were HGSC and OSE. Pearson correlations and hierarchal clustering of genes, promoters, CpG islands, CpG island shores, and HOX genes all revealed the increased relatedness of HGSC and FTE methylomes. In addition, two different large data sets of publically-available HGSC methylome data confirmed these relationships. In summary, our findings support the FTE origin model for HGSC, the most common and deadly EOC subtype. Due to its tissue-specificity and biochemical stability, interrogation of the DNA methylome appears to be a valuable approach to examine cell/tissue lineage in cancer.
2016-05-10 | GSE81224 | GEO
Project description:Single cell RNA sequencing of human high-grade serous ovarian cancer (HGSC) cells and human immortalized fallopian tube epitheilal (FTE) cells
| PRJNA633883 | ENA
Project description:The cell-of-origin of high grade serous ovarian carcinoma (HGSOC) remains controversial, with fallopian tube epithelium (FTE) and ovarian surface epithelium (OSE) both considered candidates. Here, by using genetically engineered mouse models and organoids, we assessed the tumor-forming properties of FTE and OSE harboring the same oncogenic abnormalities. Combined RB family inactivation and Tp53 mutation in Pax8+ FTE caused Serous Tubal Intraepithelial Carcinoma (STIC), which metastasized rapidly to the ovarian surface. These events were recapitulated by orthotopic injection of mutant FTE organoids. Engineering the same genetic lesions into Lgr5+ OSE or OSE-derived organoids also caused metastatic HGSOC, although with longer latency and lower penetrance. FTE- and OSE-derived tumors had distinct transcriptomes, and comparative transcriptomics and genomics suggest that human HGSOC arises from both cell types. Finally, FTE- and OSE-derived organoids exhibited differential chemosensitivity. Our results comport with a dualistic origin for HGSOC and suggest that the cell-of-origin might influence therapeutic response.
2019-10-21 | GSE125016 | GEO
Project description:The purpose of this study was to identify molecular alterations potentially involved in predisposition to adnexal serous carcinoma (SerCa) in the non-malignant fallopian tube epithelium (FTE) of BRCA1/2-mutation carriers, given recent evidence implicating the distal FTE as a common source for SerCa. Experiment Overall Design: We obtained and compared gene expression profiles of laser capture microdissected non-malignant distal FTE from 12 known BRCA1/2-mutation carriers (FTEb) and 12 control women (FTEn) during the luteal and follicular phase, as well as 13 high grade tubal and ovarian SerCa.
2008-06-18 | E-GEOD-10971 | biostudies-arrayexpress
Project description:Background: The aim of this study was to identify differentially expressed miRNAs in high-grade serous ovarian carcinoma (HGSC), clear cell ovarian carcinoma (CCC) and ovarian surface epithelium (OSE). Selected miRNAs were evaluated for association with clinical parameters including survival, and miRNA/mRNA interactions were mapped. Results: Differentially expressed miRNAs between HGSC, CCC and OSE were identified, of which 18 were validated (p<0.01) using RT-qPCR in an extended cohort. Compared with OSE, miR-205-5p was the most overexpressed miRNA in HGSC. miR-200 family members and miR-182-5p were the most overexpressed in HGSC and CCC compared with OSE, whereas miR-383 was the most underexpressed. miR-509-3-5p, miR-509-5p, miR-509-3p and miR-510 were among the strongest differentiators between HGSC and CCC, all being significantly overexpressed in CCC compared with HGSC. High miR-200c-3p expression was associated with poor progression-free (p=0.031) and overall (p=0.026) survival in HGSC. Interacting miRNAs and mRNA targets, including those of a TP53-related pathway presented previously, were identified in HGSC. Conclusions: Several miRNAs are overexpressed in HGSC and CCC compared with OSE, including the miR-200 family, among which miR-200c-3p is associated with survival in HGSC. A set of miRNAs differentiates CCC from HGSC, of which miR-509-3-5p and miR-509-5p are the strongest classifiers. Several interactions between miRNAs and mRNAs in HGSC were mapped. Methods: Differences in miRNA expression between HGSC, CCC and OSE scrapings were analyzed by global miRNA expression profiling (Affymetrix GeneChip miRNA 2.0 Arrays, n=30), validated by RT-qPCR (n=63), and evaluated for associations with clinical parameters. For HGSC, differentially expressed miRNAs were linked to differentially expressed mRNAs identified previously (GSE36668).
2014-02-13 | E-GEOD-47841 | biostudies-arrayexpress
Project description:High-grade serous ovarian cancer (HGSOC) progresses to advanced stages without symptoms and the 5-year survival rate is a dismal 30%. Recent studies of ovaries and oviducts in patients with BRCA mutations revealed that premalignant HGSC is found almost exclusively in the fallopian tube. To validate this notion, we cloned and transformed the fallopian tube stem cells (FTSC). We demonstrated that the tumors derived from the transformed fallopian tube stem cells (FTSCt) share the similar histological and molecular feature of high-grade serous cancer. In addition, a whole-genome transcriptome analysis comparing between FTSC, immortalized fallopian tube stem cells (FTSCi), and FTSCt showing a clear molecular progression, which is mimicked by the gene expression comparison between laser captured normal oviducts and HGSOC ( cancer and paired normal samples from 10 patients).
2015-09-29 | GSE69428 | GEO
Project description:Our study presents the first genetic models of de novo high-grade serous carcinomas (HGSC) that originate in fallopian tube secretory epithelial cells and recapitulate the key genetic alterations and precursor lesions characteristic of human invasive ovarian cancer. Genomic copy number analysis, using array CGH, was performed on murine tumors in order to compare the overlap of copy number alterations between HGSC models and TCGA data. Array CGH was performed on genomic DNA isolated from murine HGSC tumors. Genomic DNA from three normal mouse fallopian tubes was pooled and used as the reference.
2013-12-17 | E-GEOD-49827 | biostudies-arrayexpress
Project description:The purpose of this study was to identify molecular alterations potentially involved in predisposition to adnexal serous carcinoma (SerCa) in the non-malignant fallopian tube epithelium (FTE) of BRCA1/2-mutation carriers, given recent evidence implicating the distal FTE as a common source for SerCa. Keywords: disease state analysis
2008-05-31 | GSE10971 | GEO
Project description:Profiling of loss of heterozygosity (LOH) in HGSC, subcrouping HGSC by LOH-based clustering and comparing to the LOH profiles of triple-negative breast cancer [previously submitted; GSE19594]. Study for the correlation of LOH burdern and LOH-based subgroups to clinical response to platinum-based chemotherapy in patients suffered from HGSC. SNP data (Affymetrix GenChip 250K SNP Nsp) from 47 high grade serous ovarian cancer were generated and used for LOH and copy number analysis, LOH-based hierarchical clustering to subclassify HGSC, and comparison to the chromosomal alterations in high grade brest cancer. The associstion between LOH-based subgroups and LOH burden and clinical resposne to platinum-based chemotherapy was investigated. The results were validated in two independent public opening datasets.
2012-11-06 | E-GEOD-39130 | biostudies-arrayexpress