Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Hi-C identifies structural variation associated with resistance in paired patient-derived ovarian cancer models

ABSTRACT: Purpose: To establish a bioinformatics pipeline for identifying structural variation in cancer cell lines using Hi-C. Results: We were able to identify translocations as the primary genomic aberration in the PEO1 and PEO4 cell lines, while copy number alterations were the primary mutational process in the PEO14 and PEO23 cell lines. Conclusions: The strategy we present can be widely applied to the analysis of structural variation in cancer, and the data we have generated provides valuable insight into the processes that occur upon treatment of ovarian cancer with cisplatin.

ORGANISM(S): Homo sapiens

PROVIDER: GSE135242 | GEO | 2025/07/22

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Expression profiling of ovarian cancer cell lines

Project description:Paired platinum-sensitive & platinum-resistant cell lines PEO1 and PEO4 (respectively) were derived from the same patient. Cell line cultures were profiled with the HT-HGU133a GeneChip to investigate chemotherapy resistance related expression of genes marked with different histone modifications in a primary ovarian tumour (clinical data for the primary ovarian tumour is available as Series supplementary file). 4 replicates of each of the PEO1 and PEO4 cell line were profiled using the HT-HGU133a GeneChip

2012-10-12 | E-GEOD-41499 | biostudies-arrayexpress

G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [RNA-seq]

Project description:G-quadruplexes are secondary DNA structures which have been shown to have an impact on gene transcription via a variety of mechanisms, In this study we generate RNA-seq data of wildtype chemotherpay sensitive (PEO1 A) and chemostherapy resistant (PEO4 A) ovarian cancer cells to intersect with G-quadruplex mapping data to assess how transcription is impacted by G-quadruplex formation. In another variation of the PEO1/4 cell line, in which the PEO1 B cell line has a reversion mutation to reinstate BRCA2, we used the G-quadruplex stabilising molecule pyridostatin (PDS) to treat PEO1 B and its counterpart PEO4 B for either 0, 2 or 6 hours to see how stabilising G-quadruplexes effects gene expression in a temporal manner.

2025-06-06 | GSE279501 | GEO

Homo sapiens

Project description:PEO1/PEO4 Exome Sequence

| PRJNA299834 | ENA

Expression profiling of ovarian cancer cell lines

2012-10-12 | GSE41499 | GEO

G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [ATAC-seq]

Project description:Chromatin accessibilty is a key regulator of gene expression. In this study we aim to map accessible chromatin regions in both chemotherapy sensitive (PEO1) and chemotherapy resistant (PEO4) ovarian cancer cell lines, to intersect with RNA-seq data to see how chromatin architecture changes and impacts gene expression between the two cell lines.

2025-06-06 | GSE279495 | GEO

G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [ChIP-seq]

Project description:G-quadruplex ChIP-seq has been performed to establish genomic maps of G-quadruplex structures in chemotherapy sensitive (PEO1) and chemotherapy resistant (PEO4) ovarian cancer cell lines to uncover how the changes in G-quadruplex landscape may contribute to the development of chemotherapy resistance for the first time.

2025-06-06 | GSE279497 | GEO

G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [CUT&Tag]

Project description:Enhancers are regulatory elements of the genome involved in transcriptional regulation and reprogramming. Similarly, we propose that secondary DNA structures termed G-quadruplexes could also be impacting transcription in an enhancer based way via long-range interactions to bring together regulatory elements of the genome. In this study, we map G-quadruplex structures and h3k27ac enhancer marks in a paired ovarian cancer cell line; PEO1 and PEO4. We endeavour to use these findings to help link the transcriptional function of G-quadruplexes with enchancer in chemotherapy sensitive (PEO1) and chemotherapy resistant (PEO4) ovarian cancer cells.

2025-06-06 | GSE279641 | GEO

Proteomic landscapes of 3D and 2D models of High-Grade Serous Ovarian Carcinoma: Implications for Carboplatin Response

Project description:High-Grade Serous Ovarian Carcinoma (HGSOC) is is the most common form of ovarian cancer and finding new treatments remains an unmet need. While drug discovery is typically performed in two-dimensional (2D) monolayers, three-dimensional (3D) culture systems better mimic in vivo conditions. However, a comprehensive comparison of 3D vs 2D ovarian cancer models is lacking. Here, we quantitatively compared the whole cell proteomic signatures of 4 ovarian cell lines—PEO1, PEO4, UWB1.289, and UWB1.289+BRCA1— with different status of BRCA genes grown, in 2D and in 3D. Using isobaric labeling proteomics, we quantified 6,668 proteins and identified 412 significantly altered proteins between 2D and 3D. Proteins upregulated in 3D were enriched for transmembrane transport and oxidoreductase activity, while energy metabolism and cell growth pathways also showed dimensionality-dependent changes. Notably, membrane-associated proteins such as EGFR were downregulated in spheroids, particularly in PEO1 and PEO4. Furthermore, 3D culture modulated the response to carboplatin, with increased expression of drug resistance-associated proteins, including NDUF family members and ATP6V0A2, in all spheroid models. These findings underscore how culture dimensionality influences both the molecular landscape and chemotherapeutic response of HGSOC cells and highlight candidate targets for overcoming carboplatin resistance.

2025-10-13 | PXD062934 | Pride

Functional effect of DOT1L pharmacological inhibition in ERα-positive Ovarian Cancer cells

Project description:Estrogen Receptor alpha (ERα), a nuclear receptor with transcriptional activity, is a master regulator of estrogen signaling, widely known as therapeutic target in hormone-responsive breast cancer (BC). Moreover, ERα is highly expressed in approximately 80% of High Grade Serous Ovarian Cancer (HGSOC), the most common epithelial ovarian carcinoma. Despite some promising clinical trials evaluating endocrine therapy in this type of tumor, the role of ERα is still unknown. Epigenetic changes, such as DNA methylation, are emerging as key contributing factors to carcinogenesis. Disruptor of telomeric silencing-1-like (DOT1L), the only known histone methyl transferase capable to produce H3K79 mono, di and tri-methylation, modulates ERα actions in hormone-responsive BC. Considering this evidence, ERα-DOT1L association was confirmed in ERα-positive OC cells, PEO1 and PEO4, by Co-IP. DOT1L pharmacological inhibition by EPZ004777 (EPZ) revealed the involvement of this epigenetic enzyme in cell proliferation, cell cycle progression and apoptosis. Transcriptome profiling after ICI (a Selective Estrogen Receptor Degrader) and EPZ treatment, in both cell lines, has underlined a deep impact of both compounds on ERα-modulated genes, including the down-regulation of ERα itself. On the other hand, functional analysis showed that commonly affected transcripts are involved in different cellular processes, such as cancer cell survival, chemoresistance and cell cycle progression. Moreover, ChIP-qPCR performed on ERα promoter highlighted ERα and DOT1L co-localization, both in PEO1 and in PEO4 cells, which was reduced after EPZ treatment, suggesting a role of this complex on receptor transcriptional activity. In addition, drug combination studies performed with EPZ and ICI showed an additive effect in cell growth inhibition. Taken together, these results suggest DOT1L as a potential therapeutic target in the treatment of OC.

2019-11-04 | E-MTAB-8198 | biostudies-arrayexpress

Proteomic landscapes of 3D and 2D models of High-Grade Serous Ovarian Carcinoma: Implications for Carboplatin Response

Project description:High-Grade Serous Ovarian Carcinoma (HGSOC) is the most common form of ovarian cancer and finding new treatments remains an unmet need. While drug discovery is typically performed in two-dimensional (2D) monolayers, three-dimensional (3D) culture systems better mimic in vivo conditions. However, a comprehensive comparison of 3D vs 2D ovarian cancer models is lacking. Here, we quantitatively compared the whole cell proteomic signatures of 4 ovarian cell lines—PEO1, PEO4, UWB1.289, and UWB1.289+BRCA1— with different status of BRCA genes grown, in 2D and in 3D. Using isobaric labeling proteomics, we quantified 6,404 proteins and identified 371 significantly and commonly altered proteins between 2D and 3D. Proteins upregulated in 3D were enriched for transmembrane transport and NADH:ubiquinone oxidoreductase Complex I, while energy metabolism and cell growth pathways also showed dimensionality-dependent changes. Notably, membrane-associated proteins were downregulated in spheroids, particularly EGFR in PEO1. Furthermore, 3D culture modulated the response to carboplatin, with increased expression of drug resistance-associated proteins, including NDUF family members in all spheroid models. These findings underscore how culture dimensionality influences both the molecular landscape and chemotherapeutic response of HGSOC cells and highlight candidate targets for overcoming carboplatin resistance.

2025-10-13 | PXD066652 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data