PLX014145

GSE147882: Transcriptome profiling of organoids and tissues derived from murine oviductal and ovary surface epithelium (OSE) to study high-grade serous ovarian cancer (HG-SOC)

  • Organsim mouse
  • Type RNASEQ
  • Target gene
  • Project ARCHS4

Purpose: Transcriptome profiling of organoids/tissues derived from murine oviduct and OSE was performed to study and compare the gene expression profiles in the both suspected origins of HG-SOC. CRISPR-Cas9 modified oviductal organoids (TBP clones, which were mutated in Trp53, Brca1 and Pten), the tumors derived upon xenotransplantation of the TBP-clones and subsequent tumor-derived organoids were additionally profiled to show the transcriptional change upon aquiring mutations and tumor development.; Methods: Both oviductal and OSE organoids as well as oviductal TBP-clones and tumor-derived organoids were grown in Wnt-conditioned media prior harvesting for RNA extraction. Additionally, RNA was extracted from healthy oviductal and OSE tissues and Ovi-TBP-clone-derived tumor tissues. RNA was converted to cDNA and libraries were prepared using the CelSeq2 method and sequenced. Samples were sequenced on Illumina NextSeq500 by using 75-bp paired-end sequencing. Paired-end reads from Illumina sequencing were aligned to the mouse genome (GRCm38 assembly) by BWA. DESeq2 (v1.18.0) package was used for read normalization and differential expression analysis. Gene set enrichment analysis (GSEA) was performed using gene lists for motile cilium assembly against normalized RNA-seq reads of healthy oviductal an OSE organoids using GSEA software v3.0 beta2. GSEA was additionally used to detect enrichment of signature gene sets of different HG-SOC subtypes in the TBP-clone-derived murine tumors; Results: Transcriptome analysis of oviductal and OSE organoids/tissues revealed tissue-specific gene expression pattern in the organoid systems. In contrast to OSE counterparts, oviductal organoids showed enrichment in motile cilium assembly genes, reflecting the presence of ciliated cells in this model.; Results: Oviductal TBP-clones gave rise to different tumor phenotypes with distinct gene expression profiles. Analysis of the transcriptomes of these tumors divided the TBP-clone-derived tumors into two distinct HG-SOC molecular subtypes (differentiated- or immunoreactive-like subtypes), confirming the potential of organoids in modeling HG-SOC.; Results: The tumor-derived organoids retained the distinct phenotypes observed in the originating Ovi-TBP-clone derived tumors. Subset of tumors showed epithelial and others mesenchymal features that were maintained in the respective organoid cultures also in the gene expression level.; Conclusions: RNA sequencing showed tissue specific differences in murine oviductal and OSE organoids, and revealed HG-SOC-like features of oviductal mutants. SOURCE: Kadi Lõhmussaar (k.lohmussaar@hubrecht.eu) - Hubrecht Institute

View on GEOView in Pluto

Key Features

Enhance your research with our curated data sets and powerful platform features. Pluto Bio makes it simple to find and use the data you need.

Learn More

14K+ Published Experiments

Access an extensive range of curated bioinformatics data sets, including genomic, transcriptomic, and proteomic data.

Easy Data Import

Request imports from GEO or TCGA directly within Pluto Bio. Seamlessly integrate external data sets into your workflow.

Advanced Search Capabilities

Utilize powerful search tools to quickly find the data sets relevant to your research. Filter by type, disease, gene, and more.

Analyze and visualize data for this experiment

Use Pluto's intuitive interface to analyze and visualize data for this experiment. Pluto's platform is equipped with an API & SDKs, making it easy to integrate into your internal bioinformatics processes.

Read about post-pipeline analysis

View QC data and experiment metadata

View quality control data and experiment metadata for this experiment.

Request import of other GEO data

Request imports from GEO or TCGA directly within Pluto Bio.

Chat with our Scientific Insights team