Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Expression data from mouse ovarian surface epithelium cells at different stages of malignancy

ABSTRACT: Ovarian cancer is one of the most deadly cancers accounting for only 3% of diagnosed cancers, but is the fifth leading cause of cancer deaths among woman; however, the progression of ovarian cancer is poorly understood. To study and further understand the early events that lead to epithelial derived ovarian cancer, we previously developed a cell model of progressive ovarian cancer. Mouse ovarian surface epithelial (MOSE) cells have undergone spontaneous transformation in cell culture and represent pre-neoplastic, non-tumorigenic to an aggressive malignant phenotype. Microarray analysis was performed with RNA isolated from different stages of MOSE cells to examine changes in gene expression as MOSE cells transition from a pre-neoplastic to a malignant state. RNA was isolated from MOSE early cell representing a pre-neoplastic, non-malignant stage, MOSE Intermediate cells representing a noeplastic, pre-invasive state, and MOSE Late cells representing a malignant, invasive stage. Three biological replicates were used to take into account variations within the heterogeneous cultures.

ORGANISM(S): Mus musculus

SUBMITTER: Eva Schmelz

PROVIDER: E-GEOD-24789 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Epithelial ovarian cancer is morphologically and clinically heterogeneous. Transcriptional profiling has revealed molecular subtypes (referred to as M-bM-^@M-^\C-signaturesM-bM-^@M-^]) that correlate to biological as well as clinical features. We aimed to determine gene expression differences between malignant, benign and borderline serous ovarian tumors, and to investigate similarities to the intrinsic molecular subtypes of breast cancer. Global gene expression profiling was performed using Illumina's HT12 Bead Arrays and applied to 59 fresh-frozen ovarian tumors. SAM analysis revealed enrichment of cell cycel processes among the malignant tumors, in line with malignant tumors being highly proliferative. The borderline tumors were split between the malignant and benign tumor clusters, indicating that borderline tumors have both malignant and benign features. Furthermore, nearest centroid classification was performed applying previously published gene profiles for the ovarian cancer C-signatures and the intrinsic breast cancer subtypes, respectively, and showed significant correlations between the malignant serous tumors and the highly aggressive C1, C2 and C4 ovarian cancer signatures, and the basal-like breast cancer subtype. The benign and borderline serous tumors together were significantly correlated to the normal-like breast cancer subtype and the ovarian cancer C3 signature. The borderline tumors, on the other hand, correlated significantly to the Luminal A breast cancer subtype. These findings remained when analyzed in a large, independent dataset. The data in this study link the transcriptional profiles of serous ovarian cancer to the intrinsic molecular subtypes of breast cancer, in line with the shared clinical and molecular features between high-grade serous ovarian cancer and basal-like breast cancer, including an aggressive phenotype, frequent TP53 mutations and a high degree of genomic instability, and suggest that biomarkers and targeted therapies may overlap between these subsets of ovarian and breast cancers. Finally, the link between benign and borderline ovarian cancer and luminal breast cancer may indicate endocrine responsiveness in a subset of ovarian cancers. Total RNA obtained from serous ovarian adenocarcinomas, adenomas and borderline tumors. Gene expression profiling using Illumina's HT12 v4 bead arrays. Application of ovarian cancer molecular subtypes and intrinsic breast cancer subtypes using nearest centroid classification. KRAS and BRAF mutation analyses in the malignant and borderline tumors.

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Expression data from mouse ovarian surface epithelium cells at different stages of malignancy

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