Single-cell RNA-seq highlights a specific carcinoembryonic cluster in ovarian cancer.

ABSTRACT: Expounding the heterogeneity for ovarian cancer (OC) with the cognition in developmental biology might be helpful to search for robust prognostic markers and effective treatments. In the present study, we employed single-cell RNA-seq with ovarian cancers, normal ovary, and embryo tissue to explore their heterogeneity. Then the differentiation process of clusters was explored; the pivotal cluster and markers were identified. Furthermore, the consensus clustering algorithm was used to explore the different clinical phenotypes in OC. At last, a prognostic model was construct and used to assess the prognosis for OCs. As a result, eight diverse clusters were identified, and the similarity existed in some clusters between embryo and tumours based on their gene expression. Meaningfully, a subtype

SUBMITTER: Zhao H 

PROVIDER: S-EPMC8590695 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature