SCENE: Signature Collection for Endometrial Cancer Prognosis

Endometrial cancer (EC) is the most common malignancy of the female reproductive tract; its prognosis is difficult to predict. Despite the technique of single-cell transcriptomic analysis (scRNA-seq) returning single-cell level expression data and promising to improve the accuracy of prognosis prediction, a tool that correlates transcriptomic signatures with survival is missing. To this aim, we have created SCENE, a database that collects information to correlate EC transcriptomic signatures with patient prognosis. We performed a review of the literature present in PubMed to collect transcriptomic signatures annotated with their characteristics, differential expression between healthy and sick patients, between patients with more and less favourable prognosis, and cellular pathways in which the genes are involved, as well as references to the original studies. The analysis of about 200 studies has allowed us to obtain 700 mRNA signatures, 60 microRNA (miRNA), and 150 long non-coding RNA (lncRNA), involved in 60 molecular pathways. Each signature is annotated with its specific prognostic outcome that it influences, such as overall survival (OS), progression-free survival (PFS), relapse-free survival (RFS), and disease-specific survival (DSS). The SCENE resource collects and annotates information that is widespread in the literature to facilitate the interpretation of transcriptomic data obtained with any technique in EC. In the case of scRNA-seq data, SCENE may reveal cells predisposed to develop therapy resistance and metastasis.