SPENCER: a comprehensive database for small peptides encoded by noncoding RNAs in cancer patients

Abstract

Abstract As an increasing number of noncoding RNAs (ncRNAs) have been suggested to encode short bioactive peptides in cancer, the exploration of ncRNA-encoded small peptides (ncPEPs) is emerging as a fascinating field in cancer research. To assist in studies on the regulatory mechanisms of ncPEPs, we describe here a database called SPENCER (http://spencer.renlab.org). Currently, SPENCER has collected a total of 2806 mass spectrometry (MS) data points from 55 studies, covering 1007 tumor samples and 719 normal samples. Using an MS-based proteomics analysis pipeline, SPENCER identified 29 526 ncPEPs across 15 different cancer types. Specifically, 22 060 of these ncPEPs were experimentally validated in other studies. By comparing tumor and normal samples, the identified ncPEPs were divided into four expression groups: tumor-specific, upregulated in cancer, downregulated in cancer, and others. Additionally, since ncPEPs are potential targets for neoantigen-based cancer immunotherapy, SPENCER also predicted the immunogenicity of all the identified ncPEPs by assessing their MHC-I binding affinity, stability, and TCR recognition probability. As a result, 4497 ncPEPs curated in SPENCER were predicted to be immunogenic. Overall, SPENCER will be a useful resource for investigating cancer-associated ncPEPs and may boost further research in cancer.