Pan-cancer analysis of transcripts encoding novel open-reading frames (nORFs) and their potential biological functions

Abstract

Uncharacterized and unannotated open-reading frames, which we refer to as novel open reading frames (nORFs), may sometimes encode peptides that remain unexplored for novel therapeutic opportunities. To our knowledge, no systematic identification and characterization of transcripts encoding nORFs or their translation products in cancer, or in any other physiological process has been performed. We use our curated nORFs database (nORFs.org), together with RNA-Seq data from The Cancer Genome Atlas (TCGA) and Genotype-Expression (GTEx) consortiums, to identify transcripts containing nORFs that are expressed frequently in cancer or matched normal tissue across 22 cancer types. We show nORFs are subject to extensive dysregulation at the transcript level in cancer tissue and that a small subset of nORFs are associated with overall patient survival, suggesting that nORFs may have prognostic value. We also show that nORF products can form protein-like structures with post-translational modifications. Finally, we perform in silico screening for inhibitors against nORF-encoded proteins that are disrupted in stomach and esophageal cancer, showing that they can potentially be targeted by inhibitors. We hope this work will guide and motivate future studies that perform in-depth characterization of nORF functions in cancer and other diseases.

Bottom‐up and top‐down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame‐encoded peptides

“…These non-classical ORFs have been termed alternative ORFs (altORFs), in order to distinguish them from classical ORFs (reference ORFs). These altORFs can be further divided into different subclasses, [7] such as upstream and downstream ORFs (uORFs and dORFs), small or short ORFs (smORFs or sORFs), ORFs from noncoding RNA (altORFs nc ), or novel ORFs (nORFs; uncharacterized or unannotated ORFs, e.g, denovogenes or orphan genes) [8]. However, there is an overlap between the different subclasses (Figure 1).…”

“…As there is a longstanding debate about the boundary between peptides and proteins, the terms mini-and microproteins are used but are a potential matter of discussion. In addition, the terms "ghost proteins" and "novel proteins" are used for altORF gene products, of which SEPs form a subclass [8,14]. Therefore, we recommend to use all these different search terms when a literature search is performed.…”

“…In addition, classical proteomic workflows depend on protein databases and only proteins in this database can be identified. Therefore, either six-frame translations or de novo sequencing, which is completely independent of any protein database, can offer interesting analytical approaches for the identification of novel SEP [8]. It is worth mentioning that this will also require further development of bioinformatics methods for quality control and validation of the identifications.…”

“…A recent publication described the application of in silico modelings for SEPs, showing that they have an increased level of disorder compared to canonical proteins [8]. In addition, the PTM prevalence in SEPs, based on amino acid sequence, was predicted.…”

“…For most PTM types, the PTM density was predicted to be equivalent or higher in SEPs compared to canonical proteins. In addition, LC-MS data provided evidence on the presence of six phosphorylation events on sORF-encoded peptides and 297 phosphorylations across 259 nORF gene products [8].…”