The Emerging Role of uORF-Encoded uPeptides and HLA uLigands in Cellular and Tumor Biology.
Lara JürgensKlaus WethmarPublished in: Cancers (2022)
Recent technological advances have facilitated the detection of numerous non-canonical human peptides derived from regulatory regions of mRNAs, long non-coding RNAs, and other cryptic transcripts. In this review, we first give an overview of the classification of these novel peptides and summarize recent improvements in their annotation and detection by ribosome profiling, mass spectrometry, and individual experimental analysis. A large fraction of the novel peptides originates from translation at upstream open reading frames (uORFs) that are located within the transcript leader sequence of regular mRNA. In humans, uORF-encoded peptides (uPeptides) have been detected in both healthy and malignantly transformed cells and emerge as important regulators in cellular and immunological pathways. In the second part of the review, we focus on various functional implications of uPeptides. As uPeptides frequently act at the transition of translational regulation and individual peptide function, we describe the mechanistic modes of translational regulation through ribosome stalling, the involvement in cellular programs through protein interaction and complex formation, and their role within the human leukocyte antigen (HLA)-associated immunopeptidome as HLA uLigands. We delineate how malignant transformation may lead to the formation of novel uORFs, uPeptides, or HLA uLigands and explain their potential implication in tumor biology. Ultimately, we speculate on a potential use of uPeptides as peptide drugs and discuss how uPeptides and HLA uLigands may facilitate translational inhibition of oncogenic protein messages and immunotherapeutic approaches in cancer therapy.
Keyphrases
- amino acid
- long non coding rna
- endothelial cells
- cancer therapy
- mass spectrometry
- transcription factor
- induced apoptosis
- induced pluripotent stem cells
- pluripotent stem cells
- binding protein
- deep learning
- poor prognosis
- drug delivery
- real time pcr
- rna seq
- protein protein
- label free
- working memory
- cell cycle arrest
- risk assessment
- cell proliferation
- human health
- cell death