ABSTRACT
Introduction
Cancer is a disease of (altered) biological pathways, often driven by somatic mutations and with several implications. Therefore, the identification of potential markers of disease is challenging. Given the large amount of biological data generated with omics approaches, oncology has experienced significant contributions. Proteomics mapping of protein fragments, derived from proteolytic processing events during oncogenesis, may shed light on (i) the role of active proteases and (ii) the functional implications of processed substrates in biological signaling circuits. Both outcomes have the potential for predicting diagnosis/prognosis in diseases like cancer. Therefore, understanding proteolytic processing events and their downstream implications may contribute to advances in the understanding of tumor biology and targeted therapies in precision medicine.
Areas covered
Proteolytic events associated with some hallmarks of cancer (cell migration and proliferation, angiogenesis, metastasis, as well as extracellular matrix degradation) will be discussed. Moreover, biomarker discovery and the use of proteomics approaches to uncover proteolytic signaling events will also be covered.
Expert opinion
Proteolytic processing is an irreversible protein post-translational modification and the deconvolution of biological data resulting from the study of proteolytic signaling events may be used in both patient diagnosis/prognosis and targeted therapies in cancer.
Article highlights
Proteolytic processing is an irreversible protein post-translational modification; that affects the fate of processed proteins.
Proteolytic signaling is nearly ubiquitously present among the hallmarks of cancer.
Targeting (proteolytically processed) protein fragments may help in the detection/prognostics of cancer, contributing to improving personalized medicine.
Declaration of interest
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants, or patents received or pending, or royalties.
Reviewer disclosures
Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
Author contributions
Murilo Salardani and Uilla Barcick have contributed equally to this work. André Zelanis wrote and revised the manuscript.
Acknowledgments
The authors thank Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP; grants # 2022/15421-0 and 2021/05087-3) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).