Proteolytic signaling in cancer.

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.

Heterotypic communication as the promoter of phenotypic plasticity of cancer cells: The role of cancer secretomes.

Cellular communication relies on signaling circuits whose statuses are mainly modulated by soluble biomolecules such as carbohydrates, lipids, proteins, and metabolites as well as extracellular vesicles (EVs). Therefore, the active secretion of such biomolecules is critical for both cell homeostasis and proper pathophysiological responses in a timely fashion. In this context, proteins are among the main modulators of such biological responses. Hence, profiling cell line secretomes may be an opportunity for the identification of "signatures" of specific cell types (i.e., stromal or metastatic cells) with important prognostic/therapeutic value. This review will focus on the biological implications of cell secretomes in the context of cancer, as well as their functional roles in shaping the tumoral microenvironment (TME) and communication status of participating cells.

A proteomics-MM/PBSA dual approach for the analysis of SARS-CoV-2 main protease substrate peptide specificity.

The main protease Mpro of SARS-CoV-2 is a well-studied major drug target. Additionally, it has been linked to this virus' pathogenicity, possibly through off-target effects. It is also an interesting diagnostic target. To obtain more data on possible substrates as well as to assess the enzyme's primary specificity a two-step approach was introduced. First, Terminal Amine Isobaric Labeling of Substrates (TAILS) was employed to identify novel Mpro cleavage sites in a mouse lung proteome library. In a second step, using a structural homology model, the MM/PBSA variant MM/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized Born Surface Area) free binding energy calculations were carried out to determine relevant interacting amino acids. As a result, 58 unique cleavage sites were detected, including six that displayed glutamine at the P1 position. Furthermore, modeling results indicated that Mpro has a far higher potential promiscuity towards substrates than expected. The combination of proteomics and MM/PBSA modeling analysis can thus be useful for elucidating the specificity of Mpro, and thus open novel perspectives for the development of future peptidomimetic drugs against COVID-19, as well as diagnostic tools.

Assessing proteolytic events in bioinformatic reanalysis of public secretome data from melanoma cell lines.

Autocrine and paracrine signals are of paramount importance in both normal and oncogenic events and the composition of such secreted molecular signals (i.e the secretome) designate the communication status of cells. In this context, the analysis of post-translational modifications in secreted proteins may unravel biological circuits regulated by irreversible modifications such as proteolytic processing. In the present study, we have performed a bioinformatic reanalysis of public proteomics data on melanoma cell line secretomes, changing database searching parameters to allow for the identification of proteolytic events generated by active proteases. Such approach enabled the identification of proteolytic signatures which suggested active proteases and whose expression profiles might be targeted in patient tissues or liquid biopsies, as well as their cleaved substrates. Although N-terminomics approaches continue to be the method of choice for the evaluation of proteolytic signaling events in complex samples, the simple approach performed in this work resulted in the gain of biological insights derived from shotgun proteomics data.

A proteomics-MM/PBSA dual approach for the analysis of SARS-CoV-2 main protease substrate peptide specificity

The main protease Mpro of SARS-CoV-2 is a well-studied major drug target. Additionally, it has been linked to this virus’ pathogenicity, possibly through off-target effects. It is also an interesting diagnostic target. To obtain more data on possible substrates as well as to assess the enzyme’s primary specificity a two-step approach was introduced. First, Terminal Amine Isobaric Labeling of Substrates (TAILS) was employed to identify novel Mpro cleavage sites in a mouse lung proteome library. In a second step, using a structural homology model, the MM/PBSA variant MM/GBSA (Molecular Mechanics Poisson-Boltzmann/Generalized Born Surface Area) free binding energy calculations were carried out to determine relevant interacting amino acids. As a result, 58 unique cleavage sites were detected, including six that displayed glutamine at the P1 position. Furthermore, modeling results indicated that Mpro has a far higher potential promiscuity towards substrates than expected. The combination of proteomics and MM/PBSA modeling analysis can thus be useful for elucidating the specificity of Mpro, and thus open novel perspectives for the development of future peptidomimetic drugs against COVID-19, as well as diagnostic tools.