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

ABSTRACT: 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.

SUBMITTER: Salardani M

PROVIDER: S-EPMC9018387 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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

Salardani Murilo M Barcick Uilla U Zelanis André A

Biochemistry and biophysics reports 20220411

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 ...[more]

PMID: 35462751

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Project description:ObjectiveTo reanalyze the Bypass Angioplasty Revascularization Investigation 2 Diabetes trial using a new composite cardiovascular disease (CVD) outcome to determine how best to treat patients with type 2 diabetes mellitus and stable coronary artery disease.Patients and methodsFrom January 1, 2001, to November 30, 2008, 2368 patients with type 2 diabetes mellitus and angiographically proven coronary artery disease were randomly assigned to insulin-sensitizing (IS) or insulin-providing (IP) therapy and simultaneously to coronary revascularization (REV) or no or delayed REV (intensive medical therapy [MED]), with all patients receiving intensive medical treatment. The outcome of this analysis was a composite of 8 CVD events.ResultsFour-year Kaplan-Meier rates for the composite CVD outcome were 35.8% (95% CI, 33.1%-38.5%) with IS therapy and 41.6% (95% CI, 38.7%-44.5%) with IP therapy (P=.004). Much of this difference was associated with lower in-trial levels of fibrinogen, C-reactive protein, and hemoglobin A1c with IS therapy. Four-year composite CVD rates were 32.7% (95% CI, 30.0%-35.4%) with REV and 44.7% (95% CI, 41.8%-47.6%) with MED (P<.001). A beneficial effect of IS vs IP therapy was present with REV (27.7%; 95% CI, 24.0%-31.4% vs 37.5%; 95% CI, 33.6%-41.4%; P<.001), but not with MED (43.6%; 95% CI, 39.5%-47.7% vs 45.7%; 95% CI, 41.6%-49.8%; P=.37) (homogeneity, P=.05). This interaction between IS therapy and REV was limited to participants preselected for coronary artery bypass grafting (CABG). The lowest composite CVD rates occurred in patients preselected for CABG and assigned to IS therapy and REV (17.3%; 95% CI, 11.8%-22.8%).ConclusionIn the Bypass Angioplasty Revascularization Investigation 2 Diabetes trial, the IS treatment strategy and the REV treatment strategy each reduces cardiovascular events. The combination of IS drugs and CABG results in the lowest risk of subsequent CVD events.Trial registrationclinicaltrials.gov Identifier: NCT00006305.

Dataset Information

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

Publications

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

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