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Supplementary Table S6 from Proteomic Profiling of Advanced Melanoma Patients to Predict Therapeutic Response to Anti-PD-1 Therapy

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journal contribution
posted on 2024-01-05, 08:21 authored by Nina Zila, Ossia M. Eichhoff, Irene Steiner, Thomas Mohr, Andrea Bileck, Phil F. Cheng, Alexander Leitner, Ludovic Gillet, Tatjana Sajic, Sandra Goetze, Betty Friedrich, Patricia Bortel, Johanna Strobl, René Reitermaier, Sabrina A. Hogan, Julia M. Martínez Gómez, Ramon Staeger, Felix Tuchmann, Sophie Peters, Georg Stary, Mario Kuttke, Adelheid Elbe-Bürger, Christoph Hoeller, Rainer Kunstfeld, Wolfgang Weninger, Bernd Wollscheid, Reinhard Dummer, Lars E. French, Christopher Gerner, Ruedi Aebersold, Mitchell P. Levesque, Verena Paulitschke

Results of the Wilcoxon rank sum tests, dependent variable = first component of the PCA.

Funding

Promedica Grant

Mobilty Grant of Medical University of Vienna

Forschungsfoerderung der Initiative Krebsforschung des Comprehensive Cancer Center (CCC)of Medical University Vienna

University of Zurich URPP Translational Cancer Research Grant

PHRT strategic focus area of ETH

Austrian Science Fund (FWF)

Swiss National Science Foundation

History

ARTICLE ABSTRACT

Despite high clinical need, there are no biomarkers that accurately predict the response of patients with metastatic melanoma to anti-PD-1 therapy. In this multicenter study, we applied protein depletion and enrichment methods prior to various proteomic techniques to analyze a serum discovery cohort (n = 56) and three independent serum validation cohorts (n = 80, n = 12, n = 17). Further validation analyses by literature and survival analysis followed. We identified several significantly regulated proteins as well as biological processes such as neutrophil degranulation, cell–substrate adhesion, and extracellular matrix organization. Analysis of the three independent serum validation cohorts confirmed the significant differences between responders (R) and nonresponders (NR) observed in the initial discovery cohort. In addition, literature-based validation highlighted 30 markers overlapping with previously published signatures. Survival analysis using the TCGA database showed that overexpression of 17 of the markers we identified correlated with lower overall survival in patients with melanoma. Ultimately, this multilayered serum analysis led to a potential marker signature with 10 key markers significantly altered in at least two independent serum cohorts: CRP, LYVE1, SAA2, C1RL, CFHR3, LBP, LDHB, S100A8, S100A9, and SAA1, which will serve as the basis for further investigation. In addition to patient serum, we analyzed primary melanoma tumor cells from NR and found a potential marker signature with four key markers: LAMC1, PXDN, SERPINE1, and VCAN.