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Updated: Feb 18, 2026
High Throughput Sequential ELISA for Validation of Biomarkers of Acute Graft-Versus-Host Disease
Published on: October 31, 2012
Evaluation of two high-throughput proteomic technologies for plasma biomarker discovery in immunotherapy-treated
Su Yin Lim1,2, Jenny H Lee1,2, Sarah J Welsh1,2
1Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia.
Background:
Selective kinase and immune checkpoint inhibitors, and their combinations, have significantly improved the survival of patients with advanced metastatic melanoma. Not all patients will respond to treatment however, and some patients will present with significant toxicities. Hence, the identification of biomarkers is critical for the selection and management of patients receiving treatment. Biomarker discovery often involves proteomic techniques that simultaneously profile multiple proteins but few studies have compared these platforms.
Methods:
In this study, we used the multiplex bead-based Eve Technologies Discovery assay and the aptamer-based SomaLogic SOMAscan assay to identify circulating proteins predictive of response to immunotherapy in melanoma patients treated with combination immune checkpoint inhibitors. Expression of four plasma proteins were further validated using the bead-based Millipore Milliplex assay.
Results:
Both the Discovery and the SOMAscan assays detected circulating plasma proteins in immunotherapy-treated melanoma patients. However, these widely used assays showed limited correlation in relative protein quantification, due to differences in specificity and the dynamic range of protein detection. Protein data derived from the Discovery and Milliplex bead-based assays were highly correlated.
Conclusions:
Our study highlights significant limitations imposed by inconsistent sensitivity and specificity due to differences in the detection antibodies or aptamers of these widespread biomarker discovery approaches. Our findings emphasize the need to improve these technologies for the accurate identification of biomarkers.
