INTRODUCTION: The blood-based VeriStrat® proteomic test (VS) predicts patient response to therapy based on the intensities of eight different features in a mass spectrum obtained from MALDI-TOF analysis of human serum/plasma specimens. An interim analysis of the INSIGHT clinical trial (NCT03289780) demonstrated that VS labels, VS Good and VS Poor, predict patients with non-small cell lung cancer (NSCLC) who are likely sensitive or resistant to immune checkpoint inhibitor (ICI) therapy [1]. While VS measures intensities of eight spectral features by matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) mass spectrometry from patient serum/plasma samples, the individual proteoforms underlying these features have not been rigorously and comprehensively identified. OBJECTIVES: The objective of this study was to identify the proteoforms measured by VS. METHODS: Mass spectra for VS are acquired using a standard low-resolution MALDI-TOF procedure that generates broad, composite features. DeepMALDI [2] analysis of serum samples was used to resolve these features into finer peaks. Top-down proteomics analysis of human serum, combining reversed-phase fractionation and liquid chromatography - tandem mass spectrometry (LC-MS/MS), was then used to identify the key proteoform constituents of these peaks. RESULTS: It was determined that proteoforms of serum amyloid A1, serum amyloid A2, serum amyloid A4, C-reactive protein, and beta-2 microglobulin are primary constituents of the VS spectral features. CONCLUSION: Proteoforms of several proteins related to host immunity were identified as major constituents of these features. This information advances our understanding of how VS can predict patient response to therapy and opens the way for further translational studies.