Christopoulos, PetrosHarel, MichalMcGregor, KimberlyBrody, YehudaPuzanov, IgorBar, JairElon, YehonatanSela, ItamarYellin, BenLahav, CorenRaveh, ShaniReiner-Benaim, AnatReinmuth, NielsNechushtan, HovavFarrugia, DavidBustinza-Linares, ErnestoLou, YanyanLeibowitz, RayaKamer, IrisZer Kuch, AlonaMoskovitz, MorLevy-Barda, AdvaKoch, InaLotem, MichalKatzenelson, RivkaAgbarya, AbedPrice, GillianCheley, HelenAbu-Amna, MahmoudGeldart, TomGottfried, MayaTepper, EllaPolychronis, AndreasWolf, IdoDicker, AdamCarbone, DavidGandara, David2025-07-092025-07-092024-03-21Christopoulos, P., Harel, M., McGregor, K., Brody, Y., Puzanov, I., Bar, J., Elon, Y., Sela, I., Yellin, B., Lahav, C., Raveh, S., Reiner-Benaim, A., Reinmuth, N., Nechushtan, H., Farrugia, D., Bustinza-Linares, E., Lou, Y., Leibowitz, R., Kamer, I., Zer Kuch, A., … Gandara, D. R. (2024). Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer. JCO precision oncology, 8, e2300555. https://doi.org/10.1200/PO.23.0055510.1200/PO.23.00555https://hdl.handle.net/20.500.14709/255Purpose: Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions. Patients and methods: We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1. Results: Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424). Conclusion: Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.Full Text UploadedenCC BY-NC-ND 4.0https://creativecommons.org/licenses/by-nc-nd/4.0/OncologyJournal Articlehttps://gerr.openrepository.com/bitstreams/381c563d-1dc5-4eba-b163-dccf7c8768a4/download