ArticleTherapeutic advances in medical oncology2024
Multiplex analysis for the identification of plasma protein biomarkers for predicting lung cancer immunotherapy response.
Article in Therapeutic advances in medical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Plasma proteomic profiling and molecular clustering reveal immune-defined prognostic subtypes in lung adenocarcinoma.International journal of cancer · 2026Article
- Plasma proteomics to explore benefit from anti-PD-(L)1 in advanced solid tumors: a prospective pilot study.Scientific reports · 2025Article
- Immunological and nutritional perspectives on macromolecular therapies for thoracic tumors.Frontiers in immunology · 2025Review
- Plasma immune proteome-based risk score predicts survival in advanced gastric cancer treated with PD-1 inhibitors and chemotherapy.Frontiers in immunology · 2025Article
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Authors and funding
6 authors.
Funding
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Abstract
Background: Programmed death-ligand (PD-L1) expression serves as a predictive biomarker for immune checkpoint inhibitor (ICI) sensitivity in non-small cell lung cancer (NSCLC). Nevertheless, the development of biomarkers that reliably predict ICI response remains an ongoing endeavor due to imperfections in existing methodologies. Objectives: ICIs have led to a new paradigm in the treatment of NSCLC. The current companion PD-L1 diagnostics are insufficient in predicting ICI response. Therefore, we sought whether the Olink platform could be applied to predict response to ICIs in NSCLC. Design: We collected blood samples from patients with NSCLC before ICI treatment and retrospectively analyzed proteomes based on their response to ICI. Methods: Overall, 76 NSCLC patients' samples were analyzed. Proteomic plasma analysis was performed using the Olink platform. Intraplate reproducibility, validation, and statistical analyses using elastic net regression and generalized linear models with clinical parameters were evaluated. Results: Intraplate coefficient of variation (CV) assays ranged from 3% to 6%, and the interplate CV was 14%. In addition, the Pearson correlation coefficient of the Olink Normalized Protein eXpression data was validated. No statistical differences were observed in the analyses of progressive disease and response to ICIs. Furthermore, no single proteome showed prognostic value in terms of progression-free survival. Conclusion: In this study, the proximity extension assay-based approach of the Olink panel could not predict the patient's response to ICIs. Our proteomic analysis failed to achieve predictive value in both response or progression to ICIs and progression-free survival (PFS).
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