ArticleFrontiers in immunology2024
Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 9 citations in OpenAlex.
- Distinct changes in plasma protein profiles of cancer patients receiving immune checkpoint inhibitors versus chemotherapy: implications for thrombosis risk and adverse outcomes.Research and practice in thrombosis and haemostasis · 2026Article
- Identification and validation of serum SLIT1 as a biomarker for predicting anti-PD-1/PD-L1 resistance in non-small cell lung cancer.Biological procedures online · 2026Article
- Dissecting non-small cell lung cancer (NSCLC) with blood proteomics-from surgical to immunotherapeutic responses.NPJ precision oncology · 2026Article
- Plasma proteomics reveals the molecular features in rapidly progressive pneumoconiosis.Frontiers in immunology · 2026Article
- Decoding resistance to immune checkpoint inhibitors in non-small cell lung cancer: a comprehensive analysis of plasma proteomics and therapeutic implications.Journal for immunotherapy of cancer · 2025Article
- Article
- Potential predictive value of CD8A and PGF protein expression in gastric cancer patients treated with neoadjuvant immunotherapy.BMC cancer · 2025Article
- Article
- Investigating causal relationships between plasma proteins and lung adenocarcinoma: result from proteomics and Mendelian randomization study.Discover oncology · 2025Article
- Integrated Multi-Omics Approaches for Predicting Immune Checkpoint Inhibitor Response in NSCLC - Insights From Genomics, Proteomics, and Metabolomics.Lung Cancer (Auckland, N.Z.) · 2025Review
- The latest advances in liquid biopsy for lung cancer-a narrative review.Translational lung cancer research · 2024Review
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Authors and funding
27 authors at 15 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance. Methods: Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes. Results: The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage. Conclusions: Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.