Observational studyJCO precision oncology2024
Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer.
Observational study in JCO precision oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04056247 (PROPHETIC - Predicting Responsiveness in Oncology Patients Based on Host Response Evaluation During Anti Cancer Treatments), which is not on this map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
PROPHETIC - Predicting Responsiveness in Oncology Patients Based on Host Response Evaluation During Anti Cancer Treatments
Who cites it
23 citing papers in PubMed, 15 citations in OpenAlex.
- Towards liquid biopsy-based analysis of antitumour immunity.Nature reviews. Clinical oncology · 2026Review
- Bridging the gap: A systematic approach to integrating serum and plasma proteomic datasets for biomarker studies.Journal of pharmaceutical and biomedical analysis · 2026Article
- Circulating proteins as biomarkers of response to cancer immunotherapy (Review).International journal of oncology · 2026Review
- Blood-based kinase activity profiling to predict response to immune checkpoint inhibitors in patients with advanced stage NSCLC: the prospective IOpener study.Journal for immunotherapy of cancer · 2026Article
- PD-1 Blockade-Induced DKK1 Expression by CD8+ T Cells Promotes Blood-Brain Barrier Permeabilization.Cancer discovery · 2026Article
- Article
- LANTERN-XGB: An Interpretable Multi-Modal Machine Learning for Improving Clinical Decision-Making in Lung Cancer.International journal of molecular sciences · 2026Article
- A Mitochondrial Plasma Proteomic Signature Identifies Metastatic Chromophobe Renal Cell Carcinoma.Cancers · 2026Article
- Blood Based Biomarkers for Predicting Treatment Response to Immune Checkpoint Inhibitors After EGFR-TKI Resistance in Non-Small Cell Lung Cancer.Thoracic cancer · 2026Article
- Discovery of predictive biomarkers for cancer therapy through computational approaches.Nature reviews. Clinical oncology · 2026Review
- Deep-Learning Serial CT Prediction of Survival in Immunotherapy-Treated Non-Small Cell Lung Cancer.JAMA network open · 2026Article
- Multi-omics biomarkers for predicting resistance, hyperprogression, and immune-related toxicity during PD-1/PD-L1 therapy in lung cancer: a literature review.Frontiers in immunology · 2026Review
- Integrating chemokine signatures and multi-omic biomarkers to predict immunotherapy response in non-small cell lung cancer: a comprehensive narrative review.Frontiers in oncology · 2026Review
- Liquid biopsies for detection, characterization, and interception of therapy resistance in thoracic malignancies.Frontiers in oncology · 2026Review
- Emerging Predictive Biomarkers of Immunotherapy Sensitivity in Patients with Non-Small Cell Lung Cancer.ImmunoTargets and therapy · 2026Review
- Prospective proteomics for discovering biomarkers in lung adenocarcinoma: a literature review.Translational cancer research · 2025Review
- Review
- Refining Criteria for Choosing the First-Line Treatment for Real-World Patients with AdvancedInternational journal of molecular sciences · 2025Review
- 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
- Serum analytes as predictors of disease recurrence and the duration of invasive disease-free survival in patients with triple negative breast cancer enrolled in the OXEL trial treated with immunotherapy, chemotherapy, or chemoimmunotherapy.Journal for immunotherapy of cancer · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
37 authors at 20 institutions in 4 countries.
Funding
Abstract
purposeCurrent 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
methodsWe 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.
resultsOur 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 (
conclusionPlasma 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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 OpenQuestion graph.