Validation of a multiomic model of plasma extracellular vesicle PD-L1 and radiomics for prediction of response to immunotherapy in NSCLC

Background Immune-checkpoint inhibitors (ICIs) have showed unprecedent efficacy in the treatment of patients with advanced non-small cell lung cancer (NSCLC). However, not all patients manifest clinical benefit due to the lack of reliable predictive biomarkers. We showed preliminary data on the pred...

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Veröffentlicht in:Journal of experimental & clinical cancer research Jg. 43; H. 1; S. 81 - 6
Hauptverfasser: de Miguel‑Perez, Diego, Ak, Murat, Mamindla, Priyadarshini, Russo, Alessandro, Zenkin, Serafettin, Ak, Nursima, Peddagangireddy, Vishal, Lara‑Mejia, Luis, Gunasekaran, Muthukumar, Cardona, Andres F., Naing, Aung, Hirsch, Fred R., Arrieta, Oscar, Colen, Rivka R., Rolfo, Christian
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 15.03.2024
BioMed Central Ltd
Springer Nature B.V
BMC
Schlagworte:
Apoptosis
Biomarker
Biomarkers
Biomedical and Life Sciences
Biomedicine
Biopsy
Cancer
Cancer Research
Cancer therapies
Care and treatment
Chemotherapy
Clinical trials
Commentary
Comparative analysis
Extracellular vesicle PD-L1
Extracellular vesicles
Immune-checkpoint inhibitors
Immunology
Immunotherapy
Liquid biopsy
Lung cancer
Lung cancer, Non-small cell
Medical colleges
Medical imaging
Non-small cell lung cancer
Oncology
Performance evaluation
Radiomics
Tomography
Liquid biopsy
Biomarker
Extracellular vesicle PD-L1
Non-small cell lung cancer
Immune-checkpoint inhibitors
Radiomics
ISSN:1756-9966, 0392-9078, 1756-9966
Online-Zugang:Volltext
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Zusammenfassung:Background Immune-checkpoint inhibitors (ICIs) have showed unprecedent efficacy in the treatment of patients with advanced non-small cell lung cancer (NSCLC). However, not all patients manifest clinical benefit due to the lack of reliable predictive biomarkers. We showed preliminary data on the predictive role of the combination of radiomics and plasma extracellular vesicle (EV) PD-L1 to predict durable response to ICIs. Main body Here, we validated this model in a prospective cohort of patients receiving ICIs plus chemotherapy and compared it with patients undergoing chemotherapy alone. This multiparametric model showed high sensitivity and specificity at identifying non-responders to ICIs and outperformed tissue PD-L1, being directly correlated with tumor change. Short conclusion These findings indicate that the combination of radiomics and EV PD-L1 dynamics is a minimally invasive and promising biomarker for the stratification of patients to receive ICIs.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Commentary-1
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ObjectType-Correspondence-1
ISSN:1756-9966
0392-9078
1756-9966
DOI:10.1186/s13046-024-02997-x