2023 World Conference on Lung Cancer (Posters)-P1.21. Extracellular Vesicles and Radiomics Predict Durable Response to Immune-Checkpoint Inhibitors in Patients with Non-small Cell Lung Cancer

P1.21. Extracellular Vesicles and Radiomics Predict Durable Response to Immune-Checkpoint Inhibitors in Patients with Non-small Cell Lung Cancer - PDF(Abstract)

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This study aimed to investigate the role of minimally invasive biomarkers in predicting the response to immune-checkpoint inhibitors (ICIs) in patients with non-small cell lung cancer (NSCLC). The commonly used biomarker, tissue PD-L1, has low accuracy, highlighting the need for new biomarkers. The study focused on two biomarkers: plasma extracellular vesicles (EVs) and radiomics.<br /><br />EVs contain immune suppressive factors, including TGF-β, which plays a critical role in the tumor microenvironment. EVs also contain PD-L1, which can inhibit the anti-tumor immune response or bind to specific ICIs antibodies in circulation. Radiomics involves analyzing computerized tomography (CT) images to understand tumor heterogeneity and the microenvironment, showing potential as a predictive biomarker.<br /><br />The study analyzed plasma samples and CT scan images from 27 patients with advanced/metastatic NSCLC. Durable responses were determined using CT scans following RECISTv1.1. The results showed that a lower pre-treatment level of EV TGF-β and a decrease in EV PD-L1 during treatment were associated with a durable response. However, tissue PD-L1 tumor proportion score (TPS) was not predictive.<br /><br />The study identified a model using six specific radiomic features as the most sensitive and accurate biomarker, followed by EV PD-L1. Combining the pre-treatment biomarkers (radiomics and EV TGF-β) achieved high accuracy. Replacing TGF-β with on-treatment ΔEV PD-L1 further improved the accuracy of prediction.<br /><br />The combination of pre-treatment EV TGF-β and radiomics is a potential biomarker for accurately predicting the response to ICIs in NSCLC patients. Additionally, monitoring the dynamics of EV PD-L1 during treatment can increase the sensitivity and accuracy of prediction. If validated, these minimally invasive biomarkers could supplement or surpass the current standard of care, tissue PD-L1, in predicting responders to ICIs.

Asset Subtitle

Diego de Miguel Perez

Meta Tag

Speaker Diego de Miguel Perez

Topic Pathology & Biomarkers: Biomarkers for Immuno-oncology

Keywords

minimally invasive biomarkers

immune-checkpoint inhibitors

non-small cell lung cancer

tissue PD-L1

plasma extracellular vesicles

EVs

radiomics

computerized tomography

durable response

predictive biomarker