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(Slides)

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A study investigated the use of plasma extracellular vesicles (EVs) and radiomics as biomarkers to predict the response to immune-checkpoint inhibitors (ICIs) in patients with non-small cell lung cancer (NSCLC). The study found that a combination of pre-treatment EV transforming growth factor-beta (TGF-β) and radiomics can accurately predict the response to ICIs. Additionally, the study showed that monitoring the dynamics of EV programmed death-ligand 1 (PD-L1) during treatment can provide additional information for prediction. This combination of minimally invasive biomarkers in plasma EVs and CT scan images can potentially outperform or complement the current standard of care using tissue PD-L1 to predict responders to ICIs.<br /><br />The study analyzed plasma samples and radiomic features in CT scan images from 27 patients with advanced/metastatic NSCLC receiving ICIs. The levels of PD-L1 and TGF-β in plasma EVs were evaluated, and a total of 400 radiomic features were assessed. Durable responses to treatment were determined by CT scans. The study found that decreasing levels of EV PD-L1 during treatment and lower pre-treatment levels of EV TGF-β were associated with durable response to ICIs. In terms of predictive models, the combination of radiomics and EV TGF-β achieved high accuracy, which was further improved when EV PD-L1 dynamics during treatment were considered.<br /><br />The use of EVs as biomarkers is promising since they can contain immune suppressive factors like TGF-β and can also carry PD-L1. Radiomics, which involves the analysis of CT scan images, can provide information on tumor heterogeneity and the tumor microenvironment. The combination of these biomarkers can offer a non-invasive and accurate way to predict the response to ICIs in NSCLC patients.<br /><br />The study was approved by the Institutional Review Board, and written informed consent was obtained from all patients. The researchers express their gratitude to the patients and supporting institutions.

Asset Subtitle

Diego de Miguel Perez

Meta Tag

Speaker Diego de Miguel Perez

Topic Pathology & Biomarkers: Biomarkers for Immuno-oncology

Keywords

plasma extracellular vesicles

radiomics

biomarkers

immune-checkpoint inhibitors

non-small cell lung cancer

TGF-β

PD-L1

CT scan images

predictive models

tumor heterogeneity