TY - JOUR
T1 - Validation of a multiomic model of plasma extracellular vesicle PD-L1 and radiomics for prediction of response to immunotherapy in NSCLC
AU - de Miguel‑Perez, Diego
AU - Ak, Murat
AU - Mamindla, Priyadarshini
AU - Russo, Alessandro
AU - Zenkin, Serafettin
AU - Ak, Nursima
AU - Peddagangireddy, Vishal
AU - Lara‑Mejia, Luis
AU - Gunasekaran, Muthukumar
AU - Cardona, Andres F.
AU - Naing, Aung
AU - Hirsch, Fred R.
AU - Arrieta, Oscar
AU - Colen, Rivka R.
AU - Rolfo, Christian
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - 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.
AB - 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.
KW - Biomarker
KW - Extracellular vesicle PD-L1
KW - Immune-checkpoint inhibitors
KW - Liquid biopsy
KW - Non-small cell lung cancer
KW - Radiomics
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U2 - 10.1186/s13046-024-02997-x
DO - 10.1186/s13046-024-02997-x
M3 - Comment/debate
C2 - 38486328
AN - SCOPUS:85187914402
SN - 0392-9078
VL - 43
JO - Journal of Experimental and Clinical Cancer Research
JF - Journal of Experimental and Clinical Cancer Research
IS - 1
M1 - 81
ER -