Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 24, Issue 15, Pages -Publisher
MDPI
DOI: 10.3390/ijms241511887
Keywords
immunotherapy; immune checkpoint inhibitors; non-small cell lung cancer; PD-L1; predictive biomarkers
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Lung cancer has the highest mortality rate among all cancer types, with over 1.8 million deaths annually. Immunotherapy using immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). PD-L1 expression is currently the established biomarker for predicting ICI response, but alternative biomarkers are being developed and validated to improve classification of responders and non-responders to ICI therapy.
Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.
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