Machine Learning-based Exceptional Response Prediction of Nivolumab Monotherapy with Circulating MicroRNAs in Non-Small Cell Lung Cancer

Detecting cancer patients with exceptional response to immune check-point inhibition therapy is necessary to improve the treatment. This study demonstrated machine learning models that utilize both microRNA expression and clinical information achieved much higher sensitivity and accuracy in identifying Exceptional-responder to nivolumab monotherapy when comparing to conventional method only using companion PD-L1 testing. This case control study profiled circulating microRNA expressions of 213 non-small cell lung cancer (NSCLC) patients treated with nivolumab monotherapy to identify patients with exceptional response.