TY - JOUR
T1 - A Serum Protein Classifier Identifying Patients with Advanced Non–Small Cell Lung Cancer Who Derive Clinical Benefit from Treatment with Immune Checkpoint Inhibitors
AU - Muller, Mirte
AU - Hummelink, Karlijn
AU - Hurkmans, Daan P.
AU - Niemeijer, Anna-Larissa N.
AU - Monkhorst, Kim
AU - Roder, Joanna
AU - Oliveira, Carlos
AU - Roder, Heinrich
AU - Aerts, Joachim G.
AU - Smit, Egbert F.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - Purpose: Pretreatment selection of patients with non–small cell lung cancer (NSCLC) who would derive clinical benefit from treatment with immune checkpoint inhibitors (CPIs) would fulfill an unmet clinical need by reducing unnecessary toxicities from treatment and result in substantial health care savings. Experimental Design: In a retrospective study, mass spectrometry (MS)-based proteomic analysis was performed on pretreatment sera derived from patients with advanced NSCLC treated with nivolumab as part of routine clinical care (n ¼ 289). Machine learning combined spectral and clinical data to stratify patients into three groups with good (“sensitive”), intermediate, and poor (“resistant”) outcomes following treatment in the second-line setting. The test was applied to three independent patient cohorts and its biology was investigated using protein set enrichment analyses (PSEA). Results: A signature consisting of 274 MS features derived from a development set of 116 patients was associated with
AB - Purpose: Pretreatment selection of patients with non–small cell lung cancer (NSCLC) who would derive clinical benefit from treatment with immune checkpoint inhibitors (CPIs) would fulfill an unmet clinical need by reducing unnecessary toxicities from treatment and result in substantial health care savings. Experimental Design: In a retrospective study, mass spectrometry (MS)-based proteomic analysis was performed on pretreatment sera derived from patients with advanced NSCLC treated with nivolumab as part of routine clinical care (n ¼ 289). Machine learning combined spectral and clinical data to stratify patients into three groups with good (“sensitive”), intermediate, and poor (“resistant”) outcomes following treatment in the second-line setting. The test was applied to three independent patient cohorts and its biology was investigated using protein set enrichment analyses (PSEA). Results: A signature consisting of 274 MS features derived from a development set of 116 patients was associated with
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85093892179&origin=inward
UR - https://www.ncbi.nlm.nih.gov/pubmed/32631957
U2 - https://doi.org/10.1158/1078-0432.CCR-20-0538
DO - https://doi.org/10.1158/1078-0432.CCR-20-0538
M3 - Article
C2 - 32631957
SN - 1078-0432
VL - 26
SP - 5188
EP - 5197
JO - Clinical Cancer Research
JF - Clinical Cancer Research
IS - 19
ER -