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A Serum Protein Classifier Identifying Patients with Advanced Non-Small Cell Lung Cancer Who Derive Clinical Benefit from Treatment with Immune Checkpoint Inhibitors. | LitMetric

AI Article Synopsis

  • The study aims to identify patients with non-small cell lung cancer (NSCLC) who would benefit from immune checkpoint inhibitors, potentially reducing unnecessary treatment side effects and healthcare costs.
  • A mass spectrometry-based proteomic analysis was conducted on serum samples from 289 NSCLC patients treated with nivolumab, using machine learning to classify them into three outcome groups: sensitive, intermediate, and resistant to treatment.
  • The results identified a protein signature linked to better survival outcomes and suggested that proteomic analysis could offer valuable prognostic information for future treatments, warranting further investigation.

Article Abstract

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 ( = 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 progression-free survival (PFS) and overall survival (OS) across two validation cohorts ( = 98 and = 75). In pooled analysis, significantly better OS was demonstrated for "sensitive" relative to "not sensitive" patients treated with nivolumab; HR, 0.58 (95% confidence interval, 0.38-0-87; = 0.009). There was no significant association with clinical factors including PD-L1 expression, available from 133 of 289 patients. The test demonstrated no significant association with PFS or OS in a historical cohort ( = 68) of second-line NSCLC patients treated with docetaxel. PSEA revealed proteomic classification to be significantly associated with complement and wound-healing cascades.

Conclusions: This serum-derived protein signature successfully stratified outcomes in cohorts of patients with advanced NSCLC treated with second-line PD-1 CPIs and deserves further prospective study.

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Source
http://dx.doi.org/10.1158/1078-0432.CCR-20-0538DOI Listing

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