Machine learning-based insights into circulating autoantibody dynamics and treatment outcomes in patients with NSCLC receiving immune checkpoint inhibitors.

ABSTRACT:

Introduction

Immune checkpoint inhibitors (ICIs) targeting the programmed death-1/ligand-1 (PD-1/PD-L1) axis have significantly improved treatment outcomes in non-small cell lung cancer (NSCLC); however, challenges remain owing to the limited durability of therapeutic responses and the occurrence of immune-related adverse events (irAEs). This study aimed to characterize dynamic changes in the circulating autoantibody (CAAB) profile during ICI treatment and explore their association with treatment outcomes in patients with NSCLC.

Methods

A panel of 59 CAABs showing substantial treatment-related changes was initially identified using AlphaScreen assays in a primary screening of five patients who developed ir-pneumonitis. These CAABs were subsequently profiled in paired pre-and

SUBMITTER: Wei F 

PROVIDER: S-EPMC12531255 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature