Work

Mapping the genetic–transcriptional landscape of thyroid irAEs in sintilimab therapy: toward biomarker-guided immunotoxicity prediction

Year: 2025

Type: article

Abstract: Objective: By integrating whole-genome resequencing (WGR) with longitudinal transcriptomic profiling, this study aimed to unravel the genetic-transcriptional regulatory network underlying thyroid immune-related adverse events (irAEs) in non-small cell lung cancer (NSCLC) patients treated with sintilimab. A key objective was to identify molecular biomarkers with predictive and therapeutic relevance. Methods: This prospective study included NSCLC patients receiving sintilimab, from whom peripheral blood samples were collected at three time points: baseline, post-first treatment, and post-second treatment. RNA sequencing (RNA-seq) and 30× WGR were performed. Differential gene expression analysis was conducted on the RNA-seq data, followed by longitudinal consistency filtering using the Longitudinal Concordant Gene Intersection (LCGI) algorithm to identify robust differentially expressed genes (DEGs). These DEGs underwent downstream integration with protein-protein interaction (PPI) network analysis and cis-expression quantitative trait loci (cis-eQTL) mapping to pinpoint key genes and regulatory single-nucleotide polymorphisms (SNPs) associated with thyroid irAEs. Results: The LCGI algorithm identified 13 DEGs exhibiting sustained directional shifts across treatment timepoints. Integration with conventional DEG signatures revealed a functionally cohesive module, with C1QA/B/C, FLT1, TEK, PDGFRB, SPP1, and HLA-DPB1 emerging as central regulators of thyroid irAEs. Cis-eQTL mapping identified 500 SNPs with significant cis-regulatory effects on 153 genes. A "C3 complement-matrix axis" was uncovered as a pivotal node, promoting macrophage polarization toward a pro-inflammatory phenotype. Based on the refined PPI network, we proposed a cascading pathological model in which a self-sustaining feedback loop drove progressive and irreversible thyroid autoimmunity. Conclusion: This study established a genetic-transcriptional regulatory framework for sintilimab-induced thyroid irAEs and identified a candidate gene set with biomarker potential. Our findings highlighted the central role of complement-driven mechanisms, providing a foundation for precision risk prediction and targeted intervention strategies that preserve antitumor efficacy while mitigating autoimmune toxicity.

Source: Frontiers in Immunology

DOI: 10.3389/fimmu.2025.1671594