Neutrophil Extracellular Traps as Predictive Biomarkers in Trastuzumab-Treated HER2-Positive Breast Cancer: A Prospective Cohort Study.

Abstract

Neutrophil extracellular traps (NETs) have been implicated in cancer progression and therapy resistance, but their value as predictive biomarkers in HER2-positive breast cancer remains unclear. In this prospective cohort study, we measured circulating myeloperoxidase-DNA (MPO-DNA) complexes as a surrogate marker of NETs in patients with HER2-positive breast cancer receiving adjuvant trastuzumab-based therapy. Serial blood samples were collected at baseline and during treatment, and patients were classified as having progressive disease (PD) or disease control (DC). Baseline NETs, CEA, and CA15-3 levels were significantly higher in patients with PD compared to those with DC. Longitudinal analysis revealed a significant Group × Time interaction, with NETs decreasing in the DC group but increasing in the PD group over the course of treatment. In Firth-penalized logistic regression, higher baseline NETs were independently associated with increased odds of progression (OR per 1-U/L increase, 1.026; 95% CI, 1.004-1.048; p = 0.023). An exploratory NETs cutoff of 97.32 U/L stratified patients into low- and high-NETs groups with significantly different progression-free survival (log-rank p = 0.045); continuous NETs remained associated with shorter PFS in multivariable Cox models adjusted for CEA and CA15-3 (HR per 1-U/L increase, 1.018; 95% CI, 1.003-1.033; p = 0.021). Bootstrap internal validation yielded an optimism-corrected C-index of 0.739 (95% CI, 0.613-0.866). Adding CEA and CA15-3 to NETs improved risk reclassification (NRI = 0.931; p = 0.018) and discrimination (IDI = 0.146; p < 0.001), although the increase in AUC was not statistically significant by DeLong's test. Tissue MPO fluorescence correlated with circulating MPO-DNA even after controlling for disease group. These findings suggest that NETs are associated with trastuzumab efficacy and may serve as adjunctive biomarkers for risk stratification, but the modest sample size, exploratory cutoffs, and single-center design warrant validation in larger prospective cohorts before any clinical application.