Abstract PS2-09-02: Neutrophil extracellular traps signature to predict pathological complete response in patients with triple negative breast cancer after neoadjuvant systemic therapy

Abstract BACKGROUND: While neoadjuvant systemic therapy has improved outcomes in triple-negative breast cancer (TNBC), patients who do not achieve a pathological complete response (pCR) remain at high risk of recurrence and poor survival. As pCR is a surrogate marker for long-term outcomes and a key endpoint in early-stage TNBC trials, identifying patients unlikely to achieve pCR is critical for optimizing therapy. There is an unmet need for predictive biomarkers to guide treatment decisions. Neutrophils, abundant in the tumor microenvironment, form neutrophil extracellular traps (NETs), which are reported to have a context-dependent role in promoting or suppressing tumor progression and metastasis. We hypothesize that a NET-related gene signature predicts pCR following neoadjuvant systemic therapy in TNBC. Our primary objective is to develop and externally validate a NET-based predictive score using publicly available transcriptomic datasets in TNBC. MATERIALS AND METHODS: We used a transcriptomic dataset (GSE1238545) of baseline pretreatment tumor biopsies from patients with TNBC who underwent neoadjuvant systemic therapy to develop a transcriptome-based NET-related gene score, termed “TNBC-NET score” (training cohort). Differentially expressed genes (DEGs) between pCR and non-pCR groups were identified using a false discovery rate (FDR) 0.1 and log2 fold change≥0.3 as cut-off. The TNBC-NET score was externally validated in an independent TNBC transcriptomic dataset (GSE164458; validation cohort). Logistic regression model was used to assess the association between the TNBC-NET score and pCR. Fisher’s exact test was used to compare categorical variables. Gene set enrichment analysis (GSEA) was performed to identify pathways significantly enriched between high and low TNBC-NET score groups. Results: Among 131 previously reported NET-related genes, 13 were significantly upregulated in patients who achieved pCR (n=16) compared to those who did not (n=23) in the training cohort. A TNBC-NET score was calculated for each patient based on the expression of these 13 genes. In logistic regression models treating the TNBC-NET score as a continuous variable, a higher score was significantly associated with increased likelihood of pCR in both the training (n=39; odds ratio OR: 4.13, 95% confidence interval CI: 1.06-16.1, p=0.04) and validation (n=160; OR: 3.22, 95% CI: 1.52-6.80, p=0.002) cohorts. When the validation cohort was stratified into high and low TNBC-NET score groups using the median as the cutoff, the pCR rate was significantly higher in the high-score group compared to the low-score group (71.7% vs. 43.3%, p=0.003). Gene set enrichment analysis (GSEA) revealed that the epithelial-mesenchymal transition (EMT) pathway was enriched in tumors from the low TNBC-NET score group, which was associated with a lower likelihood of achieving pCR. Conclusions: We developed and validated a 13-gene TNBC-NET score predictive of pCR following neoadjuvant systemic therapy in TNBC. The EMT pathway was enriched in patients with low TNBC-NET scores, suggesting a potential role in treatment resistance. The TNBC-NET score may serve as a clinically actionable biomarker to guide personalized treatment and risk-adapted clinical trial enrollment aimed at improving pCR rates. Prospective studies are warranted to validate its utility and investigate resistance mechanisms in TNBC-NET score low group. Citation Format: T. Fujii, S. You, H. Furuya, M. Nomura, M. Muto. Neutrophil extracellular traps signature to predict pathological complete response in patients with triple negative breast cancer after neoadjuvant systemic therapy abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS2-09-02.