Integrating dynamic analysis of serial ctDNA testing to enhance diagnostic and prognostic assessments in patients with metastatic breast cancer.

Abstract

1042 Background: The monitoring of circulating tumor DNA (ctDNA) in patient with metastatic breast cancer (MBC) plays a critical role in predicting therapy resistance, metastasis, and prognosis. Our previous studies have highlighted the importance of dynamic ctDNA analysis correlated with treatment resistance and prognosis in MBC (ASCO 2022 (#1057), AACR 2023 (#1031), and CCR Zhang Q., 2024). Here, we report that multivariable analysis of ctDNA mutations including P53, Myc, and BRAF, provides a significantly greater prognostic impact on survival. Methods: This study included 391 MBC patients who received systemic treatment between 2016 and 2022 (IRB-approved non-interventional trial, NU16B06) at the Robert H. Lurie Cancer Center, Northwestern University. Blood samples (15 ml each) were collected from patients at 3 time points: before treatment, and 3 and 6 months after treatment. Plasma ctDNA was analyzed by Guardant 360 using NGS for a 74-gene panel. The median follow-up was 26.6 months since enrollment. Causal Inference-Ensemble Learning was used for statistical analyses. Results: Among 391 patients (54.4% Luminal-like, 17.7% HER2-positive, 27.9% Triple-negative), the most common ctDNA mutations were TP53 Mut (160 patients, 40.92%), PIK3CA Mut (39 patients, 29.4%), and Myc Mut (53 patients, 13.55%) at any time point. Other notable mutations included HER2 Mut (49 patients, 12.5%), FGFR1 Mut (45 patients, 11.5%), PTEN Mut (39 patients, 9.9%), and BRAF Mut (35 patients, 8.95%). Less frequent mutations were FGFR2 Mut (13 patients, 3.3%), MAPK Mut (8 patients, 2.0%), BRCA1 Mut (20 patients, 5.1%), BRCA2 Mut (17 patients, 4.3%), and CDH1 Mut (21 patients, 5.37%). Patients in mutation groups showed significantly shorter median overall survival (OS) compared to wild-type groups: TP53 Mut vs TP53 WT , Hazard Ratio (HR) = 1.91 (P = 0.0002); Myc Mut vs Myc WT , HR = 3.24 (P < 0.0001); and BRAF Mut vs BRAF WT , HR = 2.45 (P = 0.007). No significant correlations were found between other gene mutations and OS. Analysis of multiple ctDNA mutations (TP53, Myc, and BRAF) revealed significant prognostic differences. Cohort 1 (no mutations, 231 patients) had a significantly longer median OS of 32.2 months compared to 20.5 months in cohort 2 (at least one mutation, 119 patients) and 15.3 months in cohort 3 (two or more mutations, 59 patients). Cohort 3 exhibited the worst prognosis compared to both cohort 1 and cohort 2 (Chi-square = 13.3, P = 0.0003). These findings suggest that combined analysis of ctDNA mutations enhances the ability to predict prognosis. Conclusions: In this study, we identified multiple ctDNA mutations during long-term follow-up, which are associated with prognosis. The synergy of multivariable analysis of ctDNA mutations during treatment enhances the role of single ctDNA alterations in monitoring metastatic prognosis, thereby supporting clinical decision-making.