Abstract 407P
Background
Circulating tumor DNA (ctDNA) plays an important role in guiding treatment choice. Our previous study found that the molecular tumor burden index (mTBI) which was based on a comprehensive analysis of somatic variations in ctDNA presented potential therapeutic response and prognosis predictive value in metastatic breast cancer patients treated with chemotherapy or targeted therapy. We aimed to present plasma genomic profiling and explore the prediction role of mTBI for advanced HR+HER2- patients receiving endocrine therapy.
Methods
We retrospectively analysed ctDNA which was quantified in 375 samples collected from 213 patients. 159 samples were collected prior to endocrine therapy. Targeted next-generation sequencing (NGS) of 1021 genes that are frequently mutated in breast cancer and other solid tumors was performed.
Results
The most commonly altered genes included PIK3CA (38%), TP53 (30%), ESR1 (19%), MLL3 (13%) and ERBB2 (8%). Mutations of PI3KCA (45.2% vs. 29.5%), MAP3K1 (9.5% vs. 1.8%), SF3B1 (6.2% vs. 0%), PIK3R1 (5.2% vs. 0%) and NOTCH2 (4.3% vs. 0%) are more frequently occurring in patients receiving at least two lines endocrine therapy. Patients with brain metastasis showed a higher frequency of RB1 mutation (16.7% vs. 4.6%). ESR1 was more frequently detected in patients with liver (25.5% vs. 12.8%) and bone metastasis (23.4% vs. 10.4%). As for genetic interactions, FOXA1mut-MLL3mut, TP53mut-PI3KCAmut and MAP3K1mut-MLL3mut were found co-occurrence exist. ESR1mut-ERBB2mut was found mutual exclusivity. Patients treated with endocrine therapy with baseline high mTBI presented worse progression-free survival (PFS) (3.4 vs.5.6 months, HR 1.4, 95% CI 1.2 - 1.7, p < 0.001), overall survival (OS) (14.2 vs.38.4 months, HR 1.7, 95% CI 1.4 - 2.1, p < 0.001) and disease control rate (DCR) (50.6% vs. 69.4%, p = 0.015), no matter receiving mono or combined endocrine therapy. High mTBI was significantly associated with worse PFS and OS even after multivariate analysis.
Conclusions
Our study presents a comprehensive mutational landscape of advanced HR+HER2- breast cancer patients. mTBI may be a potential biomarker for the prediction of treatment response and prognosis in HR+HER2- patients treated with endocrine therapy.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
545P - HIBRID: Histology and ct-DNA based risk-stratification with deep learning
Presenter: Chiara Loeffler
Session: Poster session 15
546P - An artificial intelligence system integrating deep learning-proteomics, pathomics and clinicopathological features to determine risk of T1 colorectal cancer metastasis to lymph node
Presenter: Yijiao Chen
Session: Poster session 15