Abstract 91P
Background
Breast cancer is the most common cancer in women worldwide, primarily presenting as hormone receptor (HR)-positive and HER2-negative. Despite improved outcomes with endocrine therapies, disease progression remains a risk, often occurring early in treatment. Current liquid biopsy assays lack the sensitivity required for early molecular profiling. This study introduces an ultra-sensitive ctDNA NGS assay for detailed genomic profiling of breast cancer patients experiencing early progression during endocrine therapy.
Methods
This ongoing study has enrolled 46 patients with advanced HR-positive, HER2-negative breast cancer. Plasma samples were collected after aromatase inhibitor treatment and before starting Fulvestrant. Using PredicineCARE ULTRA, a highly sensitive liquid biopsy assay with a proprietary NGS panel targeting key oncogenic drivers, deep sequencing at over 100,000x coverage enables ultra-sensitive detection of genomic changes, greatly surpassing standard ctDNA NGS assays' typical 20,000x coverage.
Results
Among the 46 patients analyzed, the assay detected 193 somatic mutations, 95 gene copy number variations (CNVs), and an FGFR3 gene fusion. The most frequent mutations, found in at least 20% of patients, included TP53 (33%), PIK3CA (26%), ATM (24%), ESR1 (22%), and BRCA2 (20%). The ultra-sensitive assay identified 31.3% more mutations and 30.1% more CNVs compared to a simulated standard 20,000x ctDNA assay. It excelled at detecting mutations with minor MAF below 0.1% and in patients with low tumor fractions (<1%). The assay also detected 30.7% more PIK3CA and 11.1% more ESR1 variants, with MAFs as low as 0.08% and 0.06%, respectively. The FGFR3-BAIAP2L1 gene fusion was also uniquely detected at a 0.09% MAF.
Conclusions
The ultra-sensitive ctDNA NGS assay outperformed standard liquid biopsy assays in detecting low-frequency mutations and those from samples with low tumor fractions in HR-positive, HER2-negative breast cancer. Its superior detection may help identify patients suitable for targeted therapies like PIK3CA and ESR1 inhibitors, improving early detection of treatment resistance and disease monitoring for more effective personalized treatment strategies.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
H. Tang, C. Jia, F. Xie, Y. Zhang, S. Jia: Financial Interests, Personal, Full or part-time Employment: Huidu. All other authors have declared no conflicts of interest.
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