Abstract 3608: Molecular fingerprint sequencing for minimal residual disease detection in breast cancer

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Abstract Introduction: The substantial majority of breast cancers present with early-stage disease, although micro-metastatic disease may be established at the time of diagnosis and may ultimately result in metastatic disease recurrence. Prior studies have shown that analysis of circulating tumour DNA (ctDNA) can detect micro-scopic minimal residual disease (MRD) serving as biomarker to anticipate future cancer recurrence, although sensitivity of current assays is limited. We present a novel molecular fingerprint ctDNA assay that exploits tumour whole genome sequencing (WGS) to develop highly personalised assays. Methods: WGS was conducted on paired tumor and germline DNA from 11 early breast cancer patients to identify tumour specific small indels (SIs) to track in plasma as individual molecular fingerprints. Patient-specific amplicon-based panels were designed and validated to identify somatic reporters with no sequencing background. DNA was extracted from plasma samples taken at pre-surgery (baseline), post-surgery, and every 3 months until 1 year and every 6 months thereafter, and sequenced to 100,000X. Results: Molecular fingerprint assays were demonstrated to detect less than a single cancer genome, with undetectable background in control samples. Using plasma samples from patients with early stage breast cancer, we detected ctDNA in 80% of the baseline plasma time-points with 100% specificity (95% confidence limits (CI) 98.7%-100%). ctDNA was detected in all patients prior to relapse, with an observed lead-time of 15.5 months, substantially improved compared with previous techniques, detecting residual disease that was not detectable by tracking mutations using digital PCR. Conclusions: This proof-of-principle study demonstrates that tumor-specific molecular fingerprints combined with ultra-deep plasma DNA sequencing have the potential to transform MRD detection. Identifying those patients who have undetectable recurrence would pave the way for identifying who is cured by surgery alone and who requires further therapy. Citation Format: Iñaki Comino-Mendez, Ros Cutts, Isaac García-Murillas, Neha Chopra, Maria Afentakis, Abigail Evans, Duncan Wheatley, Anthony Skene, Simon Russell, Mohini Varughese, Mitch Dowsett, Ian E. Smith, Nick Turner. Molecular fingerprint sequencing for minimal residual disease detection in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3608.