Abstract P5-05-08: Dual ctDNA and tissue sequencing improves detection of actionable variants in breast cancer patients
Authors: Mackay Matthew , Manghnani Kabir , Hockenberry Adam , Drews Joshua , Chen James , Ben-Shachar Rotem , Guinney Justin 
Published: March 2023

Background: Next-generation sequencing of circulating tumor DNA (ctDNA) and solid-tissue can identify clinically actionable genomic variants that may be used for both treatment selection and disease surveillance. Due to differences in tumor biology and assay design, ctDNA and solid biopsies may identify unique variants. Here, we investigate a real-world dataset of breast cancer patients to determine whether clinically actionable variant detection is enhanced by dual ctDNA and solid tissue testing. Methods: We used the deidentified Tempus Lens database to retrospectively analyze stage IV breast cancer patients with known hormonal subtype. Each patient had dual testing defined as Tempus xF (ctDNA) and Tempus xT (tumor tissue)—which resulted in clinical reports for both tests. Patients were further stratified according to the timing of ctDNA biopsy relative to tissue biopsy. Concurrent dual testing was defined as samples collected ≤30 days apart and longitudinal dual testing was defined as liquid &gt;30 days after solid. Variants were included in analyses if they met the limit of detection criteria of both assays. Clinical actionability was defined by indication-matched OncoKB Level 1-3. Fisher exact test was used to calculate significance. Results: Of the 1,341 breast cancer patients with dual ctDNA and tissue sequencing, at least one actionable variant was identified in 61% (n=823) of patients. In the subset of concurrent tested patients (n=782), 60% (n=473) had one or more actionable findings: 54% (n=257/473) of patients with actionable variants had perfectly concordant variants, 29% (n=136/473) had at least one unique variant detected only by solid tumor testing, and 20% (n=93/473) had at least one unique variant detected only by ctDNA testing. Similarly, in the longitudinal set (n=559), 63% (n=350) had one or more actionable findings: 34% (n=118/350) were concordant, 43% (n=150/350) were unique to solid, and 27% (n=96/350) were unique to ctDNA. When stratifying concurrent patients by OncoKB levels of evidence, 72% (n=98/136) of patients with variants unique in solid had at least one level 1-2 variant, while 39% (n=53/136) contained unique level 3 variants. Level 1-2 variants in PIK3CA were the most frequent variants seen uniquely in solid tumors, occurring in 54% (n=73/136) of patients. In contrast, in patients with unique ctDNA variants, 37% (n=34/93) of patients had at least one level 1-2 variants and 72% (n=67/93) had level 3 variants. Level 3 variants in ESR1 were the most frequent variants seen uniquely in ctDNA, occurring in 57% (n=53/93) of patients. The proportion of concurrent patients with actionable variants found exclusively in ctDNA significantly differed by subtype (p=0.04): Luminal A (22%) and Luminal B (23%) contained the most patients with unique ctDNA variants. This ability to detect additional variants in ctDNA remained true even if profiling occurred over time. Indeed, in patients with ESR1 variants tested with ctDNA &gt; 1 year after tissue, 78% (n=43/55) had ESR1 variants only detected in blood. Conclusions: We show that dual testing in breast cancer patients improves the identification of clinically actionable variants which may be missed by either ctDNA or solid tissue biopsy alone. Adoption of dual testing should be considered as standard practice to provide a comprehensive view of actionable molecular alterations.

Citation Format: Matthew Mackay, Kabir Manghnani, Adam Hockenberry, Joshua Drews, James Chen, Rotem Ben-Shachar, Justin Guinney. Dual ctDNA and tissue sequencing improves detection of actionable variants in breast cancer patients [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-05-08.