Ibiayi Dagogo-Jack1, Marguerite Rooney1, Rebecca J Nagy2, Jessica J Lin1, Emily Chin1, Lorin A Ferris1, Jennifer Ackil1, Jochen K Lennerz3, Richard B Lanman2, Justin F Gainor1, Alice T Shaw4. 1. Massachusetts General Hospital Cancer Center and Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts. 2. Guardant Health, Inc., Redwood City, California. 3. Department of Molecular Pathology, Massachusetts General Hospital, Boston, Massachusetts. 4. Massachusetts General Hospital Cancer Center and Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts. Electronic address: ashaw1@mgh.harvard.edu.
Abstract
INTRODUCTION: Circulating tumor DNA analysis is an emerging genotyping strategy that can identify tumor-specific genetic alterations in plasma including mutations and rearrangements. Detection of ROS1 fusions in plasma requires genotyping approaches that cover multiple breakpoints and target a variety of fusion partners. Compared to other molecular subsets of NSCLC, experience with detecting ROS1 genetic alterations in plasma is limited. METHODS: To describe the spectrum of ROS1 fusions in NSCLC and determine sensitivity for detecting ROS1 fusions in plasma, we queried the Guardant Health plasma dataset and an institutional tissue database and compared plasma findings to tissue results. In addition, we used the Guardant360 NGS assay to detect potential genetic mediators of resistance in plasma from patients with ROS1-positive NSCLC who were relapsing on crizotinib. RESULTS: We detected seven distinct fusion partners in plasma, most of which (n = 6 of 7) were also represented in the tissue dataset. Fusions pairing CD74 with ROS1 predominated in both cohorts (plasma: n = 35 of 56, 63%; tissue: n = 26 of 52, 50%). There was 100% concordance between the specific tissue- and plasma-detected ROS1 fusion for seven patients genotyped with both methods. Sensitivity for detecting ROS1 fusions in plasma at relapse on ROS1-directed therapy was 50%. Six (33%) of 18 post-crizotinib plasma specimens harbored ROS1 kinase domain mutations, five of which were ROS1 G2032R. Two (11%) post-crizotinib plasma specimens had genetic alterations (n = 1 each BRAF V600E and PIK3CA E545K) potentially associated with ROS1-independent signaling. CONCLUSIONS: Plasma genotyping captures the spectrum of ROS1 fusions observed in tissue. Plasma genotyping is a promising approach to detecting mutations that drive resistance to ROS1-directed therapies.
INTRODUCTION: Circulating tumor DNA analysis is an emerging genotyping strategy that can identify tumor-specific genetic alterations in plasma including mutations and rearrangements. Detection of ROS1 fusions in plasma requires genotyping approaches that cover multiple breakpoints and target a variety of fusion partners. Compared to other molecular subsets of NSCLC, experience with detecting ROS1 genetic alterations in plasma is limited. METHODS: To describe the spectrum of ROS1 fusions in NSCLC and determine sensitivity for detecting ROS1 fusions in plasma, we queried the Guardant Health plasma dataset and an institutional tissue database and compared plasma findings to tissue results. In addition, we used the Guardant360 NGS assay to detect potential genetic mediators of resistance in plasma from patients with ROS1-positive NSCLC who were relapsing on crizotinib. RESULTS: We detected seven distinct fusion partners in plasma, most of which (n = 6 of 7) were also represented in the tissue dataset. Fusions pairing CD74 with ROS1 predominated in both cohorts (plasma: n = 35 of 56, 63%; tissue: n = 26 of 52, 50%). There was 100% concordance between the specific tissue- and plasma-detected ROS1 fusion for seven patients genotyped with both methods. Sensitivity for detecting ROS1 fusions in plasma at relapse on ROS1-directed therapy was 50%. Six (33%) of 18 post-crizotinib plasma specimens harbored ROS1 kinase domain mutations, five of which were ROS1G2032R. Two (11%) post-crizotinib plasma specimens had genetic alterations (n = 1 each BRAFV600E and PIK3CAE545K) potentially associated with ROS1-independent signaling. CONCLUSIONS: Plasma genotyping captures the spectrum of ROS1 fusions observed in tissue. Plasma genotyping is a promising approach to detecting mutations that drive resistance to ROS1-directed therapies.
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