Kurtis D Davies1, Anh T Le2, Jamie Sheren1, Hala Nijmeh1, Katherine Gowan3, Kenneth L Jones3, Marileila Varella-Garcia4, Dara L Aisner1, Robert C Doebele5. 1. Department of Pathology, University of Colorado - Anschutz Medical Campus, Aurora, Colorado. 2. Department of Medicine - Division of Medical Oncology, University of Colorado - Anschutz Medical Campus, Aurora, Colorado. 3. Department of Pediatrics - Section of Hematology, Oncology, and Bone Marrow Transplant, University of Colorado - Anschutz Medical Campus, Aurora, Colorado. 4. Department of Pathology, University of Colorado - Anschutz Medical Campus, Aurora, Colorado; Department of Medicine - Division of Medical Oncology, University of Colorado - Anschutz Medical Campus, Aurora, Colorado. 5. Department of Medicine - Division of Medical Oncology, University of Colorado - Anschutz Medical Campus, Aurora, Colorado. Electronic address: robert.doebele@ucdenver.edu.
Abstract
INTRODUCTION: ROS1 gene fusions are a well-characterized class of oncogenic driver found in approximately 1% to 2% of NSCLC patients. ROS1-directed therapy in these patients is more efficacious and is associated with fewer side effects compared to chemotherapy and is thus now considered standard-of-care for patients with advanced disease. Consequently, accurate detection of ROS1 rearrangements/fusions in clinical tumor samples is vital. In this study, we compared the performance of three common molecular testing approaches on a cohort of ROS1 rearrangement/fusion-positive patient samples. METHODS: Twenty-three ROS1 rearrangement/fusion-positive clinical samples were assessed by at least two of the following molecular testing methodologies: break-apart fluorescence in situ hybridization, DNA-based hybrid capture library preparation followed by next-generation sequencing (NGS), and RNA-based anchored multiplex polymerase chain reaction library preparation followed by NGS. RESULTS: None of the testing methodologies demonstrated 100% sensitivity in detection of ROS1 rearrangements/fusions. Fluorescence in situ hybridization results were negative in 2 of 20 tested samples, the DNA-based NGS assay was negative in 4 of 18 tested samples, and the RNA-based NGS assay was negative in 3 of 19 tested samples. For all three testing approaches, we identified assay characteristics that likely contributed to false-negative results. Additionally, we report that genomic breakpoints are an unreliable predictor of breakpoints at the transcript level, likely due to alternative splicing. CONCLUSIONS: ROS1 rearrangement/fusion detection in the clinical setting is complex and all methodologies have inherent limitations of which users must be aware to correctly interpret results.
INTRODUCTION:ROS1 gene fusions are a well-characterized class of oncogenic driver found in approximately 1% to 2% of NSCLCpatients. ROS1-directed therapy in these patients is more efficacious and is associated with fewer side effects compared to chemotherapy and is thus now considered standard-of-care for patients with advanced disease. Consequently, accurate detection of ROS1 rearrangements/fusions in clinicaltumor samples is vital. In this study, we compared the performance of three common molecular testing approaches on a cohort of ROS1 rearrangement/fusion-positive patient samples. METHODS: Twenty-three ROS1 rearrangement/fusion-positive clinical samples were assessed by at least two of the following molecular testing methodologies: break-apart fluorescence in situ hybridization, DNA-based hybrid capture library preparation followed by next-generation sequencing (NGS), and RNA-based anchored multiplex polymerase chain reaction library preparation followed by NGS. RESULTS: None of the testing methodologies demonstrated 100% sensitivity in detection of ROS1 rearrangements/fusions. Fluorescence in situ hybridization results were negative in 2 of 20 tested samples, the DNA-based NGS assay was negative in 4 of 18 tested samples, and the RNA-based NGS assay was negative in 3 of 19 tested samples. For all three testing approaches, we identified assay characteristics that likely contributed to false-negative results. Additionally, we report that genomic breakpoints are an unreliable predictor of breakpoints at the transcript level, likely due to alternative splicing. CONCLUSIONS:ROS1 rearrangement/fusion detection in the clinical setting is complex and all methodologies have inherent limitations of which users must be aware to correctly interpret results.
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