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Halper-Stromberg E, McCall CM, Haley LM, Lin MT, Vogt S, Gocke CD, Eshleman JR, Stevens W, Martinson NA, Epeldegui M, Holdhoff M, Bettegowda C, Glantz MJ, Ambinder RF, Xian RR. CloneRetriever: An Automated Algorithm to Identify Clonal B and T Cell Gene Rearrangements by Next-Generation Sequencing for the Diagnosis of Lymphoid Malignancies. Clin Chem 2021; 67:1524-1533. [PMID: 34491318 PMCID: PMC8965457 DOI: 10.1093/clinchem/hvab141] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 07/10/2021] [Indexed: 12/24/2022]
Abstract
BACKGROUND Clonal immunoglobulin and T-cell receptor rearrangements serve as tumor-specific markers that have become mainstays of the diagnosis and monitoring of lymphoid malignancy. Next-generation sequencing (NGS) techniques targeting these loci have been successfully applied to lymphoblastic leukemia and multiple myeloma for minimal residual disease detection. However, adoption of NGS for primary diagnosis remains limited. METHODS We addressed the bioinformatics challenges associated with immune cell sequencing and clone detection by designing a novel web tool, CloneRetriever (CR), which uses machine-learning principles to generate clone classification schemes that are customizable, and can be applied to large datasets. CR has 2 applications-a "validation" mode to derive a clonality classifier, and a "live" mode to screen for clones by applying a validated and/or customized classifier. In this study, CR-generated multiple classifiers using 2 datasets comprising 106 annotated patient samples. A custom classifier was then applied to 36 unannotated samples. RESULTS The optimal classifier for clonality required clonal dominance ≥4.5× above background, read representation ≥8% of all reads, and technical replicate agreement. Depending on the dataset and analysis step, the optimal algorithm yielded sensitivities of 81%-90%, specificities of 97%-100%, areas under the curve of 91%-94%, positive predictive values of 92-100%, and negative predictive values of 88%-98%. Customization of the algorithms yielded 95%-100% concordance with gold-standard clonality determination, including rescue of indeterminate samples. Application to a set of unknowns showed concordance rates of 83%-96%. CONCLUSIONS CR is an out-of-the-box ready and user-friendly software designed to identify clonal rearrangements in large NGS datasets for the diagnosis of lymphoid malignancies.
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Affiliation(s)
| | - Chad M McCall
- Department of Pathology, Duke University School of Medicine, Durham, NC
| | - Lisa M Haley
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
| | - Ming-Tseh Lin
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
| | - Samantha Vogt
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD
| | - Christopher D Gocke
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
| | - James R Eshleman
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
| | - Wendy Stevens
- Department of Molecular Medicine and Haematology, University of the Witwatersrand, Johannesburg, South Africa
| | - Neil A Martinson
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD
- Perinatal HIV Research Unit (PHRU), University of the Witwatersrand, Johannesburg, South Africa
| | - Marta Epeldegui
- Department of Obstetrics and Gynecology, David Geffen School of Medicine at UCLA, Los Angeles, CA
| | - Matthias Holdhoff
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
| | - Chetan Bettegowda
- Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins School of Medicine, Baltimore, MD
| | - Michael J Glantz
- Department of Neurosurgery, Medicine, and Neurology, Penn State Milton S. Hershey Medical Center, Hershey, PA
| | - Richard F Ambinder
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
| | - Rena R Xian
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD
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