Clinical Utility of High-Throughput and Complimentary Genomic Tumor Profiling in Hematologic Malignancies
Autor: | Taylor Hartley, Christopher D. Coldren, Ian W. Flinn, Kristina J. Fasig, Patrick A. Lennon, Jesus G. Berdeja, William B. Donnellan, Zeqiang Ma, Dan Connor, James L. Prescott, Heather Rietz, Pranil Chandra, David C. Spence, Terence T. Casey, Vladimir Kravstov, Scott R. Wheeler, Jason Gottwals, Malini Sathanoori, Ron Turnicky, Sandeep Mukherjee, Hao Ho |
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Rok vydání: | 2015 |
Předmět: | |
Zdroj: | Blood. 126:1388-1388 |
ISSN: | 1528-0020 0006-4971 |
Popis: | Background: NCCN guidelines and a continuously expanding collection of high-impact publications recommend interrogating hematologic neoplasms for biomarkers that yield diagnostic, prognostic, and/or therapeutic information. The advent of comprehensive, high-throughput genomic profiling technologies has enabled the detection of multiple genomic alterations in an efficient and cost effective manner, and provides insights into disease initiation, progression, therapy response and identification of therapeutic targets not available through conventional methods. Design: Based on NCCN guidelines and literature review, we designed a genomic profiling strategy composed of a targeted amplicon-based next generation sequencing (NGS) assay and cytogenomic microarray (CGA) to identify clinically actionable genomic alterations. In the current context, "actionable" was defined as helping establish a diagnosis through demonstration of "clonal hematopoiesis" as recommended by NCCN guidelines, informing prognosis, and/or providing a potential therapeutic target. These assays complement the routine work-up of hematologic tumors, which include flow cytometry, morphologic evaluation and FISH/cytogenetic analyses. Initial data from implementation of this testing strategy in our broad community-based practice are presented. Results: 865 patient samples were analyzed, which included the following: AML (168), ALL (24), MDS (194), MDS/MPN (34), CLL (82), MPN (156), samples with suspicion of a myeloid stem cell disorder (107) and others. Of the cases evaluated by NGS and CGA, genomic aberrations were detected in 70% and 48%, respectively. Conventional cytogenetic analyses revealed abnormalities in 38% of the cases for which conclusive results were obtained; abnormal FISH results were observed in 44.7%. In cases where conventional cytogenetics and FISH tests were negative, 70% were abnormal by either NGS or CGA (~81% in cases with evidence of a myeloid stem cell disorder or acute leukemia) (Figure 1). Importantly, 12% of 51 cases with normal FISH, cytogenetics and NGS results were abnormal by CGA, and 60% of 111 cases with normal FISH, cytogenetics and CGA results had actionable mutations detected by NGS. CGA and NGS aberrations were frequently detected in MPN or MDS/MPN cases with negative cytogenetics and FISH results. For example, among 156 MPN cases, CGA and NGS abnormalities were observed in 42% and 65% of cases respectively, while only 11% of cases had abnormal cytogenetics results and 10% of cases were FISH positive (Figure 2). In contrast, in cases without actionable mutations detected by NGS and CGA, which also had been analyzed by FISH/cytogenetics, 11% of 89 were cytogenetically abnormal, and 36% of 75 had genomic alterations detected by FISH. Conclusions: High throughput genomic tumor profiling through targeted DNA sequencing and analysis of copy number alterations complements conventional methods of tumor interrogation and leads to more frequent detection of actionable alterations. This is especially apparent in the context of morphologic and/or clinical suspicion of a myeloid stem cell disorder. These data indicate that integrating multiple strategies to identify informative biomarkers can enhance diagnosis, prognosis and/or therapy in hematologic disorders. Most importantly, we have observed changes in clinical management decisions across different disease states including AML, ALL, other myeloid malignancies, and CLL. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures Ma: PathGroup: Employment. Gottwals:PathGroup: Employment. Ho:PathGroup: Employment. Fasig:PathGroup: Employment. Rietz:PathGroup: Employment. Hartley:PathGroup: Employment. Kravstov:PathGroup: Employment. Spence:PathGroup: Employment. Connor:PathGroup: Employment. Turnicky:PathGroup: Employment. Prescott:PathGroup: Employment. Lennon:PathGroup: Employment. Sathanoori:PathGroup: Employment. Flinn:Celgene Corporation: Research Funding. Berdeja:Celgene: Research Funding; Takeda: Research Funding; Curis: Research Funding; Abbvie: Research Funding; Onyx: Research Funding; MEI: Research Funding; Acetylon: Research Funding; Novartis: Research Funding; Array: Research Funding; Janssen: Research Funding; BMS: Research Funding. Wheeler:PathGroup: Employment. Coldren:PathGroup: Employment. Chandra:PathGroup: Employment. Mukherjee:PathGroup: Employment. Casey:PathGroup: Employment. |
Databáze: | OpenAIRE |
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