TY - JOUR
T1 - Targeted RNA-sequencing for the quantification of measurable residual disease in acute myeloid leukemia
AU - Dillon, Laura W.
AU - Hayati, Sheida
AU - Roloff, Gregory W.
AU - Tunc, Ilker
AU - Pirooznia, Mehdi
AU - Mitrofanova, Antonina
AU - Hourigan, Christopher S.
N1 - Funding Information:
This work was supported by the Intramural Research Program of the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH). GWR is supported by the Medical Research Scholars Program, a public-private partnership supported jointly by the NIH, and by generous contributions to the Foundation for the NIH by the Doris Duke Charitable Foundation (Grant #2014194). The authors thank Samuel J. Rulli and Melanie Hussong of Qiagen, Inc. for their insight and advice during the assay development. The authors also thank Yuesheng Li, Yan Luo, and Patrick Burr of the NHLBI DNA Sequencing and Genomics Core for providing next-generation sequencing services and troubleshooting issues that arose during data collection. Finally, the authors also thank A. John Barrett of the National Heart, Lung and Blood Institute, Paul Liu of the NHLBI, and Gabriel Ghiaur of the Sidney Kimmel Cancer Center at Johns Hopkins for kindly providing patient samples or cell lines.
Publisher Copyright:
© 2019 Ferrata Storti Foundation.
PY - 2019/1/31
Y1 - 2019/1/31
N2 - Great effort is spent on developing therapies to improve the dire outcomes of those diagnosed with acute myeloid leukemia. The methods for quantifying response to therapeutic intervention have however lacked sensitivity. Patients achieving a complete remission as defined by conventional cytomorphological methods therefore remain at risk of subsequent relapse due to disease persistence. Improved risk stratification is possible based on tests designed to detect this residual leukemic burden (measurable residual disease). However, acute myeloid leukemia is a genetically diverse set of diseases, which has made it difficult to develop a single, highly reproducible, and sensitive assay for measurable residual disease. Here we present the development of a digital targeted RNA-sequencing-based approach designed to overcome these limitations by detecting all newly approved European LeukemiaNet molecular targets for measurable residual disease in acute myeloid leukemia in a single standardized assay. Iterative modifications and novel bioinformatics approaches resulted in a greater than 100-fold increase in performance compared with commercially available targeted RNA-sequencing approaches and a limit of detection as low as one leukemic cell in 100,000 cells measured, which is comparable to quantitative polymerase chain reaction analysis, the current gold standard for the detection of measurable residual disease. This assay, which can be customized and expanded, is the first demonstrated use of high-sensitivity RNA-sequencing for measurable residual disease detection in acute myeloid leukemia and could serve as a broadly applicable standardized tool.
AB - Great effort is spent on developing therapies to improve the dire outcomes of those diagnosed with acute myeloid leukemia. The methods for quantifying response to therapeutic intervention have however lacked sensitivity. Patients achieving a complete remission as defined by conventional cytomorphological methods therefore remain at risk of subsequent relapse due to disease persistence. Improved risk stratification is possible based on tests designed to detect this residual leukemic burden (measurable residual disease). However, acute myeloid leukemia is a genetically diverse set of diseases, which has made it difficult to develop a single, highly reproducible, and sensitive assay for measurable residual disease. Here we present the development of a digital targeted RNA-sequencing-based approach designed to overcome these limitations by detecting all newly approved European LeukemiaNet molecular targets for measurable residual disease in acute myeloid leukemia in a single standardized assay. Iterative modifications and novel bioinformatics approaches resulted in a greater than 100-fold increase in performance compared with commercially available targeted RNA-sequencing approaches and a limit of detection as low as one leukemic cell in 100,000 cells measured, which is comparable to quantitative polymerase chain reaction analysis, the current gold standard for the detection of measurable residual disease. This assay, which can be customized and expanded, is the first demonstrated use of high-sensitivity RNA-sequencing for measurable residual disease detection in acute myeloid leukemia and could serve as a broadly applicable standardized tool.
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U2 - 10.3324/haematol.2018.203133
DO - 10.3324/haematol.2018.203133
M3 - Article
C2 - 30171026
AN - SCOPUS:85060915794
SN - 0390-6078
VL - 104
SP - 297
EP - 304
JO - Haematologica
JF - Haematologica
IS - 2
ER -