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Cited by 423

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.

Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia

Open access
Faham, Malek, Zheng, Jianbiao, Moorhead, Martin, Carlton, Victoria E. H., Stow, Patricia, Coustan-Smith, Elaine, Pui, Ching-Hon, Campana, Dario·2012·Blood

Abstract

The persistence of minimal residual disease (MRD) during therapy is the strongest adverse prognostic factor in acute lymphoblastic leukemia (ALL). We developed a high-throughput sequencing method that universally amplifies antigen-receptor gene segments and identifies all clonal gene rearrangements (ie, leukemia-specific sequences) at diagnosis, allowing monitoring of disease progression and clonal evolution during therapy. In the present study, the assay specifically detected 1 leukemic cell among greater than 1 million leukocytes in spike-in experiments. We compared this method with the gold-standard MRD assays multiparameter flow cytometry and allele-specific oligonucleotide polymerase chain reaction (ASO-PCR) using diagnostic and follow-up samples from 106 patients with ALL. Sequencing detected MRD in all 28 samples shown to be positive by flow cytometry and in 35 of the 36 shown to be positive by ASO-PCR and revealed MRD in 10 and 3 additional samples that were negative by flow cytometry and ASO-PCR, respectively. We conclude that this new method allows monitoring of treatment response in ALL and other lymphoid malignancies with great sensitivity and precision. The www.clinicaltrials.gov identifier number for the Total XV study is NCT00137111.

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Metadata

Authors
Faham, M., Zheng, J., Moorhead, M., Carlton, V. E. H., Stow, P., Coustan-Smith, E., Pui, C.-H., & Campana, D.
Venue
Blood
Published
2012-12-20
Volume
120
Issue
26
Pages
5173-5180
ISSN
  • 0006-4971 (ISSN-L)
  • 1528-0020
OpenAlex
W2168109746
Cited by
423
References
32
FWCI
26.91
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia. https://app.cochat.ai/papers/10.1182/blood-2012-07-444042
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Faham, M., Zheng, J., Moorhead, M., Carlton, V. E. H., Stow, P., Coustan-Smith, E., Pui, C.-H., & Campana, D. (2012). Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia. Blood. https://doi.org/10.1182/blood-2012-07-444042

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