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High-throughput VDJ sequencing for quantification of minimal residual disease in chronic lymphocytic leukemia and immune reconstitution assessment
Open accessAbstract
The primary cause of poor outcome following allogeneic hematopoietic cell transplantation (HCT) for chronic lymphocytic leukemia (CLL) is disease recurrence. Detection of increasing minimal residual disease (MRD) following HCT may permit early intervention to prevent clinical relapse; however, MRD quantification remains an uncommon diagnostic test because of logistical and financial barriers to widespread use. Here we describe a method for quantifying CLL MRD using widely available consensus primers for amplification of all Ig heavy chain (IGH) genes in a mixture of peripheral blood mononuclear cells, followed by high-throughput sequencing (HTS) for disease-specific IGH sequence quantification. To achieve accurate MRD quantification, we developed a systematic bioinformatic methodology to aggregate cancer clone sequence variants arising from systematic and random artifacts occurring during IGH-HTS. We then compared the sensitivity of IGH-HTS, flow cytometry, and allele-specific oligonucleotide PCR for MRD quantification in 28 samples collected from 6 CLL patients following allogeneic HCT. Using amplimer libraries generated with consensus primers from patient blood samples, we demonstrate the sensitivity of IGH-HTS with 454 pyrosequencing to be 10 −5 , with a high correlation between quantification by allele-specific oligonucleotide PCR and IGH-HTS ( r = 0.85). From the same dataset used to quantify MRD, IGH-HTS also allowed us to profile IGH repertoire reconstitution after HCT—information not provided by the other MRD methods. IGH-HTS using consensus primers will broaden the availability of MRD quantification in CLL and other B cell malignancies, and this approach has potential for quantitative evaluation of immune diversification following transplant and nontransplant therapies.
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Cited by
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Georgiou, G., Ippolito, G. C., Beausang, J., Busse, C. E., Wardemann, H., & Quake, S. R. (2014) · Nature Biotechnology · doi:10.1038/nbt.2782 · Cited by 652
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Carlson, C. S., Emerson, R. O., Sherwood, A. M., Desmarais, C., Chung, M.-W., Parsons, J. M., Steen, M. S., LaMadrid-Herrmannsfeldt, M. A., Williamson, D. W., Livingston, R. J., et al. (2013) · Nature Communications · doi:10.1038/ncomms3680 · Cited by 565
Rogosch, T., Kerzel, S., Hoi, K. H., Zhang, Z., Maier, R. F., Ippolito, G. C., & Zemlin, M. (2012) · Frontiers in Immunology · doi:10.3389/fimmu.2012.00176 · Cited by 555
Towards error-free profiling of immune repertoires
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Deep-sequencing approach for minimal residual disease detection in acute lymphoblastic leukemia
Faham, M., Zheng, J., Moorhead, M., Carlton, V. E. H., Stow, P., Coustan-Smith, E., Pui, C.-H., & Campana, D. (2012) · Blood · doi:10.1182/blood-2012-07-444042 · Cited by 423
Metadata
- Authors
- Logan, A. C., Gao, H., Wang, C., Sahaf, B., Jones, C. D., Marshall, E. L., Buño, I., Armstrong, R., Fire, A. Z., Weinberg, K. I., Mindrinos, M., Zehnder, J. L., Boyd, S. D., Xiao, W., Davis, R. W., & Miklos, D. B.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2011-12-12
- Volume
- 108
- Issue
- 52
- Pages
- 21194-21199
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2171240476
- Cited by
- 167
- References
- 0
- FWCI
- 7.80
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: High-throughput VDJ sequencing for quantification of minimal residual disease in chronic lymphocytic leukemia and immune reconstitution assessment. https://app.cochat.ai/papers/10.1073/pnas.1118357109
- The paper
- Logan, A. C., Gao, H., Wang, C., Sahaf, B., Jones, C. D., Marshall, E. L., Buño, I., Armstrong, R., Fire, A. Z., Weinberg, K. I., Mindrinos, M., Zehnder, J. L., Boyd, S. D., Xiao, W., Davis, R. W., & Miklos, D. B. (2011). High-throughput VDJ sequencing for quantification of minimal residual disease in chronic lymphocytic leukemia and immune reconstitution assessment. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1118357109
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