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Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling

Author

Listed:
  • Ash A. Alizadeh

    (Departments of Biochemistry)

  • Michael B. Eisen

    (Genetics
    Life Sciences Division, Lawrence Orlando Berkeley National Labs and Department of Molecular and Cellular Biology, University of California)

  • R. Eric Davis

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

  • Chi Ma

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

  • Izidore S. Lossos

    (Medicine)

  • Andreas Rosenwald

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

  • Jennifer C. Boldrick

    (Departments of Biochemistry)

  • Hajeer Sabet

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

  • Truc Tran

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

  • Xin Yu

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

  • John I. Powell

    (Bioinformatics and Molecular Analysis Section, CBEL, CIT, NIH)

  • Liming Yang

    (Bioinformatics and Molecular Analysis Section, CBEL, CIT, NIH)

  • Gerald E. Marti

    (CBER, FDA)

  • Troy Moore

    (Research Genetics)

  • James Hudson

    (Research Genetics)

  • Lisheng Lu

    (Pediatrics)

  • David B. Lewis

    (Pediatrics)

  • Robert Tibshirani

    (Health Research & Policy and Statistics)

  • Gavin Sherlock

    (Life Sciences Division, Lawrence Orlando Berkeley National Labs and Department of Molecular and Cellular Biology, University of California)

  • Wing C. Chan

    (Departments of Pathology and Microbiology)

  • Timothy C. Greiner

    (Departments of Pathology and Microbiology)

  • Dennis D. Weisenburger

    (Departments of Pathology and Microbiology)

  • James O. Armitage

    (Internal Medicine, University of Nebraska Medical Center)

  • Roger Warnke

    (Pathology)

  • Ronald Levy

    (Medicine)

  • Wyndham Wilson

    (Medicine Branch, National Cancer Institute, National Institutes of Health)

  • Michael R. Grever

    (Johns Hopkins Oncology Center, Johns Hopkins School of Medicine)

  • John C. Byrd

    (Walter Reed Army Medical Center)

  • David Botstein

    (Life Sciences Division, Lawrence Orlando Berkeley National Labs and Department of Molecular and Cellular Biology, University of California)

  • Patrick O. Brown

    (Departments of Biochemistry
    Howard Hughes Medical Institute, Stanford University School of Medicine)

  • Louis M. Staudt

    (Metabolism Branch, National Cancer Institute, National Institutes of Health)

Abstract

Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin's lymphoma, is clinically heterogeneous: 40% of patients respond well to current therapy and have prolonged survival, whereas the remainder succumb to the disease. We proposed that this variability in natural history reflects unrecognized molecular heterogeneity in the tumours. Using DNA microarrays, we have conducted a systematic characterization of gene expression in B-cell malignancies. Here we show that there is diversity in gene expression among the tumours of DLBCL patients, apparently reflecting the variation in tumour proliferation rate, host response and differentiation state of the tumour. We identified two molecularly distinct forms of DLBCL which had gene expression patterns indicative of different stages of B-cell differentiation. One type expressed genes characteristic of germinal centre B cells (‘germinal centre B-like DLBCL’); the second type expressed genes normally induced during in vitro activation of peripheral blood B cells (‘activated B-like DLBCL’). Patients with germinal centre B-like DLBCL had a significantly better overall survival than those with activated B-like DLBCL. The molecular classification of tumours on the basis of gene expression can thus identify previously undetected and clinically significant subtypes of cancer.

Suggested Citation

  • Ash A. Alizadeh & Michael B. Eisen & R. Eric Davis & Chi Ma & Izidore S. Lossos & Andreas Rosenwald & Jennifer C. Boldrick & Hajeer Sabet & Truc Tran & Xin Yu & John I. Powell & Liming Yang & Gerald E, 2000. "Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling," Nature, Nature, vol. 403(6769), pages 503-511, February.
    • Handle: RePEc:nat:nature:v:403:y:2000:i:6769:d:10.1038_35000501
    DOI: 10.1038/35000501
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    Cited by:

    1. You, Jinhong & Zhou, Haibo, 2008. "A two-stage approach to semilinear in-slide models," Journal of Multivariate Analysis, Elsevier, vol. 99(8), pages 1610-1634, September.
    2. Maureen Stone & Xiaofeng Liu & Hegang Chen & Jerry L. Prince, 2010. "A preliminary application of principal components and cluster analysis to internal tongue deformation patterns," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 13(4), pages 493-503.
    3. Dettling, Marcel & Bühlmann, Peter, 2004. "Finding predictive gene groups from microarray data," Journal of Multivariate Analysis, Elsevier, vol. 90(1), pages 106-131, July.
    4. Sewell, Daniel K., 2018. "Visualizing data through curvilinear representations of matrices," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 255-270.
    5. Stella Amanda & Tze King Tan & Jolynn Zu Lin Ong & Madelaine Skolastika Theardy & Regina Wan Ju Wong & Xiao Zi Huang & Muhammad Zulfaqar Ali & Yan Li & Zhiyuan Gong & Hiroshi Inagaki & Ee Yong Foo & B, 2022. "IRF4 drives clonal evolution and lineage choice in a zebrafish model of T-cell lymphoma," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    6. M. Moghadam & K. Aminian & M. Asghari & M. Parnianpour, 2013. "How well do the muscular synergies extracted via non-negative matrix factorisation explain the variation of torque at shoulder joint?," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 16(3), pages 291-301.
    7. Prendergast, Luke A. & Li Wai Suen, Connie, 2011. "A new and practical influence measure for subsets of covariance matrix sample principal components with applications to high dimensional datasets," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 752-764, January.
    8. Juan C. Laria & M. Carmen Aguilera-Morillo & Rosa E. Lillo, 2023. "Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models," Statistical Papers, Springer, vol. 64(1), pages 227-253, February.
    9. Laura Anderlucci & Francesca Fortunato & Angela Montanari, 2022. "High-Dimensional Clustering via Random Projections," Journal of Classification, Springer;The Classification Society, vol. 39(1), pages 191-216, March.
    10. Ai, Chunrong & You, Jinhong & Zhou, Yong, 2011. "Statistical inference using a weighted difference-based series approach for partially linear regression models," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 601-618, March.
    11. Nilsen Gro & Borgan Ørnulf & LiestØl Knut & Lingjærde Ole Christian, 2013. "Identifying clusters in genomics data by recursive partitioning," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(5), pages 637-652, October.
    12. van Wieringen, Wessel N. & Kun, David & Hampel, Regina & Boulesteix, Anne-Laure, 2009. "Survival prediction using gene expression data: A review and comparison," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1590-1603, March.
    13. Min Liu & Giorgio Bertolazzi & Shruti Sridhar & Rui Xue Lee & Patrick Jaynes & Kevin Mulder & Nicholas Syn & Michal Marek Hoppe & Shuangyi Fan & Yanfen Peng & Jocelyn Thng & Reiya Chua & Jayalakshmi &, 2024. "Spatially-resolved transcriptomics reveal macrophage heterogeneity and prognostic significance in diffuse large B-cell lymphoma," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    14. Salas-Gonzalez, Diego & Kuruoglu, Ercan E. & Ruiz, Diego P., 2009. "A heavy-tailed empirical Bayes method for replicated microarray data," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1535-1546, March.

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