Letter | Published:

A loss-of-function RNA interference screen for molecular targets in cancer

Nature volume 441, pages 106110 (04 May 2006) | Download Citation



The pursuit of novel therapeutic agents in cancer relies on the identification and validation of molecular targets. Hallmarks of cancer include self-sufficiency in growth signals and evasion from apoptosis1; genes that regulate these processes may be optimal for therapeutic attack. Here we describe a loss-of-function screen for genes required for the proliferation and survival of cancer cells using an RNA interference library. We used a doxycycline-inducible retroviral vector for the expression of small hairpin RNAs (shRNAs) to construct a library targeting 2,500 human genes. We used retroviral pools from this library to infect cell lines representing two distinct molecular subgroups of diffuse large B-cell lymphoma (DLBCL), termed activated B-cell-like DLBCL and germinal centre B-cell-like DLBCL. Each vector was engineered to contain a unique 60-base-pair ‘bar code’, allowing the abundance of an individual shRNA vector within a population of transduced cells to be measured using microarrays of the bar-code sequences. We observed that a subset of shRNA vectors was depleted from the transduced cells after three weeks in culture only if shRNA expression was induced. In activated B-cell-like DLBCL cells, but not germinal centre B-cell-like DLBCL cells, shRNAs targeting the NF-κB pathway were depleted, in keeping with the essential role of this pathway in the survival of activated B-cell-like DLBCL. This screen uncovered CARD11 as a key upstream signalling component responsible for the constitutive IκB kinase activity in activated B-cell-like DLBCL. The methodology that we describe can be used to establish a functional taxonomy of cancer and help reveal new classes of therapeutic targets distinct from known oncogenes.

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This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Center for Cancer Research. V.N.N. was also supported by a Damon Runyon-Walter Winchell Cancer Research Foundation Fellowship.

Author information

Author notes

    • Vu N. Ngo
    •  & R. Eric Davis

    *These authors contributed equally to this work


  1. Metabolism Branch, Center for Cancer Research, National Cancer Institute, and

    • Vu N. Ngo
    • , R. Eric Davis
    • , Laurence Lamy
    • , Xin Yu
    • , Hong Zhao
    • , Georg Lenz
    • , Lloyd T. Lam
    • , Sandeep Dave
    •  & Louis M. Staudt
  2. Bioinformatics and Molecular Analysis Section, Computational Bioscience and Engineering Laboratory, CIT, National Institutes of Health, Bethesda, Maryland 20892, USA

    • Liming Yang
    •  & John Powell


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Competing interests

The microarray data discussed in this publication have been deposited in the Gene Expression Omnibus of NCBI (GEO, http://www.ncbi.nlm.nih.gov/geo/) and are accessible through GEO series accession number GSE3896. Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

Corresponding author

Correspondence to Louis M. Staudt.

Supplementary information

PDF files

  1. 1.

    Supplementary Figure 1

    Knockdown of gene expression depends upon induction of shRNA expression by doxycycline. This figure shows Q-PCR and Western blot analysis of shRNA-mediated knockdown of target gene expression in DLBCL cell lines.

  2. 2.

    Supplementary Figure 2

    Identification of shRNAs that block the proliferation or survival of lymphoma cell lines.

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    Supplementary Figure 3

    Gene expression profiles and NF-κB pathway activity in DLBCL cell lines.

  4. 4.

    Supplementary Figure 4

    CARD11 mRNA expression in ABC DLBCL, GCB DLBCL, and PMBL tumor biopsies.

Word documents

  1. 1.

    Supplementary Table 1

    Sequence of effective shRNAs and position within the targeted Refseq mRNA sequence.

  2. 2.

    Supplementary Methods

    More detailed methods are described here for preparing doxycycline-inducible cell lines; performing barcode DNA microarrays; cell-based IKK assay; cytokine measurement; and survival assay.

  3. 3.

    Supplementary Figure Legends

    Text to accompany the above Supplementary Figures.

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