Molecular assembly of an aptamer–drug conjugate for targeted drug delivery to tumor cells

  • Huang Y
  • Shangguan D
  • Liu H
 et al. 
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The conjugation of antitumor drugs to targeting reagents such as antibodies is a promising method that can increase the efficacy of chemotherapy and reduce their overall toxicity. In this paper, we covalently link an antitumor agent doxorubicin (Dox) to the DNA aptamer sgc8c, which was selected by the cell-SELEX method. In doing so, we expected that this sgc8c-Dox conjugate would specifically kill the target CCRF-CEM (T-cell Acute Lymphoblastic Leukemia, T-cell ALL) cells, but with minimal toxicity towards non-target cells. The results demonstrated that sgc8c-Dox conjugate possesses many of the properties of the sgc8c aptamer, including high binding affinity (Kd = 2.0 ± 0.2 nM), and the capability to be efficiently internalized by target cells. Moreover, due to the specific conjugation method, the acid-labile linkage connecting the sgc8c-Dox conjugate can be cleaved inside the acidic endosomal environment. Cell viability tests demonstrate that the sgc8c-Dox conjugates not only possess potency similar to the unconjugated Dox, but also have the required molecular specificity which is lacking in most current targeted drug delivery strategies. Furthermore, we found that nonspecific uptake of membrane-permeable Dox to non-target cell lines could also be inhibited by linking the drug with the aptamer, thus, it makes the conjugates selective to the cells which express higher amounts of target proteins. Compared to the less effective reported Dox-immunoconjugates, this sgc8c-Dox conjugates make targeted chemotherapy more feasible with drugs having various potencies. When combined with the large number of recently created DNA aptamers that specifically target a wide variety of cancer cells, this drug-aptoconjugation method will have broad implications for targeted drug delivery.

Author-supplied keywords

  • aptamer
  • cancer therapy
  • ccrf-cem
  • doxorubicin
  • targeted drug delivery

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  • Y.F. Huang

  • D. Shangguan

  • H. Liu

  • J.A. Phillips

  • X. Zhang

  • Y. Chen

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