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Targeting DDX3 with a small molecule inhibitor for lung cancer therapy.

Bol GM, Vesuna F, Xie M, Zeng J, Aziz K, Gandhi N, Levine A, Irving A, Korz D, Tantravedi S, Heerma van Voss MR, Gabrielson K, Bordt EA, Polster BM, Cope L, van der Groep P, Kondaskar A, Rudek MA, Hosmane RS, van der Wall E, van Diest PJ, Tran PT, Raman V - EMBO Mol Med (2015)

Bottom Line: We designed a first-in-class small molecule inhibitor, RK-33, which binds to DDX3 and abrogates its activity.Mechanistically, loss of DDX3 function either by shRNA or by RK-33 impaired Wnt signaling through disruption of the DDX3-β-catenin axis and inhibited non-homologous end joining-the major DNA repair pathway in mammalian somatic cells.Overall, inhibition of DDX3 by RK-33 promotes tumor regression, thus providing a compelling argument to develop DDX3 inhibitors for lung cancer therapy.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.

No MeSH data available.


Related in: MedlinePlus

Comparison of the GI50 values of RK-33 with FDA-approved drugs on the NCI-60 panel of cell linesA, B The graph depicts the growth inhibitory properties (GI50) of RK-33 for the NCI-60 panel of cell lines. The NCI-60 is a panel of 60 extensively characterized human cell lines derived from nine distinct tumor types: melanoma, ovarian, renal, breast, leukemia, lung, prostate, colon, and CNS.C Network analysis of 102 FDA-approved drugs and RK-33 based on GI50 in the NCI-60 cell line panel.D Unsupervised cluster analysis of the 102 FDA-approved drugs based on the correlation structure of the GI50 levels. The result is shown as a symmetric heat map with positive associations depicted in yellow and negative associations shown in blue.Data information: Error bars represent SD and all experiments were done in replicates.
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fig04: Comparison of the GI50 values of RK-33 with FDA-approved drugs on the NCI-60 panel of cell linesA, B The graph depicts the growth inhibitory properties (GI50) of RK-33 for the NCI-60 panel of cell lines. The NCI-60 is a panel of 60 extensively characterized human cell lines derived from nine distinct tumor types: melanoma, ovarian, renal, breast, leukemia, lung, prostate, colon, and CNS.C Network analysis of 102 FDA-approved drugs and RK-33 based on GI50 in the NCI-60 cell line panel.D Unsupervised cluster analysis of the 102 FDA-approved drugs based on the correlation structure of the GI50 levels. The result is shown as a symmetric heat map with positive associations depicted in yellow and negative associations shown in blue.Data information: Error bars represent SD and all experiments were done in replicates.

Mentions: To assess the effect of RK-33 on a wide variety of cell lines, we tested the NCI-60 panel of cell lines (Shoemaker et al, 1988; Shoemaker, 2006) for a decrease in cellular growth (Fig4A and B). Next, we compared the growth inhibition of the NCI-60 cell lines by RK-33 with that of 102 common FDA-approved drugs using network analysis (Fig4C). A well-connected sub-network in the middle of the plot indicates that all of these drugs have similar patterns of sensitivity across the cell lines. RK-33 and several other agents are not connected to networks, indicating that none of these have near-neighbors among FDA-approved drugs in cancer. We also performed an unsupervised cluster analysis of the 102 FDA-approved drugs based on the correlation structure of the GI50 levels (Fig4D). RK-33 sits in the bottom right corner in a small cluster of weak-to-moderately correlated agents including dacarbazine, thioguanine, temozolomide, and vorinostat, supporting the distinctive working mechanism of RK-33 as compared to other drugs.


Targeting DDX3 with a small molecule inhibitor for lung cancer therapy.

Bol GM, Vesuna F, Xie M, Zeng J, Aziz K, Gandhi N, Levine A, Irving A, Korz D, Tantravedi S, Heerma van Voss MR, Gabrielson K, Bordt EA, Polster BM, Cope L, van der Groep P, Kondaskar A, Rudek MA, Hosmane RS, van der Wall E, van Diest PJ, Tran PT, Raman V - EMBO Mol Med (2015)

Comparison of the GI50 values of RK-33 with FDA-approved drugs on the NCI-60 panel of cell linesA, B The graph depicts the growth inhibitory properties (GI50) of RK-33 for the NCI-60 panel of cell lines. The NCI-60 is a panel of 60 extensively characterized human cell lines derived from nine distinct tumor types: melanoma, ovarian, renal, breast, leukemia, lung, prostate, colon, and CNS.C Network analysis of 102 FDA-approved drugs and RK-33 based on GI50 in the NCI-60 cell line panel.D Unsupervised cluster analysis of the 102 FDA-approved drugs based on the correlation structure of the GI50 levels. The result is shown as a symmetric heat map with positive associations depicted in yellow and negative associations shown in blue.Data information: Error bars represent SD and all experiments were done in replicates.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492822&req=5

fig04: Comparison of the GI50 values of RK-33 with FDA-approved drugs on the NCI-60 panel of cell linesA, B The graph depicts the growth inhibitory properties (GI50) of RK-33 for the NCI-60 panel of cell lines. The NCI-60 is a panel of 60 extensively characterized human cell lines derived from nine distinct tumor types: melanoma, ovarian, renal, breast, leukemia, lung, prostate, colon, and CNS.C Network analysis of 102 FDA-approved drugs and RK-33 based on GI50 in the NCI-60 cell line panel.D Unsupervised cluster analysis of the 102 FDA-approved drugs based on the correlation structure of the GI50 levels. The result is shown as a symmetric heat map with positive associations depicted in yellow and negative associations shown in blue.Data information: Error bars represent SD and all experiments were done in replicates.
Mentions: To assess the effect of RK-33 on a wide variety of cell lines, we tested the NCI-60 panel of cell lines (Shoemaker et al, 1988; Shoemaker, 2006) for a decrease in cellular growth (Fig4A and B). Next, we compared the growth inhibition of the NCI-60 cell lines by RK-33 with that of 102 common FDA-approved drugs using network analysis (Fig4C). A well-connected sub-network in the middle of the plot indicates that all of these drugs have similar patterns of sensitivity across the cell lines. RK-33 and several other agents are not connected to networks, indicating that none of these have near-neighbors among FDA-approved drugs in cancer. We also performed an unsupervised cluster analysis of the 102 FDA-approved drugs based on the correlation structure of the GI50 levels (Fig4D). RK-33 sits in the bottom right corner in a small cluster of weak-to-moderately correlated agents including dacarbazine, thioguanine, temozolomide, and vorinostat, supporting the distinctive working mechanism of RK-33 as compared to other drugs.

Bottom Line: We designed a first-in-class small molecule inhibitor, RK-33, which binds to DDX3 and abrogates its activity.Mechanistically, loss of DDX3 function either by shRNA or by RK-33 impaired Wnt signaling through disruption of the DDX3-β-catenin axis and inhibited non-homologous end joining-the major DNA repair pathway in mammalian somatic cells.Overall, inhibition of DDX3 by RK-33 promotes tumor regression, thus providing a compelling argument to develop DDX3 inhibitors for lung cancer therapy.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA Department of Pathology, University Medical Center Utrecht, Utrecht, The Netherlands.

No MeSH data available.


Related in: MedlinePlus