Abstract
p53 is the most frequently mutated gene in human cancer. Compelling evidence argues that full transformation involves loss of growth suppression encoded by wild-type p53 together with poorly understood oncogenic activity encoded by missense mutations. Furthermore, distinguishing disease alleles from natural polymorphisms is an important clinical challenge. To interrogate the genetic activity of human p53 variants, we leveraged the Drosophila model as an in vivo platform. We engineered strains that replace the fly p53 gene with human alleles, producing a collection of stocks that are, in effect, ‘humanized’ for p53 variants. Like the fly counterpart, human p53 transcriptionally activated a biosensor and induced apoptosis after DNA damage. However, all humanized strains representing common alleles found in cancer patients failed to complement in these assays. Surprisingly, stimulus-dependent activation of hp53 occurred without stabilization, demonstrating that these two processes can be uncoupled. Like its fly counterpart, hp53 formed prominent nuclear foci in germline cells but cancer-associated p53 variants did not. Moreover, these same mutant alleles disrupted hp53 foci and inhibited biosensor activity, suggesting that these properties are functionally linked. Together these findings establish a functional platform for interrogating human p53 alleles and suggest that simple phenotypes could be used to stratify disease variants.
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Acknowledgements
We acknowledge Melissa O’neal for help cloning constructs for humanized lines and Akash Patel for help with crosses to make humanized lines. We are grateful to Anne Dejean for the dSmt3/dSUMO antibody and to Michael Buszczak for the coilin and lsm11 antibodies. We thank Kate Luby-Phelps, Abhijit Bugde and the Live Cell Imaging Facility at UT Southwestern for help with confocal imaging, deconvolution and Imaris. We also thank Po Chen, Nichole Link, Annika Wylie, Gianella Garcia-Hughes, Mike Buszczak, Robin Hiesinger and Helmut Kramer for discussion, advice and comments. This work was supported by the NIH (GM072124) and (GM115682), the Welch Foundation (I-I865), the Ellison Medical Foundation and CPRIT (RP110076) as well as NRSA (F31 GM108472-03) to Paula Kurtz and NIH (S10 RR029731-01) to Kate Luby-Phelps.
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D'Brot, A., Kurtz, P., Regan, E. et al. A platform for interrogating cancer-associated p53 alleles. Oncogene 36, 286–291 (2017). https://doi.org/10.1038/onc.2016.48
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DOI: https://doi.org/10.1038/onc.2016.48
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