TP53 exon-6 truncating mutations produce separation of function isoforms with pro-tumorigenic functions
Abstract
TP53 truncating mutations are common in human tumors and are thought to give rise to p53-null alleles. Here, we show that TP53 exon-6 truncating mutations occur at higher than expected frequencies and produce proteins that lack canonical p53 tumor suppressor activities but promote cancer cell proliferation, survival, and metastasis. Functionally and molecularly, these p53 mutants resemble the naturally occurring alternative p53 splice variant, p53-psi. Accordingly, these mutants can localize to mitochondria where they promote tumor phenotypes by binding and activating the mitochondria inner pore permeability regulator, Cyclophilin D (CypD). Together, our studies reveal that TP53 exon-6 truncating mutations, contrary to current beliefs, act beyond p53 loss to promote tumorigenesis, and could inform the development of strategies to target cancers driven by these prevalent mutations.
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Article and author information
Author details
Funding
National Cancer Institute (NCI P01 CA129243-06)
- Raffaella Sordella
- Marc Ladanyi
- Scott W Lowe
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All animal experiments were performed in accordance with National Research Council's Guide for the Care and Use of Laboratory Animals. Protocols were approved by the Cold Spring Harbor Laboratory Animal Care and Use Committee (933922-1 Development of mouse models to study human lung cancer - integrated protocols).
Reviewing Editor
- Joaquín M Espinosa, University of Colorado School of Medicine, United States
Publication history
- Received: May 18, 2016
- Accepted: October 17, 2016
- Accepted Manuscript published: October 19, 2016 (version 1)
- Accepted Manuscript updated: October 24, 2016 (version 2)
- Version of Record published: November 2, 2016 (version 3)
- Version of Record updated: February 1, 2017 (version 4)
Copyright
© 2016, Shirole et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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- Cancer Biology
- Computational and Systems Biology
Chronic myeloid leukemia (CML) is a blood cancer characterized by dysregulated production of maturing myeloid cells driven by the product of the Philadelphia chromosome, the BCR-ABL1 tyrosine kinase. Tyrosine kinase inhibitors (TKIs) have proved effective in treating CML, but there is still a cohort of patients who do not respond to TKI therapy even in the absence of mutations in the BCR-ABL1 kinase domain that mediate drug resistance. To discover novel strategies to improve TKI therapy in CML, we developed a nonlinear mathematical model of CML hematopoiesis that incorporates feedback control and lineage branching. Cell–cell interactions were constrained using an automated model selection method together with previous observations and new in vivo data from a chimeric BCR-ABL1 transgenic mouse model of CML. The resulting quantitative model captures the dynamics of normal and CML cells at various stages of the disease and exhibits variable responses to TKI treatment, consistent with those of CML patients. The model predicts that an increase in the proportion of CML stem cells in the bone marrow would decrease the tendency of the disease to respond to TKI therapy, in concordance with clinical data and confirmed experimentally in mice. The model further suggests that, under our assumed similarities between normal and leukemic cells, a key predictor of refractory response to TKI treatment is an increased maximum probability of self-renewal of normal hematopoietic stem cells. We use these insights to develop a clinical prognostic criterion to predict the efficacy of TKI treatment and design strategies to improve treatment response. The model predicts that stimulating the differentiation of leukemic stem cells while applying TKI therapy can significantly improve treatment outcomes.