Abstract

The disproportionately high prevalence of male cancer is poorly understood. We tested for sex-disparity in the functional integrity of the major tumor suppressor p53 in sporadic cancers. Our bioinformatics analyses expose three novel levels of p53 impact on sex-disparity in 12 non-reproductive cancer types. First, TP53 mutation is more frequent in these cancers among US males than females, with poorest survival correlating with its mutation. Second, numerous X-linked genes are associated with p53, including vital genomic regulators. Males are at unique risk from alterations of their single copies of these genes. High expression of X-linked negative regulators of p53 in wild-type TP53 cancers corresponds with reduced survival. Third, females exhibit an exceptional incidence of non-expressed mutations among p53-associated X-linked genes. Our data indicate that poor survival in males is contributed by high frequencies of TP53 mutations and an inability to shield against deregulated X-linked genes that engage in p53 networks.

Details

Title
Identification of cancer sex-disparity in the functional integrity of p53 and its X chromosome network
Author
Haupt, Sue 1   VIAFID ORCID Logo  ; Caramia, Franco 1   VIAFID ORCID Logo  ; Herschtal, Alan 2 ; Soussi, Thierry 3   VIAFID ORCID Logo  ; Lozano, Guillermina 4   VIAFID ORCID Logo  ; Hu, Chen 5 ; Han, Liang 6   VIAFID ORCID Logo  ; Speed, Terence P 7   VIAFID ORCID Logo  ; Haupt, Ygal 8 

 Tumor Suppression Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia 
 Department of Biometrics Novotech, Carlton, Victoria, Australia 
 Department of Oncology-Pathology, Karolinska Institute, Cancer Center Karolinska, Solna, Sweden; INSERM, U1138, Centre de Recherche des Cordeliers, Paris, France 
 The University of Texas, MD Anderson Cancer Center, Houston, TX, USA 
 Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 
 Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA 
 Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia; Department of Mathematics and Statistics, University of Melbourne, Parkville, Victoria, Australia 
 Tumor Suppression Laboratory, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia; Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia; Department of Clinical Pathology, University of Melbourne, Parkville, Victoria, Australia; Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Victoria, Australia 
Pages
1-12
Publication year
2019
Publication date
Nov 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2318727596
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.