Identification of cancer sex-disparity in the functional integrity of p53 and its X chromosome network

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.


Supplementary Table 1: Application of the laws of probability to infer the rate of male and female TP53 mutation frequency in cancers in the general population: STAD the most common male cancer as an example
Notation. Let pr(A|B) denote the probability or relative frequency of the event A, within some well defined population, given an event or condition B. Here the vertical bar | is read as "given". For example, if µ denotes the event that a person in a population has a pathogenic TP53 mutation, and M denotes the event that a person is male, then pr(µ|M) is the probability that a male person in that population has a pathogenic TP53 mutation (where 80% of TP53 mutations are predicted to be pathogenic 1 ). In general this will depend on the age and other characteristics of members of the population, but as what follows is simply an illustrative analysis, we will only consider the sex of the person. Let F denote the event that a person is female, C that a person has a cancer of one of the kind under discussion, and nC that a person does not have a cancer of the kind under discussion.
Our interest lies in comparing pr(µ|M) with pr(µ|F), in the knowledge that there is no information on the population frequencies of pathogenic mutations of TP53, outside the context of cancer. One further piece of notation is the ampersand &, simply read as "and". For example, pr(µ|M&C) is the probability that a male with cancer has a pathogenic mutation in TP53: "|M&C" being read "given the person is male and has a cancer.
We will now start with certain established facts, and draw some tentative conclusions using STAD as an example.
Next we use one of the basic laws of probability, here stating that pr(µ&C|M) = pr(C|M)×pr(µ|C&M), and similarly for the other 3 terms. In other words,
Plausible assumption: pr(µ|nC&M) and pr(µ|nC&F) are both quite small in comparison with the frequencies of cancer in males and females. This is almost a consequence of the definition of a pathogenic mutation.
Conclusion: Given Facts 1 and 2, and the Plausible Assumption, and rounding a little This predicts that in the general population, the incidence of pathogenic TP53 mutations in male STAD, the most common non-reproductive cancer in males is ~two times as frequent as in female STAD.