An information-theoretic analysis of genetics, gender and age in cancer patients

• Published in: PloS one 2008-04, Vol.3 (4), p.e1951-e1951
• Main Authors: Atwal, Gurinder Singh, Rabadán, Raúl, Lozano, Guillermina, Strong, Louise C, Ruijs, Mariëlle W G, Schmidt, Marjanka K, van't Veer, Laura J, Nevanlinna, Heli, Tommiska, Johanna, Aittomäki, Kristiina, Bougeard, Gaelle, Frebourg, Thierry, Levine, Arnold J, Bond, Gareth L
• Format: Article
• Language: English
• Subjects: Age Factors; Analysis; Bioassays; Biological activity; Biological assays; Biomedical research; Breast cancer; Cancer; Cancer genetics; Cancer patients; Cancer prevention; Cancer research; Cancer treatment; Carriers; Colorectal cancer; Dimorphism; Female; Gender; Genes, p53; Genetic diversity; Genetic Predisposition to Disease; Genetic variance; Genetic Variation; Genetics; Genetics and Genomics/Cancer Genetics; Genomes; Germ-Line Mutation; Gynecology; Health risk assessment; Health risks; Hormone replacement therapy; Human genetics; Humans; Hypotheses; Independent study; Information processing; Information theory; Life Sciences; Lung cancer; Lymphoma; Lymphomas; Male; Mathematics/Statistics; MDM2 protein; Medical diagnosis; Medical Informatics; Medical research; Models, Theoretical; Mutation; Neoplasms; Neoplasms - genetics; Neoplasms - pathology; Obstetrics; p53 Protein; Phenotype; Prevention; Risk analysis; Risk factors; Sex Characteristics; Sex Factors; Sexual dimorphism; Signal Transduction; Studies; Tumor proteins; Tumor suppressor genes; Tumorigenesis; Tumors
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0001951

Germline genetics, gender and hormonal-signaling pathways are all well described modifiers of cancer risk and progression. Although an improved understanding of how germline genetic variants interact with other cancer risk factors may allow better prevention and treatment of human cancer, measuring and quantifying these interactions is challenging. In other areas of research, Information Theory has been used to quantitatively describe similar multivariate interactions. We implemented a novel information-theoretic analysis to measure the joint effect of a high frequency germline genetic variant of the p53 tumor suppressor pathway (MDM2 SNP309 T/G) and gender on clinical cancer phenotypes. This analysis quantitatively describes synergistic interactions among gender, the MDM2 SNP309 locus, and the age of onset of tumorigenesis in p53 mutation carriers. These results offer a molecular and genetic basis for the observed sexual dimorphism of cancer risk in p53 mutation carriers and a model is proposed that suggests a novel cancer prevention strategy for p53 mutation carriers.