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Special considerations in prognostic research in cancer involving genetic polymorphisms

Sevtap Savas12*, Geoffrey Liu345 and Wei Xu356

Author Affiliations

1 Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada

2 Discipline of Oncology, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, Newfoundland, Canada

3 Division of Applied Molecular Oncology, Ontario Cancer Institute, Toronto, Ontario, Canada

4 Division of Medical Oncology and Hematology, Department of Medicine, Princess Margaret Hospital/University Health Network and University of Toronto, Toronto, Ontario, Canada

5 Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

6 Department of Biostatistics, Princess Margaret Hospital/University Health Network, Toronto, Ontario, Canada

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BMC Medicine 2013, 11:149  doi:10.1186/1741-7015-11-149

Published: 17 June 2013


Analysis of genetic polymorphisms may help identify putative prognostic markers and determine the biological basis of variable prognosis in patients. However, in contrast to other variables commonly used in the prognostic studies, there are special considerations when studying genetic polymorphisms. For example, variable inheritance patterns (recessive, dominant, codominant, and additive genetic models) need to be explored to identify the specific genotypes associated with the outcome. In addition, several characteristics of genetic polymorphisms, such as their minor allele frequency and linkage disequilibrium among multiple polymorphisms, and the population substructure of the cohort investigated need to be accounted for in the analyses. In addition, in cancer research due to the genomic differences between the tumor and non-tumor DNA, differences in the genetic information obtained using these tissues need to be carefully assessed in prognostic studies. In this article, we review these and other considerations specific to genetic polymorphism by focusing on genetic prognostic studies in cancer.

Genetic models; Genetic polymorphisms; Genetic prognostic factors; Genotypes; Prognostic research; Tumor DNA