Abstract
As biotechnology advances rapidly, a tremendous amount of cancer genetic data has become available, providing an unprecedented opportunity for understanding the genetic mechanisms of cancer. To understand the effects of duplications and deletions on cancer progression, two genomes (normal and tumor) were sequenced from each of five stomach cancer patients in different stages (I, II, III and IV). We developed a phylogenetic model for analyzing stomach cancer data. The model assumes that duplication and deletion occur in accordance with a continuous time Markov Chain along the branches of a phylogenetic tree attached with five extended branches leading to the tumor genomes. Moreover, coalescence times of the phylogenetic tree follow a coalescence process. The simulation study suggests that the maximum likelihood approach can accurately estimate parameters in the phylogenetic model. The phylogenetic model was applied to the stomach cancer data. We found that the expected number of changes (duplication and deletion) per gene for the tumor genomes is significantly higher than that for the normal genomes. The goodness-of-fit test suggests that the phylogenetic model with constant duplication and deletion rates can adequately fit the duplication data for the normal genomes. The analysis found nine duplicated genes that are significantly associated with stomach cancer.
Highlights
Cancer is one of the leading causes of death in Americans [1]
There is a high degree of individual variation in this data, this might suggest that duplication and deletion rates may vary across different stages of stomach cancer
As duplication and deletion rates depend on the total number of genes in the human genomes, the duplication and deletion rates estimated from the stomach cancer data set are relative rates
Summary
Cancer is one of the leading causes of death in Americans [1]. Cancer research has led to a variety of effective treatments and diagnostic techniques for cancers. The availability of genetic data ignites the hope that we may discover the genetic mechanisms of cancer by examining the genetic differences between normal and cancer genomes [5]. It is, a challenging task to effectively analyze such genetic data by modeling the genetic variation observed within and between the normal and cancer groups [6]. Previous studies have demonstrated that cancer progression is an evolutionary process in which mutation and natural selection are two key factors [7,8]. Mutation causes genetic variation among normal cells that can trigger cancer [9]. Selection plays an important role in therapeutic resistance [10,11,12] and in the birth and death process of cancer cells, as cancer cells vary and the fittest ones survive after competition [13]
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