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Development of a phylogenetic tree model to investigate the role of genetic mutations in endometrial tumors
Journal article   Open access   Peer reviewed

Development of a phylogenetic tree model to investigate the role of genetic mutations in endometrial tumors

Guoyi Zhang, Brandon B Beck, Wentao Luo, Fan Wu, Stephen F Kingsmore and Donghai Dai
Oncology reports, Vol.25(5), pp.1447-1454
05/01/2011
DOI: 10.3892/or.2011.1186
PMID: 21327331
url
https://doi.org/10.3892/or.2011.1186View
Published (Version of record) Open Access

Abstract

With the advancement of modern genome sequencing technology, thousands of genetic mutations have been identified in human tumors. However, analysis of the role of genetic mutations in tumor development is limited by the need for prevalence information among multiple tumors and by the lack of analytic capability to define the functional contribution of genetic mutations in patients, individually and collectively. To understand the genetic basis of human endometrial cancer, the fourth most common cancer in women, transcriptome sequencing was performed on an endometrial tumor paired with normal cervical tissue. Twenty-six non-synonymous somatic mutations were validated in the tumor genome. A phylogenetic tree illustrating the mutational time-line was developed based upon the distribution of 26 mutations in 30 randomly-selected laser-captured single cells from the tumor sections. Five ubiquitous mutations were identified that are presumed to occur in the cancer founder cell of the tumor, and may collectively play critical roles in endometrial oncogenesis. However, further testing in 10 additional endometrial tumors failed to show overlapping mutations in the cancer founder cells, indicating the lack of a single common oncogenic pathway for these endometrial tumors. The effects of individual mutations in cancer cell proliferation were calculated based on descendant cell number and time span since acquiring each mutation. We have developed a phylogenetic approach to characterize individual genetic mutations in cancer cell proliferation in a single resected patient tumor. This approach provides the capability to study the tumor-specific role of genetic mutations, without relying on prevalence information from other patients.

Computational Biology Mutation DNA Transcription Obstetrics and Gynecology Adult Endometrial Neoplasms/genetics/metabolism Female Genetic Heterogeneity Humans Models Genetic Phylogeny Sequence Analysis

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