Tumor heterogeneity is believed to be important in tumor progression and its response to therapies. However, despite numerous mutations being reported in human tumors, genetic intra-tumor heterogeneity remains poorly defined. We have developed a novel strategy to provide a chronological annotation of mutational events in a tumor. We used an endometrial tumor from a patient and transplanted it into athymic mice to create many tumor xenografts. While the patient tumor xenografts were initially responsive to raloxifene treatment, xenografts created with cancer cell clones isolated from the same patient tumor showed dramatic differences in response to raloxifene, indicating existence of intra-tumor heterogeneity with some subpopulations inherently resistant to the drug. A 250K single nucleotide polymorphism (SNP) array from Affymetrix was used to profile genotype changes on 3 xenografts and 10 single cells from another 10 xenografts. We found 797 SNP sites containing loss of heterozygosity (LOH) common to all these specimens, indicating that genetic mutations in these regions may contain the earliest genetic events in the original patient tumor. Based upon the genotype information from the 10 single cancer cells, we developed a phylogenetic tree using neighbor-joining method. We showed that there are at least 3 distinct subpopulations in the patient tumor. Additionally, the phylogenetic tree was used to determine the order of genetic events, thus providing a chronological annotation to genetic mutations. Our approach represents an important analytic strategy for defining genetic intra-tumor heterogeneity and providing chronological annotations to the genetic landscape revealed by future whole genome sequencing in tumors.
Cancer, chronology, genetic intra-tumor heterogeneity, single nucleotide polymorphism, cancer genome
This work was supported in part by American Cancer Society Research Scholar Grant RSG-06-105-01-CCE (DD) and University of New Mexico Cancer Research Treatment Center grant NIH P30 CA118100. The authors have no financial interests to disclose.
Copyright © Wentao Luo, Fan Wu, Susan R. Atlas, Gavin Pickett, Kimberly K. Leslie, and Donghai Dai, 2010.
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