Molecular Evolutionary Analysis of Cancer Cell Lines

Abstract

With genome-wide cancer studies producing large DNA sequence data sets, novel computational approaches toward better understanding the role of mutations in tumor survival and proliferation are greatly needed. Tumors are widely viewed to be influenced by Darwinian processes, yet molecular evolutionary analysis, invaluable in other DNA sequence studies, has seen little application in cancer biology. Here, we describe the phylogenetic analysis of 353 cancer cell lines based on multiple sequence alignments of 3,252 nucleotides and 1,170 amino acids built from the concatenation of variant codons and residues across 494 and 523 genes, respectively. Reconstructed phylogenetic trees cluster cell lines by shared DNA variant patterns rather than cancer tissue type, suggesting that tumors originating from diverse histologies have similar oncogenic pathways. A well-supported clade of 91 cancer cell lines representing multiple tumor types also had significantly different gene expression profiles from the remaining cell lines according to statistical analyses of mRNA microarray data. This suggests that phylogenetic clustering of tumor cell lines based on DNA variants might reflect functional similarities in cellular pathways. Positive selection analysis revealed specific DNA variants that might be potential driver mutations. Our study shows the potential role of molecular evolutionary analyses in tumor classification and the development of novel anticancer strategies.Mol Cancer Ther; 9(2); 279-91. ©2010 AACR.

Phylogenomics of phosphoinositide lipid kinases: perspectives on the evolution of second messenger signaling and drug discovery

“…Gymnopoulos and co-workers mapped H1047R/L mutations onto a structural model of PIK3CA which suggested that these changes are located near the hinge region of the activation loop and could serve to increase catalytic activity [28]. Given the importance of mutated kinases in tumor cell viability and their increased exploitation as cancer drug targets, better insights into delineating between passenger and driver mutations might be gained through broader sequence comparisons across different species as well as related protein family members [29,30]. …”

Evolution of the cancer genome

“…Using this approach, a ranked list of the top ~1000 genes was assembled with mutations affecting protein function relevant to cancer [41]. A variety of additional approaches have been implemented to uncover drivers by, for example, integrating copy-number variation and gene expression [31] and phylogenetic analysis [23,42]. …”

Domain Altering SNPs in the Human Proteome and Their Impact on Signaling Pathways

“…The table covers proteins associated with a variety of diseases ranging from pancreatic cancer, epilepsy, and to carpal tunnel syndrome. Beside the OMIM evaluations, SNPs reported in various cancer lines were tested [31] for their position relative to domains and domain altering potential. Out of 13 unique SNP IDs presented in Table 2 of Zhang [31], one was found in the PROSITE domain region, and it corresponded to a domain-altering SNP associated with pancreas cancer.…”