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TP53 Cancerous Mutations Exhibit Selection for Translation Efficiency

¹ Blavatnik School of Computer Science, ² Department of Molecular Microbiology and Biotechnology, and ³ School of Medicine, Tel Aviv University, Ramat Aviv, Israel

Requests for reprints: Tamir Tuller, Tel Aviv University, Tel Aviv, 69978 Israel. Phone: 972-3-640-7466; Fax: 972-3-640-9357; E-mail: tamirtul{at}post.tau.ac.il and Eytan Ruppin, Tel Aviv University, Tel Aviv, 69978 Israel. E-mail: ruppin{at}post.tau.ac.il.

The tumor suppressor gene TP53 is known to be a key regulator in cancer, and more than half of human cancers exhibit mutations in this gene. Recent evidence shows that point mutations in TP53 not only disrupt its function but also possess gain-of-function and dominant-negative effects on wild-type copies, thus making the mutated gene an oncogene. Hence, this brings about the possibility that TP53 mutations may be under selection for increasing the overall translation efficiency (TE) of defected TP53 in cancerous cells. Here, we perform the first large-scale analysis of TE in human cancer mutated TP53 variants, identifying a significant increase in TE that is correlated with the frequency of TP53 mutations. Furthermore, mutations with a known oncogenic effect significantly increase their TE compared with the other TP53 mutations. Further analysis shows that TE may have influence both on selecting the location of the mutation and on its outcome: codons with lower TE show stronger selection toward nonsynonymous mutations and, for each codon, frequent mutations show stronger increase in TE compared with less frequent mutations. Additionally, we find that TP53 mutations have significantly higher TE increase in progressive versus primary tumors. Finally, an analysis of TP53 NCI-60 cell lines points to a coadaptation between the mutations and the tRNA pool, increasing the overall TP53 TE. Taken together, these results show that TE plays an important role in the selection of TP53 cancerous mutations. [Cancer Res 2009;69(22):8807–13]

Key Words: translation efficiency • TP53 gene • point mutation • codon bias