Loss-of-function uORF mutations in human malignancies

人类恶性肿瘤中的功能丧失型 uORF 突变

阅读:7
作者:Julia Schulz, Nancy Mah, Martin Neuenschwander, Tabea Kischka, Richard Ratei, Peter M Schlag, Esmeralda Castaños-Vélez, Iduna Fichtner, Per-Ulf Tunn, Carsten Denkert, Oliver Klaas, Wolfgang E Berdel, Jens P von Kries, Wojciech Makalowski, Miguel A Andrade-Navarro, Achim Leutz, Klaus Wethmar

Abstract

Ribosome profiling revealed widespread translational activity at upstream open reading frames (uORFs) and validated uORF-mediated translational control as a commonly repressive mechanism of gene expression. Translational activation of proto-oncogenes through loss-of-uORF mutations has been demonstrated, yet a systematic search for cancer-associated genetic alterations in uORFs is lacking. Here, we applied a PCR-based, multiplex identifier-tagged deep sequencing approach to screen 404 uORF translation initiation sites of 83 human tyrosine kinases and 49 other proto-oncogenes in 308 human malignancies. We identified loss-of-function uORF mutations in EPHB1 in two samples derived from breast and colon cancer, and in MAP2K6 in a sample of colon adenocarcinoma. Both mutations were associated with enhanced translation, suggesting that loss-of-uORF-mediated translational induction of the downstream main protein coding sequence may have contributed to carcinogenesis. Computational analysis of whole exome sequencing datasets of 464 colon adenocarcinomas subsequently revealed another 53 non-recurrent somatic mutations functionally deleting 22 uORF initiation and 31 uORF termination codons, respectively. These data provide evidence for somatic mutations affecting uORF initiation and termination codons in human cancer. The insufficient coverage of uORF regions in current whole exome sequencing datasets demands for future genome-wide analyses to ultimately define the contribution of uORF-mediated translational deregulation in oncogenesis.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。