Literature DB >> 33199641

Mutation bias within oncogene families is related to proliferation-specific codon usage.

Hannah Benisty1, Marc Weber1, Xavier Hernandez-Alias1, Martin H Schaefer2,3, Luis Serrano2,4,5.   

Abstract

It is well known that in cancer gene families some members are more frequently mutated in tumor samples than their family counterparts. A paradigmatic case of this phenomenon is KRAS from the RAS family. Different explanations have been proposed ranging from differential interaction with other proteins to preferential expression or localization. Interestingly, it has been described that despite the high amino acid identity between RAS family members, KRAS employs an intriguing differential codon usage. Here, we found that this phenomenon is not exclusive to the RAS family. Indeed, in the RAS family and other oncogene families with two or three members, the most prevalently mutated gene in tumor samples employs a differential codon usage that is characteristic of genes involved in proliferation. Prompted by these observations, we chose the RAS family to experimentally demonstrate that the translation efficiency of oncogenes that are preferentially mutated in tumor samples is increased in proliferative cells compared to quiescent cells. These results were further validated by assessing the translation efficiency of KRAS in cell lines that differ in their tRNA expression profile. These differences are related to the cell division rate of the studied cells and thus suggest an important role in context-specific oncogene expression regulation. Altogether, our study demonstrates that dynamic translation programs contribute to shaping the expression profiles of oncogenes. Therefore, we propose this codon bias as a regulatory layer to control cell context-specific expression and explain the differential prevalence of mutations in certain members of oncogene families.

Entities:  

Keywords:  KRAS; codon usage; oncogene; tRNA; translation

Mesh:

Substances:

Year:  2020        PMID: 33199641      PMCID: PMC7720162          DOI: 10.1073/pnas.2016119117

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  57 in total

1.  Wild-type NRas and KRas perform distinct functions during transformation.

Authors:  Poppy P Fotiadou; Chiaki Takahashi; Hasan N Rajabi; Mark E Ewen
Journal:  Mol Cell Biol       Date:  2007-07-16       Impact factor: 4.272

2.  Ras GTPases: codon bias holds KRas down but not out.

Authors:  Brian O Bodemann; Michael A White
Journal:  Curr Biol       Date:  2013-01-07       Impact factor: 10.834

3.  Widespread and Functional RNA Circularization in Localized Prostate Cancer.

Authors:  Sujun Chen; Vincent Huang; Xin Xu; Julie Livingstone; Fraser Soares; Jouhyun Jeon; Yong Zeng; Junjie Tony Hua; Jessica Petricca; Haiyang Guo; Miranda Wang; Fouad Yousif; Yuzhe Zhang; Nilgun Donmez; Musaddeque Ahmed; Stas Volik; Anna Lapuk; Melvin L K Chua; Lawrence E Heisler; Adrien Foucal; Natalie S Fox; Michael Fraser; Vinayak Bhandari; Yu-Jia Shiah; Jiansheng Guan; Jixi Li; Michèle Orain; Valérie Picard; Hélène Hovington; Alain Bergeron; Louis Lacombe; Yves Fradet; Bernard Têtu; Stanley Liu; Felix Feng; Xue Wu; Yang W Shao; Malgorzata A Komor; Cenk Sahinalp; Colin Collins; Youri Hoogstrate; Mark de Jong; Remond J A Fijneman; Teng Fei; Guido Jenster; Theodorus van der Kwast; Robert G Bristow; Paul C Boutros; Housheng Hansen He
Journal:  Cell       Date:  2019-02-07       Impact factor: 41.582

4.  K-ras is essential for the development of the mouse embryo.

Authors:  K Koera; K Nakamura; K Nakao; J Miyoshi; K Toyoshima; T Hatta; H Otani; A Aiba; M Katsuki
Journal:  Oncogene       Date:  1997-09-04       Impact factor: 9.867

Review 5.  RAS isoforms and mutations in cancer at a glance.

Authors:  G Aaron Hobbs; Channing J Der; Kent L Rossman
Journal:  J Cell Sci       Date:  2016-03-16       Impact factor: 5.285

6.  The DEAD-Box Protein Dhh1p Couples mRNA Decay and Translation by Monitoring Codon Optimality.

Authors:  Aditya Radhakrishnan; Ying-Hsin Chen; Sophie Martin; Najwa Alhusaini; Rachel Green; Jeff Coller
Journal:  Cell       Date:  2016-09-15       Impact factor: 41.582

7.  Codon usage regulates human KRAS expression at both transcriptional and translational levels.

Authors:  Jingjing Fu; Yunkun Dang; Christopher Counter; Yi Liu
Journal:  J Biol Chem       Date:  2018-10-01       Impact factor: 5.157

8.  K-Ras and H-Ras activation promote distinct consequences on endometrial cell survival.

Authors:  Yumiko Ninomiya; Kiyoko Kato; Akira Takahashi; Yousuke Ueoka; Tetsuya Kamikihara; Takahiro Arima; Takao Matsuda; Hidenori Kato; Jun-Ichi Nishida; Norio Wake
Journal:  Cancer Res       Date:  2004-04-15       Impact factor: 12.701

9.  OncodriveROLE classifies cancer driver genes in loss of function and activating mode of action.

Authors:  Michael P Schroeder; Carlota Rubio-Perez; David Tamborero; Abel Gonzalez-Perez; Nuria Lopez-Bigas
Journal:  Bioinformatics       Date:  2014-09-01       Impact factor: 6.937

10.  IntOGen-mutations identifies cancer drivers across tumor types.

Authors:  Abel Gonzalez-Perez; Christian Perez-Llamas; Jordi Deu-Pons; David Tamborero; Michael P Schroeder; Alba Jene-Sanz; Alberto Santos; Nuria Lopez-Bigas
Journal:  Nat Methods       Date:  2013-09-15       Impact factor: 28.547

View more
  5 in total

1.  Pan-cancer analyses of synonymous mutations based on tissue-specific codon optimality.

Authors:  Xia Ran; Jinyuan Xiao; Fang Cheng; Tao Wang; Huajing Teng; Zhongsheng Sun
Journal:  Comput Struct Biotechnol J       Date:  2022-07-06       Impact factor: 6.155

Review 2.  Protein synthesis control in cancer: selectivity and therapeutic targeting.

Authors:  Joanna R Kovalski; Duygu Kuzuoglu-Ozturk; Davide Ruggero
Journal:  EMBO J       Date:  2022-03-22       Impact factor: 14.012

Review 3.  KRAS-related long noncoding RNAs in human cancers.

Authors:  Mahsa Saliani; Amin Mirzaiebadizi; Ali Javadmanesh; Akram Siavoshi; Mohammad Reza Ahmadian
Journal:  Cancer Gene Ther       Date:  2021-09-06       Impact factor: 5.854

Review 4.  Codon optimality in cancer.

Authors:  Sarah L Gillen; Joseph A Waldron; Martin Bushell
Journal:  Oncogene       Date:  2021-09-28       Impact factor: 9.867

5.  Distinct signatures of codon and codon pair usage in 32 primary tumor types in the novel database CancerCoCoPUTs for cancer-specific codon usage.

Authors:  Douglas Meyer; Jacob Kames; Haim Bar; Anton A Komar; Aikaterini Alexaki; Juan Ibla; Ryan C Hunt; Luis V Santana-Quintero; Anton Golikov; Michael DiCuccio; Chava Kimchi-Sarfaty
Journal:  Genome Med       Date:  2021-07-28       Impact factor: 11.117

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.