Dysfunctional tRNA reprogramming and codon-biased translation in cancer

Abstract

Many cancers hijack translation to increase the synthesis of tumor-driving proteins, the messenger mRNAs of which have specific codon usage patterns. Termed 'codon-biased translation' and originally identified in stress response regulation, this mechanism is supported by diverse studies demonstrating how the 50 RNA modifications of the epitranscriptome, specific tRNAs, and codon-biased mRNAs are used by oncogenic programs to promote proliferation and chemoresistance. The epitranscriptome writers METTL1-WDR4, Elongator complex protein (ELP)1-6, CTU1-2, and ALKBH8-TRM112 illustrate the principal mechanism of codon-biased translation, with gene amplifications, increased RNA modifications, and enhanced tRNA stability promoting cancer proliferation. Furthermore, systems-level analyses of 34 tRNA writers and 493 tRNA genes highlight the theme of tRNA epitranscriptome dysregulation in many cancers and identify candidate tRNA writers, tRNA modifications, and tRNA molecules as drivers of pathological codon-biased translation.

Keywords: cancer; codon; epitranscriptome; gene expression; systems biology; tRNA modifications; translational regulation.

Fig. 1.. tRNA as a driver of translational dysfunction in human disease.

After initiation, translational control of gene expression can be guided by tRNAs, modifications, and writers that promote the synthesis of mRNAs with specific codon biases, with normal function of this system regulating stress responses, cell cycle, and growth programs (left). In the pathophysiology of cancer and other diseases, this system can be corrupted to alter translational regulation of gene expression, with some cancers using writers, modifications, and tRNAs to increase the translation of mRNAs with specific codon biases to promote growth programs, such as changes in oncogenic pathways, cell cycle and metabolism (right). RMP: RNA-modifying protein; METTL1: methyltransferase 1, tRNA methylguanosine.

Fig. 2.. tRNA modifications and writers linked to cancer.

(A) A canonical tRNA structure showing the locations of specific tRNA modifications and their writers shown to be drivers of cancer proliferation. (B) Complex biochemical pathways for the synthesis of wobble uridine modifications by ALKBH8-TRM112, ELP1-6, CTU1/2 and FTSJ1 writers, illustrating the many potential points for corruption of tRNA reprogramming and codon-biased translation in cancer and the many possible targets for therapeutic intervention.

Fig. 3.. Variations of codon-biased translational regulation.

(A) tRNAs, modifications, anticodons, and mRNAs provide key control points regulating codon-biased translation of multiple types of proteins, here illustrated with tRNA-Arg-TCT and METTL1 modification with m⁷G at position 46 and a wobble U modification. (B) Blue-shaded synonymous codons for specific amino acids have been mechanistically linked to codon-biased translation. (C) Gene-specific codon counting reveals highly biased codon usage patterns in families of stress response genes. Heat maps of (upper panel) yeast and (lower panel) human gene-specific analyses reveal significant over- (yellow) and under-use (purple) of individual codons (columns) in 100’s of yeast and 1000’s of human genes (rows). These heat maps do not provide details about gene regulation per se, but instead highlight groups of genes that are heavily biased in usage of groups of codons, as detailed in a previous publication [68]. (D) Writers (left), modifications (middle), and proteins derived from targets of codon-biased translational regulation (right).

Fig. 4.. Gene amplification changes for RNA modification writers in cancers.

(A) Bar graph detailing the top 10 cancers that have amplification of the gene for METTL. (B) Hierarchical clustering of gene amplifications for 34 writers in 55 cancers from 181 studies representing 47,534 samples in the TCGA. Data represent the alteration frequency, with a minimum of 50 total cases and a minimum of 1% alteration. Colored arrows highlight specific RNA-modifying proteins and cancers that are discussed in the text; black, METTL1; green, TRMT12; red, bladder/urinary tract cancer and serious ovarian cancer.

Fig. 5.. Gene deletion changes for RNA modification writers in cancers.

(A) Bar graph detailing the top 10 cancers that have deletion of the gene for TRMT9B. (B) Hierarchical clustering of gene deletions for 34 writers in 55 cancers from 181 studies representing 47,534 samples in the TCGA. Data represent the alteration frequency, with a minimum of 50 total cases and a minimum of 1% alteration.

Fig. 6.. Writer RNA expression data in cancers.

(A) Bar graph detailing the 10 cancer cell lines with increased METTL expression. (B) Hierarchical clustering of the log₂(fold-change) values for mRNA expression for 34 writers in 798 CCLE samples found in DepMap (Expression 22Q1 Public).