Codon optimality in cancer

Abstract

A key characteristic of cancer cells is their increased proliferative capacity, which requires elevated levels of protein synthesis. The process of protein synthesis involves the translation of codons within the mRNA coding sequence into a string of amino acids to form a polypeptide chain. As most amino acids are encoded by multiple codons, the nucleotide sequence of a coding region can vary dramatically without altering the polypeptide sequence of the encoded protein. Although mutations that do not alter the final amino acid sequence are often thought of as silent/synonymous, these can still have dramatic effects on protein output. Because each codon has a distinct translation elongation rate and can differentially impact mRNA stability, each codon has a different degree of ‘optimality’ for protein synthesis. Recent data demonstrates that the codon preference of a transcriptome matches the abundance of tRNAs within the cell and that this supply and demand between tRNAs and mRNAs varies between different cell types. The largest observed distinction is between mRNAs encoding proteins associated with proliferation or differentiation. Nevertheless, precisely how codon optimality and tRNA expression levels regulate cell fate decisions and their role in malignancy is not fully understood. This review describes the current mechanistic understanding on codon optimality, its role in malignancy and discusses the potential to target codon optimality therapeutically in the context of cancer.

Arginine Depletion in Human Cancers

“…This codon usage bias has a major role in gene expression, regulating translation speed and protein folding [ 28 , 29 , 30 ], as well as mRNA structure, processing, and stability [ 31 , 32 , 33 , 34 ]. Additionally, in cancer cells, codon usage is optimized to accommodate high translation of cell cycle regulatory genes [ 35 ]. Codon usage bias is species-specific [ 36 ] with biases in arginine usage correlating with speciation [ 16 ].…”

“…Purifying selection acting at the amino acid level then reinforces this asymmetry, which can occur in a protein- or tissue-dependent manner. For example, stomach cancers show a pronounced Arg > His bias, whereas skin cancers have a strong Arg > Cys bias [ 35 ]. Determining why such context-dependent behaviors happen, and whether this model of “sequential selection” extends to other signatures, are important next steps for the field.…”

Perseverance of protein homeostasis despite mistranslation of glycine codons with alanine

“…A recent approach based on experimental data as well as sequence properties of the tRNA genomic loci predicted that at least 314 tRNAs are functional and expressed [34]. Different human cells and tissues show differential regulation of tRNA genes [30,35,36], which include different tRNAs for each proteinogenic amino acid as well as many copies of each tRNA isoacceptor. Even the tRNA isodecoders that share the same anticodon are found in multiple copies.…”

Identification, expression, and association analysis of calcineurin B-like protein–interacting protein kinase genes in peanut

“…The polymorphic site in AdCIPK12 [A09_ 903,480 (G/K/T) ], located in the predicted first exon region of the gene, A09_903480 (G/K/T) , led no transition (synonymous mutation) in the peanut population. Recent studies proved that synonymous mutations also have dramatic effects on protein output ( Gillen et al, 2021 ). These results indicated that the B09_903480 (G/K/T) sequence polymorphisms might be the actual functional sites.…”