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Arginine Depletion in Human Cancers.
Devi D Nelakurti1, Tiffany Rossetti2, Aman Y Husbands3
1Biomedical Science Undergraduate Program, The Ohio State University Medical School, Columbus, OH 43210, USA.
Cancer mutations show a bias towards specific DNA changes, particularly C > T and G > A transitions, affecting arginine codons. This suggests a "purifying selection" mechanism influencing cancer development.
Area of Science:
- Genetics
- Cancer Biology
- Molecular Evolution
Background:
- Arginine is encoded by six codons, and mutations can lead to various amino acid substitutions or stop codons.
- A significant bias exists in arginine substitutions, with four amino acids (histidine, cysteine, glutamine, tryptophan) accounting for over 75% of changes.
- This mutational bias is linked to C > T and G > A transitions in arginine codons, a pattern observed across diverse cancer types.
Purpose of the Study:
- To review literature and reanalyze data on arginine substitution bias in cancer.
- To identify genes exhibiting this bias, including known and novel cancer drivers.
- To propose a model where base pair substitution bias and amino acid physiology contribute to purifying selection.
Main Methods:
- Literature review.
- Reanalysis of publicly available cancer mutation data from the Catalogue of Somatic Mutations in Cancer (COSMIC).
- Identification and analysis of genes with significant arginine substitution bias.
Main Results:
- The study confirms a universal C > T and G > A transition bias in four of the six arginine codons, independent of cancer origin or histology.
- Several genes were identified with arginine substitution bias, including IDH1, FGFR3, PPP6C, MAX, and GNAQ.
- The findings highlight specific genes, including four cancer driver genes, affected by this mutational bias.
Conclusions:
- A mutational bias, driven by specific base pair transitions, influences arginine substitutions in cancer.
- Both base pair substitution patterns and amino acid physiology likely contribute to purifying selection.
- The proposed model helps explain the observed arginine substitution bias in various cancers.
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