Convergent Usage of Amino Acids in Human Cancers as A Reversed Process of Tissue Development

Yikai Luo, Han Liang

Research output: Contribution to journalArticlepeer-review

Abstract

Genome- and transcriptome-wide amino acid usage preference across different species is a well-studied phenomenon in molecular evolution, but its characteristics and implication in cancer evolution and therapy remain largely unexplored. Here, we analyzed large-scale transcriptome/proteome profiles, such as The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx), and the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and found that compared to normal tissues, different cancer types showed a convergent pattern toward using biosynthetically low-cost amino acids. Such a pattern can be accurately captured by a single index based on the average biosynthetic energy cost of amino acids, termed energy cost per amino acid (ECPA). With this index, we further compared the trends of amino acid usage and the contributing genes in cancer and tissue development, and revealed their reversed patterns. Finally, focusing on the liver, a tissue with a dramatic increase in ECPA during development, we found that ECPA represents a powerful biomarker that could distinguish liver tumors from normal liver samples consistently across 11 independent patient cohorts and outperforms any index based on single genes. Our study reveals an important principle underlying cancer evolution and suggests the global amino acid usage as a system-level biomarker for cancer diagnosis.

Original languageEnglish (US)
Pages (from-to)147-162
Number of pages16
JournalGenomics, Proteomics and Bioinformatics
Volume20
Issue number1
DOIs
StatePublished - Feb 2022

Keywords

  • Amino acid usage
  • Biosynthetic energy
  • Diagnostic biomarker
  • Tissue development

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Genetics
  • Computational Mathematics

MD Anderson CCSG core facilities

  • Bioinformatics Shared Resource

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