Genomics Proteomics & BioinformaticsBioinformaticsPeer-reviewed journal article
Convergent Usage of Amino Acids in Human Cancers as a Reversed Process of Tissue Development
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 TCGA, GTEx, and CPTAC and found that compared to normal tissues, different cancer types showed a convergent pattern towards 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 EPCA represented a powerful biomarker that could distinguish liver tumors from normal liver samples consistently across 11 independent patient cohorts (AUROC = ~0.99) and outperformed 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.
- organism: human
- assay: bulk RNA-seq
- assay: proteomics
- research focus: differential expression
- research focus: benchmarking
- research focus: gene regulatory network inference
- research focus: cell type annotation
- approach: statistical model
- Citations
- 2
- FWCI
- 0.08
- Field percentile
- 33th percentile
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