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.

不同物种的全基因组和转录组氨基酸使用偏好是分子进化中一个经过充分研究的现象，但其特征和在癌症进化和治疗中的意义在很大程度上仍未得到探索。在这里，我们分析了大规模转录组/蛋白质组图谱，例如癌症基因组图谱 (TCGA)、基因型组织表达 (GTEx) 和临床蛋白质组肿瘤分析联合会 (CPTAC)，发现与正常组织相比，不同的癌症类型显示出使用生物合成低成本氨基酸的趋同模式。这种模式可以通过基于平均生物合成能量的单一指标准确捕获氨基酸的成本，称为每个氨基酸的能量成本（ECPA）。有了这个指数，我们进一步比较了氨基酸使用的趋势以及癌症和组织发展中的贡献基因，并揭示了它们的逆转模式。最后，关注在发育过程中 ECPA 显着增加的肝脏组织，我们发现 ECPA 代表了一种强大的生物标志物，可以在 11 个独立的患者队列中始终如一地将肝脏肿瘤与正常肝脏样本区分开来，并且优于任何基于单一基因的指标。我们的研究揭示了癌症进化的一个重要原则，并建议将全球氨基酸用作癌症诊断的系统级生物标志物。