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人类癌症中氨基酸的趋同使用作为组织发育的逆向过程

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

作者信息

Luo Yikai, Liang Han

机构信息

Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

Graduate Program in Quantitative and Computational Biosciences, Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

出版信息

Genomics Proteomics Bioinformatics. 2022 Feb;20(1):147-162. doi: 10.1016/j.gpb.2021.08.004. Epub 2021 Sep 4.

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.

摘要

不同物种间全基因组和转录组水平的氨基酸使用偏好是分子进化中一个已被充分研究的现象,但其在癌症进化和治疗中的特征及意义仍 largely 未被探索。在此,我们分析了大规模转录组/蛋白质组图谱,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盟(CPTAC),发现与正常组织相比,不同癌症类型在使用生物合成成本低的氨基酸方面呈现出趋同模式。这种模式可以通过基于氨基酸平均生物合成能量成本的单一指标准确捕捉,该指标称为每氨基酸能量成本(ECPA)。利用这个指标,我们进一步比较了癌症和组织发育过程中氨基酸使用趋势及相关基因,揭示了它们相反的模式。最后,聚焦于肝脏,一个在发育过程中 ECPA 显著增加的组织,我们发现 ECPA 是一个强大的生物标志物,能够在 11 个独立患者队列中始终如一地将肝肿瘤与正常肝脏样本区分开来,并且优于任何基于单基因的指标。我们的研究揭示了癌症进化的一个重要原则,并提出全球氨基酸使用作为癌症诊断的系统水平生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5de/9510935/b74002b7afe5/gr1.jpg

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