Andrieux Geoffroy, Chakraborty Sajib, Das Tonmoy, Boerries Melanie
Faculty of Medicine, Medical Center-University of Freiburg, Institute of Medical Bioinformatics and Systems Medicine, University of Freiburg, Freiburg, Germany.
German Cancer Consortium (DKTK) Partner Site Freiburg, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Front Cell Dev Biol. 2020 Dec 15;8:586479. doi: 10.3389/fcell.2020.586479. eCollection 2020.
The proteotranscriptomic landscape depends on the transcription, mRNA-turnover, translation, and regulated-destruction of proteins. Gene-specific mRNA-to-protein correlation is the consequence of the dynamic interplays of the different regulatory processes of proteotranscriptomic landscape. So far, the critical impact of mRNA and protein stability on their subsequent correlation on a global scale remained unresolved. Whether the mRNA-to-protein correlations are constrained by their stability and conserved across mammalian species including human is unknown. Moreover, whether the stability-dependent correlation pattern is altered in the tumor has not been explored. To establish the quantitative relationship between stability and correlation between mRNA and protein levels, we performed a multi-omics data integration study across mammalian systems including diverse types of human tissues and cell lines in a genome-wide manner. The current study illuminated an important aspect of the mammalian proteotranscriptomic landscape by providing evidence that stability-constrained mRNA-to-protein correlation follows a hierarchical pattern that remains conserved across different tissues and mammalian species. By analyzing the tumor and non-tumor tissues, we further illustrated that mRNA-to-protein correlations deviate in tumor tissues. By gene-centric analysis, we harnessed the hierarchical correlation patterns to identify altered mRNA-to-protein correlation in tumors and characterized the tumor correlation-enhancing and -repressing genes. We elucidated the transcriptional regulatory circuits controlling the correlation-enhancing and -repressing genes that are associated with metabolic reprogramming and cancer-associated pathways in tumor tissue. By tightly controlling the mRNA-to-protein correlation of specific genes, the transcriptional regulatory circuits may enable the tumor cells to evolve in varying tumor microenvironment. The mRNA-to-protein correlation analysis thus can serve as a unique approach to identify the pathways prioritized by the tumor cells at different clinical stages. The component of transcriptional regulatory circuits identified by the current study can serve as potential candidates for stage-dependent anticancer therapy.
蛋白质转录组格局取决于蛋白质的转录、mRNA 周转、翻译及调控性降解。基因特异性的 mRNA 与蛋白质的相关性是蛋白质转录组格局中不同调控过程动态相互作用的结果。到目前为止，mRNA 和蛋白质稳定性对其在全球范围内后续相关性的关键影响仍未得到解决。mRNA 与蛋白质的相关性是否受其稳定性的限制并在包括人类在内的哺乳动物物种中保守尚不清楚。此外，稳定性依赖的相关模式在肿瘤中是否改变也尚未被探索。为了建立稳定性与 mRNA 和蛋白质水平之间相关性的定量关系，我们以全基因组方式对包括多种类型人类组织和细胞系在内的哺乳动物系统进行了多组学数据整合研究。当前的研究通过提供证据表明稳定性受限的 mRNA 与蛋白质的相关性遵循一种在不同组织和哺乳动物物种中都保守的层次模式，阐明了哺乳动物蛋白质转录组格局的一个重要方面。通过分析肿瘤组织和非肿瘤组织，我们进一步表明 mRNA 与蛋白质的相关性在肿瘤组织中存在偏差。通过以基因为中心的分析，我们利用层次相关模式来识别肿瘤中改变的 mRNA 与蛋白质的相关性，并对增强和抑制肿瘤相关性的基因进行了表征。我们阐明了控制与肿瘤组织中代谢重编程和癌症相关途径相关的增强和抑制相关性基因的转录调控回路。通过严格控制特定基因的 mRNA 与蛋白质的相关性，转录调控回路可能使肿瘤细胞在不同的肿瘤微环境中进化。因此，mRNA 与蛋白质的相关性分析可作为一种独特的方法来识别肿瘤细胞在不同临床阶段优先选择 的途径。本研究确定的转录调控回路的组成部分可作为阶段依赖性抗癌治疗的潜在候选者。
