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单细胞转录组的基因剂量分析:将共翻译蛋白靶向与转移性三阴性乳腺癌联系起来

Gene Dosage Analysis on the Single-Cell Transcriptomes Linking Cotranslational Protein Targeting to Metastatic Triple-Negative Breast Cancer.

作者信息

Liu Yining, Zhao Min

机构信息

The School of Public Health, Institute for Chemical Carcinogenesis, Guangzhou Medical University, Guangzhou 511436, China.

School of Science, Technology and Engineering, University of the Sunshine Coast, Maroochydore, QLD 4558, Australia.

出版信息

Pharmaceuticals (Basel). 2021 Sep 10;14(9):918. doi: 10.3390/ph14090918.

Abstract

Many recent efforts have been put into the association between expression heterogeneity and different cell types and states using single-cell RNA transcriptome analysis. There is only limited understanding of gene dosage effects for the genetic heterogeneity at the single-cell level. By focusing on concordant copy number variation (CNV) and expression, we presented a computational framework to explore dosage effect for aggressive metastatic triple-negative breast cancer (TNBC) at the single-cell level. In practice, we collected CNV and single-cell expression data from the same patients with independent technologies. By focusing on 47,198 consistent copy number gains (CNG) and gene up-regulation from 1145 single cells, ribosome proteins with important roles in protein targeting were enriched. Independent validation in another metastatic TNBC dataset further prioritized signal recognition particle-dependent protein targeting as the top functional module. More interesting, the increased ribosome gene copies in TNBC may associate with their enhanced stemness and metastatic potential. Indeed, the prioritization of a well-upregulated functional module confirmed by high copy numbers at the single-cell level and contributing to patient survival may indicate the possibility of targeted therapy based on ribosome proteins for TNBC.

摘要

最近,人们利用单细胞RNA转录组分析,对表达异质性与不同细胞类型和状态之间的关联进行了许多研究。对于单细胞水平上遗传异质性的基因剂量效应,人们的了解还很有限。通过关注一致的拷贝数变异(CNV)和表达,我们提出了一个计算框架,以在单细胞水平上探索侵袭性转移性三阴性乳腺癌(TNBC)的剂量效应。在实践中,我们通过独立技术收集了同一患者的CNV和单细胞表达数据。通过关注来自1145个单细胞的47198个一致的拷贝数增加(CNG)和基因上调,在蛋白质靶向中起重要作用的核糖体蛋白得到了富集。在另一个转移性TNBC数据集中的独立验证进一步将信号识别颗粒依赖性蛋白质靶向确定为顶级功能模块。更有趣的是,TNBC中核糖体基因拷贝数的增加可能与其增强的干性和转移潜力有关。事实上,一个在单细胞水平上由高拷贝数确认且对患者生存有影响的上调功能模块的优先级排序,可能表明基于核糖体蛋白对TNBC进行靶向治疗的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e0d6/8472593/832879066a6e/pharmaceuticals-14-00918-g001.jpg

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