超越合成致死性：绘制与癌症患者生存相关的成对基因表达状态图谱。
Beyond Synthetic Lethality: Charting the Landscape of Pairwise Gene Expression States Associated with Survival in Cancer.
机构信息
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Cancer Data Science Laboratory, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA; Department of Biostatistics and Computational Biology, Harvard School of Public Health, Boston, MA, USA; Massachusetts General Hospital Cancer Center, Harvard Medical School, Boston, MA, USA.
出版信息
Cell Rep. 2019 Jul 23;28(4):938-948.e6. doi: 10.1016/j.celrep.2019.06.067.
The phenotypic effect of perturbing a gene's activity depends on the activity level of other genes, reflecting the notion that phenotypes are emergent properties of a network of functionally interacting genes. In the context of cancer, contemporary investigations have primarily focused on just one type of functional relationship between two genes-synthetic lethality (SL). Here, we define the more general concept of "survival-associated pairwise gene expression states" (SPAGEs) as gene pairs whose joint expression levels are associated with survival. We describe a data-driven approach called SPAGE-finder that when applied to The Cancer Genome Atlas (TCGA) data identified 71,946 SPAGEs spanning 12 distinct types, only a minority of which are SLs. The detected SPAGEs explain cancer driver genes' tissue specificity and differences in patients' response to drugs and stratify breast cancer tumors into refined subtypes. These results expand the scope of cancer SPAGEs and lay a conceptual basis for future studies of SPAGEs and their translational applications.
基因活性的表型效应取决于其他基因的活性水平，反映了表型是功能相互作用基因网络的涌现特性这一概念。在癌症的背景下，当代的研究主要集中在两种基因之间的一种功能关系上——合成致死性 (SL)。在这里，我们将更广泛的概念“与生存相关的成对基因表达状态”（SPAGE）定义为其共同表达水平与生存相关的基因对。我们描述了一种称为 SPAGE-finder 的数据驱动方法，当应用于癌症基因组图谱（TCGA）数据时，该方法确定了跨越 12 种不同类型的 71946 个 SPAGE，其中只有少数是 SL。检测到的 SPAGE 解释了癌症驱动基因的组织特异性以及患者对药物反应的差异，并将乳腺癌肿瘤分为精细的亚型。这些结果扩展了癌症 SPAGE 的范围，并为未来的 SPAGE 及其转化应用研究奠定了概念基础。
Zotero 插件