鉴定基质抗胎盘和癌症侵袭平行进化的基因。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Yasir Suhail, Wenqiang Du, Junaid Afzal, Günter P Wagner, Kshitiz
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引用次数: 0

摘要

肿瘤传播的基质调控是公认的,但致病基因仍未确定。我们之前已经证明上皮物种已经获得了对胎盘侵袭的基质抗性,这与恶性肿瘤发生率的降低有关,并确定了与胎盘侵袭深度相关的基质基因,称为ELI(进化的入侵水平)基因。同样地,人子宫内膜成纤维细胞的去个体化也能抵抗胎盘的侵袭。我们假设这两种轨迹可能会趋同地使用相似的途径,从而为鉴定调节上皮细胞侵袭的基质基因提供了机会。我们创建了一个基因集ELI-D1 (ELI-Decidual 1),推测它是基质易受侵袭的基础。ELI-D1在许多人类癌症的T1-T2期转移中呈负富集,通常在扩散之前。我们还发现了真核动物中ELI-D1基因变异的候选转录调节因子,功能上显示Nr2f6和JDP2可以调节人成纤维细胞对侵袭的基质抗性。我们的比较方法为我们提供了一个与人类癌症基质易感性相关的基因集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying genes underlying parallel evolution of stromal resistance to placental and cancer invasion.

Stromal regulation of cancer dissemination is well recognized, however causal genes remain unidentified. We previously demonstrated that epitheliochorial species have acquired stromal resistance to placental invasion, correlating with reduced rate of cancer malignancies, identifying stromal genes correlating with depth of placental invasion called ELI (Evolved Levels of Invasibility) genes. Similarly, decidualization of human endometrial fibroblasts confers resistance to placental invasion. We hypothesized that both trajectories may convergently use similar pathways, providing an opportunity to identify stromal genes regulating epithelial invasion. We created a gene-set ELI-D1 (ELI-Decidual 1), putatively underlying stromal vulnerability to invasion. ELI-D1 were negatively enriched in T1-T2 stage transition in many human cancers, typically preceding dissemination. We also identified candidate transcriptional regulators underlying variation in ELI-D1 genes across eutherians, functionally showing Nr2f6, and JDP2 can regulate stromal resistance to invasion in human fibroblasts. Our comparative approach provides us with a gene-set linked to stromal vulnerability in human cancers.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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