系统剖析揭示了ER+乳腺癌患者血液中反复失调的细胞因子信号反应。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Brian Orcutt-Jahns, Joao Rodrigues Lima Junior, Emily Lin, Russell C Rockne, Adina Matache, Sergio Branciamore, Ethan Hung, Andrei S Rodin, Peter P Lee, Aaron S Meyer
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引用次数: 0

摘要

细胞因子协同作用,维持免疫平衡并协调免疫反应。在ER+乳腺癌病例中,外周免疫细胞对多种细胞因子的反应发生了改变,这些改变与患者的预后密切相关。为了从系统层面了解这种失调,我们测量了健康对照组和ER+乳腺癌患者外周血中各种免疫细胞类型的细胞因子反应和受体丰度。利用张量因子化技术对这些多维数据进行建模,我们发现乳腺癌患者的反应发生了广泛的改变,包括对IL-10的反应急剧下降,pSmad2/3和pSTAT4的基础水平升高。ER+患者还表现出PD-L1、IL6Rα和IL2Rα等受体的上调。尽管如此,受体丰度的变化并不能解释对细胞因子反应的改变。因此,张量因子化有助于揭示免疫系统的协调重编程,这种重编程在我们的队列中是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systems profiling reveals recurrently dysregulated cytokine signaling responses in ER+ breast cancer patients' blood.

Cytokines operate in concert to maintain immune homeostasis and coordinate immune responses. In cases of ER+ breast cancer, peripheral immune cells exhibit altered responses to several cytokines, and these alterations are correlated strongly with patient outcomes. To develop a systems-level understanding of this dysregulation, we measured a panel of cytokine responses and receptor abundances in the peripheral blood of healthy controls and ER+ breast cancer patients across immune cell types. Using tensor factorization to model this multidimensional data, we found that breast cancer patients exhibited widespread alterations in response, including drastically reduced response to IL-10 and heightened basal levels of pSmad2/3 and pSTAT4. ER+ patients also featured upregulation of PD-L1, IL6Rα, and IL2Rα, among other receptors. Despite this, alterations in response to cytokines were not explained by changes in receptor abundances. Thus, tensor factorization helped to reveal a coordinated reprogramming of the immune system that was consistent across our cohort.

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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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