Robust classification of wound healing stages in both mice and humans for acute and burn wounds based on transcriptomic data.

Robust classification of wound healing stages in both mice and humans for acute and burn wounds based on transcriptomic data.
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DOI:
10.1186/s12859-023-05295-z
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发表时间:
2023-04-25
期刊:
影响因子:
3
通讯作者:
--
中科院分区:
生物学4区
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伤口愈合涉及各种细胞类型之间的仔细协调,执行独特甚至多方面的功能。将这一复杂的动态过程抽象为四个主要伤口阶段对于伤口护理的研究至关重要,以便及时治疗和跟踪伤口进展。例如,在炎症阶段可以促进愈合的治疗在增殖阶段可能是有害的。此外,个体反应的时间尺度在同一物种之间和同一物种内差异很大。因此,评估伤口阶段的可靠方法可以帮助推进从动物到人类的转化工作。在这项工作中,我们提出了一个数据驱动的模型,该模型使用从小鼠和人类伤口(烧伤和手术)收集的活组织检查的转录组学数据,有力地识别了主要的伤口愈合阶段。由公开可用的转录组阵列组成的训练数据集用于获得58个通常差异表达的共享基因。根据时间基因表达动态将它们分为5类。簇表示包含伤口愈合轨迹的5维参数空间。然后,我们在5维空间中创建了一个数学分类算法,并证明它可以区分伤口愈合的四个阶段:止血,炎症,增殖和重塑。在这项工作中,我们提出了一种基于基因表达的伤口阶段检测算法。这项工作表明,尽管物种和伤口之间似乎存在差异,但伤口愈合阶段的基因表达具有普遍特征。我们的算法对于烧伤和手术类型的人类和小鼠伤口都表现良好。该算法有可能作为一种诊断工具,通过提供一种跟踪伤口愈合进展的方法,与视觉指标相比,具有更高的准确性和更精细的时间分辨率,从而促进精确的伤口护理。这增加了采取预防行动的可能性。在线版本包含补充材料,可通过10.1186/s12859-023-05295-z获得。
Wound healing involves careful coordination among various cell types carrying out unique or even multifaceted functions. The abstraction of this complex dynamic process into four primary wound stages is essential to the study of wound care for timing treatment and tracking wound progression. For example, a treatment that may promote healing in the inflammatory stage may prove detrimental in the proliferative stage. Additionally, the time scale of individual responses varies widely across and within the same species. Therefore, a robust method to assess wound stages can help advance translational work from animals to humans. In this work, we present a data-driven model that robustly identifies the dominant wound healing stage using transcriptomic data from biopsies gathered from mouse and human wounds, both burn and surgical. A training dataset composed of publicly available transcriptomic arrays is used to derive 58 shared genes that are commonly differentially expressed. They are divided into 5 clusters based on temporal gene expression dynamics. The clusters represent a 5-dimensional parametric space containing the wound healing trajectory. We then create a mathematical classification algorithm in the 5-dimensional space and demonstrate that it can distinguish between the four stages of wound healing: hemostasis, inflammation, proliferation, and remodeling. In this work, we present an algorithm for wound stage detection based on gene expression. This work suggests that there are universal characteristics of gene expression in wound healing stages despite the seeming disparities across species and wounds. Our algorithm performs well for human and mouse wounds of both burn and surgical types. The algorithm has the potential to serve as a diagnostic tool that can advance precision wound care by providing a way of tracking wound healing progression with more accuracy and finer temporal resolution compared to visual indicators. This increases the potential for preventive action. The online version contains supplementary material available at 10.1186/s12859-023-05295-z.
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