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一个可解释的图形神经框架来识别与癌症相关的内微生物群落

Zhaoqian Liu^1,2, Yuhan Sun¹, Yingjie Li³

¹School of Mathematics, Shandong University, Jinan, Shandong, 250100, China.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)

|September 3, 2024

概括

这项研究介绍了MICAH,一种新的图形神经网络框架,用于在瘤中识别与癌症相关的微生物. MICAH显著缩小了实验验证的微生物范围,推进了微生物组癌症研究.

科学领域:

在瘤学瘤学.
微生物学微生物学
生物信息学是一种生物信息学.

背景情况:

内微生物与癌症的发展和治疗有关,但它们的特定作用和与瘤的相互作用尚未得到充分理解.
现有的方法难以全面分析各种微生物群落和癌症组织之间的复杂关系.

研究的目的:

开发和验证一个计算框架,MICAH (使用异质图形变压器进行微生物癌症关联分析),用于识别与癌症相关的内微生物.
提高微生物与癌症关联分析的可解释性和准确性.

主要方法:

将微生物代谢和遗传学数据整合到异构图中.
应用图形变压器模型来捕捉复杂的微生物-瘤关系.
使用多种癌症类型数据集 (5种细菌,5种真菌) 和实验小鼠模型进行验证.

主要成果:

在多种癌症类型中,MICAH成功地确定了与癌症相关的微生物群落.
该框架证明了其可通用性和可重复性.
实验验证证证实了MICAH预测的微生物与瘤的相互作用.
源追踪表明,器官特异性是癌症相关微生物群落的关键因素.

结论:

MICAH提供了一个强大的,可解释的图形神经网络方法来分析内微生物组.
该框架显著减少了实验研究候选微生物的数量,加速了对瘤微生物组的研究.
了解特定器官的微生物贡献对于破译癌症和微生物相互作用至关重要.

关键词:

注意力机制注意力机制图表神经网络的神经网络不同质的图形表示形式.肠道内口微生物群

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相关概念视频

The Tumor Microenvironment

The Tumor Microenvironment

Every normal cell or tissue is embedded in a complex local environment called stroma, consisting of different cell types, a basal membrane, and blood vessels. As normal cells mutate and develop into cancer cells, their local environment also changes to allow cancer progression. The tumor microenvironment (TME) consists of a complex cellular matrix of stromal cells and the developing tumor. The cross-talk between cancer cells and surrounding stromal cells is critical to disrupt normal tissue...