癌症是一种复杂的疾病，具有影响患者预后的多种分子机制。基于网络的方法可以有效揭示癌症预后和基因相互作用的整体情况。然而，跨多种癌症类型的共表达网络和预后基因模块的全面景观仍然难以捉摸。在这项研究中，我们对 32 种癌症类型的共表达网络进行了系统分析。我们的分析确定了 4749 个预后模块，它们在调节癌症进展中发挥着至关重要的作用。综合表观基因组分析表明，这些模块受到基因表达和甲基化之间相互作用的调节。网络模块的共调控基因在染色体细胞带中富集，并优先位于开放染色质区域。保留的网络模块形成了 330 个位于染色体热点的模块簇。癌症类型特异性预后模块参与不同癌症类型中独特的重要生物过程。总体而言，我们的研究提供了丰富的流行基因网络资源和驱动癌症预后的潜在多尺度调控机制，为生物标志物发现和治疗靶点开发奠定了基础。© 2023 Xu和Zhang；由冷泉港实验室出版社出版。

Cancer is a complex disease with diverse molecular mechanisms that affect patient prognosis. Network-based approaches are effective in revealing a holistic picture of cancer prognosis and gene interactions. However, a comprehensive landscape of coexpression networks and prognostic gene modules across multiple cancer types remains elusive. In this study, we performed a systematic analysis of coexpression networks in 32 cancer types. Our analysis identified 4749 prognostic modules that play a vital role in regulating cancer progression. Integrative epigenomic analyses revealed that these modules were regulated by interactions between gene expression and methylation. Coregulated genes of network modules were enriched in chromosome cytobands and preferentially localized in open chromatin regions. The preserved network modules formed 330 module clusters that resided in chromosome hot spots. The cancer-type-specific prognostic modules participated in unique essential biological processes in different cancer types. Overall, our study provides rich resources of prevalent gene networks and underlying multiscale regulatory mechanisms driving cancer prognosis, which lay a foundation for biomarker discovery and therapeutic target development.© 2023 Xu and Zhang; Published by Cold Spring Harbor Laboratory Press.