Tumor development is a process involving loss of the differentiation phenotype and acquisition of stem-like characteristics, which is driven by intracellular rewiring of signaling network. The measurement of network reprogramming and disorder would be challenging due to the complexity and heterogeneity of tumors. Here, we proposed signaling entropy to assess the degree of tumor network disorder. We calculated signaling entropy for 33 tumor types in The Cancer Genome Atlas database based on transcriptomic and proteomic data. The signaling entropy of tumors was significantly higher than that of normal samples and was highly correlated with cell stemness, cancer type, tumor grade, and metastasis. We further demonstrated the sensitivity and accuracy of using local signaling entropy in prognosis prediction and drug response evaluation. Overall, signaling entropy could reveal cancer network disorders related to tumor malignant potency, clinical prognosis, and drug response.

中文翻译：

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整体和局部信号熵揭示的泛癌网络障碍

肿瘤发展是一个涉及分化表型丧失和获得干细胞样特征的过程，这是由信号网络的细胞内重新布线驱动的。由于肿瘤的复杂性和异质性，网络重编程和紊乱的测量将具有挑战性。在这里，我们提出信号熵来评估肿瘤网络紊乱的程度。我们根据转录组和蛋白质组数据计算了癌症基因组图谱数据库中 33 种肿瘤类型的信号熵。肿瘤的信号熵显着高于正常样本，并且与细胞干性、癌症类型、肿瘤分级和转移高度相关。我们进一步证明了在预后预测和药物反应评估中使用局部信号熵的敏感性和准确性。全面的，