School of Automation, Northwestern Polytechnical University, No.127, Youyi West Road, Xi'an 710072, China.
Brief Bioinform. 2021 Nov 5;22(6). doi: 10.1093/bib/bbab175.
Considerable evidence suggests that during the progression of cancer initiation, the state transition from wellness to disease is not necessarily smooth but manifests switch-like nonlinear behaviors, preventing the cancer prediction and early interventional therapy for patients. Understanding the mechanism of such wellness-to-disease transitions is a fundamental and challenging task. Despite the advances in flux theory of nonequilibrium dynamics and 'critical slowing down'-based system resilience theory, a system-level approach still lacks to fully describe this state transition. Here, we present a novel framework (called bioRFR) to quantify such wellness-to-disease transition during cancer initiation through uncovering the biological system's resilience function from gene expression data. We used bioRFR to reconstruct the biologically and dynamically significant resilience functions for cancer initiation processes (e.g. BRCA, LUSC and LUAD). The resilience functions display the similar resilience pattern with hysteresis feature but different numbers of tipping points, which implies that once the cell become cancerous, it is very difficult or even impossible to reverse to the normal state. More importantly, bioRFR can measure the severe degree of cancer patients and identify the personalized key genes that are associated with the individual system's state transition from normal to tumor in resilience perspective, indicating that bioRFR can contribute to personalized medicine and targeted cancer therapy.
大量证据表明，在癌症发生的过程中，从健康到疾病的状态转变并不一定是平稳的，而是表现出类似于开关的非线性行为，这使得对患者进行癌症预测和早期干预治疗变得困难。理解这种从健康到疾病的转变机制是一个基本而具有挑战性的任务。尽管非平衡动力学的通量理论和基于“临界减速”的系统恢复力理论取得了进展，但系统级方法仍然缺乏对这种状态转变的全面描述。在这里，我们提出了一种新的框架（称为 bioRFR），通过从基因表达数据中揭示生物系统的恢复力函数，来量化癌症发生过程中的这种从健康到疾病的转变。我们使用 bioRFR 为癌症发生过程（例如 BRCA、LUSC 和 LUAD）重建了具有生物学意义和动态意义的恢复力函数。这些恢复力函数显示出类似的恢复力模式和滞后特征，但转折点的数量不同，这意味着一旦细胞癌变，就很难甚至不可能恢复到正常状态。更重要的是，bioRFR 可以衡量癌症患者的严重程度，并从恢复力的角度识别与个体系统从正常到肿瘤的状态转变相关的个性化关键基因，这表明 bioRFR 可以为个性化医疗和靶向癌症治疗做出贡献。
