系统功能失调对恶性肿瘤病因的影响。

Gene regulation and systems biology Pub Date : 2013-01-01 Epub Date: 2013-02-06 DOI:10.4137/GRSB.S10943
Sarah S Knox, Michael F Ochs
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引用次数: 0

摘要

目前的肿瘤治疗方法是用药物治疗取代一般的细胞毒性化疗,使与癌症发展和恶化相关的特定分子靶点失活。其目的是将细胞损伤限制在被认为直接导致恶性肿瘤的通路上。其基本假设有两个方面:(1) 个别通路是恶性肿瘤的原因;(2) 治疗目标应该是摧毁肿瘤或功能失调的通路。然而,数据在多大程度上实际支持这些假设还没有得到直接探讨。不断积累的证据表明,在大多数成人癌症中,全身功能障碍先于特定基因/分子途径的破坏,激酶抑制剂等靶向治疗可能在成功治疗某一途径的同时,对其他非靶向途径产生意外的改变。本文将讨论:(1) 恶性肿瘤的系统性基础;(2) 更好地分析与高风险相关的癌前生物标志物,以便及早采取预防性生活方式调整措施,在肿瘤发生前逆转高风险的表观遗传变化;(3) 早期肿瘤的治疗重点是通过加强机体的先天防御机制来恢复系统平衡;(4) 建立更好的系统定量模型,以捕捉肿瘤进展各个阶段的足够复杂性,从而实现可预测性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implications of systemic dysfunction for the etiology of malignancy.

The current approach to treatment in oncology is to replace the generally cytotoxic chemotherapies with pharmaceutical treatment which inactivates specific molecular targets associated with cancer development and progression. The goal is to limit cellular damage to pathways perceived to be directly responsible for the malignancy. Its underlying assumptions are twofold: (1) that individual pathways are the cause of malignancy; and (2) that the treatment objective should be destruction-either of the tumor or the dysfunctional pathway. However, the extent to which data actually support these assumptions has not been directly addressed. Accumulating evidence suggests that systemic dysfunction precedes the disruption of specific genetic/molecular pathways in most adult cancers and that targeted treatments such as kinase inhibitors may successfully treat one pathway while generating unintended changes to other, non-targeted pathways. This article discusses (1) the systemic basis of malignancy; (2) better profiling of pre-cancerous biomarkers associated with elevated risk so that preventive lifestyle modifications can be instituted early to revert high-risk epigenetic changes before tumors develop; (3) a treatment emphasis in early stage tumors that would target the restoration of systemic balance by strengthening the body's innate defense mechanisms; and (4) establishing better quantitative models of systems to capture adequate complexity for predictability at all stages of tumor progression.

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