化学疗法相关毒性预测性风险因素分析的演变
Daniel L Hertz1, Maryam B Lustberg2, Stephen Sonis3
1Department of Clinical Pharmacy, University of Michigan College of Pharmacy, 428 Church St., Room 3054 College of Pharmacy, Ann Arbor, MI, 48109-1065, USA. DLHertz@med.umich.edu.
概括
预测癌症治疗毒性需要超越生殖基因组学. 综合生物标志物方法,结合各种"omic"和非omic因素,为个性化瘤学提供了一个有希望的途径,并最大限度地减少患者的副作用.
科学领域:
- 在瘤学中发现生物标志物
- 药物遗传学和治疗毒性
背景情况:
- 由于未知的因素,患者对癌症治疗的反应有很大差异.
- 生殖系基因组学最初承诺个性化治疗,但在预测毒性方面取得了有限的成功.
- 将药物遗传预测因子转化为临床实践仍然是一个重大挑战.
研究的目的:
- 突出目前毒性预测器发现和翻译的局限性.
- 为预测与治疗相关的毒性提出一个综合生物标志物发现方法.
- 讨论针对个性化瘤学的利用多核和非核因素的机遇和挑战.
主要方法:
- 在临床和药物遗传毒性预测因子的发现和翻译方面取得的有限成功的审查.
- 插图使用税诱导的外围神经病变作为一个案例研究.
- 讨论非基因组 (代谢学,脂质学,转录学,蛋白质学,微生物学,医学,行为学,环境学) 和综合生物标记机遇.
主要成果:
- 在发现和翻译治疗毒性的生殖系药物遗传预测因素方面取得了有限的成功.
- 塔肯诱导的外围神经病变是常见的,使人虚弱的治疗副作用的例子.
- 非基因组和综合生物标志物显示出改善毒性预测的潜力.
结论:
- 预测癌症治疗毒性需要超越生殖基因组学.
- 综合生物标志物方法,考虑各种因素,可以提高毒性预测.
- 这种方法可以推进精确瘤学,最大限度地提高治疗效益,同时最大限度地降低毒性.
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