首页> 外文期刊>Cancer Communications >Predictive biomarkers in precision medicine and drug development against lung cancer
【24h】

Predictive biomarkers in precision medicine and drug development against lung cancer

机译:精准药物和抗肺癌药物开发中的预测性生物标志物

获取原文
           

摘要

The molecular characterization of various cancers has shown that cancers with the same origins, histopathologic diagnoses, and clinical stages can be highly heterogeneous in their genetic and epigenetic alterations that cause tumorigenesis. A number of cancer driver genes with functional abnormalities that trigger malignant transformation and that are required for the survival of cancer cells have been identified. Therapeutic agents targeting some of these cancer drivers have been successfully developed, resulting in substantial improvements in clinical symptom amelioration and outcomes in a subset of cancer patients. However, because such therapeutic drugs often benefit only a limited number of patients, the successes of clinical development and applications rely on the ability to identify those patients who are sensitive to the targeted therapies. Thus, biomarkers that can predict treatment responses are critical for the success of precision therapy for cancer patients and of anticancer drug development. This review discusses the molecular heterogeneity of lung cancer pathogenesis; predictive biomarkers for precision medicine in lung cancer therapy with drugs targeting epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-ros oncogene 1 receptor tyrosine kinase (ROS1), and immune checkpoints; biomarkers associated with resistance to these therapeutics; and approaches to identify predictive biomarkers in anticancer drug development. The identification of predictive biomarkers during anticancer drug development is expected to greatly facilitate such development because it will increase the chance of success or reduce the attrition rate. Additionally, such identification will accelerate the drug approval process by providing effective patient stratification strategies in clinical trials to reduce the sample size required to demonstrate clinical benefits.
机译:各种癌症的分子特征表明,具有相同起源,组织病理学诊断和临床阶段的癌症在引起肿瘤发生的遗传和表观遗传学改变方面可能高度异质。已经鉴定出具有功能异常的许多癌症驱动基因,这些基因触发恶性转化并且是癌细胞存活所必需的。已经成功开发出了针对这些癌症驱动因素中某些药物的治疗剂,从而在部分癌症患者中改善了临床症状并改善了治疗效果。但是,由于此类治疗药物通常仅使有限的患者受益,因此临床开发和应用的成功取决于识别对目标疗法敏感的患者的能力。因此,可以预测治疗反应的生物标志物对于癌症患者的精确治疗和抗癌药物开发的成功至关重要。本文综述了肺癌发病机理的分子异质性。用于肺癌治疗的精密医学的预测性生物标志物,其靶向表皮生长因子受体(EGFR),间变性淋巴瘤激酶(ALK),c-ros癌基因1受体酪氨酸激酶(ROS1)和免疫检查点;与这些疗法的耐药性相关的生物标志物;和在抗癌药物开发中鉴定预测性生物标志物的方法。预期在抗癌药物开发过程中鉴定预测性生物标志物将大大促进此类开发,因为这将增加成功的机会或降低损耗率。此外,通过在临床试验中提供有效的患者分层策略以减少证明临床益处​​所需的样本量,此类鉴定将加速药物批准过程。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号