Ahmadzada Tamkin, Kao Steven, Reid Glen, Boyer Michael, Mahar Annabelle, Cooper Wendy A
Sydney Medical School, The University of Sydney, Sydney 2006, Australia.
Chris O'Brien Lifehouse, Sydney 2050, Australia.
J Clin Med. 2018 Jun 15;7(6):153. doi: 10.3390/jcm7060153.
It is now widely established that management of lung cancer is much more complex and cannot be centered on the binary classification of small-cell versus non-small cell lung cancer (NSCLC). Lung cancer is now recognized as a highly heterogeneous disease that develops from genetic mutations and gene expression patterns, which initiate uncontrolled cellular growth, proliferation and progression, as well as immune evasion. Accurate biomarker assessment to determine the mutational status of driver mutations such as , and , which can be targeted by specific tyrosine kinase inhibitors, is now essential for treatment decision making in advanced stage NSCLC and has shifted the treatment paradigm of NSCLC to more individualized therapy. Rapid advancements in immunotherapeutic approaches to NSCLC treatment have been paralleled by development of a range of potential predictive biomarkers that can enrich for patient response, including PD-L1 expression and tumor mutational burden. Here, we review the key biomarkers that help predict response to treatment options in NSCLC patients.
现在已经广泛确定，肺癌的管理要复杂得多，不能以小细胞肺癌与非小细胞肺癌（NSCLC）的二元分类为中心。肺癌现在被认为是一种高度异质性疾病，它由基因突变和基因表达模式发展而来，这些基因突变和基因表达模式引发了不受控制的细胞生长、增殖和进展，以及免疫逃逸。准确的生物标志物评估以确定驱动突变的突变状态，如 、 和 ，这些突变可被特定的酪氨酸激酶抑制剂靶向，现在对于晚期NSCLC的治疗决策至关重要，并已将NSCLC的治疗模式转向更个体化的治疗。NSCLC治疗的免疫治疗方法的快速进展与一系列潜在的预测生物标志物的发展并行，这些生物标志物可以富集患者反应，包括PD-L1表达和肿瘤突变负荷。在这里，我们回顾了有助于预测NSCLC患者对治疗方案反应的关键生物标志物。
