Tan Wenyong, Yang Ming, Yang Hongli, Zhou Fangbin, Shen Weixi
Department of Oncology, Shenzhen Hospital of Southern Medical University, Shenzhen, People's Republic of China,
Clinical Medical Research Center, The Second Clinical Medical College (Shenzhen People Hospital), Jinan University, Shenzhen, People's Republic of China,
Cancer Manag Res. 2018 Oct 9;10:4333-4347. doi: 10.2147/CMAR.S174435. eCollection 2018.
Neoadjuvant therapy (NAT) has been used increasingly in patients with locally advanced or early-stage breast cancer. However, the accurate evaluation and prediction of response to NAT remain the great challenge. Biomarkers could prove useful to identify responders or nonresponders, or even to distinguish between early and delayed responses. These biomarkers could include markers from the tumor itself, such as versatile proteins, genes, and ribonucleic acids, various biological factors or peripheral blood cells, and clinical and pathological features. Possible predictive markers could also include multiple features from functional imaging, such as standard uptake values in positron emission tomography, apparent diffusion coefficient in magnetic resonance, or radiomics imaging biomarkers. In addition, cells that indirectly present the immune status of tumor cells and/or their host could also potentially be used as biomarkers, eg, tumor-infiltrating lymphocytes, tumor-associated macrophages, and myeloid-derived suppressor cells. Though numerous biomarkers have been widely investigated, only estrogen and/or progesterone receptors and human epidermal growth factor receptor have been proven to be reliable biomarkers to predict the response to NAT. They are the only biomarkers recommended in several international guidelines. The other aforementioned biomarkers warrant further validation studies. Some multigene profiling assays that are commercially available, eg, Oncotype DX and MammaPrint, should be used with caution when extrapolated to NAT settings. A panel of combined multilevel biomarkers might be able to predict the response to NAT more robustly than individual biomarkers. To establish such a panel and its prediction model, reliable methods and extensive clinical validation are warranted.
新辅助治疗(NAT)已越来越多地应用于局部晚期或早期乳腺癌患者。然而,准确评估和预测NAT的疗效仍然是巨大的挑战。生物标志物可能有助于识别反应者或无反应者,甚至区分早期和延迟反应。这些生物标志物可包括来自肿瘤本身的标志物,如多种蛋白质、基因和核糖核酸、各种生物因子或外周血细胞,以及临床和病理特征。可能的预测标志物还可包括功能成像的多种特征,如正电子发射断层扫描中的标准摄取值、磁共振中的表观扩散系数或放射组学成像生物标志物。此外,间接反映肿瘤细胞和/或其宿主免疫状态的细胞也有可能用作生物标志物,例如肿瘤浸润淋巴细胞、肿瘤相关巨噬细胞和髓系来源的抑制细胞。尽管已经对众多生物标志物进行了广泛研究,但只有雌激素和/或孕激素受体以及人表皮生长因子受体被证明是预测NAT疗效的可靠生物标志物。它们是几项国际指南中推荐的唯一生物标志物。上述其他生物标志物需要进一步的验证研究。一些市售的多基因分析检测方法,如Oncotype DX和MammaPrint,外推至NAT情况时应谨慎使用。一组组合的多层次生物标志物可能比单个生物标志物更能有力地预测NAT的疗效。为建立这样一组生物标志物及其预测模型,可靠的方法和广泛的临床验证是必要的。