Starmans M H W, Krishnapuram B, Steck H, Horlings H, Nuyten D S A, van de Vijver M J, Seigneuric R, Buffa F M, Harris A L, Wouters B G, Lambin P
Maastricht Radiation Oncology (Maastro), GROW Research Institute, University of Maastricht, Uns 50/23, PO box 616, Maastricht 6200MD, The Netherlands.
Br J Cancer. 2008 Dec 2;99(11):1884-90. doi: 10.1038/sj.bjc.6604746. Epub 2008 Nov 4.
Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualizing treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them.
肿瘤增殖是肿瘤学中限制治愈的主要生物学表型之一。目前正在进行广泛的研究以揭示这一过程中的关键因素。为了利用已发表的基因表达数据的潜力,创建增殖特征可以提供有关肿瘤状态、预后和预测的有价值信息。这将有助于实现个体化治疗,并应能更好地控制肿瘤,以及更快速且经济高效地进行研发。从已发表的体外微阵列研究中,汇编了两种增殖特征。在五个大型临床微阵列数据集里测试了这些特征的预后价值。纳入了1000多名乳腺癌、肾癌或肺癌患者。其中一个特征(110个基因)在所有数据集中都具有显著的预后价值。将患者分层分组后,生存情况有明显差异(P值<0.05)。多变量Cox回归分析表明,该特征为用于预后的临床因素增加了重要价值。将进一步的患者分层与使用几个知名已发表特征进行的患者分层进行了比较。列联表和克莱姆V统计表明,这些主要识别出与增殖特征相同的患者。增殖特征是一个强大的预后因素,有潜力转化为预测性检测。此外,有证据支持这样一种观点,即许多已发表的特征追踪相同的生物学过程,而增殖就是其中之一。