癌症的标志捕获了恶性转化和进展的最重要的表型特征。尽管这个多步骤过程中涉及的许多因素至今仍然未知,在大规模癌症基因组计划中,越来越多的突变/改变的候选基因被鉴定.因此,研究人员需要了解能够确定每个标志特征的可用和适当的技术。我们回顾了为实验性癌症研究人员量身定制的评估细胞增殖的方法,程序性细胞死亡,复制永生,血管生成的诱导,侵袭和转移,基因组不稳定,和能量代谢的重新编程。选择理想的方法是基于研究者的目标,可用的设备以及财政限制。多路复用策略可以从单个实验中更深入地收集数据-从单个程序中获得多个结果可以减少可变性,节省时间和相对成本。与单终点测量相比,得出更可靠的结论。每个标志都具有可以通过免疫印迹分析的特征,RT-PCR,免疫细胞化学,免疫沉淀,RNA微阵列或RNA-seq。总的来说,流式细胞术,荧光显微镜,多井阅读器是非常通用的工具,通过适当的样品制备,允许检测大量的标志特征。最后,我们还提供了在转录组水平研究中需要测量的标记特异性基因列表.虽然我们的清单并不详尽,我们提供了最广泛使用的方法的快照,重点是能够同时评估多个标志特征的方法。
The hallmarks of cancer capture the most essential phenotypic characteristics of malignant transformation and progression. Although numerous factors involved in this multi-step process are still unknown to date, an ever-increasing number of mutated/altered candidate genes are being identified within large-scale cancer genomic projects. Therefore, investigators need to be aware of available and appropriate techniques capable of determining characteristic features of each hallmark. We review the methods tailored to experimental cancer researchers to evaluate cell proliferation, programmed cell death, replicative immortality, induction of angiogenesis, invasion and metastasis, genome instability, and reprogramming of energy metabolism. Selecting the ideal method is based on the investigator\'s goals, available equipment and also on financial constraints. Multiplexing strategies enable a more in-depth data collection from a single experiment - obtaining several results from a single procedure reduces variability and saves time and relative cost, leading to more robust conclusions compared to a single end point measurement. Each hallmark possesses characteristics that can be analyzed by immunoblot, RT-PCR, immunocytochemistry, immunoprecipitation, RNA microarray or RNA-seq. In general, flow cytometry, fluorescence microscopy, and multiwell readers are extremely versatile tools and, with proper sample preparation, allow the detection of a vast number of hallmark features. Finally, we also provide a list of hallmark-specific genes to be measured in transcriptome-level studies. Although our list is not exhaustive, we provide a snapshot of the most widely used methods, with an emphasis on methods enabling the simultaneous evaluation of multiple hallmark features.