Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.
Int J Cancer. 2013 Dec 1;133(11):2512-21. doi: 10.1002/ijc.28124. Epub 2013 Mar 16.
High-grade osteosarcoma is an extremely genomically unstable tumor. This, together with other challenges, such as the heterogeneity within and between tumor samples, and the rarity of the disease, renders it difficult to study this tumor on a genome-wide level. Now that most laboratories change from genome-wide microarray experiments to Next-Generation Sequencing it is important to discuss the lessons we have learned from microarray studies. In this review, we discuss the challenges of high-grade osteosarcoma data analysis. We give an overview of microarray studies that have been conducted so far on both osteosarcoma tissue samples and cell lines. We discuss recent findings from integration of different data types, which is particularly relevant in a tumor with such a complex genomic profile. Finally, we elaborate on the translation of results obtained with bioinformatics into functional studies, which has lead to valuable findings, especially when keeping in mind that no new therapies with a significant impact on survival have been developed in the past decades.
高级别骨肉瘤是一种基因组极不稳定的肿瘤。这与其他挑战(如肿瘤样本内和样本之间的异质性以及疾病的罕见性)一起,使得在全基因组水平上研究这种肿瘤变得困难。现在,大多数实验室已经从全基因组微阵列实验转变为下一代测序,因此讨论我们从微阵列研究中吸取的经验教训非常重要。在这篇综述中,我们讨论了高级别骨肉瘤数据分析的挑战。我们概述了迄今为止在骨肉瘤组织样本和细胞系上进行的微阵列研究。我们讨论了整合不同数据类型的最新发现,这在具有如此复杂基因组特征的肿瘤中尤为相关。最后,我们详细阐述了将生物信息学获得的结果转化为功能研究的情况,这带来了有价值的发现,特别是考虑到在过去几十年中,并没有开发出对生存率有重大影响的新疗法。