Tang Ka-Wei, Larsson Erik
Department of Infectious Diseases, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 9A, 405 30 Gothenburg, Sweden.
Department of Medical Biochemistry and Cell Biology, Institute of Biomedicine, The Sahlgrenska Academy, University of Gothenburg, Medicinaregatan 9A, 405 30 Gothenburg, Sweden
Philos Trans R Soc Lond B Biol Sci. 2017 Oct 19;372(1732). doi: 10.1098/rstb.2016.0265.
With the advent of massively parallel sequencing, oncogenic viruses in tumours can now be detected in an unbiased and comprehensive manner. Additionally, new viruses or strains can be discovered based on sequence similarity with known viruses. Using this approach, the causative agent for Merkel cell carcinoma was identified. Subsequent studies using data from large collections of tumours have confirmed models built during decades of hypothesis-driven and low-throughput research, and a more detailed and comprehensive description of virus-tumour associations have emerged. Notably, large cohorts and high sequencing depth, in combination with newly developed bioinformatical techniques, have made it possible to rule out several suggested virus-tumour associations with a high degree of confidence. In this review we discuss possibilities, limitations and insights gained from using massively parallel sequencing to characterize tumours with viral content, with emphasis on detection of viral sequences and genomic integration events.This article is part of the themed issue 'Human oncogenic viruses'.
随着大规模平行测序技术的出现，现在可以以无偏且全面的方式检测肿瘤中的致癌病毒。此外，基于与已知病毒的序列相似性，可以发现新的病毒或毒株。利用这种方法，确定了默克尔细胞癌的病原体。随后使用来自大量肿瘤样本的数据进行的研究证实了数十年来基于假设驱动和低通量研究所建立的模型，并且对病毒与肿瘤关联的描述变得更加详细和全面。值得注意的是，大型队列和高测序深度，再加上新开发的生物信息学技术，使得我们能够高度自信地排除几种提出的病毒与肿瘤的关联。在这篇综述中，我们讨论了使用大规模平行测序来表征含有病毒的肿瘤所获得的可能性、局限性和见解，重点是病毒序列的检测和基因组整合事件。本文是主题为“人类致癌病毒”的特刊的一部分。
