MRC Cancer Unit, Hutchison/MRC Research Centre, University of Cambridge, UK / Academic Laboratory of Medical Genetics, Addenbrookes Treatment Centre, Cambridge, UK.
Swiss Med Wkly. 2020 Jan 27;150:w20158. doi: 10.4414/smw.2020.20158. eCollection 2020 Jan 13.
Technological advances in the ability to read the human genome have accelerated the speed of sequencing, such that today we can perform whole genome sequencing (WGS) in one day. Until recently, genomic studies have largely been limited to seeking novel scientific discoveries. The application of new insights gained through cancer WGS into the clinical domain, have been relatively limited. Looking ahead, a vast amount of data can be generated by genomic studies. Of note, excellent organisation of genomic and clinical data permits the application of machine-learning methods which can lead to the development of clinical algorithms that could assist future clinicians and genomicists in the analysis and interpretation of individual cancer genomes. Here, we describe what can be gleaned from holistic whole cancer genome profiling and argue that we must build the infrastructure and educational frameworks to support the modern clinical genomicist to prepare for a future where WGS will be the norm.
在人类基因组读取能力方面的技术进步加速了测序速度，以至于如今我们可以在一天内完成全基因组测序（WGS）。直到最近，基因组研究主要限于寻求新的科学发现。通过癌症 WGS 获得的新见解在临床领域的应用相对有限。展望未来，基因组研究可以产生大量数据。值得注意的是，基因组和临床数据的出色组织允许应用机器学习方法，从而可以开发出临床算法，帮助未来的临床医生和基因组学家分析和解释个体癌症基因组。在这里，我们描述了从整体癌症基因组分析中可以获得的信息，并认为我们必须建立基础设施和教育框架，以支持现代临床基因组学家为 WGS 将成为常态的未来做好准备。
