PDF(Pubmed)
Abstract：
Metastasis is the main fatal cause of colorectal cancer (CRC). Although enormous efforts have been made to date to identify biomarkers associated with metastasis, there is still a huge gap to translate these efforts into effective clinical applications due to the poor consistency of biomarkers in dealing with the genetic heterogeneity of CRCs. In this study, a small cohort of eight CRC patients was recruited, from whom we collected cancer, paracancer, and normal tissues simultaneously and performed whole-exome sequencing. Given the exomes, a novel statistical parameter LIP was introduced to quantitatively measure the local invasion power for every somatic and germline mutation, whereby we affirmed that the innate germline mutations instead of somatic mutations might serve as the major driving force in promoting local invasion. Furthermore, via bioinformatic analyses of big data derived from the public zone, we identified ten potential driver variants that likely urged the local invasion of tumor cells into nearby tissue. Of them, six corresponding genes were new to CRC metastasis. In addition, a metastasis resister variant was also identified. Based on these eleven variants, we constructed a logistic regression model for rapid risk assessment of early metastasis, which was also deployed as an online server, AmetaRisk (http://www.bio-add.org/AmetaRisk). In summary, we made a valuable attempt in this study to exome-wide explore the genetic driving force to local invasion, which provides new insights into the mechanistic understanding of metastasis. Furthermore, the risk assessment model can assist in prioritizing therapeutic regimens in clinics and discovering new drug targets, and thus substantially increase the survival rate of CRC patients.
摘要：
转移是结直肠癌(CRC)的主要致死原因。尽管迄今为止已经做出了巨大的努力来鉴定与转移相关的生物标志物，由于生物标志物在处理CRC遗传异质性方面的一致性较差,因此将这些努力转化为有效的临床应用仍存在巨大差距.在这项研究中,招募了一个由8名CRC患者组成的小队列，我们从他那里收集癌症，副癌者,和正常组织同时进行全外显子组测序。鉴于外显子，引入了一个新的统计参数LIP来定量测量每个体细胞和种系突变的局部入侵能力，因此，我们确认先天种系突变而不是体细胞突变可能是促进局部入侵的主要驱动力。此外，通过对来自公共区域的大数据进行生物信息学分析，我们确定了10种可能促使肿瘤细胞局部侵入附近组织的潜在驱动变异。其中,6个相应的基因是CRC转移的新基因。此外,还发现了一个转移抗性变体。基于这十一种变体，我们构建了一个快速评估早期转移风险的logistic回归模型，它也被部署为在线服务器，AmetaRisk(http://www.bio-add.org/AmetaRisk)。总之,我们在这项研究中进行了有价值的尝试，以探索整个外显子组局部入侵的遗传驱动力，这提供了对转移机理理解的新见解。此外，风险评估模型可以帮助在诊所优先考虑治疗方案和发现新的药物靶点，从而大大提高CRC患者的生存率。
