AUTHOR=Ding Ruo-Fan , Zhang Yun , Wu Lv-Ying , You Pan , Fang Zan-Xi , Li Zhi-Yuan , Zhang Zhong-Ying , Ji Zhi-Liang 

TITLE=Discovering Innate Driver Variants for Risk Assessment of Early Colorectal Cancer Metastasis

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.898117

DOI=10.3389/fonc.2022.898117

ISSN=2234-943X

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 consistence 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-wide mutation profiling by deep sequencing. A novel statistical parameter LIP was introduced to quantitatively measure the local invasion power for every somatic and germline mutations; 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. Upon 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 mechanistic understanding of metastasis. Furthermore, the risk assessment model can assist in prioritizing therapeutic regimen in clinics, discovering new drug targets, and thus substantially increase the survival rate of CRC patients.