CCLHunter: An efficient toolkit for cancer cell line authentication - Congfan Bu; Xinchang Zheng; Jialin Mai; Zhi Nie; Jingyao Zeng; Qiheng Qian; Tianyi Xu; Yanling Sun; Yiming Bao; Jingfa Xiao (Computational and Structural Biotechnology Journal, 2023)
Cancer cell lines are essential in cancer research, yet accurate authentication of these cell lines can be challenging, particularly for consanguineous cell lines with close genetic similarities. We introduce a new Cancer Cell Line Hunter (CCLHunter) method to tackle this challenge. This approach utilizes the information of single nucleotide polymorphisms, expression profiles, and kindred topology to authenticate 1389 human cancer cell lines accurately. CCLHunter can precisely and efficiently authenticate cell lines from consanguineous lineages and those derived from other tissues of the same individual. Our evaluation results indicate that CCLHunter has a complete accuracy rate of 93.27%, with an accuracy of 89.28% even for consanguineous cell lines, outperforming existing methods. Additionally, we provide convenient access to CCLHunter through standalone software and a web server at https://ngdc.cncb.ac.cn/cclhunter.