APSiC: Analysis of Perturbation Screens for the Identification of Novel Cancer Genes

Systematic perturbation screens provide comprehensive resources for the elucidation of cancer driver genes. The perturbation of many genes in relatively few cell lines in such functional screens necessitates the development of specialized computational tools with sufficient statistical power. Here we developed APSiC (<em>A</em>nalysis of <em>P</em>erturbation <em>S</em>creens for <em>i</em>dentifying novel <em>C</em>ancer genes) to identify genetic and non-genetic drivers in perturbation screens even with few samples. Applying APSiC to the shRNA screen Project DRIVE, APSiC identified well-known, pan-cancer genetic drivers, novel putative genetic drivers known to be dysregulated in specific cancer types and the context dependency of mRNA-splicing between cancer types. Additionally, APSiC discovered a median of 28 and 35 putative non-genetic oncogenes and tumor suppressor genes, respectively, for individual cancer types, including genes involved in genome stability maintenance and cell cycle. We functionally demonstrated that <em>LRRC4B, </em>a putative novel non-genetic tumor suppressor gene, suppresses proliferation by delaying cell cycle and modulates apoptosis in breast cancer. We demonstrate APSiC is a robust statistical framework for discovery of novel cancer genes through analysis of large-scale perturbation screens. The analysis of DRIVE using APSiC is provided as a web portal and represents a valuable resource for the discovery of novel cancer genes.系统性扰动筛选可为癌症驱动基因的阐明提供全面的研究资源。此类功能筛选往往针对少量细胞系内的大量基因开展扰动实验，因此亟需开发具备足够统计效力的专用计算工具。本研究开发了APSiC（Analysis of Perturbation Screens for identifying novel Cancer genes，即面向新型癌症基因识别的扰动筛选分析工具），可在样本量有限的扰动筛选数据中同时识别遗传与非遗传驱动因子。将APSiC应用于短发卡RNA（shRNA）筛选项目DRIVE后，该工具成功识别出经典的泛癌遗传驱动基因、已知在特定癌症类型中失调的新型潜在遗传驱动基因，以及不同癌症类型间mRNA剪接的情境依赖性特征。此外，APSiC在各癌症类型中分别筛选得到中位数为28个的潜在非遗传致癌基因与35个的潜在非遗传肿瘤抑制基因，其中包含参与基因组稳定性维持与细胞周期调控的基因。本研究通过功能实验证实，新型潜在非遗传肿瘤抑制基因LRRC4B可通过阻滞细胞周期抑制乳腺癌细胞增殖，并调控细胞凋亡过程。本研究证实，APSiC是一套稳健的统计框架，可通过分析大规模扰动筛选数据挖掘新型癌症基因。基于APSiC对DRIVE项目的分析结果已以网络门户形式开放，可为新型癌症基因的挖掘提供宝贵的研究资源。