预测驱动基因（肿瘤抑制基因和癌基因）是理解癌症发展和发现潜在新型治疗方法的关键步骤。我们最近提出了一个名为月光的生物信息学框架，以基因组学整合为基础，以系统生物学为导向的方式预测驱动基因并对其进行分析。月光将基因表达作为主要数据源，结合与肿瘤特征和调控网络相关的模式，以识别致癌介质。一旦识别出致癌介质，就需要包含额外的证据层次，即机械指标，以识别驱动基因并将观察到的基因表达变化与促使它们的潜在变化联系起来。这样的机械指标可以是候选基因调控区域的突变。在这里，我们开发了新的功能，并发布了Moonlight2，以提供基于突变的机械指标作为第二层证据。这些功能分析了癌症队列中的突变，将其分类为驱动突变和旅客突变。那些至少有一个驱动突变的致癌介质被保留为最终的驱动基因集。我们应用Moonlight2对基底样乳腺癌亚型、肺腺癌和甲状腺癌进行了分析，使用了来自癌症基因组图谱的数据。例如，在基底样乳腺癌中，我们发现了四个致癌基因（COPZ2，SF3B4，KRTCAP2和POLR2J）和九个肿瘤抑制基因（KIR2DL4，KIF26B，ARL15，ARHGAP25，EMCN，GMFG，TPK1，NR5A2和TEK），它们在其启动子区域中含有驱动突变，可能解释了它们的失调。Moonlight2R可以在https://github.com/ELELAB/Moonlight2R中获得。© 作者 2023。由牛津大学出版社发表。版权所有。请发送电子邮件至journals.permissions@oup.com以获得许可。

Prediction of driver genes (tumor suppressors and oncogenes) is an essential step in understanding cancer development and discovering potential novel treatments. We recently proposed Moonlight as a bioinformatics framework to predict driver genes and analyze them in a system-biology-oriented manner based on -omics integration. Moonlight uses gene expression as a primary data source and combines it with patterns related to cancer hallmarks and regulatory networks to identify oncogenic mediators. Once the oncogenic mediators are identified, it is important to include extra levels of evidence, called mechanistic indicators, to identify driver genes and to link the observed gene expression changes to the underlying alteration that promotes them. Such a mechanistic indicator could be for example a mutation in the regulatory regions for the candidate gene. Here, we developed new functionalities and released Moonlight2 to provide the user with a mutation-based mechanistic indicator as a second layer of evidence. These functionalities analyze mutations in a cancer cohort to classify them into driver and passenger mutations. Those oncogenic mediators with at least one driver mutation are retained as the final set of driver genes. We applied Moonlight2 to the basal-like breast cancer subtype, lung adenocarcinoma and thyroid carcinoma using data from The Cancer Genome Atlas. For example, in basal-like breast cancer, we found four oncogenes (COPZ2, SF3B4, KRTCAP2 and POLR2J) and nine tumor suppressor genes (KIR2DL4, KIF26B, ARL15, ARHGAP25, EMCN, GMFG, TPK1, NR5A2 and TEK) containing a driver mutation in their promoter region, possibly explaining their deregulation. Moonlight2R is available at https://github.com/ELELAB/Moonlight2R.© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.