Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway.
Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
Int J Cancer. 2023 Nov 15;153(10):1819-1828. doi: 10.1002/ijc.34666. Epub 2023 Aug 8.
Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based service hosted by the Galaxy platform (https://oncotools.elixir.no), and can also be accessed as a stand-alone R package (https://github.com/sigven/oncoEnrichR).
癌症的全基因组筛选实验产生了大量的候选基因,这些基因需要进行广泛的解释,以提供生物学见解,并为后续研究确定优先级。对基因列表的查询通常是一项重大且耗时的任务,实验生物学家通常会结合各种生物信息学资源的结果,试图描绘和理解癌症的相关性。为了简化和加强这一努力的支持,我们开发了 oncoEnrichR,这是一个灵活的生物信息学工具,允许癌症研究人员沿着多个癌症相关性方面全面查询给定的基因列表。oncoEnrichR 与一般的基因集分析框架不同,它集成了大量专门针对癌症的先验知识,包括按排名排列的基因-肿瘤类型关联、文献支持的原癌基因和肿瘤抑制基因注释、靶向药物可及性数据、调控相互作用、合成致死性预测,以及肿瘤类型之间的预后关联、基因异常和共表达模式。该软件的主要输出是一个结构化的、用户友好的分析报告,其中明确记录了所有底层数据资源的版本,这对于可重复的科学是一个关键组成部分。我们通过对蛋白质组学和 CRISPR 筛选的两个候选列表的查询,展示了 oncoEnrichR 的有用性。oncoEnrichR 作为 Galaxy 平台(https://oncotools.elixir.no)上托管的基于网络的服务免费提供,也可以作为独立的 R 包(https://github.com/sigven/oncoEnrichR)访问。