Life Sciences Department, Barcelona Supercomputing Center (BSC), Barcelona, Spain.
Institut Curie, Paris, France; U900, Paris, France; PSL Research University, Paris, France; Mines Paris Tech, Fontainebleau, France.
Cell Genom. 2024 Sep 11;4(9):100639. doi: 10.1016/j.xgen.2024.100639. Epub 2024 Aug 30.
The characterization of somatic genomic variation associated with the biology of tumors is fundamental for cancer research and personalized medicine, as it guides the reliability and impact of cancer studies and genomic-based decisions in clinical oncology. However, the quality and scope of tumor genome analysis across cancer research centers and hospitals are currently highly heterogeneous, limiting the consistency of tumor diagnoses across hospitals and the possibilities of data sharing and data integration across studies. With the aim of providing users with actionable and personalized recommendations for the overall enhancement and harmonization of somatic variant identification across research and clinical environments, we have developed ONCOLINER. Using specifically designed mosaic and tumorized genomes for the analysis of recall and precision across somatic SNVs, insertions or deletions (indels), and structural variants (SVs), we demonstrate that ONCOLINER is capable of improving and harmonizing genome analysis across three state-of-the-art variant discovery pipelines in genomic oncology.
肿瘤生物学相关体细胞基因组变异的特征对于癌症研究和个性化医疗至关重要,因为它指导着癌症研究和临床肿瘤学中基于基因组的决策的可靠性和影响。然而,目前癌症研究中心和医院之间的肿瘤基因组分析的质量和范围存在很大差异,限制了医院之间肿瘤诊断的一致性,以及数据共享和研究之间数据集成的可能性。为了为研究和临床环境中的体细胞变异识别的整体增强和协调提供可操作和个性化的建议,我们开发了 ONCOLINER。我们使用专门设计的镶嵌体和肿瘤化基因组来分析体细胞单核苷酸变异 (SNVs)、插入或缺失 (indels) 和结构变异 (SVs) 的召回率和精确度,结果表明,ONCOLINER 能够改进和协调三个最先进的基因组肿瘤学变异发现管道中的基因组分析。