Departments of Systems Biology and Biomedical Informatics, Columbia University, 1130 St. Nicholas Ave., New York, NY, 10032, USA.
Departamento de Bioquimica y Biologia Molecular, Universidad de Oviedo, Oviedo, Asturias, Spain.
Nat Commun. 2020 Jul 30;11(1):3808. doi: 10.1038/s41467-020-17659-7.
Large-scale cancer genomic studies enable the systematic identification of mutations that lead to the genesis and progression of tumors, uncovering the underlying molecular mechanisms and potential therapies. While some such mutations are recurrently found in many tumors, many others exist solely within a few samples, precluding detection by conventional recurrence-based statistical approaches. Integrated analysis of somatic mutations and RNA expression data across 12 tumor types reveals that mutations of cancer genes are usually accompanied by substantial changes in expression. We use topological data analysis to leverage this observation and uncover 38 elusive candidate cancer-associated genes, including inactivating mutations of the metalloproteinase ADAMTS12 in lung adenocarcinoma. We show that ADAMTS12 mice have a five-fold increase in the susceptibility to develop lung tumors, confirming the role of ADAMTS12 as a tumor suppressor gene. Our results demonstrate that data integration through topological techniques can increase our ability to identify previously unreported cancer-related alterations.
大规模癌症基因组研究使系统地识别导致肿瘤发生和发展的突变成为可能，揭示了潜在的分子机制和潜在的治疗方法。虽然有些这样的突变在许多肿瘤中经常被发现，但还有许多突变仅存在于少数样本中，传统的基于复发的统计方法无法检测到。对 12 种肿瘤类型的体细胞突变和 RNA 表达数据进行综合分析表明，癌症基因的突变通常伴随着表达的显著变化。我们使用拓扑数据分析来利用这一观察结果，并发现了 38 个难以捉摸的候选癌症相关基因，包括肺腺癌中金属蛋白酶 ADAMTS12 的失活突变。我们表明，ADAMTS12 小鼠发生肺肿瘤的易感性增加了五倍，证实了 ADAMTS12 作为肿瘤抑制基因的作用。我们的结果表明，通过拓扑技术进行数据集成可以提高我们识别以前未报道的癌症相关改变的能力。
