Department of Human Genetics, University of Utah, Salt Lake City, UT, 84112, USA.
Utah Center for Genetic Discovery, University of Utah, Salt Lake City, UT, 84112, USA.
Genome Med. 2021 Mar 26;13(1):46. doi: 10.1186/s13073-021-00854-6.
DNA sequencing has unveiled extensive tumor heterogeneity in several different cancer types, with many exhibiting diverse subclonal populations. Identifying and tracing mutations throughout the expansion and progression of a tumor represents a significant challenge. Furthermore, prioritizing the subset of such mutations most likely to contribute to tumor evolution or that could serve as potential therapeutic targets represents an ongoing problem.
Here, we describe OncoGEMINI, a new tool designed for exploring the complex patterns and trajectory of somatic and inherited variation observed in heterogeneous tumors biopsied over the course of treatment. This is accomplished by creating a searchable database of variants that includes tumor sampling time points and allows for filtering methods that reflect specific changes in variant allele frequencies over time. Additionally, by incorporating existing annotations and resources that facilitate the interpretation of cancer mutations (e.g., CIViC, DGIdb), OncoGEMINI enables rapid searches for, and potential identification of, mutations that may be driving subclonal evolution.
By combining relevant genomic annotations alongside specific filtering tools, OncoGEMINI provides powerful and customizable approaches that enable the quick identification of individual tumor variants that meet specified criteria. It can be applied to a wide range of tumor-derived sequence data, but is especially designed for studies with multiple samples, including longitudinal datasets. It is available under an MIT license at github.com/fakedrtom/oncogemini .
DNA 测序已经揭示了几种不同癌症类型中的广泛肿瘤异质性，其中许多表现出不同的亚克隆群体。在肿瘤的扩张和进展过程中识别和追踪突变是一项重大挑战。此外，优先考虑那些最有可能导致肿瘤进化或可能成为潜在治疗靶点的突变亚群也是一个持续存在的问题。
在这里，我们描述了 OncoGEMINI，这是一种新的工具，用于探索在治疗过程中对异质肿瘤进行活检时观察到的体细胞和遗传变异的复杂模式和轨迹。这是通过创建一个可搜索的变体数据库来实现的，该数据库包括肿瘤采样时间点，并允许使用反映变体等位基因频率随时间变化的过滤方法。此外，通过整合有助于癌症突变解释的现有注释和资源（例如 CIViC、DGIdb），OncoGEMINI 能够快速搜索并可能识别可能驱动亚克隆进化的突变。
通过将相关基因组注释与特定的过滤工具相结合，OncoGEMINI 提供了强大且可定制的方法，能够快速识别符合特定标准的个体肿瘤变体。它可以应用于广泛的肿瘤衍生序列数据，但特别设计用于具有多个样本的研究，包括纵向数据集。它在 MIT 许可证下可在 github.com/fakedrtom/oncogemini 获得。
