Beyond the Variants: Mutational Patterns in Next-Generation Sequencing Data for Cancer Precision Medicine

超越变异:下一代测序数据中癌症精准医学的突变模式

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Abstract

Massively parallel sequencing, also referred to as "next-generation sequencing" (NGS) provides not only information about simple, single nucleotide alterations, but it can also provide information on complex variations, such as insertions and deletions, copy number alterations, and structural variants. In addition to identifying individual alterations, genome-wide biomarkers can be discerned from somatic cancer NGS data, broadly termed mutational patterns and signatures. This review will focus on several of the most common genome-wide biomarkers such as tumor mutational burden, microsatellite instability, homologous recombination deficiency, and mutational signatures.

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