Hopp Children's Cancer Center Heidelberg (KiTZ) & Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Semin Cancer Biol. 2022 Sep;84:103-112. doi: 10.1016/j.semcancer.2020.12.020. Epub 2021 Jan 18.
High-throughput molecular profiling of tumors is a fundamental aspect of precision oncology, enabling the identification of genomic alterations that can be targeted therapeutically. In this context, a patient is matched to a specific drug or therapy based on the tumor's underlying genetic driver events rather than the histologic classification. This approach requires extensive bioinformatics methodology and workflows, including raw sequencing data processing and quality control, variant calling and annotation, integration of different molecular data types, visualization and finally reporting the data to physicians, cancer researchers and pharmacologists in a format that is readily interpretable for clinical decision making. This review comprises a broad overview of these bioinformatics aspects and discusses the multiple analytical, technical and interpretational challenges that remain to efficiently translate molecular findings into personalized treatment recommendations.
肿瘤高通量分子分析是精准肿瘤学的一个基本方面,它可以识别出潜在的可靶向治疗的基因组改变。在这种情况下,患者会根据肿瘤的潜在遗传驱动事件而不是组织学分类来匹配特定的药物或治疗方法。这种方法需要广泛的生物信息学方法和工作流程,包括原始测序数据处理和质量控制、变异调用和注释、不同分子数据类型的整合、可视化,最后以一种易于为临床决策提供解释的格式将数据报告给医生、癌症研究人员和药理学家。这篇综述广泛概述了这些生物信息学方面,并讨论了仍存在的多个分析、技术和解释性挑战,以便有效地将分子发现转化为个性化治疗建议。