Charité Comprehensive Cancer Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany.
Department of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Charitéplatz 1, 10117, Berlin, Germany; IRI Life Sciences, Humboldt-Universität zu Berlin, Philippstraße 13, 10115, Berlin, Germany.
Eur J Cancer. 2020 Mar;127:41-51. doi: 10.1016/j.ejca.2019.12.017. Epub 2020 Jan 23.
Reliable and reproducible interpretation of molecular aberrations constitutes a bottleneck of precision medicine. Evidence-based decision management systems may improve rational therapy recommendations. To cope with an increasing amount of complex molecular data in the clinical care of patients with cancer, we established a workflow for the interpretation of molecular analyses.
A specialized physician screened results from molecular analyses for potential biomarkers, irrespective of the diagnostic modality. Best available evidence was retrieved and categorized through establishment of an in-house database and interrogation of publicly available databases. Annotated biomarkers were ranked using predefined evidence levels and subsequently discussed at a molecular tumour board (MTB), which generated treatment recommendations. Subsequent translation into patient treatment and clinical outcomes were followed up.
One hundred patients were discussed in the MTB between January 2016 and May 2017. Molecular data were obtained for 70 of 100 patients (50 whole exome/RNA sequencing, 18 panel sequencing, 2 immunohistochemistry (IHC)/microsatellite instability analysis). The MTB generated a median of two treatment recommendations each for 63 patients. Thirty-nine patients were treated: 6 partial responses and 12 stable diseases were achieved as best responses. Genetic counselling for germline events was recommended for seven patients.
The development of an evidence-based workflow allowed for the clinical interpretation of complex molecular data and facilitated the translation of personalized treatment strategies into routine clinical care. The high number of treatment recommendations in patients with comprehensive genomic data and promising responses in patients treated with combination therapy warrant larger clinical studies.
可靠且可重复的分子异常解读是精准医学的瓶颈。基于证据的决策管理系统可以提高合理治疗建议的质量。为了应对癌症患者临床护理中日益增加的复杂分子数据，我们建立了一种分子分析解读的工作流程。
一名专科医生筛选出潜在生物标志物的分子分析结果，无论诊断方式如何。通过建立内部数据库和查询公开可用的数据库，检索并分类最佳可用证据。使用预先定义的证据水平对注释生物标志物进行排序，然后在分子肿瘤委员会（MTB）上进行讨论，生成治疗建议。随后对治疗建议在患者治疗和临床结果中的转化进行跟踪。
2016 年 1 月至 2017 年 5 月期间，有 100 名患者在 MTB 上进行了讨论。对 100 名患者中的 70 名患者进行了分子数据分析（50 名全外显子/RNA 测序、18 名基因panel 测序、2 名免疫组化（IHC）/微卫星不稳定性分析）。MTB 为 63 名患者中的每一位患者生成了中位数为两条的治疗建议。39 名患者接受了治疗：6 名患者达到最佳反应部分缓解，12 名患者疾病稳定。为 7 名患者推荐进行胚系事件的遗传咨询。
基于证据的工作流程的发展允许对复杂的分子数据进行临床解读，并促进将个性化治疗策略转化为常规临床护理。在接受全面基因组数据治疗的患者中提出了大量的治疗建议，且联合治疗的效果较好，这表明有必要进行更大规模的临床研究。
