Comprehensive Cancer Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Chariteplatz 1, 10117, Berlin, Germany.
Department of Hematology, Oncology and Cancer Immunology, Campus Benjamin Franklin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Hindenburgdamm 30, 12203, Berlin, Germany.
BMC Med. 2022 Oct 24;20(1):367. doi: 10.1186/s12916-022-02560-5.
Structured and harmonized implementation of molecular tumor boards (MTB) for the clinical interpretation of molecular data presents a current challenge for precision oncology. Heterogeneity in the interpretation of molecular data was shown for patients even with a limited number of molecular alterations. Integration of high-dimensional molecular data, including RNA- (RNA-Seq) and whole-exome sequencing (WES), is expected to further complicate clinical application. To analyze challenges for MTB harmonization based on complex molecular datasets, we retrospectively compared clinical interpretation of WES and RNA-Seq data by two independent molecular tumor boards.
High-dimensional molecular cancer profiling including WES and RNA-Seq was performed for patients with advanced solid tumors, no available standard therapy, ECOG performance status of 0-1, and available fresh-frozen tissue within the DKTK-MASTER Program from 2016 to 2018. Identical molecular profiling data of 40 patients were independently discussed by two molecular tumor boards (MTB) after prior annotation by specialized physicians, following independent, but similar workflows. Identified biomarkers and resulting treatment options were compared between the MTBs and patients were followed up clinically.
A median of 309 molecular aberrations from WES and RNA-Seq (n = 38) and 82 molecular aberrations from WES only (n = 3) were considered for clinical interpretation for 40 patients (one patient sequenced twice). A median of 3 and 2 targeted treatment options were identified per patient, respectively. Most treatment options were identified for receptor tyrosine kinase, PARP, and mTOR inhibitors, as well as immunotherapy. The mean overlap coefficient between both MTB was 66%. Highest agreement rates were observed with the interpretation of single nucleotide variants, clinical evidence levels 1 and 2, and monotherapy whereas the interpretation of gene expression changes, preclinical evidence levels 3 and 4, and combination therapy yielded lower agreement rates. Patients receiving treatment following concordant MTB recommendations had significantly longer overall survival than patients receiving treatment following discrepant recommendations or physician's choice.
Reproducible clinical interpretation of high-dimensional molecular data is feasible and agreement rates are encouraging, when compared to previous reports. The interpretation of molecular aberrations beyond single nucleotide variants and preclinically validated biomarkers as well as combination therapies were identified as additional difficulties for ongoing harmonization efforts.
为了实现精准肿瘤学，对分子数据进行结构化和协调的分子肿瘤委员会（MTB）实施是当前的一项挑战。即使分子改变数量有限，患者的分子数据解读也存在异质性。高维分子数据的整合，包括 RNA（RNA-Seq）和全外显子组测序（WES），预计将进一步使临床应用复杂化。为了分析基于复杂分子数据集的 MTB 协调所面临的挑战，我们回顾性地比较了两个独立的分子肿瘤委员会对 WES 和 RNA-Seq 数据的临床解读。
在 2016 年至 2018 年期间，DKTK-MASTER 计划对晚期实体瘤、无标准治疗方案、ECOG 体能状态为 0-1 且有新鲜冷冻组织的患者进行了包括 WES 和 RNA-Seq 在内的高维分子癌症分析。40 名患者的相同分子分析数据在由专门医生预先注释后，由两个分子肿瘤委员会（MTB）独立讨论，采用独立但相似的工作流程。比较 MTB 之间的鉴定生物标志物和相应的治疗选择，并对患者进行临床随访。
对 40 名患者（一名患者两次测序）的 WES 和 RNA-Seq（n=38）中的 309 个分子异常和 WES 中的 82 个分子异常进行了临床解读中位数。每位患者确定了中位数为 3 和 2 种靶向治疗选择。最常见的治疗选择是受体酪氨酸激酶、PARP 和 mTOR 抑制剂以及免疫疗法。两个 MTB 的平均重叠系数为 66%。对于单核苷酸变异、临床证据水平 1 和 2 以及单药治疗的解释，一致性最高；而对于基因表达变化、临床前证据水平 3 和 4 以及联合治疗的解释，一致性较低。接受符合 MTB 建议的治疗的患者的总生存期明显长于接受不一致建议或医生选择的治疗的患者。
与之前的报告相比，对高维分子数据进行可重复的临床解读是可行的，并且一致性率令人鼓舞。除单核苷酸变异和经临床验证的生物标志物以及联合治疗外，对分子异常的解释被认为是正在进行的协调工作的额外困难。
