Kuschel Luis P, Hench Jürgen, Frank Stephan, Hench Ivana Bratic, Girard Elodie, Blanluet Maud, Masliah-Planchon Julien, Misch Martin, Onken Julia, Czabanka Marcus, Yuan Dongsheng, Lukassen Sören, Karau Philipp, Ishaque Naveed, Hain Elisabeth G, Heppner Frank, Idbaih Ahmed, Behr Nikolaus, Harms Christoph, Capper David, Euskirchen Philipp
Department of Neurology with Experimental Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Department of Pathology, Universitätsspital Basel, Basel, Switzerland.
Neuropathol Appl Neurobiol. 2023 Feb;49(1):e12856. doi: 10.1111/nan.12856. Epub 2022 Nov 9.
DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementation using hybridisation microarrays is time consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows us to discriminate a wide spectrum of primary brain tumours.
Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on 382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of 55 cases, we found that a minimum set of 1000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as a confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (n = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100% specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), the median time to results was 21.1 h.
In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.
基于DNA甲基化的癌症分类为肿瘤诊断提供了一种全面的分子方法。事实上，人类脑肿瘤的DNA甲基化谱分析已经对临床神经肿瘤学产生了深远影响。然而，目前使用杂交微阵列的方法既耗时又昂贵。我们最近报道了通过浅层纳米孔全基因组测序，能够快速且经济高效地生成全基因组5-甲基胞嘧啶谱，作为监督分类的输入。在此，我们证明这种方法能够让我们区分多种原发性脑肿瘤。
利用82种不同肿瘤实体的公共参考数据，我们对覆盖46种脑肿瘤（亚）类型的382个组织样本进行了纳米孔基因组测序。在一组55例病例中使用自助抽样法，我们发现最少1000个随机CpG特征集足以通过临时随机森林进行高置信度分类。我们实施了分数重新校准作为临床背景下解释的置信度度量，并在随机抽样的发现队列（N = 185）中凭经验确定了平台特定阈值。将此临界值应用于独立验证系列（n = 184）产生了148例可分类病例（敏感性80.4%），并显示出100%的特异性。跨实验室验证表明该方法具有稳健性，在四个实验室的10/11（90.9%）病例中结果一致。在一项前瞻性基准测试（N = 15）中，获得结果的中位时间为21.1小时。
总之，纳米孔测序能够对全谱脑肿瘤进行稳健且快速的基于甲基化的分类。平台特定的置信度分数有助于临床应用，对此有必要且正在进行前瞻性评估。
