Establishing the utility of multi-platform liquid biopsy by integrating the CSF methylome and proteome in CNS tumours.

IF 3.2 2区 医学 Q2 CLINICAL NEUROLOGY Journal of Neuro-Oncology Pub Date : 2024-09-01 Epub Date: 2024-08-05 DOI:10.1007/s11060-024-04695-2
A P Landry, J A Zuccato, V Patil, M R Voisin, J Z Wang, Y Ellenbogen, C Gui, A Ajisebutu, T Kislinger, F Nassiri, G Zadeh
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Abstract

Background: Liquid biopsy represents a major development in cancer research, with significant translational potential. Similarly, it is increasingly recognized that multi-omic molecular approaches are a powerful avenue through which to understand complex and heterogeneous disease biology. We hypothesize that merging these two promising frontiers of cancer research will improve the discriminatory capacity of current models and allow for improved clinical utility.

Methods: We have compiled a cohort of patients with glioblastoma, brain metastasis, and primary central nervous system lymphoma. Cell-free methylated DNA immunoprecipitation (cfMeDIP) and shotgun proteomic profiling was obtained from the cerebrospinal fluid (CSF) of each patient and used to build tumour-specific classifiers.

Results: We show that the DNA methylation and protein profiles of cerebrospinal fluid can be integrated to fully discriminate lymphoma from its diagnostic counterparts with perfect AUC of 1 (95% confidence interval 1-1) and 100% specificity, significantly outperforming single-platform classifiers.

Conclusions: We present the most specific and accurate CNS lymphoma classifier to date and demonstrates the synergistic capability of multi-platform liquid biopsies. This has far-reaching translational utility for patients with newly diagnosed intra-axial brain tumours.

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通过整合中枢神经系统肿瘤 CSF 甲基组和蛋白质组,建立多平台液体活检的实用性。
背景:液体活检是癌症研究的一大发展,具有巨大的转化潜力。同样,人们越来越认识到,多原子分子方法是了解复杂和异质性疾病生物学的有力途径。我们假设,将这两个前景广阔的癌症研究前沿合并起来,将提高现有模型的鉴别能力,并改善临床实用性:方法:我们收集了一批胶质母细胞瘤、脑转移瘤和原发性中枢神经系统淋巴瘤患者。我们从每位患者的脑脊液(CSF)中获得了无细胞甲基化DNA免疫沉淀(cfMeDIP)和枪弹蛋白质组图谱,并将其用于建立肿瘤特异性分类器:我们的研究表明,脑脊液的DNA甲基化和蛋白质图谱可以整合到淋巴瘤的诊断中,以完美的AUC值1(95%置信区间1-1)和100%的特异性完全区分淋巴瘤,明显优于单一平台的分类器:我们提出了迄今为止最特异、最准确的中枢神经系统淋巴瘤分类器,展示了多平台液体活检的协同能力。这对新诊断的轴内脑肿瘤患者具有深远的转化用途。
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来源期刊
Journal of Neuro-Oncology
Journal of Neuro-Oncology 医学-临床神经学
CiteScore
6.60
自引率
7.70%
发文量
277
审稿时长
3.3 months
期刊介绍: The Journal of Neuro-Oncology is a multi-disciplinary journal encompassing basic, applied, and clinical investigations in all research areas as they relate to cancer and the central nervous system. It provides a single forum for communication among neurologists, neurosurgeons, radiotherapists, medical oncologists, neuropathologists, neurodiagnosticians, and laboratory-based oncologists conducting relevant research. The Journal of Neuro-Oncology does not seek to isolate the field, but rather to focus the efforts of many disciplines in one publication through a format which pulls together these diverse interests. More than any other field of oncology, cancer of the central nervous system requires multi-disciplinary approaches. To alleviate having to scan dozens of journals of cell biology, pathology, laboratory and clinical endeavours, JNO is a periodical in which current, high-quality, relevant research in all aspects of neuro-oncology may be found.
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