Detection of human brain cancers using genomic and immune cell characterization of cerebrospinal fluid through CSF-BAM.

Alexander H Pearlman, Yuxuan Wang, Anita Kalluri, Megan Parker, Joshua D Cohen, Jonathan Dudley, Jordina Rincon-Torroella, Yuanxuan Xia, Ryan Gensler, Melanie Alfonzo Horwitz, John Theodore, Lisa Dobbyn, Maria Popoli, Janine Ptak, Natalie Silliman, Kathy Judge, Mari Groves, Christopher M Jackson, Eric M Jackson, George I Jallo, Michael Lim, Mark Luciano, Debraj Mukherjee, Jarushka Naidoo, Sima Rozati, Cole H Sterling, Jon Weingart, Carl Koschmann, Alireza Mansouri, Michael Glantz, David Kamson, Karisa C Schreck, Carlos A Pardo, Matthias Holdhoff, Suman Paul, Kenneth W Kinzler, Nickolas Papadopoulos, Bert Vogelstein, Christopher Douville, Chetan Bettegowda
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Abstract

Patients who have radiographically detectable lesions in their brain or other symptoms compatible with brain tumors pose challenges for diagnosis. The only definitive way to diagnose such patients is through brain biopsy, an obviously invasive and dangerous procedure. Here we present a new workflow termed "CSF-BAM" that simultaneously identifies B cell or T cell receptor rearrangements, A neuploidy, and M utations using PCR-mediated amplification of both strands of the DNA from CSF samples. We first describe the details of the molecular genetic assessments and then establish thresholds for positivity using training sets of libraries from patients with or without cancer. We then applied CSF-BAM to an independent set of 206 DNA samples from patients with common, aggressive cancer types as well as other forms of brain cancers. Among the 126 samples from patients with the most common aggressive cancer types (high grade gliomas, medulloblastomas, or metastatic cancers to the brain), the sensitivity of detection was >81%. None of 33 CSF-BAM assays (100% specificity, 90% to 100% credible interval) were positive in CSF samples from patients without brain cancers. The sensitivity of CSF-BAM was considerably higher than that achieved with cytology. CSF-BAM provides an integrated multi-analyte approach to identify neoplasia in the central nervous system, provides information about the immune environment in patients with or without cancer, and has the potential to inform the subsequent management of such patients.

Statement of significance: There is a paucity of technologies beyond surgical biopsy that can accurately diagnose central nervous system neoplasms. We developed a novel, sensitive and highly specific assay that can detect brain cancers by comprehensively identifying somatic mutations, chromosomal copy number changes, and adaptive immunoreceptor repertoires from samples of cerebrospinal fluid.

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通过 CSF-BAM,利用脑脊液的基因组和免疫细胞特征检测人类脑癌。
脑部有放射线可检测到的病变或其他与脑肿瘤相符的症状的患者给诊断带来了挑战。诊断这类患者的唯一明确方法是进行脑活检,而这显然是一种侵入性且危险的过程。在这里,我们介绍了一种名为 "CSF-BAM "的新工作流程,该流程利用 PCR 技术扩增 CSF 样品的两条 DNA 链,可同时鉴定 B 细胞或 T 细胞受体重排、A 非整倍体和 M 细胞变异。我们首先描述了分子遗传评估的细节,然后利用癌症或非癌症患者的训练库集确定了阳性阈值。然后,我们将 CSF-BAM 应用于一组独立的 206 个 DNA 样本,这些样本来自常见的侵袭性癌症类型以及其他形式的脑癌患者。在来自最常见侵袭性癌症类型(高级别胶质瘤、髓母细胞瘤或脑转移癌)患者的 126 份样本中,检测灵敏度大于 81%。33种CSF-BAM检测方法(特异性100%,可信区间90%至100%)在非脑癌患者的CSF样本中均未出现阳性结果。CSF-BAM 的灵敏度大大高于细胞学检测。CSF-BAM提供了一种综合的多分析方法来识别中枢神经系统的肿瘤,提供了有关癌症或非癌症患者免疫环境的信息,并有可能为此类患者的后续管理提供参考:除手术活检外,能准确诊断中枢神经系统肿瘤的技术还很少。我们开发了一种新型、灵敏且特异性极高的检测方法,可从脑脊液样本中全面识别体细胞突变、染色体拷贝数变化和适应性免疫受体复合物,从而检测出脑癌。
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Leveraging hierarchical structures for genetic block interaction studies using the hierarchical transformer. Explainable artificial intelligence for neuroimaging-based dementia diagnosis and prognosis. Advancing the prediction and understanding of placebo responses in chronic back pain using large language models. Detection of human brain cancers using genomic and immune cell characterization of cerebrospinal fluid through CSF-BAM. Uncertainty quantification in epigenetic clocks via conformalized quantile regression.
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