Noninvasive detection of brain gliomas using plasma cell‐free DNA 5‐hydroxymethylcytosine sequencing

Abstract

Liquid biopsy techniques based on deep sequencing of plasma cell-free DNA (cfDNA) could detect the low-frequency somatic mutations and provide an accurate diagnosis for many cancers. However, for brain gliomas, reliable performance of these techniques currently requires obtaining cfDNA from patients' cerebral spinal fluid, which is cumbersome and risky. Here we report a liquid biopsy method based on sequencing of plasma cfDNA fragments carrying 5-hydroxymethylcytosine (5hmC) using selective chemical labeling (hMe-Seal). We first constructed a dataset including 180 glioma patients and 229 non-glioma controls. We found marked concordance between cfDNA hydroxymethylome and the aberrant transcriptome of the underlying gliomas. Functional analysis also revealed overrepresentation of the differentially hydroxymethylated genes (DhmGs) in oncogenic and neural pathways. After splitting our dataset into training and test cohort, we showed that a penalized logistic model constructed with training set DhmGs could distinguish glioma patients from healthy controls in both our test set (AUC = 0.962) and an independent dataset (AUC = 0.930) consisting of 111 gliomas and 111 controls. Additionally, the DhmGs between gliomas with mutant and wild-type isocitrate dehydrogenase (IDH) could be used to train a cfDNA predictor of the IDH mutation status of the underlying tumor (AUC = 0.816), and patients with predicted IDH mutant gliomas had significantly better outcome (P = .01). These results indicate that our plasma cfDNA 5hmC sequencing method could obtain glioma-specific signals, which may be used to noninvasively detect these patients and predict the aggressiveness of their tumors.

Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

“…We included 5hmC sequencing data from 33 LUAD [18] , 74 PDAC [20] , 132 HCC [21] , 72 GBM [22] and 85 control [20] samples. All samples belonged to one study, and get published in four publications.…”

An overview of multiomics: a powerful tool applied in cancer molecular subtyping for cancer therapy

“…Zhang et al built a data set containing 180 glioma patients and 229 nonglioma controls by collecting venous plasma. A penalized logistic model constructed with training set differentially hydroxymethylated genes (DhmGs) could help glioma diagnosis in both test set (AUC = 0.962) and an independent data set (AUC = 0.930) consisting of 111 gliomas and 111 controls [82].…”

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

“…Several studies have reported attempts to identify and grade gliomas based on the analysis of nonspecific molecular and cellular components in a patient's blood such as glial fibrillary acidic protein, other proteins, and neutrophil/lymphocyte ratios [16][17][18][19]. Similarly, the identification of IDH mutations based on circulating DNA [20], and the usefulness of hydroxy methylome analysis of circulating DNA in plasma [21] have also been reported. Each of these methods, which focus on specific components, require different sample-processing methods and reagents, and costs for each component.…”