Project description:Using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq), we analyzed methylation profiles in 93 plasma samples from 77 pediatric brain tumor patients and 16 non-neoplastic patients. Binomial GLMnet classifiers of tumor and tumor subtypes were built in training sets, and performance was evaluated in test sets. The methylation profiles from plasma cfMeDIP-seq discriminated tumor from non-tumor patients with 0.83 accuracy (precision = 0.93, sensitivity = 0.86, and specificity = 0.67). Among major tumor subtypes vs. nontumors, circumscribed astrocytic glioma showed an accuracy of 0.86 (precision = 0.88, sensitivity = 0.88, and specificity = 0.83), and glioneuronal tumors had an accuracy of 0.83 (precision, sensitivity, and specificity = 0.83). Circumscribed astrocytic glioma and glioneuronal tumors could be discriminated from other tumor subtypes with 0.79 and 0.82 accuracy, respectively.
Project description:Epigenetics tightly regulates gene expression during brain development, which ensemble distinct cell types and form complicated functional brain organ. DNA methylation is an important mark which undergo dramatically changes during brain development. The disturb of this process will lead to various brain tumors. To study the concordant DNA methylation changes during normal brain development, we sequenced DNA methylome of pediatric brain tissues from autopsy with various ages. We systematically compared the DNA methylome of pediatric brain and adult brain and identified candidate DMRs that contribute to normal brain development. This comprehensive analysis will provide important epigenetic reference for human brain development which will be a valuable data to study the epigenetic mechanism of pediatric brain tumor.
Project description:Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and are often misdiagnosed because of a lack of advanced molecular diagnostic tools. In this study, we explored the utility of circulating cell-free RNA (cfRNA) in plasma as an analyte for the differential diagnosis and characterization of pediatric inflammatory syndromes. We profiled cfRNA in 370 plasma samples from pediatric patients with a range of inflammatory conditions, including Kawasaki disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), viral infections and bacterial infections. We developed machine learning models based on these cfRNA profiles, which effectively differentiated KD from MIS-C — two conditions presenting with overlapping symptoms — with high performance (Test Area Under the Curve (AUC) = 0.97). We further extended this methodology into a multiclass machine learning framework that achieved 81% accuracy in distinguishing among KD, MIS-C, viral, and bacterial infections. We further demonstrated that cfRNA profiles can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system, and the upper respiratory tract. Overall, this study identified cfRNA as a versatile analyte for the differential diagnosis and characterization of a wide range of pediatric inflammatory syndromes.
Project description:We analyzed cell-free microRNAs (cfmiRs) in blood, tissue, and urine samples of melanoma patients to find potential biomarkers for monitoring and assessing early detection of melanoma metastasis. This study demonstrates that identifying cfmiR signatures in body fluids may allow for detection and assessment of melanoma brain metastasis (MBM) and metastatic melanoma patients undergoing checkpoint inhibitor immunotherapy treatments.
Project description:We sequenced cell-free RNA (cfRNA) for five cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer and esophageal cancer) and healthy individuals in 230 plasma samples collected from 6 clinical centers in China. Cancer related signaling pathway and microbial genus were identified. Cancer detection and specific classification were achieved through combining both host and microbial cfRNA reads.
Project description:In this study, we examined if the composition of plasma miRNAs is altered in patients with traumatic brain injury (TBI), and if these changes can be used as diagnostic markers. A microarray containing 875 human miRNAs was used to compare the miRNA profile of plasma collected from severe TBI patients (GCS M-bM-^IM-$ 8) to that of age-, gender-, and race-matched healthy volunteers. This screen identified 108 miRNAs in the plasma of healthy volunteers. Of these, 52 were found to be altered in plasma samples from persons with severe TBI, and an additional 8 miRNAs were detected only in the plasma of TBI patients. Plasma samples from 10 patients from either severe TBI (experimental group) or healthy volunteers (reference group; age-, gender-, and race-matched ) were pooled, the total RNA extracted in parallel, eluted in 100ul, and dried to 30 ul. Equal volumes of extracted plasma RNAs were assayed for global miRNA content using a service provider (LC Sciences, Houston, TX). There were no replicates performed for this screen. Healthy volunteer group served as the reference.
Project description:In this study, we examined if the composition of plasma miRNAs is altered in patients with traumatic brain injury (TBI), and if these changes can be used as diagnostic markers. A microarray containing 875 human miRNAs was used to compare the miRNA profile of plasma collected from severe TBI patients (GCS ≤ 8) to that of age-, gender-, and race-matched healthy volunteers. This screen identified 108 miRNAs in the plasma of healthy volunteers. Of these, 52 were found to be altered in plasma samples from persons with severe TBI, and an additional 8 miRNAs were detected only in the plasma of TBI patients.