Detection and discrimination of intracranial tumors using plasma cell-free DNA methylomes.
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ABSTRACT:
SUBMITTER: Nassiri F
PROVIDER: S-EPMC8500275 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundOvarian cancer (OC) is a highly lethal gynecologic cancer, and it is hard to diagnose at an early stage. Clinically, there are no ovarian cancer-specific markers for early detection. Here, we demonstrate the use of cell-free DNA (cfDNA) methylomes to detect ovarian cancer, especially the early-stage OC.Experimental designPlasma from 74 epithelial ovarian cancer patients, 86 healthy volunteers, and 20 patients with benign pelvic masses was collected. The cfDNA methylomes of these samples were generated by cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). The differentially methylated regions (DMRs) were identified by the contrasts between tumor and non-tumor groups, and the discrimination performance was evaluated with the iterative training and testing method.ResultsThe DMRs identified for cfDNA methylomes can well discriminate tumor groups and non-tumor groups (ROC values from 0.86 to 0.98). The late-stage top 300 DMRs are more late-stage-specific and failed to detect early-stage OC. However, the early-stage markers have the potential to discriminate all-stage OCs from non-tumor samples.ConclusionsThis study demonstrates that cfDNA methylomes generated with cfMeDIP-seq could be used to identify OC-specific biomarkers for OC, especially early OC detection. To detect early-stage OC, the biomarkers should be directly identified from early OC plasma samples rather than mix-stage ones. Further exploration of DMRs from a k larger early-stage OC cohort is warranted.
| S-EPMC9185905 | biostudies-literature
Project description:Improving early cancer detection has the potential to substantially reduce cancer-related mortality. Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a highly sensitive assay capable of detecting early-stage tumors. We report accurate classification of patients across all stages of renal cell carcinoma (RCC) in plasma (area under the receiver operating characteristic (AUROC) curve of 0.99) and demonstrate the validity of this assay to identify patients with RCC using urine cell-free DNA (cfDNA; AUROC of 0.86).
| S-EPMC8288043 | biostudies-literature
Project description:Medulloblastoma (MB) is an embryonal tumor of the cerebellum and a highly malignant childhood brain tumor. Cell-free circulating tumor DNA (ctDNA) from the cerebrospinal fluid (CSF) of patients with brain tumors faithfully represent genomic alterations of brain tumors. Distinct epigenetic signatures among subgroups of MB allow us to detect epigenetic alterations in CSF to aid classify and guide therapy of MB tumors. Here, we evaluate DNA methylation and hydroxymethylation of ctDNA derived from small amount of CSF (200 µL) and matched tumor DNA from 3 MB patients. We find highly concordance of DNA methylation and hydroxymethylation between CSF ctDNA and tumor DNA, especially in CpG islands. Importantly, CSF ctDNA can mostly recapitulate the dynamic changes of DNA methylation and hydroxymehtylation in tumor species compared to healthy cerebellums. Those MB tumor signature CpGs’ DNA methylation status are recovered in CSF ctDNA can clearly distinguish MB subgroups by utilizing public large cohort data. We further identified potential diagnostic and prognostic DNA methylation markers in CSF ctDNA. Our results show that CSF ctNDA methylation and hydroxymethylation can be a minimal invasive method to assess epigenetic alterations of MB, which is complementary to current diagnoses of MB tumors.
2020-10-28 | GSE142241 | GEO
Project description: Not available
| S-EPMC7049928 | biostudies-literature
Project description:BackgroundEarly diagnosis benefits lung cancer patients with higher survival, but most patients are diagnosed after metastasis. Although cell-free DNA (cfDNA) analysis holds promise, its sensitivity for detecting early-stage lung cancer is unsatisfying. We leveraged cfDNA fragmentomics to develop a predictive model for invasive stage I lung adenocarcinoma (LUAD).Methods292 stage I LUAD patients from three medical centers were included together with 230 healthy controls whose plasma cfDNA samples were profiled by whole-genome sequencing (WGS). Multiple cfDNA fragmentomic motif features and machine learning models were compared in the training cohort to select the best model. Model performance was assessed in the internal and external validation cohorts and an additional dataset.FindingsA logistic regression model using the 6bp-breakpoint-motif feature was selected. It yielded 98·0% sensitivity and 94·7% specificity in the internal validation cohort [Area Under the Curve (AUC): 0·985], while 92·5% sensitivity and 90·0% specificity were achieved in the external validation cohort (AUC: 0·954). It is sensitive for early-stage (100% sensitivity for minimally invasive adenocarcinoma, MIA) and <1 cm (92·9%-97·7% sensitivity) tumors. The predictive power remained high when reducing sequencing depth to 0·5× (AUC: 0·977 and 0·931 for internal and external cohorts).InterpretationHere we have established a cfDNA breakpoint motif-based model for detecting early-stage LUAD, including MIA and very small-size tumors, shedding light on early cancer diagnosis in clinical practice.FundingNational Key R&D Program of China; National Natural Science Foundation of China; CAMS Initiative for Innovative Medicine; Special Research Fund for Central Universities, Peking Union Medical College; Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences; Beijing Hope Run Special Fund of Cancer Foundation of China.
| S-EPMC9251329 | biostudies-literature
Project description:Circulating cell-free DNA (cfDNA) is extracellular DNA released into the bloodstream by apoptotic or necrotic tumor cells, with cfDNA determination proposed as a noninvasive, sensitive marker for the diagnosis of human cancer. We evaluated cfDNA quantification as a diagnostic and prognostic tool in dogs with various tumors. We quantified plasma cfDNA concentration by absolute real-time PCR of long interspersed nuclear elements in 50 dogs with malignant tumors, 13 dogs with benign tumors or nodules, and 11 healthy controls. Six patients with malignant tumors were followed-up, and plasma cfDNA was quantified throughout disease progression. We found that plasma cfDNA concentrations were significantly elevated in dogs with malignant tumors compared with dogs with benign nodules or healthy controls. The DNA integrity index (the ratio between long and short cfDNA fragments) was significantly lower in dogs with malignant tumors compared to healthy controls. Significantly higher cfDNA levels and a lower DNA integrity index were observed in dogs with lymphoma or leukemia, hemangiosarcoma, and distant metastasis; cfDNA levels correlated well with clinical stage and tended to increase during or before periods of disease progression, suggesting potential efficacy of cfDNA for the detection of distant metastasis and to monitor the clinical stage of neoplasia.
| S-EPMC6900719 | biostudies-literature
Project description:Reliable tumor detection using cerebrospinal fluid cell-free DNA methylomes in pediatric medulloblastoma
| PRJNA596280 | ENA
Project description:Somatic genetic alterations including copy number and point mutations in the androgen receptor (AR) are associated with resistance to therapies targeting the androgen/AR axis in patients with metastatic castration resistant prostate cancer (mCRPC). Due to limitations associated with biopsying metastatic lesions, plasma derived cell-free DNA (cfDNA) is increasingly being used as substrate for genetic testing. AR mutations detected by deep next generation sequencing (NGS) of cfDNA from patients with mCRPC have been reported at allelic fractions ranging from over 25% to below 1%. The lower bound threshold for accurate mutation detection by deep sequencing of cfDNA has not been comprehensively determined and may have locus specific variability. Herein, we used NGS for AR mutation discovery in plasma-derived cfDNA from patients with mCRPC and then used droplet digital polymerase chain reaction (ddPCR) for validation. Our findings show the AR (tTC>cTC) F877L hotspot was prone to false positive mutations during NGS. The rate of error at AR (tTC>cTC) F877L during amplification prior to ddPCR was variable among high fidelity polymerases. These results highlight the importance of validating low-abundant mutations detected by NGS and optimizing and controlling for amplification conditions prior to ddPCR.
| S-EPMC5362513 | biostudies-literature
Project description:A suitable clinical-grade platform is required for detection of somatic mutations with high sensitivity in cell-free DNA (cfDNA) of patients with solid tumors. In this study, we evaluated in parallel ultra-deep NGS with MassARRAY and allele-specific droplet digital PCR (ddPCR) for cfDNA genotyping and correlated cfDNA yield and mutation status with overall survival (OS) of patients. We assessed plasma samples from 46 patients with various advanced metastatic solid tumors and known mutations by deep sequencing using an Ampliseq cancer hotspot panel V2 on Ion Proton. A subset of these samples with DNA availability was tested by ddPCR and UltraSEEK MassARRAY for mutation detection in 5 genes (IDH1, PIK3CA, KRAS, BRAF, and NRAS). Sixty one of 104 expected tissue mutations and 6 additional mutations not present in the tissue were detected in cfDNA. ddPCR and MassARRAY showed 83% and 77% concordance with NGS for mutation detection with 100% and 79% sensitivity, respectively. The median OS of patients with lower cfDNA yield (74 vs 50 months; P < 0.03) and cfDNA negative for mutations (74.2 vs 53 months; p < 0.04) was significantly longer than in patients with higher cfDNA yield and positive for mutations. A limit-of-detection of 0.1% was demonstrated for ddPCR and MassARRAY platforms using a serially diluted positive cfDNA sample. The MassARRAY and ddPCR systems enable fast and cost-effective genotyping for a targeted set of mutations and can be used for single gene testing to guide response to chemotherapy or for orthogonal validation of NGS results.
| S-EPMC5828199 | biostudies-literature
Project description:Lung cancer is a leading cause of cancer-related deaths worldwide, with a low 5-year survival rate due in part to a lack of clinically useful biomarkers. Recent studies have identified DNA methylation changes as potential cancer biomarkers. The present study identified cancer-specific CpG methylation changes by comparing genome-wide methylation data of cfDNA from lung adenocarcinomas (LUAD) patients and healthy donors in the discovery cohort. A total of 725 cell-free CpGs associated with LUAD risk were identified. Then XGBoost algorithm was performed to identify seven CpGs associated with LUAD risk. In the training phase, the 7-CpGs methylation panel was established to classify two different prognostic subgroups and showed a significant association with overall survival (OS) in LUAD patients. We found that the methylation of cg02261780 was negatively correlated with the expression of its representing gene GNA11. The methylation and expression of GNA11 were significantly associated with LAUD prognosis. Based on bisulfite PCR, the methylation levels of five CpGs (cg02261780, cg09595050, cg20193802, cg15309457, and cg05726109) were further validated in tumor tissues and matched non-malignant tissues from 20 LUAD patients. Finally, validation of the seven CpGs with RRBS data of cfDNA methylation was conducted and further proved the reliability of the 7-CpGs methylation panel. In conclusion, our study identified seven novel methylation markers from cfDNA methylation data which may contribute to better prognosis for LUAD patients.
| S-EPMC10311559 | biostudies-literature