Genome-wide cell-free DNA fragmentation profiling for early cancer detection.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 3018-3018
Author(s):  
Alessandro Leal ◽  
Stephen Cristiano ◽  
Jillian Phallen ◽  
Jacob Fiksel ◽  
Vilmos Adleff ◽  
...  
Keyword(s):  
Dna Fragmentation ◽  
White Blood Cells ◽  
Targeted Sequencing ◽  
Healthy Individuals ◽  
Cell Free Dna ◽  
Patients With Cancer ◽  
Molecular Features ◽  
Free Dna ◽  
Genome Wide ◽  
Fragmentation Patterns

3018 Background: Analyses of cell-free DNA (cfDNA) in the blood provide a noninvasive diagnostic avenue for patients with cancer. However, cfDNA analyses have largely focused on targeted sequencing of specific genes, and the characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an ultrasensitive approach that allows simultaneous examination of a large number of abnormalities in cfDNA through genome-wide analysis of fragmentation patterns. Methods: We used a machine learning model to examined cfDNA fragmentation profiles of 236 patients with largely localized breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancer and 245 healthy individuals. Estimation of performance was determined by ten-fold cross validation repeated ten times. Results: cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation patterns. The degree of abnormality in fragmentation profiles during therapy closely matched levels of mutant allele fractions in cfDNA as determined using ultra-deep targeted sequencing. The sensitivity of detection ranged from 57% to > 99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cfDNA analyses detected 91% of cancer patients. Conclusions: This effort is the first study to demonstrate genome-wide cell-free DNA fragmentation abnormalities in patients with cancer. Results of these analyses highlight important properties of cfDNA and provide a facile approach for screening, early detection, and monitoring of human cancer.

scholarly journals Genome-wide cell-free DNA fragmentation in patients with cancer

Nature ◽  
2019 ◽  
Vol 570 (7761) ◽  
pp. 385-389 ◽  
Author(s):  
Stephen Cristiano ◽  
Alessandro Leal ◽  
Jillian Phallen ◽  
Jacob Fiksel ◽  
Vilmos Adleff ◽  
...  
Keyword(s):  
Dna Fragmentation ◽  
Cell Free Dna ◽  
Patients With Cancer ◽  
Free Dna ◽  
Genome Wide

scholarly journals An integrative analysis of genome-wide 5-hydroxymethylcytosines in circulating cell-free DNA detects non-invasive diagnostic markers for gliomas

2021 ◽  
Author(s):  
Jiajun Cai ◽  
Chang Zeng ◽  
Wei Hua ◽  
Zengxin Qi ◽  
Yanqun Song ◽  
...  
Keyword(s):  
Clinical Outcomes ◽  
Idh1 Mutation ◽  
Healthy Individuals ◽  
Cell Free Dna ◽  
Mutation Status ◽  
Non Invasive ◽  
Free Dna ◽  
Genome Wide ◽  
Validation Set ◽  
Circulating Cell Free Dna

Abstract Background Gliomas, especially the high-grade glioblastomas (GBM), are highly aggressive tumors in the central nervous system (CNS) with dismal clinical outcomes. Effective biomarkers, which are not currently available, may improve clinical outcomes through early detection. We sought to develop a non-invasive diagnostic approach for gliomas based on 5-hydroxymethylcytosines (5hmC) in circulating cell-free DNA (cfDNA). Methods We obtained genome-wide 5hmC profiles using the 5hmC-Seal technique in cfDNA samples from 111 prospectively enrolled patients with gliomas and 111 age-, gender-matched healthy individuals, which were split into a training set and a validation set. Integrated models comprised of 5hmC levels summarized for gene bodies, long non-coding RNAs (lncRNAs), cis-regulatory elements, and repetitive elements were developed using the elastic net regularization under a case-control design. Results The integrated 5hmC-based models differentiated healthy individuals from gliomas (AUC [area under the curve] = 84%; 95% confidence interval [CI], 74-93%), GBM patients (AUC = 84%; 95% CI, 74-94%), WHO II-III glioma patients (AUC = 86%; 95% CI, 76-96%), regardless of IDH1 (encoding isocitrate dehydrogenase) mutation status or other glioma-related pathological features such as TERT, TP53 in the validation set. Furthermore, the 5hmC biomarkers in cfDNA showed the potential as an independent indicator from IDH1 mutation status and worked in synergy with IDH1 mutation to distinguish GBM from WHO II-III gliomas. Exploration of the 5hmC biomarkers for gliomas revealed relevance to glioma biology. Conclusions The 5hmC-Seal in cfDNA offers the promise as a non-invasive approach for effective detection of gliomas in a screening program.

scholarly journals Genome-Wide Analysis of Cell-Free DNA Methylation Profiling for the Early Diagnosis of Pancreatic Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Shengyue Li ◽  
Lei Wang ◽  
Qiang Zhao ◽  
Zhihao Wang ◽  
Shuxian Lu ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Early Diagnosis ◽  
Healthy Individuals ◽  
Promoter Regions ◽  
Cell Free Dna ◽  
Non Invasive ◽  
Early Cancer Diagnosis ◽  
Free Dna ◽  
Genome Wide ◽  
Methylation Profiling

As one of the most malicious cancers, pancreatic cancer is difficult to treat due to the lack of effective early diagnosis. Therefore, it is urgent to find reliable diagnostic and predictive markers for the early detection of pancreatic cancer. In recent years, the detection of circulating cell-free DNA (cfDNA) methylation in plasma has attracted global attention for non-invasive and early cancer diagnosis. Here, we carried out a genome-wide cfDNA methylation profiling study of pancreatic ductal adenocarcinoma (PDAC) patients by methylated DNA immunoprecipitation coupled with high-throughput sequencing (MeDIP-seq). Compared with healthy individuals, 775 differentially methylated regions (DMRs) located in promoter regions were identified in PDAC patients with 761 hypermethylated and 14 hypomethylated regions; meanwhile, 761 DMRs in CpG islands (CGIs) were identified in PDAC patients with 734 hypermethylated and 27 hypomethylated regions (p-value < 0.0001). Then, 143 hypermethylated DMRs were further selected which were located in promoter regions and completely overlapped with CGIs. After performing the least absolute shrinkage and selection operator (LASSO) method, a total of eight markers were found to fairly distinguish PDAC patients from healthy individuals, including TRIM73, FAM150A, EPB41L3, SIX3, MIR663, MAPT, LOC100128977, and LOC100130148. In conclusion, this work identified a set of eight differentially methylated markers that may be potentially applied in non-invasive diagnosis of pancreatic cancer.

scholarly journals The effect of pre-analytical and physiological variables on cell-free DNA fragmentation.

2021 ◽  
Author(s):  
Ymke van der Pol ◽  
Norbert Moldovan ◽  
Sandra Verkuijlen ◽  
Jip Ramaker ◽  
Dries Boers ◽  
...  
Keyword(s):  
Biological Properties ◽  
Physiological Factors ◽  
Cell Free Dna ◽  
Physiological Variables ◽  
Processing Times ◽  
Free Dna ◽  
Genome Wide ◽  
Collection Tube ◽  
Fragmentation Patterns ◽  
The Impact

Assays that account for the biological properties and fragmentation of cell-free DNA (cfDNA) can improve the performance of liquid biopsy. However, pre-analytic and physiological differences between individuals on fragmentomic analysis are poorly defined. We analyzed the impact of collection tube, plasma processing time and physiology on the size distribution of cfDNA, their genome-wide representation and sequence diversity at the cfDNA fragment-ends using shallow Whole Genome Sequencing. We observed that using different stabilizing collection tubes, or processing times does not affect the cfDNA fragment sizes, but can impact the genome-wide fragmentation patterns and fragment-end sequences of cfDNA. In addition, beyond differences depending on the gender, the physiological conditions tested between 63 individuals (age, body mass index, use of medication and chronic conditions) minimally influenced the outcome of fragmentomic methods. Our results highlight that fragmentomic approaches have potential for implementation in the clinic, pending clear traceability of analytical and physiological factors.

scholarly journals De novo characterization of cell-free DNA fragmentation hotspots boosts the power for early detection and localization of multi-cancer

2020 ◽  
Author(s):  
Xionghui Zhou ◽  
Yaping Liu
Keyword(s):  
Dna Fragmentation ◽  
De Novo ◽  
Early Stage ◽  
Fine Scale ◽  
Cell Free Dna ◽  
Early Stage Cancer ◽  
Free Dna ◽  
Cancer Types ◽  
Fragmentation Patterns

AbstractThe global variation of cell-free DNA fragmentation patterns is a promising biomarker for cancer diagnosis. However, the characterization of its hotspots and aberrations in early-stage cancer at the fine-scale is still poorly understood. Here, we developed an approach to de novo characterize genome-wide cell-free DNA fragmentation hotspots by integrating both fragment coverage and size from whole-genome sequencing. These hotspots are highly enriched in regulatory elements, such as promoters, and hematopoietic-specific enhancers. Surprisingly, half of the high-confident hotspots are still largely protected by the nucleosome and located near repeats, named inaccessible hotspots, which suggests the unknown origin of cell-free DNA fragmentation. In early-stage cancer, we observed the increases of fragmentation level at these inaccessible hotspots from microsatellite repeats and the decreases of fragmentation level at accessible hotspots near promoter regions, mostly with the silenced biological processes from peripheral immune cells and enriched in CTCF insulators. We identified the fragmentation hotspots from 298 cancer samples across 8 different cancer types (92% in stage I to III), 103 benign samples, and 247 healthy samples. The fine-scale fragmentation level at most variable hotspots showed cancer-specific fragmentation patterns across multiple cancer types and non-cancer controls. Therefore, with the fine-scale fragmentation signals alone in a machine learning model, we achieved 42% to 93% sensitivity at 100% specificity in different early-stage cancer. In cancer positive cases, we further localized cancer to a small number of anatomic sites with a median of 85% accuracy. The results here highlight the significance to characterize the fine-scale cell-free DNA fragmentation hotspot as a novel molecular marker for the screening of early-stage cancer that requires both high sensitivity and ultra-high specificity.

scholarly journals Baseline mutation profiling of 1134 samples of circulating cell-free DNA and blood cells from healthy individuals

2016 ◽  
Author(s):  
Ligang Xia ◽  
Zhoufang Li ◽  
Bo Zhou ◽  
Geng Tian ◽  
Lidong Zeng ◽  
...  
Keyword(s):  
Blood Cells ◽  
Somatic Mutations ◽  
White Blood Cells ◽  
Clinical Diagnostics ◽  
Healthy Individuals ◽  
Sequencing Data ◽  
Cell Free Dna ◽  
Early Cancer Diagnosis ◽  
Free Dna ◽  
Circulating Cell Free Dna

AbstractThe molecular alteration in circulating cell-free DNA (cfDNA) in plasma can reflect the status of the human body in a timely manner. Hence, cfDNA has emerged as important biomarkers in clinical diagnostics, particularly in cancer. However, somatic mutations are also commonly found in healthy individuals, which extensively interfere with the diagnostic results in cancer. This study was designed to examine the background somatic mutations in white blood cells (WBC) and cfDNA for healthy controls based on the sequencing data from 1134 samples, to understand the patterns and origin of mutations detected in cfDNA. We determined the mutation frequencies in both the WBC and cfDNA groups of the samples by a panel of 50 cancer-associated genes which covered 20K nucleotide regions using ultra-deep sequencing with average depth >40000 folds. Our results showed that most of mutations in cfDNA originated from WBC. We also observed that NPM1 gene was the most frequently mutant gene in both WBC and cfDNA. Our study highlighted the importance of sequencing both cfDNA and WBC, to improve the sensitivity and accuracy for calling cancer-related mutations from circulating tumor DNA, and shielded light on developing the early cancer diagnosis by cfDNA sequencing.

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