scholarly journals OCRDetector: Accurately Detecting Open Chromatin Regions via Plasma Cell-Free DNA Sequencing Data

2021 ◽  
Vol 22 (11) ◽  
pp. 5802
Author(s):  
Jiayin Wang ◽  
Liubin Chen ◽  
Xuanping Zhang ◽  
Yao Tong ◽  
Tian Zheng

Open chromatin regions (OCRs) are special regions of the human genome that can be accessed by DNA regulatory elements. Several studies have reported that a series of OCRs are associated with mechanisms involved in human diseases, such as cancers. Identifying OCRs using ATAC-seq or DNase-seq is often expensive. It has become popular to detect OCRs from plasma cell-free DNA (cfDNA) sequencing data, because both the fragmentation modes of cfDNA and the sequencing coverage in OCRs are significantly different from those in other regions. However, it is a challenging computational problem to accurately detect OCRs from plasma cfDNA-seq data, as multiple factors—e.g., sequencing and mapping bias, insufficient read depth, etc.—often mislead the computational model. In this paper, we propose a novel bioinformatics pipeline, OCRDetector, for detecting OCRs from whole-genome cfDNA sequencing data. The pipeline calculates the window protection score (WPS) waveform and the cfDNA sequencing coverage. To validate the proposed pipeline, we compared the percentage overlap of our OCRs with those obtained by other methods. The experimental results show that 81% of the TSS regions of housekeeping genes are detected, and our results have obvious tissue specificity. In addition, the overlap percentage between our OCRs and the high-confidence OCRs obtained by ATAC-seq or DNase-seq is greater than 70%.

2019 ◽  
Vol 29 (3) ◽  
pp. 418-427 ◽  
Author(s):  
Kun Sun ◽  
Peiyong Jiang ◽  
Suk Hang Cheng ◽  
Timothy H.T. Cheng ◽  
John Wong ◽  
...  

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Peter Ulz ◽  
Samantha Perakis ◽  
Qing Zhou ◽  
Tina Moser ◽  
Jelena Belic ◽  
...  

Abstract Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. Here we develop and validate a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyze whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 4-5
Author(s):  
Fernanda Gutierrez-Rodrigues ◽  
Isabel Beerman ◽  
Emma M. Groarke ◽  
Bhavisha A Patel ◽  
Nina Spitofsky ◽  
...  

Cell-free DNA (cfDNA) extracted from peripheral blood plasma has been increasingly used as a non-invasive approach for diagnosis and surveillance of solid and hematologic malignancies. Somatic variants associated with clonal hematopoiesis of indeterminate potential (CHIP) are commonly detected in such liquid biopsies, suggesting that cfDNA may be useful for their detection. CHIP has emerged as a predictor of progression to hematological malignancies; however, clones are still largely detected using peripheral blood (PB) and bone marrow (BM) cells. In this study, we investigated the performance of cfDNA for detection and quantification of CHIP compared to matched PB/BM cells. cfDNA initially was collected from a healthy cohort (n=106), part of the Baltimore Longitudinal Study of Aging/NIH; later we expanded to screen patients with aplastic anemia (AA; n=53) and myelodysplastic syndrome (MDS; n=27) monitored at the National Heart, Lung, and Blood Institute. Samples were screened for somatic mutations in myeloid neoplasm-related genes using a commercial panel of 177 genes. In HC (median age:72 [range:24-96]), 78/106 subjects (73%) were found to have one (28%) or two and more (45%) cfDNA variants in CHIP-related genes, most frequently in DNMT3A,TET2, TP53, and ASXL1 (Figure 1A). CHIP was observed in more than 60% of individuals older than 40 years, higher than typically reported. In contrast, only 17/53 of AA patients (32%; median age:51 [range:13-82]) were found to have one (n=10) or two or more (n=7) cfDNA variants, most commonly DNMT3A and SF3B1 (Figure 1B). In MDS, 17/29 (58%; median age:63 [range:35-85]) had one (n=10) or two or more (n=7) variants, TET2 and SF3B1 being most frequent (Figure 1C). Median VAF of cfDNA variants was significantly different among cohorts (HC:2.5% [95CI%:2-4] vs AA:18% [95CI%:6-32] vs MDS:38.6% [95CI%:27-42]; t-test,p<000.1). cfDNA results were validated against matched PB/BM cells collected from HC (n=25), AA (n=56), and MDS patients (n=54). cfDNA variants were classified as true, and false positives or negatives according to their presence in PB/BM (Figure 1E). In HC, cfDNA sensitivity was moderate (58%), but specificity and PPV were low compared to PB. In AA and MDS, sensitivity, specificity and PPV values were high compared with BM (Table 1). In all cohorts, the median VAF of discordant variants was significantly lower than VAF of true-positives (9.5% [95CI%:8-12] vs. 36% [95CI%:31-37]; t-test,p<000.1). Discordant pairs were mainly observed with cfDNA variants at VAF<12%; the sensitivity and PPV of variants below this threshold were very low (Table 1). Variants' discordance was correlated with sequencing coverage. Median read depth of false-positives and false-negatives was 112 (95CI%:92-143) compared to 464 [95CI%:355-563]) in true-positives. By filtering out likely discordant cfDNA variants using VAF and read depth, concordance significantly improved (Table 1). In HC, DTA genes were most commonly mutated (while TP53 variants were filtered out) and CHIP frequency was lower than in previous analysis (30% vs 60% in HC at >40yo; Figure 1A). Discordant pairs were found most often in ASXL1, KIT, TET2, and ZRSR2 (Figure 1E). Although linear regression showed high correlation between the VAF of paired samples (R2>0.7), agreement of VAF by Bland-Altman analysis was poor; this approach calculates the bias, the mean difference between the VAF of matched samples, and its standard deviation (SD) to more accurately evaluate agreement between paired values. Here, the bias and SD were both as high as 9% in HC and patients. These large variations translated to a wide range of upper and lower limits of agreement (mean ± 2*SD), which represent the limits of acceptable differences. In summary, the landscape of somatic cfDNA variants depended on variant VAF. Technical factors were an important source of assay discordance, and although cfDNA variants were reliably detected at higher VAFs, their quantification was not comparable to VAF detected in blood cells. A single cfDNA clone varied up to 9% in size and SD was unacceptably high in all cohorts. cfDNA and PB/BM may not be interchangeable, as cfDNA may either over- or under-estimate clone size, regardless of disease status. Since small changes in clone size and dynamics may influence clinical evaluation and decisions, the use of cfDNA for CHIP detection requires robust sequencing coverage and validation of variants at VAF<12% Disclosures Young: Novartis: Research Funding.


Lung Cancer ◽  
2015 ◽  
Vol 90 (1) ◽  
pp. 78-84 ◽  
Author(s):  
Shu Xia ◽  
Chiang-Ching Huang ◽  
Min Le ◽  
Rachel Dittmar ◽  
Meijun Du ◽  
...  

2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii430-iii430
Author(s):  
Ross Mangum ◽  
Jacquelyn Reuther ◽  
Koel Sen Baksi ◽  
Ryan C Zabriskie ◽  
Ilavarasi Gandhi ◽  
...  

Abstract BACKGROUND The role of plasma cell-free DNA (cfDNA) as a cancer biomarker for tracking treatment response and detecting early relapse has been well described for solid tumors outside the central nervous system (CNS). However, the presence of a blood-brain barrier complicates the application of plasma cfDNA analysis for patients with CNS malignancies. METHODS cfDNA was extracted from plasma of pediatric patients with CNS tumors utilizing a QIAmp® MinElute® kit and quantitated with Qubit 2.0 Fluorometer. Extensive genomic testing, including targeted DNA and RNA solid tumor panels, exome and transcriptome sequencing, as well as copy number array, was performed on matched tumor samples as part of the Texas KidsCanSeq study. An Archer® Reveal ctDNA28 NGS kit was then used for assaying the sensitivity of detecting tumor-specific mutations in the plasma of these patients. RESULTS A median of 10.7ng cfDNA/mL plasma (Interquartile range: 6.4 – 15.3) was extracted from 78 patients at time of study enrollment. Longitudinal samples from 24 patients exhibited a median yield of 7.7ng cfDNA/mL plasma (IQR: 5.9 – 9.1). An initial cohort of 6 patients was identified with 7 somatic variants covered by the Archer® Reveal kit. Four of seven mutations identified in matched tumor specimens were detected in patient plasma at variant allele frequencies ranging from 0.2–1%. CONCLUSIONS While challenging, detection of cfDNA in the plasma of pediatric patients with CNS tumors is possible and is being explored in a larger patient cohort along with pilot studies investigating cerebrospinal fluid as an additional source for tumor-specific cfDNA.


PLoS ONE ◽  
2020 ◽  
Vol 15 (4) ◽  
pp. e0232365 ◽  
Author(s):  
Michihito Tagawa ◽  
Naomi Tambo ◽  
Masaki Maezawa ◽  
Mizuki Tomihari ◽  
Ken-ichi Watanabe ◽  
...  

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