scholarly journals Clinical Utility of Plasma Cell-Free DNA for Detection and Quantification of Clonal Hematopoiesis

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.

Haematologica ◽  
2021 ◽  
Author(s):  
Fernanda Gutierrez-Rodrigues ◽  
Isabel Beerman ◽  
Emma M. Groarke ◽  
Bhavisha A. Patel ◽  
Nina Spitofsky ◽  
...  

Although cell-free DNA (cfDNA) tests have emerged as a potential non-invasive alterative for bone marrow biopsies in monitoring of clonal hematopoiesis (CH) in hematologic diseases, whether commercial cfDNA assays can be implemented for de novo CH detection and quantification in place of blood cells is uncertain. In this study, peripheral plasma cfDNA samples available from patients with aplastic anemia (AA; n=25), myelodysplastic syndrome (MDS; n=27) and a healthy cohort (n=107) were screened for somatic variants in genes related to hematologic malignancies using a Clinical Laboratory Improvement Amendments-certified panel. Results were further compared to DNA sequencing of matched blood cells. In reported results, 85% of healthy subjects, 36% of AA patients and 74% of MDS patients were found to have somatic cfDNA variants, most frequently in DNMT3A, TET2, ASXL1 and SF3B1. However, concordance between cfDNA and blood cells was poor for CH detection when variants were at variant allele frequency


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%.


2018 ◽  
Vol 20 (suppl_2) ◽  
pp. i184-i184
Author(s):  
Melanie Pages ◽  
Denisse Rotem ◽  
Gregory Gydush ◽  
Sarah Reed ◽  
Justin Rhoades ◽  
...  

2019 ◽  
Vol 21 (Supplement_2) ◽  
pp. ii82-ii82
Author(s):  
Mélanie Pagès ◽  
Denisse Rotem ◽  
Gregory Gydush ◽  
Sarah Reed ◽  
Justin Rhoades ◽  
...  

2018 ◽  
Vol 20 (suppl_6) ◽  
pp. vi142-vi143
Author(s):  
Mélanie Pages ◽  
Denisse Rotem ◽  
Gregory Gydush ◽  
Sarah Reed ◽  
Justin Rhoades ◽  
...  

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14530-e14530
Author(s):  
Stephanie J. Yaung ◽  
Liu Xi ◽  
Corinna Woestmann ◽  
Christine Ju ◽  
Daniel M. Klass ◽  
...  

e14530 Background: Somatic variants found in plasma cell-free DNA (cfDNA) may derive from either solid tumors or clonal hematopoiesis (CH). Little is known about how this may impact plasma-based longitudinal disease monitoring using targeted sequencing of circulating tumor DNA (ctDNA). Methods: To assess the potential impact of CH in disease monitoring, we evaluated monitoring algorithms by targeted sequencing with and without matched peripheral blood mononuclear cells (PBMC). Samples were collected from a prospective observational study, where 62 late stage lung adenocarcinoma subjects were treated with first-line chemo or chemoradiation therapy. Pre-treatment plasma cfDNA and matched PBMC were analyzed with the AVENIO ctDNA Surveillance Kit (For Research Use Only, not for use in diagnostic procedures), a sequencing panel of 198 kilobases targeting cancer genes. Median input amounts of 25 ng cfDNA and 50 ng PBMC DNA were sequenced to median deduplicated depths of 4582 and 6134, respectively. Results: A median of 120 single nucleotide variants were detected per cfDNA sample, with 93.1% of these identified in matched PBMC. Most PBMC-matched cfDNA variants were germline SNPs, with allele frequency (AF) ~ 50% or 100%. A median of 1 (range 0-5) PBMC-matched cfDNA variants per sample were detected with an AF < 10%, consistent with CH. The number of these variants was positively associated with age (p-value = 0.0039) and the most frequently mutated gene was TP53. The remaining somatic variants (i.e., in cfDNA and not PBMC) had an AF range 0.03-40.9%. These PBMC-informed variants (median of 7 per sample) were used in longitudinal monitoring in the first post-treatment plasma sample to assess early response to therapy. Association between ctDNA level and progression-free survival using the same monitoring algorithm yielded nearly identical results on somatic variants derived from filtering approaches independent of matched PBMC (HR 0.32; 95% CI 0.16 - 0.65; log-rank P = 0.0009) and the PBMC-informed method (HR 0.31; 95% CI 0.14 - 0.66; log-rank P = 0.0013). Conclusions: A targeted panel focused on solid tumors by design has limited impact from CH. For disease monitoring applications in a non-MRD setting, measuring multiple variants instead of a single variant further enables robust classifiers that can moderate the impact of variants, if any, from CH.


2018 ◽  
Vol 154 (6) ◽  
pp. S-436
Author(s):  
Michael J. Levy ◽  
Benjamin R. Kipp ◽  
Dragana Milosevic ◽  
Amber Schneider ◽  
Jesse Voss ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document