cfDNA Size Research Articles

Effects of blood-processing protocols on cell-free DNA fragmentomics in plasma: Comparisons of one- and two-step centrifugations

BackgroundCell-free DNA (cfDNA) fragmentomic characteristics are promising analytes with abundant physiological signals for non-invasive disease diagnosis and monitoring. Previous studies on plasma cfDNA fragmentomics commonly employed a two-step centrifugation process for removing cell debris, involving a low-speed centrifugation followed by a high-speed centrifugation. However, the effects of centrifugation conditions on the analysis of cfDNA fragmentome remain uncertain. MethodsWe collected blood samples from 10 healthy individuals and divided each sample into two aliquots for plasma preparation with one- and two-step centrifugation processes. We performed whole genome sequencing (WGS) of the plasma cfDNA in the two groups and comprehensively compared the cfDNA fragmentomic features. Additionally, we reanalyzed the fragmentomic features of cfDNA from 16 healthy individuals and 16 COVID-19 patients, processed through one- and two-step centrifugation in our previous study, to investigate the impact of centrifugation on disease signals. ResultsOur results showed that there were no significant differences observed in the characteristics of nuclear cfDNA, including size, motif diversity score (MDS) of end motifs, and genome distribution, between plasma samples treated with one- and two-step centrifugation. The cfDNA size shortening in COVID-19 patients was observed in plasma samples with one- and two-step centrifugation methods. However, we observed a significantly higher relative abundance and longer size of cell-free mitochondrial DNA (mtDNA) in the one-step samples compared to the two-step samples. This difference in mtDNA caused by the one- and two-step centrifugation methods surpasses the pathological difference between COVID-19 patients and healthy individuals. ConclusionsOur findings indicate that one-step low-speed centrifugation is a simple and potentially suitable method for analyzing nuclear cfDNA fragmentation characteristics. These results offer valuable guidance for cfDNA research in various clinical scenarios.

Diagnostic and Prognostic Value of Circulating DNA Fragments in Glioblastoma Multiforme Patients.

Novel blood-circulating molecules, as potential biomarkers for glioblastoma multiforme (GBM) diagnosis and monitoring, are attracting particular attention due to limitations of imaging modalities and invasive tissue biopsy procedures. This study aims to assess the diagnostic and prognostic values of circulating cell-free DNA (cfDNA) in relation to inflammatory status in GBM patients and to determine the concentration and average size of DNA fragments typical of tumour-derived DNA fractions. Preoperative plasma samples from 40 patients (GBM 65.0 ± 11.3 years) and 40 healthy controls (HC 70.4 ± 5.4 years) were compared. The cfDNA concentrations and lengths were measured using the electrophoresis platform, and inflammatory indices (NLR, PLR, LMR, and SII) were calculated from complete blood cell analysis. More fragmented cfDNA and 4-fold higher 50-700 bp cfDNA concentrations were detected in GBM patients than in healthy controls. The average cfDNA size in the GBM group was significantly longer (median 336 bp) than in the HC group (median 271 bp). Optimal threshold values were 1265 pg/μL for 50-700 bp cfDNA (AUC = 0.857) and 290 bp for average cfDNA size (AUC = 0.814). A Kaplan-Meier survival curves analysis also demonstrated a higher mortality risk in the GBM group with a cut-off >303 bp cfDNA. This study is the first to have revealed glioblastoma association with high levels of cfDNA > 1000 pg/μL of 50-700 bp in length, which can be aggravated by immunoinflammatory reactivity.

Abstract 7019: Identifying cell free DNA methylation signatures in cerebrospinal fluids for the early detection of brain metastasis in non-small cell lung cancer

Abstract Brain metastasis (BM) is major complication for adult cancer patients. Up to 2% of all cancer patients develop BM. Non-small cell lung cancer (NSCLC) contributes up to 55% of all BM. Approximately 15-20% of NSCLC patients show metastases at diagnosis, and approximately half will develop BM during their clinical course. Even after treatments like surgery, radiation and immunotherapy, the prognosis is dismal with median overall survival less than 13 months. No standard screening or early diagnostic testing exists for BM now. There is an urgent need to identify genomic features that predispose towards brain metastasis - these biomarkers could be used for early detection and disease monitoring. The cfDNA methylation and fragmentation patterns provide potential epigenetic biomarkers for detecting cancer. These patterns are specific to cell/tissue origin and cancer types. DNA methylation refers to a chemical modification of a specific carbon with an added methyl group in the cytosine. Hypomethylation in the gene body and hypermethylation in the promoter region lead to cancer development. We hypothesize that there are specific cfDNA methylation and fragmentation signatures in CSF that reflect the epigenetic states of BMs, and cancer predisposition for brain metastasis. We applied a novel single molecule sequencing approach to study CSF cfDNA methylation of BM from NSCLC. Our cohort consisted of ten patients with NSCLC-BM (samples N=14) and eleven healthy controls (N=11). Briefly, extracted cfDNA was obtained from CSF samples. Multiplexed sequencing libraries were prepared following an optimized protocol, and sequenced on PromethION flow cell for 72hr by Oxford nanopore technologies. Data were processed with the onboard base and methylation calling, followed by our bioinformatic pipelines for cfDNA size and methylation analysis. Distinct methylation patterns were found on significant CpG sites (fdr-corrected p<0.01) between cancer patients and controls, in both gene-body and promoter region. Biological pathway analysis showed enrichment in essential functions involving PI3K, ERBB2, TNF-α signaling (p<0.03), all of which play a role in NSCLC. Enriched mono-nucleosome levels (p = 1.07e-03) and differentiated mono-/tri- nucleosome ratios (p = 1.34e-03) were found in cancer vs. controls. Overall, our results suggest that a combination of cfDNA methylation and fragmentation can detect NSCLC-BM. This study will benefit BM patients with early detection and better prognosis, and extend our understanding in brain metastases in NSCLC. Citation Format: Tianqi (Kiki) Chen, Billy T. Lau, Xiangqi Bai, Melanie Hayden Gephart, Hanlee P. Ji. Identifying cell free DNA methylation signatures in cerebrospinal fluids for the early detection of brain metastasis in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7019.

Cell-free DNA fragmentomics and second malignant neoplasm risk in patients with PTEN hamartoma tumor syndrome

Individuals with PTEN hamartoma tumor syndrome (PHTS) harbor pathogenic germline PTEN variants that confer a significantly increased lifetime risk of various organ-specific cancers including second primary malignant neoplasms (SMNs). Currently, there are no reliable biomarkers that can predict individual-level cancer risk. Despite the highly promising value of cell-free DNA (cfDNA) as a biomarker for underlying sporadic cancers, the utility of cfDNA in individuals with known cancer-associated germline variants and subclinical cancers remains poorly understood. We perform ultra-low-pass whole-genome sequencing (ULP-WGS) of cfDNA from plasma samples from patients with PHTS and cancer as well as those without cancer. Analysis of cfDNA reveals that patients with PHTS and SMNs have distinct cfDNA size distribution, aberrant genome-wide fragmentation, and differential fragment end motif frequencies. Our work provides evidence that cfDNA profiles may be used as a marker for SMN risk in patients with PHTS.

Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis

The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n= 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n= 220). cfDNA detection correlates with a shorter overall (p= 0.0086) and recurrence-free (p= 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n= 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

A pilot study on salivary HPV DNA detection to monitor active disease from patients with recurrent respiratory papillomatosis

PurposeRecurrent respiratory papillomatosis (RRP) is a human papillomavirus (HPV)-related disease affecting the upper airway and saliva could be an important non-invasive sampling source for viral screening and clinical monitoring. We investigated whether HPV DNA could be detected in saliva (cellular pellets and supernatant) from RRP patients and influence on clinical manifestation of the disease. Materials and methodsIn this pilot study, saliva samples from 14 RRP patients were obtained in preoperative condition (n = 7) and in disease-free interval (DFI; n = 7). Healthy donors (n = 14) were also included. HPV DNA was investigated by polymerase chain reaction (PCR)-based assays. ResultsFrom cellular pellets, HPV-positive saliva was only detected from preoperative collections (5/7; 71.4 %) and showed a mean cycle threshold (Ct) value of 24.33 (±1.25), whereas all patients in DFI were HPV-negative (Ct ≥ 32.16), revealing significant difference between these two clinical moments (p = 0.021). Patients in DFI and healthy donors showed similar Ct values. From saliva supernatant, detectable HPV cell-free DNA (cfDNA) occurred in 42.9 % (3/7) and 57.1 % (4/7) of preoperative collections using the commercial cfDNA kits from Norgen and Qiagen, respectively. Salivary cfDNA size distribution obtained by TapeStation analysis showed a predominant size range of 150 to 400 bp in both patients and healthy controls, corresponding to mononucleosomal and dinucleosomal fragments. ConclusionsIn conclusion, HPV DNA screening in saliva (both cellular pellets and cfDNA) may have clinical utility to monitor active disease of RRP patients.

Improving the accuracy of noninvasive prenatal testing through size-selection between fetal and maternal cfDNA.

In general, fetal cfDNA is shorter than maternal cfDNA, and accuracy of noninvasive prenatal testing (NIPT) results can be improved by selecting shorter cfDNA fragments to enrich fetal-derived cfDNA. This study investigated potential improvements in the accuracy of NIPT by performing classification and analysis based on differences in cfDNA size. We performed paired-end sequencing to identify size ranges of fetal and maternal cfDNA from 62,374 pregnant women. We then developed a size-selection method to isolate and analyze both fetal and maternal cfDNA, defining fetal-derived cfDNA as less than 150 bp and maternal-derived cfDNA as greater than 180 bp. By implementing size-selection method, the accuracy of NIPT was improved, resulting in an increase in the overall positive predictive value for all aneuploidies from 89.57% to 97.1%. This was achieved by enriching both fetal and maternal-derived cfDNA, which increased fetal DNA fraction while the number of false positives for all aneuploidies was reduced by more than 70%. We identified the differences in read length between fetal and maternal-derived cfDNA, and selectively enriched both shorter and longer cfDNA fragments for subsequent analysis. Our approach can increase the detection accuracy of NIPT for detecting fetal aneuploidies and reduce the number of false positives caused by maternal chromosomal abnormalities.

Size and Concentration of Cell-Free DNA Measured Directly from Blood Plasma, without Prior DNA Extraction.

Cell-free DNA in human blood plasma (cfDNA) is now widely used and studied as a biomarker for several physiological and pathological situations. In addition to genetic and epigenetic alterations that provide information about the presence and the nature of non-constitutive DNA in the body, cfDNA concentration and size distribution may potentially be independent biomarkers suitable for monitoring at-risk patients and therapy efficacy. Here, we describe a simple, in-line, method, which measures cfDNA concentration and size distribution from only a few microliters of plasma without the need to extract and/or concentrate the DNA prior to the analysis. This method is based on a dual hydrodynamic and electrokinetic actuation, adapted for samples containing salts and proteins such as biological fluids. The method provides analytical performances equivalent to those obtained after purification and concentration of cfDNA, with a precision of ∼1% for size features and of 10-20% for the concentrations of the different size fractions. We show that concentration and size distribution of cfDNA analyzed from plasma can differentiate advanced lung cancer patients from healthy controls. This simple and cost-effective method should facilitate further investigations into the potential clinical usefulness of cfDNA size profiling.

17th International Conference on Malignant Lymphoma, Palazzo dei Congressi, Lugano, Switzerland, 13 - 17 June, 2023.

Introduction: Circulating tumor DNA (ctDNA) has been proven to be a promising tumor-specific biomarker in tumors, but its clinical utility in risk stratification and early prediction of relapse for peripheral T cell lymphoma (PTCL) has not been well explored. Methods: Using a lymphoma-specific sequencing panel, we assessed the prognostic and predictive utilities of ctDNA measurements before and after first-line therapy in 41 PTCL patients. Results: For the 41 patients, we obtained a total of 36 primary tumor specimens, 41 pretreatment blood samples and 21 serial blood samples before and after first-line therapy. By the last visit in March 2023, the median follow-up duration was 10.0 (range, 2.5–18.8) months. The clinical characteristics of the 41 patients were shown in Figure 1A. All patients received CHOP-like regimen. The top 30 somatic mutations of tissues were shown in Figure 1B. Pretreatment ctDNA (Pre-ctDNA) achieved an overall sensitivity of 81.3% (159/196) in detecting variants verified in tumor, indicating that ctDNA is a reliable source for PTCL genotyping. In addition, ctDNA allowed for the identification of additional 98 somatic mutations that were undetectable in tumor gDNA, which demonstrated that ctDNA could overcome tumor spatial heterogeneity (Figure 1C). Pre-ctDNA burden was significantly associated with clinical characteristics, including extranodal involvement (P < 0.001), lactate dehydrogenase (LDH) levels (P < 0.001), age (P = 0.047), B symptoms (P = 0.038), stage (P = 0.008) and international prognosis index (IPI) score (P < 0.001) (Figure 1D). The cell-free (cfDNA) fragments profoundly reflects both genomic and chromatin characteristics. Our results suggested that all samples had a more prominent mono-nucleosomal fragments abundance (167 bp), whereas the samples of angioimmunoblastic T-cell lymphom (AITL) and the samples with high IPI scores or non-complete response (CR) in the mid-stage of treatment had a more prominent shift towards shorter cfDNA size (Figure 1E). Similarly, when we analyzed the response to treatment, significant decline in ctDNA levels was observed at end of treatment (EOT) in patients with CR compared with those who did not achieved CR. The 4 patients with CR and EOT ctDNA negative achieved continuous CR until now (Figure 1F). Furthermore, high pre-ctDNA levels presented unfavourable PFS (P = 0.002) and OS (P = 0.020) (Figure 1G). Multivariate cox regression analysis showed that high pre-ctDNA burden (P = 0.029) and TP53 mutation (P = 0.005) (Figure 1H). Subgroup analysis showed that patients without these 2 risk factors (Type 1) had longer PFS than the other patients with more than 0 risk factor (Type 2) (P < 0.001) (Figure 1I). Keywords: Aggressive T-cell non-Hodgkin lymphoma, Diagnostic and Prognostic Biomarkers No conflicts of interests pertinent to the abstract.

Clinical relevance of cell-free DNA quantification and qualification during the first month after lung transplantation.

Many studies have reported the relevance of donor-derived cfDNA (dd-cfDNA) after lung transplantation (LTx) to diagnose and monitor acute rejection (AR) or chronic rejection or infection (INF). However, the analysis of cfDNA fragment size has not been studied. The aim of this study was to determine the clinical relevance of dd-cfDNA and cfDNA size profiles in events (AR and INF) during the first month after LTx. This prospective, single-center study includes 62 LTx recipients at the Marseille Nord Hospital, France. Total cfDNA quantification was performed by fluorimetry and digital PCR, dd-cfDNA by NGS (AlloSeq cfDNA-CareDX®), and the size profile by BIABooster (Adelis®). A bronchoalveolar lavage and transbronchial biopsies at D30 established the following groups: not-injured and injured graft (AR, INF, or AR+INF). Quantification of total cfDNA was not correlated with the patient's status at D30. The percentage of dd-cfDNA was significantly higher for injured graft patients at D30 (p=0.0004). A threshold of 1.72% of dd-cfDNA correctly classified the not-injured graft patients (negative predictive value of 91.4%). Among recipients with dd-cfDNA >1.72%, the quantification of small sizes (80-120bp) >3.70% identified the INF with high performance (specificity and positive predictive value of 100%). With the aim of considering cfDNA as a polyvalent non-invasive biomarker in transplantation, an algorithm combining the quantification of dd-cfDNA and small sizes of DNA may significantly classify the different types of allograft injuries.

Cell-Free DNA Fragmentation Patterns in a Cancer Cell Line.

Unique bits of genetic, biological and pathological information occur in differently sized cell-free DNA (cfDNA) populations. This is a significant discovery, but much of the phenomenon remains to be explored. We investigated cfDNA fragmentation patterns in cultured human bone cancer (143B) cells using increasingly sensitive electrophoresis assays, including four automated microfluidic capillary electrophoresis assays from Agilent, i.e., DNA 1000, High Sensitivity DNA, dsDNA 915 and dsDNA 930, and an optimized manual agarose gel electrophoresis protocol. This comparison showed that (i) as the sensitivity and resolution of the sizing methods increase incrementally, additional nucleosomal multiples are revealed (hepta-nucleosomes were detectable with manual agarose gel electrophoresis), while the estimated size range of high molecular weight (HMW) cfDNA fragments narrow correspondingly; (ii) the cfDNA laddering pattern extends well beyond the 1–3 nucleosomal multiples detected by commonly used methods; and (iii) the modal size of HMW cfDNA populations is exaggerated due to the limited resolving power of electrophoresis, and instead consists of several poly-nucleosomal subpopulations that continue the series of DNA laddering. Furthermore, the most sensitive automated assay used in this study (Agilent dsDNA 930) revealed an exponential decay in the relative contribution of increasingly longer cfDNA populations. This power-law distribution suggests the involvement of a stochastic inter-nucleosomal DNA cleavage process, wherein shorter populations accumulate rapidly as they are fed by the degradation of all larger populations. This may explain why similar size profiles have historically been reported for cfDNA populations originating from different processes, such as apoptosis, necrosis, accidental cell lysis and purported active release. These results not only demonstrate the diversity of size profiles generated by different methods, but also highlight the importance of caution when drawing conclusions on the mechanisms that generate different cfDNA size populations, especially when only a single method is used for sizing.

A fetal fraction enrichment method reduces false negatives and increases test success rate of fetal chromosome aneuploidy detection in early pregnancy loss

ObjectiveWe and others have previously demonstrated that the size-selection enrichment method could remarkably improve fetal fraction (FF) in the early gestational age (GA, 12–13 weeks), suggesting that 9 or 10 weeks should not be used as a threshold for GA in size-selection noninvasive prenatal screening (NIPS). Here, we assessed whether this method was reliable for detecting fetal chromosomal aneuploidy at the earliest GA (6–8 weeks).MethodsSize-selection NIPS for fetal chromosomal aneuploidy was applied to 208 pregnancy plasma samples (102 male and 106 female fetuses), while the 169 pregnancy samples with male fetuses also underwent standard NIPS. Multivariable linear regression models were used to evaluate the association between fold-change of FF and experimental factors.ResultsThe sensitivity of the cell-free DNA (cfDNA) test in detecting aneuploidy was 100% when screened with FF enrichment, whereas the sensitivity of the same patients was only 62.5% (5/8) without FF enrichment. In the 102 pregnancy samples with male fetuses, FF increased from 6.1% to 15.7%, and the median increase in FF was 2.8-fold with enrichment. Moreover, there was a trend toward an increasing success rate of the cfDNA test from 6 to 13 weeks of gestation, especially when the test success rate reached 100% after 7 weeks with FF enrichment. Multivariate linear regression analysis demonstrated that a lower initial FF, shorter cfDNA size, increased body mass index (BMI), and later GA were all independent predictors of a higher fold-change of FF. Compared with ≤ 120 bp cfDNA fragments, the mean fold-change of FF differences was 0.820 for 121–125 bp, 0.229 for 126–130 bp, − 0.154 for 131–135 bp, − 0.525 for 136–140 bp and − 0.934 for > 140 bp (Ptrend < 0.0001), suggesting that fold-change of FF significantly decreased with cfDNA fragments > 125 bp. These results were statistically significant after adjusting for confounding factors in the models for fold-change of FF.ConclusionsThe FF enrichment method is a reasonable strategy to detect fetal chromosomal aneuploidy in early pregnancy loss with reduced false negatives and increased test success rate after 7 weeks of GA and should be recommended for patients with early pregnancy loss.

Abstract 6371: Deep learning algorithm for multi-cancer detection and classification using cf-WGS

Abstract Purpose: Several cell-free DNA (cf-DNA) features, such as genome-wide coverage, fragment size, and fragment end motif frequency, have shown their potentials for cancer detection. In this study, we developed two independent models, GC (gross chromatin), and FEMS (fragment end motif frequency and size). Each model uses images generated from genome-wide normalized sequencing coverage and cf-DNA fragment end motif frequencies according to the different cf-DNA size profiles. Then we integrated them into a single ensemble model to improve cancer detection and multi-cancer type classification accuracy. Methods: Low depth cf-WGS data was generated from 1,396 patients (stage I: 14.9%, stage II: 35.6%, stage III: 24.9%, stage IV: 24.2%, unknown: 0.4%) with breast (n=702), liver (n=213), esophageal (n=155), ovarian (n=151), pancreatic (n=85), lung (n=53), head and neck (n=16), biliary tract (n=15), and colon cancer (n=6) and 417 healthy individuals. Samples were randomly split into training, validation, and test set stratifying cancer type and stages. Cancer types with a small number of samples (&amp;lt;20) were excluded for multi-cancer type classification. Each model was trained using a convolutional neural network, then integrated into a single ensemble model by averaging the predicted probabilities calculated from each model. Results: For cancer detection, the ensemble model achieved sensitivities of 85.2% [95% confidence interval (CI): 71.8% to 94.5%], 74.9% (CI: 68.0% to 88.0%), 73.2% (CI: 66.7% to 85.9%) at a specificity of 95%, 98% and 99% and the AUC value of 0.97(CI: 0.95-0.99) in the test dataset. By the cancer stages, sensitivity was 62.8% (CI: 48.8% to 83.7%) in stage I, 66.3% (CI: 57.7% to 82.7%) in stage II, 85.9% (CI: 77.5% to 94.4%) in stage III, and 76.1% (CI: 63.4% to 87.3%) in stage IV at 99% specificity. For multi-cancer classification, the overall accuracy of 85.1% (CI: 80.4% to 89.3%) was achieved including 6 cancer types. Conclusions: Highly sensitive and accurate deep learning model for cancer detection and multi-cancer classification was generated by combining different types of cf-DNA features. This result provides the opportunity for general population multi-cancer screening using various cf-DNA features. Citation Format: Tae-Rim Lee, Jin Mo Ahn, Joo Hyuk Sohn, Sook Ryun Park, Min Hwan Kim, Gun Min Kim, Ki-Byung Song, Eunsung Jun, Dongryul Oh, Jeong-Won Lee, Joseph J Noh, Young Sik Park, Sun-Young Kong, Sang Myung Woo, Bo Hyun Kim, Eui Kyu Chie, Hyun-Cheol Kang, Youn Jin Choi, Ki-Won Song, Jeong-Sik Byeon, Junnam Lee, Dasom Kim, Chang-Seok Ki, Eunhae Cho. Deep learning algorithm for multi-cancer detection and classification using cf-WGS [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6371.

Abstract 1220: Accurately genotyping HLA and KIR alleles using cfDNA assay and k-mer based algorithm for immunotherapy

Abstract Background: HLA and KIR genotypes show great promise as emerging biomarkers for immune checkpoint inhibitors (ICIs) and understanding patient prognosis. Multiple studies have shown that HLA-I heterozygosity and high sequence divergence across alleles positively correlates with response to ICIs. However the high degree of polymorphism and allele sequence similarities in HLA and KIR present a challenge to accurate allele calling. To address these difficulties we developed kmerizer, a novel allele caller optimized for short fragments, such as reads from a cfDNA assay. Methods: We tested kmerizer on MHC class1 and class2 genes, and on KIR genes, on both simulated datasets and real samples (cell lines and plasma samples). To assess the capability of the algorithm to distinguish highly homologous allele pairs, we simulated cfDNA-like fragments with errors on randomly selected allele pairs, and on allele pairs with a high level of homology. Twelve plasma samples and 19 reference cell lines fragmented to cfDNA size were analyzed using a NGS cfDNA assay. For plasma samples, paired buffy coats were sent to an external vendor for HLA typing using multiplex PCR-based amplicon and sequenced by 300bp paired-end reads. Results: Of the 19 cell lines and 12 plasma samples for HLA typing (A, B, C, and DQB1 loci), kmerizer delivered 100% sensitivity with 98% specificity. On the simulated dataset, kmerizer achieved 99% sensitivity and specificity on all the MHC class1 and class 2 loci, and 90% sensitivity and specificity on all KIR loci, for both homozygous and heterozygous pairs. The novel allele caller kmerizer also demonstrated a lighter footprint on computational resource need: one deep-sequencing plasma sample on average can be processed in less than 2 minutes which is about 15 times faster than the most commonly used HLA typing tool HISAT21, which does not support KIR typing. Conclusions: As utilization of ICIs increases, the use of genetic and genomic information to accurately identify patients more likely to respond to ICIs will be critical. kmerizer is a fast and highly sensitive and specific allele caller, and it can effectively call alleles on both HLA and KIR.

Early detection of cancer using cell-free DNA (cfDNA) size analysis on a multiplexed amplicon-based next-generation sequencing (NGS) platform.

3041 Background: Tumor-derived cfDNA fragments are observed to be shorter in length than normal cfDNA. This size (length) difference can be analyzed as a tumor-specific signal. Whole genome or probe hybridization-based NGS methods can capture cfDNA fragments of native sizes. However, amplicon-based NGS assays are not directly amenable to cfDNA size analysis due to predetermination of amplicon sizes by design. Here we present a method to extract relative distribution of cfDNA fragment lengths from a targeted amplicon-based assay and show its utility in cancer detection. Methods: The LiquidHALLMARK cfDNA assay is an amplicon-based NGS test for the sensitive detection of genomic alterations in 80 genes. Although panel design is optimized for cfDNA with average amplicon length of ̃150 bp, the consecutive tiling design of amplicons for genes with contiguously targeted regions, e.g. BRCA permits the formation of longer amplicons (&gt; 150 bp) from physically subsequent primer pairs, provided longer template cfDNA molecules are present. Cancer samples (n = 281), clinically tested by LiquidHALLMARK during Sep 2020-Sep 2021, and healthy samples (n = 28) were included for analysis. For each sample, fragment lengths were inferred from sequencing alignment files, and binned into “short” (0-150 bp) and “long” (151-500 bp) groups. A relative “size ratio” of the total number of short vs. long fragments per sample was calculated, and examined with clinical features, plasma cfDNA concentration (cfDNA/ml) and highest mutation allele frequency (AF%), in a model to predict cancer. Results: Calculated size ratios (relative abundance of short fragments) were higher in cancer than normal samples (median 47.6 vs. 31.2, p &lt; 0.001). Cholangiocarcinoma and colorectal cancer samples had the highest size ratios (medians: 62.9 and 60.9, respectively) in agreement with a genome-wide NGS study that profiled cfDNA sizes. Size ratios were higher in metastatic (n = 143) compared to early stage (n = 30) lung cancers (p = 0.0039), indicating a stage-dependent accumulation of shorter cfDNA fragments. Size ratio was correlated with cfDNA/ml ( r= 0.63, p &lt; 0.01) and AF% ( r= 0.42, p &lt; 0.01). In 20-fold cross-validation of a logistic regression model trained to predict cancer, average area under curve (AUC) was 0.82 using size ratio, 0.86 using cfDNA/ml, and increased to 0.95 with the two features combined. Conclusions: Our analysis shows that it is feasible to derive meaningful cfDNA fragment size information from amplicon-based NGS data. Importantly, relative fragment size distributions observed in cancer and healthy plasma samples by this method are concordant with alternate target capture methods. Fragment size ratios derived from relatively small, targeted amplicon panels are a novel feature that, combined with other molecular and clinical features, can enhance non-invasive methods of cancer detection.

Circulating Cell-Free DNA Assessment in Biofluids from Children with Neuroblastoma Demonstrates Feasibility and Potential for Minimally Invasive Molecular Diagnostics.

Simple SummaryThe invasive nature of surgical biopsies prevents their sequential application to monitor disease. Single biopsies fail to reflect cancer dynamics, intratumor heterogeneity, and drug sensitivities that change over time. Detection and characterization of cell-free circulating tumor DNA in biofluids from patients with solid tumors may better support disease monitoring and provide advanced molecular information for clinical decision-making toward personalized medicine. Here, we investigated the cell-free DNA characteristics in blood, bone marrow, cerebrospinal fluid, and urine provided from 84 infants and children with low-, intermediate-, or high-risk neuroblastoma. We report characteristic size distribution and concentration patterns for each biofluid to provide information to support the development of successful liquid biopsy biobanking strategies. We investigate potential correlations between disease activity and cfDNA concentration and provide strong evidence that markers specific for neuroblastoma can be detected in very small blood volumes from infants.Liquid biopsy strategies in pediatric patients are challenging due to low body weight. This study investigated cfDNA size distribution and concentration in blood, bone marrow, cerebrospinal fluid, and urine from 84 patients with neuroblastoma classified as low (n = 28), intermediate (n = 6), or high risk (n = 50) to provide key data for liquid biopsy biobanking strategies. The average volume of blood and bone marrow plasma provided ranged between 1 and 2 mL. Analysis of 637 DNA electropherograms obtained by Agilent TapeStation measurement revealed five different major profiles and characteristic DNA size distribution patterns for each of the biofluids. The proportion of samples containing primarily cfDNA was, at 85.5%, the highest for blood plasma. The median cfDNA concentration amounted to 6.28 ng/mL (blood plasma), 58.2 ng/mL (bone marrow plasma), 0.08 ng/mL (cerebrospinal fluid), and 0.49 ng/mL (urine) in samples. Meta-analysis of the dataset demonstrated that multiple cfDNA-based assays employing the same biofluid sample optimally require sampling volumes of 1 mL for blood and bone marrow plasma, 2 mL for cerebrospinal fluid, and as large as possible for urine samples. A favorable response to treatment was associated with a rapid decrease in blood-based cfDNA concentration in patients with high-risk neuroblastoma. Blood-based cfDNA concentration was not sufficient as a single parameter to indicate high-risk disease recurrence. We provide proof of concept that monitoring neuroblastoma-specific markers in very small blood volumes from infants is feasible.

Cell-free DNA is abundant in ascites and represents a liquid biopsy of ovarian cancer

ObjectiveMalignant ascites is a common clinical feature of ovarian cancer and represents a readily accessible sample of tumour cells and tumour DNA. This study aimed to characterise the cell-free DNA (cfDNA) in ascites in terms of its size profile, stability and cell-free tumour DNA (cftDNA) content. MethodsCell spheroids, loose cells and cell-free fluid was collected from ascites from 18 patients with ovarian cancer. cfDNA was isolated and assessed for size by electrophoresis, concentration by fluorometry,cftDNA content by methylation specific qPCR of HOXA9 and IFFO1 promoter regions and by targeted sequencing. Stability was assessed after ascites fluid was stored at 4 °C for 24 and 72 h before fractionating. ResultsThe concentration of cfDNA in ascites ranged from 6.6 to 300 ng/mL. cfDNA size distribution resembled blood plasma-derived cfDNA, with major peaks corresponding to mono- and di-nucleosome DNA fragments. High molecular weight cfDNA was observed in 7 of 18 patients and appeared to be associated with extracellular vesicles. IFFO1 and HOXA9 methylation was proportionately higher in cfDNA than spheroid- and loose-cell fractions and was not observed in healthy primary cells. Variant allele frequency was highest in cfDNA compared to single cells and spheroids from ascites. Though cancer cell numbers in ascites declined to near zero in recurrent ascites from one patient undertaking chemotherapy, cftDNA could still be sampled. cfDNA size, concentration and tumour content was stable over 72 h. ConclusioncfDNA in ovarian cancer ascites demonstrates inter-patient variability, yet is consistently a rich source of cftDNA, which is a stable substrate. This supports the wider clinical use of ascites in the molecular analysis of ovarian cancer.

Abstract LB059: Dual methylation and mutation analysis from a single input of plasma cfDNA without sample splitting

Abstract Genomic and epigenetic changes are known to be the underlying mechanism of cancer development. Assessing the genomic (mutation) and epigenetic (methylation) changes has become increasingly important for cancer detection and treatment selection, especially in the field of cfDNA-based liquid biopsy. Targeted Next-Generation Sequencing (NGS) enables in-depth analysis of specific genomic regions that is essential for the clinical application of liquid biopsy. However, current targeted NGS assays are complicated, lengthy, and inefficient. Two major hurdles of existing targeted NGS methods make them impractical for the clinical setting. First, there is no comprehensive, end to end, kit solution available for targeted methylation sequencing (TMS) from sample to sequencing ready library. Second, the low yield of cfDNA from clinical blood samples presents a major challenge for multi-modal analyses on one sample. Thus, an assay that is capable of both methylation and mutation analysis would be optimal for clinical research and future diagnostic assays.Here, we report the performance of Point-n-Seq, a kit solution that can provide in-depth DNA analysis with highly flexible and customizable focused panels to enable both methylation and mutation analysis without sample splitting. Custom panels of 10 to 1000s of markers can be designed with &amp;gt;99% first-pass success rate. We conducted both performance validation and multi-center, multi-operator, reproducibility studies. With spike-in titration of cancer cell-line gDNA with known mutation and methylation profile, we achieved a reliable detection level down to 0.003% of tumor DNA with a linear relationship between the measured and expected fractions.In a pilot study, we designed a colorectal cancer (CRC) TMS panel covering 560 methylation markers and a mutation panel with &amp;gt;350 hotspot mutations in 22 genes. From only 1ml of plasma from late stage CRC patients, we detected cancer-specific methylation signals in all samples tested, and hotspot mutations with clinical implications. Next, a tumor-informed mutation panel covering approximately 100 personalized mutations for each patient was compared to the tumor-independent CRC methylation panel to analyze 23 stage I and II CRC patient plasma samples. The initial results showed that tumor-independent TMS assay achieved a comparable or superior limit of detection compared to the personalized tumor-informed approach. Moreover, to further improve assay sensitivity, metrics for cfDNA size can be integrated into the analysis of the same workflow without sample splitting. The Point-n-Seq kit, with a highly streamlined workflow and dual methylation and mutation analysis, provides a highly sensitive and robust non-invasive method for cancer detection, monitoring and treatment guidance. Citation Format: Grace Q. Zhao, Yun Bao, Heng Wang, Vanita S. Natu, Jayashree Joshi, Yingmin Wang, Elena Arzumanyan, Wanping Wang, Jianmin Wang, John Coller, Shengrong Lin. Dual methylation and mutation analysis from a single input of plasma cfDNA without sample splitting [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB059.

A dual target sequencing solution to assess genomic and epigenomic alterations in cell-free DNA with no sample splitting.

3043 Background: Assessing the genomic and epigenomic changes on plasma cell-free DNA (cfDNA) using next-generation sequencing (NGS) has become increasingly important for cancer detection and treatment selection guidance. However, two major hurdles of existing targeted NGS methods make them impractical for the clinical setting. First, there is no comprehensive, end to end, kit solution available for targeted methylation sequencing (TMS), let alone one that analyzes both mutation and methylation information in one assay. Second, the low yield of cfDNA from clinical blood samples presents a major challenge for conducting multi-omic analysis. Thus, an assay that is capable of both genomic and epigenomic analysis would be advantageous for clinical research and future diagnostic assays. Methods: Here, we report the performance of Point-n-SeqTM dual analysis, a kit solution that can provide in-depth DNA analysis with highly flexible and customizable focused panels to enable both genomic and epigenomic analysis without sample splitting. With custom panels of tens to thousands of markers designed with &gt; 99% first-pass success rate, we conducted both performance validation and multi-center, multi-operator, reproducibility studies. Using spike-in titration of cancer cell-line gDNA with known mutation and methylation profiles, Point-n-Seq assay achieved a reliable detection level down to 0.003% of tumor DNA with a linear relationship between the measured and expected fractions. Benchmarked with conventional targeted sequencing and methylation sequencing, Point-n-Seq solution also demonstrated improved performance, speed and shortened hands-on time. Results: In a pilot clinical study, a colorectal cancer (CRC) TMS panel covering 560 methylation markers and a mutation panel with &gt; 350 hotspot mutations in 22 genes were used in the dual assay. Using 1ml of plasma from late-stage CRC patients, cancer-specific methylation signals were detected in all samples tested, and oncogenic mutations. In an early-stage cohort (33 stage I/II CRC patient ), comparison of the analysis between tumor-informed, personalized-mutation panels (̃100 private SNVs) for each patient and the tumor-independent CRC methylation panels were conducted. The initial results showed that tumor-independent TMS assay achieved a comparable detection compared to the personalized tumor-informed approach. Moreover, cfDNA size information (fragmentome) is also integrated into the analysis of the same Point-n-Seq workflow to improve the assay sensitivity. Conclusions: Point-n-Seq dual analysis is poised to advance both research and clinical applications of early cancer detection, minimal residual disease (MRD), and monitoring.

Serial profiling of cell-free DNA and nucleosome histone modifications in cell cultures

Recent advances in basic research have unveiled several strategies for improving the sensitivity and specificity of cell-free DNA (cfDNA) based assays, which is a prerequisite for broadening its clinical use. Included among these strategies is leveraging knowledge of both the biogenesis and physico-chemical properties of cfDNA towards the identification of better disease-defining features and optimization of methods. While good progress has been made on this front, much of cfDNA biology remains uncharted. Here, we correlated serial measurements of cfDNA size, concentration and nucleosome histone modifications with various cellular parameters, including cell growth rate, viability, apoptosis, necrosis, and cell cycle phase in three different cell lines. Collectively, the picture emerged that temporal changes in cfDNA levels are rather irregular and not the result of constitutive release from live cells. Instead, changes in cfDNA levels correlated with intermittent cell death events, wherein apoptosis contributed more to cfDNA release in non-cancer cells and necrosis more in cancer cells. Interestingly, the presence of a ~ 3 kbp cfDNA population, which is often deemed to originate from accidental cell lysis or active release, was found to originate from necrosis. High-resolution analysis of this cfDNA population revealed an underlying DNA laddering pattern consisting of several oligo-nucleosomes, identical to those generated by apoptosis. This suggests that necrosis may contribute significantly to the pool of mono-nucleosomal cfDNA fragments that are generally interrogated for cancer mutational profiling. Furthermore, since active steps are often taken to exclude longer oligo-nucleosomes from clinical biospecimens and subsequent assays this raises the question of whether important pathological information is lost.