cfDNA Fragments Research Articles

P-737 Progress in non-invasive embryo assessment with cell-free nucleic acids in blastocoel fluid

Abstract Study question Can cell-free nucleic acids (cfDNA) from blastocoel fluid (BF) after a trophectoderm (TE) biopsy be used as a non-invasive sample type to assess embryos? Summary answer Both BF and spent media carry comparable, highly fragmented cfDNA and cell-free RNA (cfRNA) which may reveal more about the quality of the embryo. What is known already Preimplantation genetic testing for aneuploidy (PGT-A) is commonly used by IVF clinics to screen embryos for any chromosomal abnormalities during the IVF process. Noninvasive preimplantation genetic testing (ni-PGT) is an emerging category of tools within the field of assisted reproductive technology. Currently, niPGT products have been developed for embryo aneuploidy detection using cfDNA released by the embryo into the spent media. Embryo spent media (ESM) carries cfDNA, which has the potential to be applied to evaluate the quality of the embryo. Previous studies have demonstrated that cfDNA in ESM is highly fragmented to the nucleosome level. Study design, size, duration The quality and quantity of cell free nucleic acid from forty BF-conditioned media (BFCM) samples were analyzed in this study. Embgenix™ Analysis Software was used to analyze and interpret sequencing data. For each sample, the concentration and fragmentation of cfDNA were examined and compared using generalized linear mixed models. To assess RNA quality at a picogram level, reverse-transcribed and amplified cDNA was used to represent the quality of cfRNA in BFCM. Participants/materials, setting, methods Embryos were washed and placed in individual biopsy media droplets for TE biopsy. After biopsy, blastocysts were collapsed, releasing BF into the droplet. The entire droplet was collected as BFCM. The Embgenix ESM Screen Kit was used to prepare sequencing libraries. The SMART-Seq® Single Cell Kit was used to evaluate the RNA quality. The BFCM cfDNA results were also compared to spent media profile that had already been obtained from a different cohort of embryos. Main results and the role of chance Amounts of cfDNA fragmentation detected in BFCM samples was comparable to ESM. Whole-genome amplification (WGA) yields correlated to the amount of cfDNA input but not the degree of cfDNA fragmentation. Informative sequencing reads and computed copy number variations (CNV) plot noise, as evaluated by distribution of log2 ratio spread (DLRS), also showed correlation and stable performance down to ∼2 pg of cfDNA input. We extracted detectable cfRNA from BFCM and created cDNA for RNA quality analysis. Our model demonstrates a significant correlation between cDNA length and RNA quality metrics, with a low DV200 of cfRNA from BFCM samples. The quantity and quality of cfDNA released into spent culture media by a developing embryo are comparable to the cfDNA released into BFCM upon TE biopsy, indicating that BFCM has potential as a noninvasive method for assessing the ploidy status of embryos. WGA yield, informative reads, and DLRS of BFCM samples were likewise comparable to data previously acquired using spent media samples. However, the severely fragmented cfRNA in these samples illustrate the inherent instability of RNA and the difficulty of utilizing RNA analysis to determine embryo health. Assays compatible with small RNA or microRNA (miRNA) are more appropriate for RNA-seq of BFCM. Limitations, reasons for caution Different clinics use varying methods for embryo culture and biopsy; the data reported here is from a single research center. The characteristic of samples may vary between clinics. Our assay estimates RNA quality using amplified cDNA; nonetheless, discrepancies between fragmented RNA and amplified cDNA may exist. Wider implications of the findings In PGT-A, BFCM samples are routinely discarded. Our findings imply BFCM samples contain considerable levels of cell-free nucleic acids which could also be used to screen embryo quality. BFCM samples, therefore, could be analyzed in conjunction with PGT-A to select and/or rank embryos for implantation. Trial registration number Not applicable

Fragmentomic analysis of circulating tumor DNA-targeted cancer panels

The isolation of cell-free DNA (cfDNA) from the bloodstream can be used to detect and analyze somatic alterations in circulating tumor DNA (ctDNA), and multiple cfDNA-targeted sequencing panels are now commercially available for Food and Drug Administration (FDA)-approved biomarker indications to guide treatment. More recently, cfDNA fragmentation patterns have emerged as a tool to infer epigenomic and transcriptomic information. However, most of these analyses used whole-genome sequencing, which is insufficient to identify FDA-approved biomarker indications in a cost-effective manner. We used machine learning models of fragmentation patterns at the first coding exon in standard targeted cancer gene cfDNA sequencing panels to distinguish between cancer and non-cancer patients, as well as the specific tumor type and subtype. We assessed this approach in two independent cohorts: a published cohort from GRAIL (breast, lung, and prostate cancers, non-cancer, n = 198) and an institutional cohort from the University of Wisconsin (UW; breast, lung, prostate, bladder cancers, n= 320). Each cohort was split 70%/30% into training and validation sets. In the UW cohort, training cross-validated accuracy was 82.1%, and accuracy in the independent validation cohort was 86.6% despite a median ctDNA fraction of only 0.06. In the GRAIL cohort, to assess how this approach performs in very low ctDNA fractions, training and independent validation were split based on ctDNA fraction. Training cross-validated accuracy was 80.6%, and accuracy in the independent validation cohort was 76.3%. In the validation cohort where the ctDNA fractions were all <0.05 and as low as 0.0003, the cancer versus non-cancer area under the curve was 0.99. To our knowledge, this is the first study to demonstrate that sequencing from targeted cfDNA panels can be utilized to analyze fragmentation patterns to classify cancer types, dramatically expanding the potential capabilities of existing clinically used panels at minimal additional cost.

Graft-Derived Cell-Free DNA Quantification following Liver Transplantation Using Tissue-Specific DNA Methylation and Donor-Specific Genotyping Techniques: An Orthogonal Comparison Study.

Background: Graft-derived cell-free DNA (gdcfDNA) analysis has shown promise as a non-invasive tool for monitoring organ health following solid organ transplantation. A number of gdcfDNA analysis techniques have been described; however, the majority rely on sequencing or prior genotyping to detect donor-recipient mis-matched genetic polymorphisms. Differentially methylated regions of DNA can be used to identify the tissue-of-origin of cell-free DNA (cfDNA) fragments. In this study, we aimed to directly compare the performance of gdcfDNA monitoring using graft-specific DNA methylation analysis and donor-recipient genotyping techniques in a pilot cohort of clinical samples from patients post-liver transplantation. Results: 7 patients were recruited prior to LT, 3 developed early, biopsy-proven TCMR in the first 6 weeks post-LT. gdcfDNA was successfully quantified in all samples using both approaches. There was a high level of technical correlation between results using the two techniques (Spearman testing, rs = 0.87, p < 0.0001). gdcfDNA levels quantified using the genotyping approach were significantly greater across all timepoints in comparison to the tissue-specific DNA methylation-based approach: e.g., day 1 post-LT median 31,350 copies/mL (IQR 6731-64,058) vs. 4133 copies/mL (IQR 1100-8422), respectively. Qualitative trends in gdcfDNA levels for each patient were concordant between the two assays. Acute TCMR was preceded by significant elevations in gdcfDNA as quantified by both techniques. Elevations in gdcfDNA, using both techniques, were suggestive of TCMR in this pilot study with a 6- and 3-day lead-time prior to histological diagnosis in patients 1 and 2. Conclusions: Both the graft-specific methylation and genotyping techniques successfully quantified gdcfDNA in patients post-LT with statistically significant concordance. A direct comparison of these two techniques is not only important from a technical perspective for orthogonal validation, but significantly adds weight to the evidence that gdcfDNA monitoring reflects the underlying biology. Both techniques identified LT recipients who developed acute TCMR, with several days lead-time in comparison to conventional diagnostic workflows. Whilst the two assays performed comparably, gdcfDNA monitoring based on graft-specific DNA methylation patterns in cfDNA offers major practical advantages over the donor-recipient genotyping, and hence enhances the potential to translate this emerging technology into clinical practice.

Pan-cancer detection and tissue-of-origin identification by whole-genome sequencing of plasma cell-free DNA.

3055 Background: Despite notable advances in cancer therapeutics, much of the mortality of human cancers results from late diagnosis. The early detection of cancer remains an unmet need that can benefit the effective treatments and better prognosis. Cell-free DNA (cfDNA) in the circulation provides an emerging diagnostic method for non-invasive cancer screening. The fragmentation signatures of cfDNA originating from different cell types or malignancies display distinct patterns, suggesting the potential as cancer biomarkers. This study aims to investigate the fragmentation profiles of cfDNA in several cancer types, and to develop a new approach for pan-cancer detection and tissue-of-origin identification. Methods: Plasma samples from 739 patients with lung (N=577), colorectal (N=98), breast (N=51) and liver (N=13) cancers, as well as 716 healthy individuals were collected in this study. Cell-free DNA was isolated and used to generate the whole-genome sequencing data. We developed an approach called PatternWGS (Pan-cancer detection and tissue-of-origin identification by whole-genome sequencing) to analyze the DNA fragmentation patterns comprehensively. Fragmentation features integrating cfDNA fragment size distribution, frequency of end motif sequence, and copy number variation were utilized to construct the optimal prediction model. We presented a multi-cancer detection model for distinguishing individuals with and without cancer using Generalized Linear Models (glmnet), and further built a cancer-origin model to predict cancer types using Random Forest algorithm. Training and testing occurred on randomly selected sampling splits of 60% and 40% of the data, respectively. Features selection and model construction were performed by only training cohort, and the test set was solely used for performance evaluation. Results: A larger proportion of shorter cfDNA fragments in cancers was observed. We proposed a fragment score indicating the degree of short fragmentation, and this fragment score was significantly higher in cancers (p&lt;0.001). Several end motifs were identified to be specifically enriched in cancer patients. The multi-cancer detection model reached an area under the curve (AUC) of 0.98, with the sensitivity of 93% at 95% specificity. The sensitivity of detecting lung, colorectal, breast, and liver cancers reached 94.2%, 87%, 100% and 100% respectively, at 95% specificity. The cancer-origin model demonstrated an overall accuracy of 81.7% for the identification of tissue of origin. Conclusions: Our prediction model demonstrated a superior performance for multi-cancer detection and cancer origin prediction, suggesting the potential of plasma cfDNA fragmentation signatures as non-invasive biomarkers for early cancer detection in clinical. The distinct fragmentation patterns in cancer provide new insight to understand the mechanism of tumorigenesis.

Preliminary results from the Female Asian Nonsmoker Screening Study (FANSS).

8510 Background: Lung cancer (LC) is the leading cause of cancer death in Asian Americans and unfortunately the majority are diagnosed at advanced or late stages. In Asia, approximately 60-80% of female LC patients are never smokers. Current screening in the U.S. with low-dose CT (LDCT) Chest scans is offered only to current or former smokers based on the National Lung Screening Trial (NLST). The LC detection rate in NLST was 1.1%. The TALENT study, a LC screening study for high-risk nonsmokers in Taiwan reported a LC detection rate of 2.6% which included invasive adenocarcinoma (adeno), adeno in situ, minimally invasive adeno and adenosquamous carcinoma. Invasive adeno detection rate was 1.52%. We are conducting the ongoing FANSS in the U.S. to screen female Asian nonsmokers with LDCT Chest scans to evaluate the feasibility of a LC screening program in this population. We report preliminary results here. Methods: This is an IRB-approved, prospective, multicenter study (NYU, MGH, UCI). Inclusion criteria are women, age between 40-74 years old (yo), never smoked or smoked &lt;100 cigarettes in one's lifetime and identify as from Asian descent (report ancestry or race from the continent of Asia). Participants (pts) with history of LC or treatment of any cancer &lt;5 years ago are excluded. Following informed consent, eligible pts undergo a shared-decision making discussion prior to obtaining a baseline LDCT Chest scan, read according to Lung-RADS 1.1 with plan for annual LDCT for two additional years. A plasma-based assay to analyze cell-free DNA (cfDNA) fragments for early detection of cancer by Delfi Diagnostics (Baltimore, MD) is sent at the time of each scan. A questionnaire regarding ethnicity, family history and environmental exposures is collected at baseline. Results: From 3/1/21 to 1/15/23, 222 pts signed consent and 201 had a baseline LDCT at NYU. Age range was 40-74 yo and median age of 56.8 yo. 83 (41%) reported a family history of LC. Of 201 pts who completed a baseline LDCT, 87 (43%) were Lung-RADS 1, 101 (50%) were Lung-RADS 2, 6 (3%) were Lung-RADS 3 and 7 (3.5%) were Lung-RADS 4. 5 pts with Lung-RADS 3 and 3 pts with Lung-RADS 4 have solid, subsolid or groundglass nodules &gt;6mm that remain in close follow-up. 3 pts were diagnosed with invasive lung adeno for a LC detection rate of 1.5%; 2 are stage IIB and 1 is stage IIIC. All pts were surgically resected, EGFR mutation positive and are receiving adjuvant osimertinib. Analysis of the cfDNA fragmentation profiles is ongoing. Conclusions: Our data shows that LC screening in Asian female nonsmokers is feasible. Preliminary results demonstrate an invasive adeno detection rate comparable with TALENT and higher than in NLST. Early detection brings new meaning with the recent FDA approval for adjuvant targeted therapy in early stage LC. The expansion of LC screening guidelines to other high-risk populations warrants further attention. FANSS is continuing to accrue at additional U.S. sites this year. Clinical trial information: NCT05164757 .

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.

Prospective evaluation of cell-free DNA fragmentation profiles for lung cancer detection.

e20521 Background: Annual lung cancer screening can save lives, but fewer than 10% of eligible persons participate each year. More widespread screening is hindered by cost, inaccessibility, and uncertainty over individual-level benefit vs risk. Screening rates could be raised by a simple, inexpensive initial blood test, if it were sensitive for cancer detection. The DELFI (DNA evaluation of fragments for early interception) technology uses low-coverage, whole-genome sequencing and machine learning to identify patterns of cell-free DNA (cfDNA) fragmentation associated with cancer. Here we report preliminary cfDNA analysis results from DELFI-L101 (NCT04825834), a prospective, observational, multistate case-control study to train and test DELFI classifiers for lung cancer detection. Methods: Enrollees were ≥50 years old with current or previous smoking histories of ≥20 pack-years and recent or planned chest CT imaging. Medical history was recorded at enrollment, and blood samples were collected for DELFI analysis. Repeated 10-fold cross-validation was used to develop a classifier for lung cancer detection. A split study approach is planned for independent validation of the classifier. Results: At this time, 242 individuals with lung cancer and 652 without cancer have enrolled. Most participants were ≥65 years old, and the proportions of men and women were similar. Lung cancer risk factors were present among both cases and controls. Like the lung cancer screening population, approximately half of lung cancer cases were stage I. Median DELFI scores were higher among individuals with lung cancer than no cancer, overall and across groups stratified by age or body mass index (BMI). Cross-validated area under the receiver operator characteristic curve was 0.81 for lung cancer detection. Clinically meaningful sensitivity to detect lung cancer was attained across all disease stages, with sensitivity increasing stepwise with stage. Conclusions: We developed a classifier based on cfDNA fragmentome patterns analyzed using DELFI that could differentiate between lung cancer cases and controls with cross-validated performance across age groups, BMI categories, and cancer stages. A blood-based DELFI fragmentome test could serve as a low-cost, high-performance blood test with potential to improve lung cancer screening efficiency. Clinical trial information: NCT04825834 .

A characteristic comparison of cell-free DNA isolated from plasma and cerebrospinal fluid in patients with cancer.

e14008 Background: Cell-free DNA (cfDNA) from plasma has proved its power as a liquid biopsy analyte in many cancer types, except cancers from central nervous system (CNS). CfDNA from cerebrospinal fluid (CSF) better recapitulates mutations for primary CNS tumors or cancer brain metastasis. The characteristics of cfDNA from plasma, including concentration range, mutation frequency, length, end motif etc. have been thoroughly studied, while the features of cfDNA from CSF are yet to be investigated. Methods: We retrospectively reviewed records since 2021 from a clinical sequencing center, and selected samples from patients with non-small cell lung cancer. CfDNA from 30 CSF and 85 plasma samples was isolated, followed by NGS library preparation procedures, and enriched with a 680-gene panel. Fragmentation features including cfDNA length distribution and frequency of 6-bp end motif sequences were analyzed after removal of UMI. K-means clustering algorithm was utilized to analyze fragment motifs. Results: The mean concentration of cfDNA isolated from plasma and CSF was 13.46 ng/mL (1.28 – 96.40, 95%) and 26.82 ng/mL (2.80-382.00, 95%) respectively. A larger proportion of longer cfDNA fragments (&gt;200bp) in CSF sample was observed, 37.8% in CSF VS 22.8% in plasma. Several end motifs were identified to be highly enriched in either sample type, and we found that sample types could be separated by K-means clustering from top 10 motifs. Conclusions: CSF is a less complicated solution system than plasma, regarding chemical constitutes. The cfDNA length distribution and motif patters are distinguishable in CSF and plasma. Our analysis demonstrated that the characteristics of cfDNA in CSF are obviously different from cfDNA in plasma, and the underlying mechanism remains to be clarified.

Analysis of cell-free DNA (cfDNA) fragmentomes and prediction scores across distinct molecular subtypes.

e15029 Background: Liquid biopsies have the advantage of being convenient in collecting tumor-derived DNA for clinical use. Genome-wide analysis of cell-free DNA (cfDNA) fragmentomes has emerged as a promising approach to detect lung cancer based on the examination of sequencing features other than actionable mutations. Here we report initial analyses of the DELFI (DNA evaluation of fragments for early interception) technology in patients enrolled in the Dutch Lung Cancer Early Molecular Assessment (LEMA) trial (NCT02894853), a prospective, observational, and multicenter study, to evaluate fragmentation patterns in genotyped blood samples with actionable alterations irrespective of disease stage and histology subtype. Methods: Plasma samples from 576 patients with an established diagnosis of lung cancer but awaiting the start of definitive treatment were processed and examined using low-coverage whole-genome sequencing. A lasso model that incorporated genome-wide fragmentation profiles was trained on an internal Delfi Diagnostics cohort and used to generate patient-specific DELFI scores for participants in LEMA. Results: Enrollees comprised 531 individuals with non-small cell lung cancer, 38 with small-cell lung cancer, and 7 with unknown lung cancer type. Most patients were diagnosed with late-stage disease (28% stage I, 10% stage II, 26% stage III, and 36% stage IV). Current smokers (N = 238; 41%) and former smokers (N = 295, 51%) outnumbered never smokers (N = 43; 8%). Analysis showed a stepwise increase of the DELFI scores from T1 to T4 and N0 to N1-3 disease, associating aberrant fragmentation profiles with the overall tumor burden. Small-cell carcinomas and squamous cell carcinomas presented with higher DELFI scores than adenocarcinomas ( p&lt; 1e-7, generalized linear model). Patients without a smoking history had similar scores to those who had a previous history of smoking. When adjusted for stage, mutation status in ALK, BRAF, EGFR, ERBB2, KRAS, MET, RET, and ROS were not associated with DELFI scores ( p= 0.5, likelihood ratio test). Similarly, PD-L1 staining did not significantly affect DELFI scores when a 1% cutoff was applied to cases with PD-L1 staining data ( p= 0.07, generalized linear model). Conclusions: Our results reveal that DELFI scores increase stepwise with stage and are higher in small-cell and squamous cell carcinomas. The LEMA study reinforces the potential usefulness of genome-wide cfDNA fragmentation profiling as a liquid biopsy approach for identifying patients with lung cancer regardless of smoking status, somatic driver mutation, and PD-L1 expression scores.

Early gastrointestinal tumour detection using cfDNA fragmentomes based on low-pass whole-genome sequencing (lp-WGS).

e15511 Background: As one of the most concerning world public health issue, cancer accounted for 21% of all deaths. Early cancer detection methods help reduce the chance of dying from cancer. The fragmentation patterns of plasma circulating cell-free DNA (cfDNA) in tumor patients and healthy people are different, which reflects aberrant gene-regulation in cancer patients. Measure cfDNA fragmentomics not only identify the biomarkers to detect cancer early, but also contribute to revealing the biological regulatory mechanism of cancer. In this study, a novel method, i.e. multi-fragmentomics early tumor detection method (METD) was developed, which combined multiple cfDNA fragmentation features and effectively predicted early stage cancer patients. Methods: Adapter sequences were removed from raw data which are then aligned to hg19 reference genome. Duplicated reads, low quality reads and reads aligned to sex chromosomes were removed. Fragment length were normalized through z-score and GC content were regressed out from each bin using GBM (Gradient Boosting Machine) regression tree. Using data from 100 healthy samples, the baseline were calculated. Six fragmentation features including FSD (fragment size distribution) that is a ratio of short/long fragment numbers, EM (end motif) which represent the frequency of 5’end 2-6bp sequence patterns, BPM (break-point motifs) that is the frequency of 5’ end break-point sequences, TFAS (transcription factor accessibility score) that is the rank of coverage at transcription factor binding sites, CFS (co-fragmentation score) which calculate the first principle component of the free-C correlation matrix, GES (gene expression score) that measures the predicted gene expression from cfDNA lp-WGS data were calculated for each sample. Then these 6 fragmentation features were fitted in a penalized logistic regression for cancer prediction. Data of each sample was also downsampled to 0.1x, 0.5x, 1x, 3x and 5x to test the minimum amount of data needed for this prediction model. Results: In training data set, 208 samples from gastrointestinal cancer patients and 100 samples from healthy individuals, our method METD detect tumor patients with a AUC of 0.98. The AUC is 0.95 when the training data were downsampled to 0.1x. This method was then tested in a validation data set containing 32 cancer patients and 32 healthy individuals, which showed a specificity of 0.9 and sensitivity of 0.88. Conclusions: In this study, we develop a new method for early cancer detection integrating different fragmentomics features and demonstrated that lp-WGS data even with 0.1x data can be used to distinguish cancer and healthy groups. Studies with larger cohorts is warranted to verify the performance of this method in future.

Liquid biopsy in combination with PET/CT versus PET/CT alone in diagnosis of lung cancer in small nodules.

3072 Background: In the National Lung Screening Trial, almost two-thirds of patients that underwent an invasive procedure for diagnosis had benign findings, suggesting a significant number of patients were exposed to risk that could be avoided. Currently, to help distinguish malignant from benign nodules, Positron Emission Tomography/Computed Tomography (PET/CT) is used. However, PET/CT can be limited in its use for lesions less than 2 cm in size. The detection of circulating tumor DNA (ctDNA) and cell-free DNA (cfDNA) in the blood stream via liquid biopsy has demonstrated potential as a non-invasive approach in both screening and diagnostic tests. The purpose of this study is to assess whether combining liquid biopsy with PET/CT findings can better detect malignancy in small lung nodules 6-20 mm in size compared to PET/CT alone, possibly allowing earlier cancer detection and reduction in unneeded invasive diagnostic testing. Methods: This was a single-center prospective observational study for which the primary objective was to compare liquid biopsy plus PET/CT to PET/CT alone for detection of lung cancer in patients with newly discovered or newly growing solid lung nodules. Patients with nodules 6-20 mm in size who were scheduled to undergo 18F-Fluorodeoxyglucose PET/CT also underwent blood collection for plasma ctDNA/cfDNA testing using an amplicon-based next-generation sequencing assay incorporating molecular barcodes for error suppression. Tumor diagnosis was based on resolution of the nodule or tissue biopsy. For liquid biopsy, a multiomic model previously built using (1) cfDNA methylation frequencies, (2) ctDNA abundance, (3) somatic ctDNA mutations, and (4) cfDNA fragment size ratio was used to predict malignancy. For imaging, lesions with a maximum standardized uptake value of 2 or greater were considered malignant. Results: Between December 2021 and November 2022, 24 patients were enrolled. Of these, 13 had a definitive diagnosis and were included in the analysis with the remainder still undergoing serial imaging follow-up. Of the 13 patients, 9 were biopsy or surgically proven to be malignant, and 4 were benign based on biopsy or resolution. The median (IQR) nodule size was 14 mm (8-15). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for PET/CT were 0.67, 1, 1, and 0.57, respectively. For multiomic liquid biopsy alone, these values were the same. However, combining multiomic liquid biopsy and PET/CT, the sensitivity, specificity, PPV, and NPV were 0.89, 1, 1, and 0.8, respectively. Conclusions: Combining multiomic liquid biopsy with PET/CT results in improved sensitivity for the detection of early-stage malignant solid lung nodules by 33% compared to PET/CT alone with no reduction in specificity. This could result in improved selection of patients requiring biopsy. Further evaluation with a larger cohort is needed to confirm the findings.

Using cell-free DNA to predict response to immunotherapy in non-small cell lung cancer pre- and post-treatment.

e21198 Background: Despite revolutionizing cancer therapy, immune checkpoint inhibitors (ICI) still do not benefit a significant proportion of patients. The risks associated with ICI-related adverse events, mixed performance of PD-L1 staining in predicting treatment response and its high cost, present a clinical need for more precise methods to define disease states in the context of ICI treatment. ICI response is thought to depend on the phenotype of the tumor and the associated immune response, especially functional state of CD8+ T cells in the tumor microenvironment (TME). Methods: Here we show that the CD8+ T cell signatures from plasma cell-free DNA (cfDNA) could be used to predict response of patients to anti-PD-1 therapy, using samples collected before and shortly after start of treatment. Blood samples were drawn just before the first dose, 1 day to 1 week before the start of treatment and 45-60 days since start of treatment. The treatment duration varied depending on response. Response was evaluated by CT scans every 8-12 weeks. 11 of the samples are from patients with no or minor response ( &lt; 6 months of treatment), and 12 are from patients with prolonged benefit of the medication ( &gt; 1 year of treatment). Exhausted CD8+ T cells, one of the targets of immunotherapy treatment are epigenetically regulated. So, we utilized naïve and PD-1high CD8+ T cell ATAC-seq data to define the repertoire of accessible chromatin specific to these cell types. We found an enrichment of short cfDNA fragments at a significant fraction of these sites, enabling us to define responder-specific and non-responder-specific accessible PD-1high regions from cfDNA. Results: We used the enrichment of short- versus long-cfDNA fragments (reflecting transcription factor-nucleosome dynamics in tissue of origin of cfDNA) as a scoring function, and repeated-cross-validation as a classifier model to identify differentially enriched features between responders and non-responders. Our model accurately predicts the two classes of response both pre-treatment (mean test AUC = 0.86; SD = 0.14). Conclusions: Notably, in addition to generating an accurate classifier, our analysis enabled us to identify predominant transcription factor motifs from predictive ATAC-seq peaks that characterize both response and lack of response, paving the way for further understanding the mechanistic basis of patient-specific response to ICI. Our results suggest the possibility of personalized prediction of treatment response that is independent of specific tumor genotype.

Global circulating free DNA methylation and fragmentome deconvolution in patients with metastatic renal cell carcinoma treated with immunotherapy (GOLDEN).

4544 Background: Metastatic renal cell carcinoma (mRCC) lacks molecular biomarkers. Cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq) is a new, non-invasive approach to the detection of RCC-derived DNA in the circulation. In the GOLDEN study (NCT03702309), we explored the role of cfMeDIP-seq and fragmentomic dynamics as a biomarker, during immune checkpoint inhibition (ICI)-based treatment in mRCC patients (pts). Methods: Blood samples from mRCC pts were collected before and during treatment. Response to treatment was defined by the treating oncologist as: response, any degree of radiological tumor regression; stable disease (SD), no radiological change; or progressive disease (PD), radiological/clinical progression. More than 10ng of plasma cfDNA was subject to cfMeDIP-seq. A prognostic pan-cancer methylation signature previously generated using TCGA tissue methylation arrays was applied to cfMeDIP-seq output and cancer-signal methylation (CSM) score was calculated. An RCC-specific methylation signature, previously generated by identifying differentially methylated regions between RCC pts and controls, was applied ( Nuzzo et al, Nat Med 2020). Genome-wide fragmentation profiles were generated using DELFI. Using medians as cut off, log-rank test was performed to assess overall survival (OS) and progression-free survival (PFS). Results: Thirty-five patients were enrolled and n=33 received systemic treatment. 31/35 pts (89%) had clear cell and 4/35 (11%) non-clear cell histology. Median age was 61 (30-81) years and the M:F ratio was 6:1. Patients’ IMDC prognostic risk score was favorable n=6/35 (17%), intermediate n=23/35 (65%) and poor n=6/35 (17%). 20/33 (61%) patients received ipilimumab/nivolumab, 10/33 (30%) nivolumab and n=3/33 (9%) pembrolizumab/axitinib. There were n=14/33 (42%) responders, n=4/33 (12%) pts with SD and 15/33 (45%) pts with PD. Patients with high pan-cancer CSM score at baseline trended towards worse OS (HR 3.86, p = 0.079). Fragmentomics signature, consisting of increased proportion of short cfDNA fragments, showed a trend for worse PFS (HR = 3.04, p = 0.075) in on-treatment samples. Using the RCC-specific methylation signature, we found that those with an increase in signature score from baseline to on-treatment had better PFS (HR=2.4x10-10, p=0.002, n=10) and a trend towards better OS (HR=0.17, p=0.074, n=10). We hypothesize that RCC tissue-specific cell death early during ICI treatment could underpin this increase in the methylation score. Conclusions: This small study is the first report on the role of cfMeDIPseq-derived methylation and fragmentomic signatures in patients with mRCC undergoing ICI-based treatment. We found several trends and one significant association between these signatures and pt outcomes, which support further validation in larger cohorts. Clinical trial information: NCT03702309 .

Dissecting small cell lung cancer subtypes with cell-free DNA fragmentomes.

8592 Background: Although small cell lung cancer (SCLC) is managed as a single cancer type, new evidence supports that subtypes (high vs low neuroendocrine) of SCLC acquire diverse transcriptional and epigenetic states. Furthermore, distinct SCLC subtypes acquire unique therapeutic vulnerabilities, such as the low-neuroendocrine highly inflamed SCLC subtype that has been linked to immunotherapy sensitivity. We have previously shown that DELFI (DNA evaluation of fragments for early interception) can be used to non-invasively distinguish SCLC from non-small cell lung cancer (NSCLC). Here, we report a preliminary analysis of using the DELFI approach for distinguishing among SCLC subtypes. Methods: Circulating cell-free DNA (cfDNA) was isolated from plasma samples of patients diagnosed with relapsed SCLC and treated with durvalumab plus olaparib in a phase II trial (NCT02484404). Over 200 cfDNA libraries were prepared for whole genome sequencing in batches with internal controls. To infer tumor gene expression profiles in cfDNA, we investigated genome-wide signals of tissue-specific transcription factors differentially regulated in SCLC, and applied a novel DELFI-based approach to inform SCLC molecular subtypes. Clinical information, patient-matched tissue transcriptome (RNA-seq), and chromatin accessibility data (ATAC-seq) were examined in orthogonal analyses. Results: The DELFI classifier detected SCLC cases (N = 47) with a median DELFI score of 1.0 (95% CI 0.99-1), significantly higher than previously reported scores for other lung cancer subtypes. Comparison of DELFI fragmentome signals to publicly available tumor transcriptomes shows subtype-level concordance ( r = 0.78, p &lt; 0.001, Pearson), particularly in pre-treatment SCLC cases separating high- vs low- neuroendocrine subtypes. High-neuroendocrine SCLCs exhibited a decrease in aggregate cfDNA fragment coverage at ASCL1 transcription factor binding sites relative to low-neuroendocrine SCLCs (r = 0.90, p &lt; 0.001, Pearson). Additionally, low-neuroendocrine SCLCs revealed a significant decrease in aggregate cfDNA fragment coverage at genomic binding sites regulated by hematopoietic transcription factors, reflecting the inflamed phenotype of this SCLC subtype. Integration of these approaches provided a cfDNA fragmentation-based machine learning model that distinguished SCLC subtypes with high performance. Conclusions: Genome-wide cfDNA fragmentome analyses can differentiate high- and low-neuroendocrine SCLC subtypes. Given the challenges for performing SCLC biopsies in a clinical setting, we believe this approach could be a viable method of subtyping SCLC in a non-invasive manner.

Use of cell-free signals as biomarkers for early and easy prediction of preeclampsia.

Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity worldwide. However, current methods of screening are complicated and require special skill sets. In this observational study of prospectively collected samples, we wanted to evaluate if cell-free (cf) DNA could be an efficient biomarker for identification of at-risk patients. One hundred patients attending a private prenatal clinic in Canada were enrolled in their first trimester of pregnancy and a blood draw was carried out at 11 + 0 to 14 + 2 weeks' (timepoint A) and 17 + 6 to 25 + 5 weeks of gestation (timepoint B). CfDNA signals, namely concentration, fetal fraction, and fragment size distribution, were correlated with clinical outcomes in the test population to develop the logistic regression model. Twelve patients developed PE-four early-stage and eight late-stage PE. Significant differences were observed between PE patients and control cases for all three cfDNA signals at timepoint A, while both fetal fraction and concentration were significantly different between PE patients and control cases at timepoint B. Overall, the model had a sensitivity of up to 100% and specificity of up to 87.5% at Timepoint A. This proof-of-principle study showed that use of this logistic regression model could identify patients at risk of preeclampsia in the first trimester of pregnancy.

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 Fragmentomes in the Diagnostic Evaluation of Patients With Symptoms Suggestive of Lung Cancer

The diagnostic workup of individuals suspected of having lung cancer can be complex and protracted because conventional symptoms of lung cancer have low specificity and sensitivity. Among individuals with symptoms of lung cancer, can a blood-based approach to analyze cell-free DNA (cfDNA) fragmentation (the DNA evaluation of fragments for early interception [DELFI] score) enhance evaluation for the possible presence of lung cancer? Adults were referred to Bispebjerg Hospital (Copenhagen, Denmark) for diagnostic evaluation of initial imaging anomalies and symptoms consistent with lung cancer. Numbers and types of symptoms were extracted from medical records. cfDNA from plasma samples obtained at the prediagnostic visit was isolated, sequenced, and analyzed for genome-wide cfDNA fragmentation patterns. The relationships among clinical presentation, cancer status, and DELFI score were examined. A total of 296 individuals were analyzed. Median DELFI scores were higher for those with lung cancer (n= 98) than those without cancer (n= 198; 0.94 vs0.19; P< .001). In a multivariate model adjusted for age, smoking history, and presenting symptoms, the addition of the DELFI score improved the prediction of lung cancer for those who demonstrated symptoms (area under the receiver operating characteristic curve, 0.74-0.94). The DELFI score distinguishes individuals with lung cancer from those without cancer better than suspicious symptoms do. These results represent proof-of-concept support that fragmentation-based biomarker approaches may facilitate diagnostic resolution for patients with concerning symptoms of lung cancer.

Fragmentation landscape of cell-free DNA revealed by deconvolutional analysis of end motifs

Cell-free DNA (cfDNA) fragmentation is nonrandom, at least partially mediated by various DNA nucleases, forming characteristic cfDNA end motifs. However, there is a paucity of tools for deciphering the relative contributions of cfDNA cleavage patterns related to underlying fragmentation factors. In this study, through non-negative matrix factorization algorithm, we used 256 5' 4-mer end motifs to identify distinct types of cfDNA cleavage patterns, referred to as "founder" end-motif profiles (F-profiles). F-profiles were associated with different DNA nucleases based on whether such patterns were disrupted in nuclease-knockout mouse models. Contributions of individual F-profiles in a cfDNA sample could be determined by deconvolutional analysis. We analyzed 93 murine cfDNA samples of different nuclease-deficient mice and identified six types of F-profiles. F-profiles I, II, and III were linked to deoxyribonuclease 1 like 3 (DNASE1L3), deoxyribonuclease 1 (DNASE1), and DNA fragmentation factor subunit beta (DFFB), respectively. We revealed that 42.9% of plasma cfDNA molecules were attributed to DNASE1L3-mediated fragmentation, whereas 43.4% of urinary cfDNA molecules involved DNASE1-mediated fragmentation. We further demonstrated that the relative contributions of F-profiles were useful to inform pathological states, such as autoimmune disorders and cancer. Among the six F-profiles, the use of F-profile I could inform the human patients with systemic lupus erythematosus. F-profile VI could be used to detect individuals with hepatocellular carcinoma, with an area under the receiver operating characteristic curve of 0.97. F-profile VI was more prominent in patients with nasopharyngeal carcinoma undergoing chemoradiotherapy. We proposed that this profile might be related to oxidative stress.

Plasma cell-free DNA promise monitoring and tissue injury assessment of COVID-19

Coronavirus 2019 (COVID-19) is a complex disease that affects billions of people worldwide. Currently, effective etiological treatment of COVID-19 is still lacking; COVID-19 also causes damages to various organs that affects therapeutics and mortality of the patients. Surveillance of the treatment responses and organ injury assessment of COVID-19 patients are of high clinical value. In this study, we investigated the characteristic fragmentation patterns and explored the potential in tissue injury assessment of plasma cell-free DNA in COVID-19 patients. Through recruitment of 37 COVID-19 patients, 32 controls and analysis of 208 blood samples upon diagnosis and during treatment, we report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA fragmentation characteristics reflect patient-specific physiological changes during treatment. Further analysis on cfDNA tissue-of-origin tracing reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, our work demonstrates and extends the translational merit of cfDNA fragmentation pattern as valuable analyte for effective treatment monitoring, as well as tissue injury assessment in COVID-19.

Abstract 1024: Improved cfDNA methylation profiling through correction of misrepaired jagged-ends

Abstract Background: cfDNA methylation profiling allows early cancer detection and tissue-of-origin classification. Recent studies show that end repair (ER) process during double strand library preparation (dsLibP) introduces differential methylation signals between original and repaired sequences. We hypothesized that algorithmic correction of cfDNA jagged-ends could allow superior cfDNA methylation profiling performance, and better preserve double-stranded cfDNA molecules. Methods: We introduce JEEPERS (Jagged-End Error Polishing of Enzymatically misRepaired Sequences), a novel approach for correction of such errors in dsLibP methylation data. Specifically, JEEPERS is not only able to detect and quantify ER-induced errors at JEs, but also to correct them in silico. When using double-stranded unique molecular identifiers, JEEPERS leverages support from 2 sources to identify/correct errors at JEs: 1) complementary strands from individual DNA duplexes, and 2) sibling reads from other, non-jagged cfDNA families. JEEPERS relies on the 5’&amp;gt;3’ polarity of ER-associated errors and JE length profiles to correct R2 for longer fragments and both R1/2 for shorter ones. Results: We quantified the prevalence of such errors at JEs of double-stranded cfDNA molecules in plasma of 2 healthy subjects. We compared library preparations on single- (SPLAT-Seq) vs double-stranded DNA (EM-Seq), and strikingly found ~40% of CpGs to be involved in jagged cfDNA ends and impacted by misrepair during enzymatic ER of dsDNA. This resulted in an artifactual 13.1-16.3% lower global methylation across the genome, an effect that was exaggerated in hypermethylated (hyper) regions (~69% of genome). While ER-associated misrepair resulted in ~10.2% lower CpG methylation within the first 110bp of cfDNA fragments (R1 AUC=0.95, R2 AUC=0.81), when comparing R1/R2, the final 30bp showed even larger biases (13.8-77.4%). Remarkably, JEEPERS could accurately detect and correct these biases and produce highly uniform R1/R2 profiles in EM-Seq on par with SPLAT-Seq, even when considering short cfDNA fragments (&amp;lt;141bp) with substantial JE fractions. We also compared JEEPERS performance with other methods, including simple JE trimming or reliance on R1 alone, finding superior performance by JEEPERS for methylation quantification. Conclusions: ER distorts a large fraction of CpGs across the genome clustering at cfDNA fragment ends, resulting in substantially decreased methylation levels in cfDNA. JEEPERS accurately recovers methylation levels distorted by such misrepair. This not only enables more accurate methylation levels, but also retains cfDNA fragmentation features and duplex information. These advantages allow not only superior cfDNA genotyping of germline and somatic variants, but also enable better identification of allele-specific methylation, hemi-methylation, and gene expression inferences, as relevant for cancer detection. Citation Format: Rui Wang, Emily G. Hamilton, Angela Hui, Diego Almanza, Mohammad S. Esfahani, Maximilian Diehn, Ash A. Alizadeh. Improved cfDNA methylation profiling through correction of misrepaired jagged-ends [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1024.