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PubMed2026

Validation of the TransplantTrace cfDNA Kidney assay for measurement of donor-derived cell-free DNA in transplant recipients.

INTRODUCTION: Donor-derived cell-free DNA (dd-cfDNA) has emerged as a promising non-invasive marker for assessing allograft status and guiding clinical management in transplant recipients. Its utility in kidney transplantation has repeatedly been demonstrated in large studies showing a strong association between elevated dd-cfDNA levels and allograft injury or rejection. This study evaluated the performance of a centralized next-generation sequencing (NGS)-based assay for measurement of dd-cfDNA in patients post-kidney transplantation. METHODS: The TransplantTrace cfDNA Kidney assay utilizes 50 insertion-deletion (indel) markers to discriminate dd-cfDNA. Evaluation of analytical performance included determination of input requirements, analytical sensitivity and specificity, as well as accuracy and precision parameters. Diagnostic performance was evaluated in a retrospective cohort of 104 post-transplantation samples by comparing dd-cfDNA results with biopsy-confirmed rejection. RESULTS: The assay required low DNA input (2 ng) and demonstrated high analytical sensitivity, with a verified limit of detection of 0.2% and limit of quantification of 0.3% dd-cfDNA. Analytical accuracy was excellent (R 2 = 1.00), with high repeatability and reproducibility across the reportable range of 0.2-30% dd-cfDNA. In the clinical validation, the assay showed high concordance with biopsy-confirmed rejection and excellent discriminatory performance for differentiating active from non-active rejection (AUC of 0.980). At a 1% cut-off, the assay exhibited a positive predictive value of 100%, supporting confident identification of patients likely to have treatable graft injury, while a high negative predictive value (95.6% at 15% prevalence) supports its reliability in ruling out active rejection. CONCLUSION: The TransplantTrace cfDNA Kidney assay demonstrated robust analytical performance and strong clinical concordance with biopsy-confirmed rejection status. Its high diagnostic accuracy supports reliable identification and exclusion of active rejection, with the potential to reduce reliance on invasive biopsy procedures in patients with elevated serum creatinine but low dd-cfDNA levels. In summary, the findings of this study support the implementation and use of this centralized assay for measurement of dd-cfDNA in patients post-kidney transplantation.

centralized↗

PubMed2025

Detection and Characterization of RB1 Mosaicism in Patients With Retinoblastoma Receiving cfDNA Test.

IMPORTANCE: Plasma cell-free DNA (cfDNA) testing is increasingly used for disease diagnosis and monitoring in retinoblastoma, with RB1 allele fraction in cfDNA actively corresponding to disease status and treatment response. However, while RB1 mosaicism has been reported in retinoblastoma, its clinical implications and potential impact on cfDNA testing remain unclear. OBJECTIVES: To identify RB1 mosaicism using paired plasma and buffy coat (containing lymphocytes, monocytes, granulocytes, and platelets) DNA testing, and to characterize the implications of RB1 mosaicism on cfDNA testing outcomes. DESIGN, SETTING, AND PARTICIPANTS: In this cross-sectional study, participants with retinoblastoma underwent testing with MSK-ACCESS (Memorial Sloan Kettering-Analysis of Circulating cfDNA to Examine Somatic Status), a clinical assay that combines plasma cfDNA and buffy coat genomic DNA sequencing, enabling the detection and differentiation of somatic, heterozygous, and mosaic variants, between July 2020 and April 2024 at the Memorial Sloan Kettering Cancer Center. Mosaic findings from MSK-ACCESS were correlated with those from a subgroup of patients who concurrently underwent testing using the MSK-IMPACT germline assay. Data analysis was performed from April to September 2024. EXPOSURE: RB1 mosaicism in retinoblastoma. MAIN OUTCOMES AND MEASURES: The RB1 variant allele fractions in cfDNA and buffy coat genomic DNA were used to detect RB1 mosaicism. RESULTS: A total of 136 consecutive patients with retinoblastoma (median age at diagnosis, 1.0 year [IQR, 0.4-1.7 years]; 74 [54.4%] female; 67 with bilateral disease and 69 with unilateral disease) who underwent testing with the MSK-ACCESS assay were included. RB1 mosaicism was identified in buffy coat DNA from 20 patients (14.7%), with consistent results detected in all 11 participants tested concurrently by the MSK-IMPACT (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) germline assay. Four participants with RB1 mosaicism previously tested negative for germline RB1 variants by external laboratories. Compared with heterozygous participants, participants with RB1 mosaicism had a lower risk of developing bilateral disease (91.7% vs 55.0%, respectively; difference, 36.7% [95% CI, 13.8%-59.6%]; P = .002). In cfDNA, the mosaicism variant was detected both before and after treatment, with variant allele fraction initially decreasing after treatment but then stabilizing at levels consistent with mosaicism, despite the absence of clinical disease. CONCLUSIONS AND RELEVANCE: The accurate detection and quantification of RB1 mosaicism are crucial. RB1 mosaicism should be considered when RB1 variants persist in cfDNA after treatment without evidence of disease; failure to do so may lead to false-positive results and overtreatment in patients with RB1 mosaicism. Identifying RB1 mosaicism may improve patient counseling, inform treatment decisions, and enhance surveillance efforts.

Humans↗

PubMed2026

cfMethDB: A Comprehensive cfDNA Methylation Data Resource for Cancer Biomarkers.

Cancer is a major global health threat, and early detection is crucial for improving patient outcomes. DNA methylation in circulating cell-free DNA (cfDNA) has emerged as a promising biomarker for non-invasive cancer diagnosis. However, the integration and utilization of existing cfDNA methylation data have been limited, hindering comprehensive research efforts, particularly in the discovery of cfDNA methylation biomarkers. To address this challenge, we introduced cfMethDB, a comprehensive database dedicated to cfDNA methylation in cancer that encompasses 4828 publicly available datasets. Through standardized analysis, we identified 1,048,770 differentially methylated cytosines (DMCs) as candidate biomarkers across seven cancer types. With cfMethDB, we not only identified known cfDNA methylation biomarkers, but also discovered several genes, such as ZIC4, that could be novel biomarkers. Moreover, cfMethDB offers a suite of user-friendly tools, including biomarker evaluation, pan-cancer search, and end motif analysis. We hope that cfMethDB will serve as a valuable platform for the discovery of novel cancer cfDNA methylation biomarkers and facilitate cancer research and clinical applications. cfMethDB is publicly available at https://cfmethdb.hzau.edu.cn/home.

Humans↗

PubMed2026

Beyond mutations: epigenetic and fragmentomic landscapes of cfDNA in lung cancer.

INTRODUCTION: Lung cancer is the most frequently diagnosed cancer worldwide and the leading cause of cancer-related mortality. Cell-free DNA (cfDNA) has emerged as a powerful biomarker in cancer detection. Early diagnostics efforts often leverage cancer-associated mutations present in cfDNA, but beyond such mutation-based assays, recent advances have shed light on other non-mutational features. The analysis of cfDNA epigenetic profiles and fragmentation patterns, known as 'fragmentomics,' has revealed a wealth of data to explore in noninvasive lung cancer diagnosis. AREAS COVERED: This review will explore this new narrative, summarizing the current understanding and use of cfDNA epigenetic modifications and fragmentomic patterns, while integrating findings to illustrate their vast potential in early-stage detection and therapeutics. By considering a range of epigenetic and fragmentomic features, cfDNA methylation (5mC, 5hmC), histone modifications, size profiles, and end signatures, this review highlights how the multidimensional integration of such signals shows promise in refining early-stage lung cancer and guiding therapeutic decisions. EXPERT OPINION: cfDNA epigenetic and fragmentomic analyses represent a transformative frontier in lung cancer diagnostics and monitoring. While these approaches demonstrate significant potential, most studies are limited by modest cohort sizes and reports of survival benefits, underscoring the need for large-scale validation and deeper mechanistic understanding.

Humans↗

PubMed2026

Uncovering the diagnostic potential of seminal fluid beyond fertility: cfDNA methylation analysis for the detection of clinically significant prostate cancer.

Research on the potential use of seminal fluid as a liquid biopsy for prostate cancer detection has been limited due to challenges associated with acquisition of this bodily fluid in clinical studies. Here we sought to expand on our previous analysis, which demonstrated high levels of prostate-derived cell free DNA (cfDNA) in seminal fluid in presumed healthy individuals, to a much larger cohort that included participants with prostate cancer. A total of 279 men scheduled for prostate biopsy were enrolled over 4 months across 12 sites. Prior to their biopsy, participants mailed a seminal fluid sample collected at home to the laboratory, from which cfDNA was extracted and underwent methylation analysis. Consistent with our earlier study in healthy individuals, we observed an abundance of high molecular weight (HMW) cfDNA in all samples. Tissue-of-origin deconvolution revealed that granulocytes and sperm were the principal contributors to seminal fluid cfDNA, while prostate-derived cfDNA was present at abundances readily detectable with current technologies. The nucleosomal fraction was very pronounced in some but not all samples and was determined to be correlated with the relative sperm signal. The sperm signal was also observed to be associated with an increase in small insert sizes (< 125 bp) in the sequenced libraries. Unsupervised clustering revealed two distinct populations driven by the abundance of sperm and granulocytes. Since summarizing at the genomic region level confounded tissues of different origins, fragment-level DNA methylation features were used to characterize and quantify the prostate cancer related signal, and features associated with clinically significant prostate cancer were identified. This study expands on our previous work to further characterize seminal fluid and highlights its potential as a promising liquid biopsy medium for the detection and monitoring of clinically significant prostate cancer.

Humans↗

PubMed2026

Plasma cfDNA hypermethylation at SNCA intron 1 as a potential blood-based epigenetic signal in Parkinson's disease and multiple system atrophy.

BACKGROUND: The accumulation of α-synuclein (SNCA) in the central nervous system is a hallmark of Parkinson's disease (PD) and multiple system atrophy (MSA). SNCA intron 1 methylation is implicated in SNCA transcriptional regulation and may serve as a peripheral epigenetic signal in synucleinopathies. However, studies of SNCA methylation in leukocyte-derived DNA have yielded inconsistent results. We aimed to evaluate whether cell-free DNA (cfDNA)-based SNCA intron 1 methylation differs in PD or MSA compared with normal controls (NC). METHODS: Plasma cfDNA was collected from 105 patients with PD, 50 with MSA, and 114 NC. DNA methylation at CpG sites 10-17 was quantified by bisulfite pyrosequencing. Multivariable linear and logistic regression models, adjusted for age, sex, and education, were used to compare methylation levels and estimate odds ratios (ORs). RESULTS: Patients with PD exhibited hypermethylation at CpG site 14 and higher mean methylation across CpG sites 10-17 compared with NC. Patients with MSA showed hypermethylation at CpG sites 10, 12, 13, and 17 and elevated mean methylation. Elevated mean methylation was also observed in drug-naïve de novo PD and early-stage PD patients. Compared with the lowest tertile, the highest mean methylation tertile was associated with increased odds of PD (OR, 2.49; 95% CI, 1.08-5.92) and MSA (OR, 5.02; 95% CI, 1.58-18.00). CONCLUSION: Plasma cfDNA SNCA intron 1 hypermethylation is associated with PD and MSA and detectable in drug-naïve and early-stage PD. It may represent a peripheral epigenetic alteration and warrants evaluation as an adjunctive signal for early screening.

Humans↗

PubMed2026

A cfDNA fragmentomics classifier for noninvasive differentiation of benign and malignant renal masses.

Noninvasive differentiation of malignant and benign renal masses remains a major clinical challenge, particularly for radiologically indeterminate lesions. Here, we developed and validated a plasma cell-free DNA (cfDNA) fragmentomics-based machine learning classifier for renal mass characterization. The model was trained on 331 participants (171 cancer, 160 benign) and independently validated on 144 participants (73 cancer, 71 benign). Three cfDNA fragmentation features, including copy number variation (CNV), fragmentation-based methylation (FRAGMA), and nucleosome footprint (NF), derived from low-pass whole-genome sequencing, were integrated into an ensemble framework. The model achieved strong discriminative performance, with area under the curve (AUC) values of 0.956 in the training cohort and 0.946 in the validation cohort, outperforming individual feature-based models. At a predefined operating threshold corresponding to 90% sensitivity, specificity reached 0.90 and 0.87, respectively. Notably, most cancer samples exhibited low tumor fraction (TF < 3%), yet the model maintained robust performance in low-TF samples (AUCs: 0.952 and 0.941, respectively). Performance remained consistent across tumor stage, grade, and histological subtypes. The classifier also demonstrated potential clinical utility in diagnostically challenging settings, including lipid-poor angiomyolipoma and oncocytoma, with 12 of 13 oncocytoma samples correctly classified in an independent cohort. In addition, the model correctly identified 85.3% of benign masses > 4 cm, for which surgical intervention is more commonly considered, and 84.6% of malignant tumors ≤ 4 cm, for which management can be challenging. Collectively, these findings support cfDNA fragmentomics as a promising noninvasive liquid biopsy approach for renal mass evaluation and clinical decision-making.

Humans↗

PubMed2025

Identification of maternal Gγ(Aγδβ)0 thalassemia through retrospective reanalysis of prenatal cfDNA sequencing data.

OBJECTIVE: Non-invasive prenatal screening (NIPS) is widely used to detect chromosomal abnormalities such as trisomies 21, 13, and 18 and is also effective in screening for copy number variations (CNVs). However, the routine application of NIPS to detect smaller CNVs within the HBB gene, specifically Gγ(Aγδβ)0 thalassemia, has yet to be well documented. This study aims to evaluate the efficacy of cfDNA-based maternal carrier screening in routine screening for Gγ(Aγδβ)0 thalassemia. METHODS: We performed a retrospective analysis of 107,300 pregnant women who underwent NIPS at Longgang Maternal and Child Healthcare Hospital in Shenzhen from December 2017 to May 2022. Using an improved algorithm, we reanalyzed NIPS data to identify maternal Gγ(Aγδβ)0 thalassemia. Positive cases were confirmed by multiplex ligation-dependent probe amplification (MLPA) using peripheral blood leukocytes. RESULTS: Among the 107,300 NIPS analyses, 38 maternal deletion CNVs within the HBB gene were identified using the improved algorithm, with a prevalence of 0.035% (38/107,300). MLPA confirmed that all detected deletions were consistent with Gγ(Aγδβ)0 thalassemia. The positive predictive value (PPV) for detecting Gγ(Aγδβ)0 thalassemia by cfDNA-based maternal carrier screening was 100%. Among the 38 Gγ(Aγδβ)0 cases, 9 were also associated with α-thalassemia deletions, including 4 cases with -SEA/αα, 4 with -α3.7/αα, and 1 with -α4.2/αα. No cases of homozygosity or compound HBB gene variants were observed. CONCLUSIONS: Gγ(Aγδβ)0 thalassemia is not uncommon in China, and repurposed NIPS methodology for maternal genomic analysis in detecting HBB gene deletions is a reliable method for identifying maternal carriers of this disease.

Humans↗

PubMed2026

A multi-analyte cfDNA-based blood test for early detection of hepatocellular carcinoma.

BACKGROUND & AIMS: Patients at high risk for hepatocellular carcinoma (HCC) are recommended to undergo biannual abdominal ultrasound surveillance; however, ultrasound has low sensitivity for small HCC nodules and is associated with poor adherence. To address these limitations, the multianalyte HelioLiver Dx blood test was developed to aid in the detection of HCC in patients with cirrhosis who are at high risk for HCC. METHODS: The performance of the HelioLiver Dx test and ultrasound for the detection of HCC in adults with cirrhosis was evaluated in a cross-sectional, prospective, blinded, multicenter validation study. All participants provided blood specimens for the HelioLiver Dx test and underwent ultrasound. All participants also underwent multiphasic MRI, which served as the reference standard for determining HCC status. RESULTS: Of 1,268 evaluable participants, 46 (3.6%) were considered to have HCC as determined by MRI, with many (46%) having small HCC lesions ≤2 cm in diameter. The HelioLiver Dx test had a sensitivity of 47.8% (95% CI 32.9-63.1) for all HCC lesions and 28.6% (95% CI 11.3-52.2) for HCC lesions ≤2 cm. In contrast, ultrasound demonstrated a lower sensitivity of 28.3% (95% CI 16.0-43.5) for all HCC lesions and failed to detect any (0%; 95% CI 0.0-16.1) HCC lesions ≤2 cm. The specificity of HelioLiver Dx and ultrasound were 87.6% (95% CI 85.6-89.4) and 93.9% (95% CI 92.5-95.2), respectively. The HelioLiver Dx test met prespecified co-primary endpoints for superior sensitivity and non-inferior specificity compared to ultrasound. CONCLUSION: Compared with ultrasound and alpha-fetoprotein, the HelioLiver Dx test identified more HCC lesions overall, including more small lesions. A convenient and accurate blood-based test may improve HCC surveillance by facilitating earlier detection and reducing patient barriers to testing. GOV IDENTIFIER: NCT03694600 IMPACT AND IMPLICATIONS: There is a significant, unmet clinical need for more sensitive and accessible methods for the early detection of hepatocellular carcinoma (HCC) in high-risk patient populations. The current study is the first blinded, multicenter, prospective study to evaluate the performance of a multianalyte blood test compared to abdominal ultrasound for the detection of HCC among patients with cirrhosis. The multianalyte HelioLiver Dx test met prespecified co-primary endpoints for superior sensitivity and non-inferior specificity compared to ultrasound for detection of HCC lesions. The availability of a more accessible, convenient and sensitive blood test to aid in the detection of HCC may improve utilization and consequently clinical outcomes for high-risk patients via reduction of care barriers and improved early HCC detection. CLINICALTRIALS: gov identifier: NCT03694600.

Humans↗

PubMed2026

Towards a Robust cell-free DNA Isolation Protocol for NGS Applications in a Clinical Molecular Diagnostics Setting.

Cell-free DNA (cfDNA), released from apoptotic and necrotic cells into body fluids, is a non-invasive source of genetic information for disease prediction, diagnosis, and monitoring. However, its low abundance makes cfDNA highly susceptible to various pre-analytical influences, potentially increasing high molecular weight (HMW) or genomic DNA (gDNA) compromising downstream cfDNA analyses. This study evaluated the impact of different cfDNA-stabilizing blood collection tubes (BCT; Cell-Free DNA BCT, Streck; S-Monovette cfDNA Exact, Sarstedt) stored at room temperature for 1, 5, or 10 days, prior to plasma isolation using different isolation methods (magnetic bead-based or silica column-based) on cfDNA stability and yield. DNA quantity and quality were assessed by fluorometric quantification, automated fragment analysis, and gene-specific quantitative PCR. Streck-based workflows maintained stable cfDNA yields and characteristic mononucleosomal fragmentation profiles across all storage times. In contrast, Sarstedt tubes showed reduced cfDNA concentrations after 5 days and a pronounced increase at 10 Days, accompanied by high-molecular weight DNA patterns consistent with white-blood cells (WBC) lysis. These trends were largely independent of the extraction method. Overall, the results demonstrate that blood collection tube chemistry critically influences cfDNA integrity during delayed processing. Streck tubes, particularly when combined with silica column-based isolation method, provided the most robust and reproducible workflow for routine molecular diagnostics, whereas Sarstedt tubes produced physiologically implausible results after extended storage.

blood collection tubes↗

PubMed2025

Donor-Derived Cell-Free DNA Stratifies Risk of Mortality and Graft Dysfunction in Severe Acute Cardiac Allograft Rejection.

BACKGROUND: Cardiac acute rejection (AR) is a risk factor for poor outcomes, however there are limited risk prediction models to stratify patients for death or sustained LV dysfunction. This study assesses the prognostic utility of percentage donor-derived cell-free DNA (%dd-cfDNA) at the diagnosis of AR for poor outcomes. METHODS: The prospective multicenter GRAfT study enrolled heart transplant recipients and collected serial plasma samples to quantitate %dd-cfDNA. AR was defined as acute cellular rejection (ACR), antibody-mediated rejection (AMR), as well as biopsy-negative AMR (donor-specific antibody positivity with LV dysfunction). AR was classified as mild-to-moderate (ACR grade 2 or AMR grade 1) or severe (ACR grade ≥3, AMR grade ≥2, or DSA+/LV dysfunction) and further stratified by a %dd-cfDNA threshold of 0.25%. Regression models assessed the association between AR and %dd-cfDNA levels at the AR diagnosis with the primary composite outcome of sustained LVEF decline <50% and/or death. RESULTS: The study included 275 patients and 3,190 %dd-cfDNA assessments. Over the median of 4.6 (IQR 1.8 - 5.0) years follow-up, 51 patients experienced the composite outcome of death or prolonged EF reduction, and 75 patients developed AR, including 16.2% patients with ACR, 9.4% with pathologic AMR, and 6.6% with DSA+/LV dysfunction. Thirty-two (42.7%) patients had severe AR and 43 (57.3%) had mild-to-moderate AR. Severe-but not mild-to-moderate-AR was associated with an increased risk of the primary composite endpoint (HR = 5.17, 95% CI 2.38 - 11.3, p < 0.001). Among those with severe AR, a %dd-cfDNA level greater than 0.25% at diagnosis was associated with a higher risk of the primary outcome (HR, 6.06, 95% CI, 1.78-20.6; p = 0.004). Percent dd-cfDNA remained elevated in severe AR patients with adverse outcomes. CONCLUSION: Severe AR with high %dd-cfDNA levels is associated with an increased risk of poor outcomes, offering novel prognostic utility.

Acute Rejection↗

PubMed2025

GCfix: a fast and accurate fragment length-specific method for correcting GC bias in cell-free DNA.

MOTIVATION: Cell-free DNA (cfDNA) analysis has wide-ranging clinical applications due to its noninvasive nature. However, cfDNA fragmentomics and copy number analysis can be complicated by GC bias. There is a lack of GC correction software based on rigorous cfDNA GC bias analysis. Furthermore, there is no standardized metric for comparing GC bias correction methods across large sample sets, nor a rigorous experiment setup to demonstrate their effectiveness on cfDNA data at various coverage levels. RESULTS: We present GCfix, a method for robust GC bias correction in cfDNA data across diverse coverages. Developed following an in-depth analysis of cfDNA GC bias at the region and fragment length levels, GCfix is both fast and accurate. It works on all reference genomes and generates correction factors, tagged BAM files, and corrected coverage tracks. We also introduce two orthogonal performance metrics for (i) comparing the fragment count density distribution of GC content between expected and corrected samples, and (ii) evaluating coverage profile improvement post-correction. GCfix outperforms existing cfDNA GC bias correction methods on these metrics. AVAILABILITY AND IMPLEMENTATION: GCfix software and code for reproducing the figures are publicly accessible on GitHub: https://github.com/Rafeed-bot/GCfix_Software.

Software↗

PubMed2024

Fragmentomics of plasma mitochondrial and nuclear DNA inform prognosis in COVID-19 patients with critical symptoms.

BACKGROUND: The mortality rate of COVID-19 patients with critical symptoms is reported to be 40.5%. Early identification of patients with poor progression in the critical cohort is essential to timely clinical intervention and reduction of mortality. Although older age, chronic diseases, have been recognized as risk factors for COVID-19 mortality, we still lack an accurate prediction method for every patient. This study aimed to delve into the cell-free DNA fragmentomics of critically ill patients, and develop new promising biomarkers for identifying the patients with high mortality risk. METHODS: We utilized whole genome sequencing on the plasma cell-free DNA (cfDNA) from 33 COVID-19 patients with critical symptoms, whose outcomes were classified as survival (n = 16) and death (n = 17). Mitochondrial DNA (mtDNA) abundance and fragmentomic properties of cfDNA, including size profiles, ends motif and promoter coverages were interrogated and compared between survival and death groups. RESULTS: Significantly decreased abundance (~ 76% reduction) and dramatically shorter fragment size of cell-free mtDNA were observed in deceased patients. Likewise, the deceased patients exhibited distinct end-motif patterns of cfDNA with an enhanced preference for "CC" started motifs, which are related to the activity of nuclease DNASE1L3. Several dysregulated genes involved in the COVID-19 progression-related pathways were further inferred from promoter coverages. These informative cfDNA features enabled a high PPV of 83.3% in predicting deceased patients in the critical cohort. CONCLUSION: The dysregulated biological processes observed in COVID-19 patients with fatal outcomes may contribute to abnormal release and modifications of plasma cfDNA. Our findings provided the feasibility of plasma cfDNA as a promising biomarker in the prognosis prediction in critically ill COVID-19 patients in clinical practice.

Humans↗

PubMed2026

Identification of a G-quadruplex-forming cell-free DNA fragment as a biomarker for the precise diagnosis of hepatocellular carcinoma.

Early detection of hepatocellular carcinoma (HCC) remains challenging, as the currently recommended surveillance strategy based on ultrasound combined with alpha-fetoprotein (AFP) is limited by suboptimal sensitivity and accessibility. Cell-free DNA (cfDNA) provides a minimally invasive avenue for cancer detection. However, most existing cfDNA-based approaches either perform unreliably in low-input samples or require analytically complex workflows. Here, we systematically profiled serum cfDNA from individuals with HCC and without HCC and identified a high-abundance tumor-associated single cfDNA fragment at the FAM230F genomic region. Integrative analysis of liver assay for transposase-accessible chromatin with sequencing (ATAC-seq) data revealed consistent tumor-specific chromatin accessibility at this locus, suggesting a tumor-derived origin. Structural characterization further demonstrated enrichment of G-quadruplex (G4) features within the target sequence, which may increase resistance to serum nuclease degradation and promote its preferential retention in circulation. Based on these properties, we established a qPCR-based detection workflow with clinical accessibility. In a validation cohort independent of the discovery cohort, a ΔC t cutoff of 2 was selected by maximizing the Youden index within the same cohort. The assay showed a sensitivity of 94.5% and a specificity of 90.5% for distinguishing HCC from non-HCC. Collectively, our study identifies FAM230F as a structurally stable tumor-associated cfDNA fragment and establishes a simple and scalable qPCR-based assay for HCC detection, providing a practical framework for translating cfDNA fragment analysis into clinical biomarkers.

Journal Article↗

PubMed2026

Large-scale simulation of coverage and error rate tradeoffs for cancer detection in cell-free DNA whole-genome sequencing.

MOTIVATION: Cell-free DNA (cfDNA) whole-genome sequencing (WGS) is a promising approach for detecting cancer recurrence. It enables cancer detection by identifying all tumor-derived cfDNA (ctDNA) molecules carrying somatic single nucleotide variants (sSNVs). While ideally, a sequencing platform should be highly accurate for reliable ctDNA detection, in reality, all sequencing platforms introduce sequencing errors that generate false positives indistinguishable from true SNVs. Understanding how sequencing parameters influence ctDNA detection sensitivity at low tumor fractions (TFs) in cfDNA samples is essential for guiding sequencing strategies in clinical contexts. To model cfDNA sequencing for tumor detection, which contains asymmetric noise and multiple interacting parameters, analytical modeling is intractable, motivating large-scale parallelized simulation. RESULTS: We developed a simulation framework to generate in silico cfDNA data across 10 cancer types. In total, 480 million cfDNA samples were simulated from tumor WGS profiles. Overall, the lowest detectable TF differs substantially between cancer types under identical sequencing conditions due to variations in mutational load. For cancers with high mutational load, 3× coverage with low-error techniques reliably detects TFs below 0.1%. In contrast, cancers with low mutational load require at least six-fold higher coverage to achieve comparable detection thresholds. Increasing sequencing quality scores from Q30 to Q55 at 30× coverage further enhances sensitivity, enabling detection of TFs as low as 1 × 10-5. This study provides a comprehensive framework for optimizing sequencing parameters, offering valuable guidance for tailoring future technology development for specific cancer types and clinical applications. AVAILABILITY AND IMPLEMENTATION: The code is publicly available at https://github.com/UMCUGenetics/cfdetect/tree/main.

Whole Genome Sequencing↗

PubMed2025

Methylome profiling of cell-free DNA during the early life course in (un)complicated pregnancies using MeD-seq: Protocol for a cohort study embedded in the prospective Rotterdam periconception cohort.

INTRODUCTION: Placental DNA methylation differences have been associated with timing in gestation and pregnancy complications. Maternal cell-free DNA (cfDNA) partly originates from the placenta and could enable the minimally invasive study of placental DNA methylation dynamics. We will for the first time longitudinally investigate cfDNA methylation during pregnancy by using Methylated DNA Sequencing (MeD-seq), which is compatible with low cfDNA levels and has an extensive genome-wide coverage. We aim to investigate DNA methylation in placental tissues and cfDNA during different trimesters in uncomplicated pregnancies, and in pregnancies with placental-related complications, including preeclampsia and fetal growth restriction. Identified gestational-age and disease-specific differentially methylated regions (DMRs) could lead to numerous applications including biomarker development. METHODS AND ANALYSIS: Our study design involves three sub-studies. Sub-study 1 is a single-centre prospective, observational subcohort embedded within the Rotterdam Periconception cohort (Predict study). We will longitudinally collect maternal plasma in each trimester and during delivery, and sample postpartum placentas (n = 300). In sub-study 2, we will prospectively collect first and second trimester placental tissues (n = 10 per trimester). In sub-study 3 we will retrospectively collect plasma after non-invasive prenatal testing (NIPT) in an independent validation case-control cohort (n = 30-60). A methylation-dependent restriction enzyme (LpnPI) will be used to generate DNA fragments followed by sequencing on the Illumina NextSeq2000 platform. DMRs will be identified in placental tissues and cell types, and in cfDNA related to gestational-age or placental-related complications. (Paired) placental methylation profiles will be correlated to DMRs in cfDNA to aid tissue-of-origin analysis. We will establish a methylation score to predict associated diseases. DISCUSSION: This study will provide insights in placental DNA methylation dynamics in health and disease, and could lead to clinical relevant biomarkers.

Humans↗

PubMed2026

Aging and Reproductive Cancers: An Integrative View on Cell-Free DNA and Transposable Elements.

Aging is one of the strongest risk factors for cancer, and its impact is particularly evident in malignancies of the reproductive system. Ovarian, endometrial, cervical, vulvar, prostate, and penile cancers are mainly diagnosed in older adults and often show different clinical and biological features compared with the same tumors in younger patients. Aging is associated with hormonal changes, immune decline, epigenetic alterations, and accumulation of DNA damage, all of which contribute to cancer development and progression. At the same time, many older patients have frailty and multiple comorbidities, which can limit the use of screening programs and invasive diagnostic procedures. This often leads to delayed diagnosis and worse outcomes. Cell-free DNA (cfDNA) is a minimally invasive biomarker that can be obtained from blood samples and provides molecular information on both tumor and host tissues. Circulating DNA reflects tumor-specific alterations but is also influenced by aging-related changes in DNA release, fragmentation, and methylation. For this reason, aging must be considered when cfDNA-based biomarkers are applied in clinical practice. In this review, we describe how aging influences the biology of reproductive system cancers and how these processes are mirrored in cfDNA profiles. We focus on the clinical use of cfDNA for cancer detection and monitoring in older and fragile patients. Special attention is given to repetitive elements in cfDNA, which are strongly affected by aging and tumor-related epigenetic changes and can be detected with high sensitivity even when the tumor fraction is low. We propose an integrative mechanistic framework in which age-related epigenetic and genomic changes influence both tumor biology and cfDNA composition, with transposable elements acting as a central link between aging and cancer.

Humans↗

PubMed2026

Innovative advances and clinical applications of cell-free DNA methylation detection technologies.

Advances in DNA methylation detection technologies have promoted disease-related cell-free DNA (cfDNA) analysis. CfDNA methylation profiling has the potential to serve as a promising clinical tool for early disease diagnosis. However, current detection technologies suffer from high costs, complex operational procedures, and insufficient sensitivity for low-input samples. Moreover, the definitive validation of its clinical value still awaits robust evidence from high-quality confirmatory studies. Therefore, this review begins by mapping the historical evolution of cfDNA methylation, followed by a comparison of the traditional approaches and recent breakthroughs in cfDNA methylation analysis. Specifically, this review systematically examines the two major strategies: the ones based on bisulfite-dependent DNA modification and the bisulfite-free methods, including the techniques for whole-genome methylation profiling and methods targeting specific genomic regions. Additionally, to evaluate the clinical application potential of these methods, this review comprehensively describes the details of these technologies, such as sample input requirements and sensing accuracy in detecting clinical samples. The future development of cfDNA methylation detection will focus on clinical translation, integrating technical innovations with the demands for efficient clinical diagnosis. We believe this review will help researchers select methods tailored to sample availability and clinical applicability.

Humans↗