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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↗

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↗

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↗

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

Cell-Free DNA Bisulfite Sequencing Reveals Epithelial-Mesenchymal Transition Signatures for Breast Cancer.

Cell-free DNA (cfDNA), shed by malignant tumor cells into extracellular fluid, provides valuable epigenetic information indicative of cancer status. Nipple aspirate fluid (NAF), a noninvasive liquid biopsy from at-risk women, contains nucleic acid and protein biomarkers from adjacent cancer cells, showing promise for breast cancer (BrC) detection. However, despite its potential, the application of cfDNA in NAF for BrC screening is still underexplored. Here, we report a proof-of-concept study for using cfDNA bisulfite sequencing (cfBS) to assess tumor DNA methylation signatures from NAF samples. For four healthy individuals and three BrC patients, cfBS achieved greater than 20× sequencing depth with an average coverage of 26.5× on the genome. A total of 7471 differentially methylated regions were identified, with significant hypermethylation in BrC samples compared to healthy controls. Gene set enrichment analysis indicated that the differentially methylated genes (DMGs) were significantly associated with epithelial-mesenchymal transition (EMT). By developing a novel EMT scoring metric, we found that BrC samples had more of a mesenchymal phenotype than samples from healthy individuals. CDH1, WNT2, and TRIM29 were hypermethylated near the promoter region, while COL5A2 was hypermethylated in the coding region. The DNA methylation and EMT changes were validated through The Cancer Genome Atlas Breast Invasive Carcinoma study, which confirmed that DMGs were associated with gene expression change and that our methylation-based EMT score reliably distinguished tumors from healthy controls. Our findings support the utilization of the NAF cfDNA cfBS methylation profile for noninvasive BrC screening and pave the way for enhanced early detection of this disease.

Humans↗

PubMed2026

Cell-free DNA genomic and fragmentomic features for early outcome prediction in large B cell lymphoma.

Curative-intent immunochemotherapy fails in ∼30% of patients with large B cell lymphoma (LBCL), yet no validated molecular tool enables early identification of high-risk individuals to guide treatment intensification. Using shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from 190 LBCL patients, we develop and validate the ACT score (aberrations, composition of fragments, and terminal motif analyses), a composite classifier integrating genomic and fragmentomic features from a single post-cycle-1 sample. ACT-positive patients have worse 2-year outcomes versus ACT-negative patients: time-to-progression 29% vs. 83% (hazard ratio [HR]: 4.4, 95% confidence interval [CI]: 1.9-10.0; p = 1.5 × 10-4) and overall survival 47% vs. 93% (HR: 8.7, 95% CI: 3.0-25.4; p = 1.8 × 10-6). The ACT score is independently prognostic of the International Prognostic Index, and their combination identifies the highest risk patients. Unlike mutation-based approaches, this assay requires neither tumor tissue, germline control, nor a baseline plasma sample. Built on open-source tools and sWGS, the ACT score offers a feasible, scalable strategy for early risk stratification in aggressive LBCL.

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↗

PubMed2026

Non-invasive strategy for gastric cancer detection: Integration of cell-free DNA fragmentomics and protein biomarkers.

Gastric cancer (GC) ranks as the fifth most common cancer worldwide, however, accurate and non-invasive diagnostic modalities for GC remain limited. Cell-free DNA (cfDNA) fragmentomics has emerged as a promising tool for cancer cell detection. Here we develop a gastric cancer detection model, named GaFraD model. The GaFraD model uses four cfDNA fragmentomics features, including fragment size ratio (FSR), copy number variation (CNV), 9-bp end motif (Motif), and fragment size at transcription start sites (TF). This model achieves an area under the receiver-operating characteristic curve (AUC) of 0.970 (95% CI: 0.944 - 0.990), a sensitivity of 95.0% and a specificity of 80.9%. By combining the GaFraD model and conventional protein biomarkers CA19-9 and PG-I/PG-II, the CONFIRM model was generated. The CONFIRM model attained an AUC of 0.986 (95% CI: 0.966 - 1.000), a sensitivity of 95.0% and a specificity of 95.6% in detecting GC. Moreover, the CONFIRM model achieved remarkable performance (AUC = 0.983, sensitivity 95.6%, specificity 94.2%) in distinguishing patients with early-stage GC from controls. Our work showed the high discriminatory power in distinguishing GC patients from controls, indicating the clinical potential of using cfDNA fragmentomics combined with protein biomarkers for non-invasive GC detection. The results of the study provide a new avenue for early, accurate, and non-invasive clinical diagnosis of GC.

Cell-free DNA↗

PubMed2026

DNAvi: integration, statistics, and visualization of cell-free DNA fragment traces.

SUMMARY: DNAvi is a Python-based tool for rapid grouped analysis and visualization of cell-free DNA fragment size profiles directly from electrophoresis data, overcoming the need for sequencing in basic fragmentomic screenings. It enables normalization, statistical comparison, and publication-ready plotting of multiple samples, supporting quality control and exploratory fragmentomics in clinical and research workflows. AVAILABILITY AND IMPLEMENTATION: DNAvi is implemented in Python and freely available on GitHub at https://github.com/anjahess/DNAvi under a GNU General Public License v3.0, along with source code, documentation, and examples. An archived version is available under https://doi.org/10.5281/zenodo.18401705.

Software↗

PubMed2026

Diagnostic value of plasma cell-free DNA metagenomic next-generation sequencing in patients with suspected infections and exploration of clinical scenarios-a retrospective study from a single center.

BACKGROUND: Plasma cell-free DNA metagenomic next-generation sequencing (mNGS) is a non-invasive comprehensive method for the etiological diagnosis of various infectious diseases. However, research on the early diagnosis and real-world clinical impact of plasma mNGS in patients with suspected infection are still limited. MATERIALS AND METHODS: This study retrospectively included 140 patients with suspected infections who underwent early plasma mNGS and conventional culture testing. Referring to the clinical diagnosis of infectious diseases, the diagnostic performance of plasma mNGS and culture tests was compared, and the application scenarios and clinical effects of plasma mNGS were evaluated. RESULTS: The positive rate of plasma mNGS was significantly higher than that of culture methods (55.71% vs 25.10%, p < 0.001) and blood cultures (55.71% vs 12.86%, p < 0.001). Regarding clinical diagnosis, the sensitivity of plasma mNGS was significantly higher than that of culture (58.27% vs 37.80%, p = 0.002). The combination of mNGS and culture achieved a higher detection sensitivity (69.29%), especially in patients with multi-site co-infections (73.68%) and blood infections (73.17%). Plasma mNGS demonstrated higher sensitivity in patients with procalcitonin (PCT) index > 5 ng/ml or human neutrophil lipocalin (HNL) index > 200 ng/ml. In terms of treatment, a total of 69 patients (54.33%) benefited from plasma mNGS. CONCLUSION: This study highlights the significant improvement in pathogen detection performance by combining conventional culture with plasma mNGS detection, especially in patients with multi-site co-infections and blood infections. Early use of plasma mNGS as an adjunct to culture can better guide clinicians to initiate appropriate anti-infective therapy.

Humans↗

PubMed2026

Epigenetic profiling of circulating cell-free DNA for early detection and minimal residual disease assessment in lung cancer: a focus on DNA methylation.

Lung Cancer (LC) continues to be the biggest cause of cancer-related deaths around the world, mostly because of delayed diagnosis. Even if tissue biopsies and circulating tumor DNA (ctDNA) tests have revolutionized clinical management of LC patients, their effectiveness is restricted in settings with lower tumor burden, molecular heterogeneity, and bias in sampling approaches. In this scenario, the epigenetic profiling of cell-free DNA (cfDNA) stands out as a promising, less invasive approach, accurately detect cancer traces. Evidence from stage I-II disease and CT-detected pulmonary nodules supports the diagnostic potential of cfDNA methylation, although further validation in prospective screening cohorts remains necessary. Beyond genomic alterations, cfDNA epigenetic changes, including DNA methylation, chromatin organization, nucleosome positioning, and fragmentation patterns, reflect multi-dimensional complexity of tumor biology. These properties convey both the functional status and the origin of the circulating DNA fragments, accelerating for tumor integrating genomic analysis. Within this group, DNA methylation is the biologically robust and clinically well-established epigenetic marker, as alterations in methylation linked to cancer often occur in the early stages of tumorigenesis and are commonly found across different cancer cell types. Here, we explored the biological and clinical relevance of the epigenetic landscape of cfDNA in LC patients, particularly focusing on DNA methylation-based biomarkers and their evolving applications towards early diagnosis and post-surgical monitoring of minimal residual disease (MRD). We aimed to comprehensively overview analytical approaches for cfDNA methylation analysis, including targeted and genome-wide profiling strategies, and discuss their integration with machine learning (ML) and multi-omics frameworks in order to improve diagnostic performance and clinical applicability in LC management.

DNA methylation↗

PubMed2025

Real-world clinical impact of plasma cell-free DNA metagenomic next-generation sequencing assay.

OBJECTIVE: To describe the real-world clinical impact of a commercially available plasma cell-free DNA metagenomic next-generation sequencing assay, the Karius test (KT). METHODS: We retrospectively evaluated the clinical impact of KT by clinical panel adjudication. Descriptive statistics were used to study associations of diagnostic indications, host characteristics, and KT-generated microbiologic patterns with the clinical impact of KT. Multivariable logistic regression modeling was used to further characterize predictors of higher positive clinical impact. RESULTS: We evaluated 1000 unique clinical cases of KT from 941 patients between January 1, 2017-August 31, 2023. The cohort included adult (70%) and pediatric (30%) patients. The overall clinical impact of KT was positive in 16%, negative in 2%, and no clinical impact in 82% of the cases. Among adult patients, multivariable logistic regression modeling showed that culture-negative endocarditis (OR 2.3; 95% CI, 1.11-4.53; P .022) and concern for fastidious/zoonotic/vector-borne pathogens (OR 2.1; 95% CI, 1.11-3.76; P .019) were associated with positive clinical impact of KT. Host immunocompromised status was not reliably associated with a positive clinical impact of KT (OR 1.03; 95% CI, 0.83-1.29; P .7806). No significant predictors of KT clinical impact were found in pediatric patients. Microbiologic result pattern was also a significant predictor of impact. CONCLUSIONS: Our study highlights that despite the positive clinical impact of KT in select situations, most testing results had no clinical impact. We also confirm diagnostic indications where KT may have the highest yield, thereby generating tools for diagnostic stewardship.

Humans↗

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

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson’s r > 0.93, p < 2.2 × 10− 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

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↗

PubMed2025

Cell-free DNA aneuploidy score as a dynamic early response marker in prostate cancer.

Cell-free circulating tumor DNA (ctDNA) has emerged as a promising biomarker for response evaluation in metastatic castration-resistant prostate cancer (mCRPC). The current study evaluated the modified fast aneuploidy screening test-sequencing system (mFast-SeqS), a quick, tumor-agnostic and affordable ctDNA assay that requires a small input of DNA, to generate a genome-wide aneuploidy (GWA) score in mCRPC patients, and correlated this to matched metastatic tumor biopsies. In this prospective multicenter study, GWA scores were evaluated from blood samples of 196 mCRPC patients prior to treatment (baseline) with taxanes (docetaxel and cabazitaxel) and androgen receptor signaling inhibitors (ARSI; abiraterone and enzalutamide), and from 74 mCRPC patients at an early timepoint during treatment (early timepoint; median 21 days). Z-scores per chromosome arm were tested for their association with tumor tissue genomic alterations. We found that a high tumor load in blood (GWAhigh) at baseline was associated with poor response to ARSI [HR: 2.63 (95% CI: 1.86-3.72) P < 0.001] but not to taxanes. Interestingly, GWAhigh score at the early timepoint was associated with poor response to both ARSIs [HR: 6.73 (95% CI: 2.60-17.42) P < 0.001] and taxanes [2.79 (95% CI: 1.34-5.78) P = 0.006]. A significant interaction in Cox proportional hazards analyses was seen when combining GWA status and type of treatment (at baseline P = 0.008; early timepoint P = 0.018). In summary, detection of ctDNA in blood by mFast-SeqS is cheap, fast and feasible, and could be used at different timepoints as a potential predictor for outcome to ARSI and taxane treatment in mCRPC.

Humans↗

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↗

PubMed2026

Development and preliminary validation of plasma cell-free DNA methylation-based diagnostic prediction model for colorectal cancer detection.

BACKGROUND: Colorectal cancer (CRC) is a common malignancy associated with genetic and epigenetic alterations. Several methylation biomarkers have been investigated for non-invasive CRC detection; however, their reported performance varies across clinical settings, and the detection of early-stage or precancerous disease and discrimination from non-malignant colorectal conditions remain challenging. This exploratory study aimed to identify reproducible CRC-associated plasma cell-free DNA (cfDNA) methylation regions and to develop and preliminarily evaluate diagnostic prediction model for distinguishing CRC from healthy controls and benign samples. METHODS: Public CRC tissue methylation datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify reproducible CRC-associated methylation alterations. Plasma cfDNA methylation was profiled using methyl-CpG-binding-domain enrichment followed by paired-end sequencing in patients with CRC, patients with colorectal polyps, and healthy controls. After quality-control filtering, 30 CRC and healthy-control samples were randomly allocated at the participant level in a 7:3 ratio to a development set comprising 10 patients with CRC and 11 healthy controls and a held-out test set comprising 4 patients with CRC and 5 healthy controls. Hypermethylated regions were selected using least absolute shrinkage and selection operator (LASSO) logistic regression. The 12-region model was evaluated in the held-out test set and subsequently applied to 10 colorectal polyp samples without refitting or recalibration. RESULTS: Tissue methylation analysis identified reproducible CRC-associated alterations across independent datasets. In the plasma development set, 707 differentially methylated regions (DMRs) were identified between CRC and healthy-control samples, including 324 hypermethylated and 383 hypomethylated regions. LASSO regression selected a 12-region hypermethylation signature. In the held-out test set, the model achieved an area under the curve (AUC) of 0.85 [95% confidence interval (CI): 0.579-1.000]. At the development-set-derived threshold, sensitivity was 75.0% (3/4), specificity was 60.0% (3/5), and accuracy was 66.7% (6/9). When the original model was applied to colorectal polyp samples, model scores were significantly higher in both CRC and polyp samples than in healthy controls, while CRC samples showed a tendency toward higher scores than polyp samples. CONCLUSIONS: This exploratory study identified a 12-region plasma cfDNA hypermethylation signature associated with CRC and developed a LASSO-based diagnostic prediction model that showed preliminary discrimination between CRC and healthy controls in a small held-out test set. By integrating tissue methylation evidence with plasma cfDNA profiling, this study expands the repertoire of candidate region-level methylation markers for blood-based CRC detection.

Colorectal cancer (CRC)↗