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PubMed2025

Noninvasive detection and differentiation of gastric malignancy using cell-free DNA biomarkers.

INTRODUCTION: Gastric cancer remains a major global health burden, with high mortality driven by late-stage diagnoses that limit treatment options and reduce survival. Current diagnostic methods such as endoscopy and biopsy are invasive, resource-intensive, and impractical for large-scale early detection. OBJECTIVES: This study aimed to develop and validate an ensemble machine learning model integrating four cell-free DNA (cfDNA) fragmentomic feature classes derived from 5 × whole genome sequencing (WGS) data to non-invasively differentiate malignant gastric cancer from benign gastric lesions in high-risk or symptomatic patients. METHODS: A total of 681 plasma samples were prospectively collected, comprising 329 from patients with gastric cancer or high-grade intraepithelial neoplasia (HGIN) and 352 from individuals with benign gastric conditions. The dataset was divided into a training cohort (n = 333) and a temporally independent validation cohort (n = 348). An external validation cohort of 305 participants was also included. RESULTS: The ensemble model achieved an AUROC of 0.920 in cross-validation testing on the training cohort, 0.912 in the independent validation cohort, and 0.896 (95% CI 0.860-0.932) in the external cohort. At a pre-specified prediction threshold of 0.402, the model demonstrated 93.3% sensitivity and 71.9% specificity in the validation cohort, yielding a PPV of 71.3% and an NPV of 93.5%. In the external cohort, sensitivity and specificity were 91.7% and 69.1%, respectively (PPV 75.7%, NPV 88.8%). Model scores correlated with clinical stage, tumor grade, and histopathological subtype. Approximately 71% of non-cancer patients could have been spared unnecessary endoscopy. CONCLUSIONS: The cfDNA fragmentomics-based ensemble model enables accurate, non-invasive differentiation between gastric cancer and benign gastric lesions in high-risk or symptomatic patients. This approach demonstrates strong potential as a pre-endoscopy triage tool, supporting earlier detection and more efficient use of diagnostic resources.

Humans↗

PubMed2025

Utility of Plasma Cell-free Chromatin Immunoprecipitation to Detect Cardiac Allograft Rejection.

BACKGROUND: Antibody-mediated rejection (AMR) remains the major risk factor for allograft loss across all solid organ transplantation. Unfortunately, its diagnosis relies on biopsy, an invasive gold standard that often sample unaffected allograft tissue leading to missed diagnosis. Plasma donor-derived cell-free DNA (dd-cfDNA) is noninvasive biomarker that has high sensitivity but low specificity for AMR diagnosis. This proof-of-concept study assessed the utility of cell-free chromatin immunoprecipitation (cfChIP) as a surrogate for gene expression to detect cardiac AMR and the associated pathobiology. METHODS: The discovery GRAfT multicenter cohort of heart transplant patients (NCT02423070) identified AMR, acute cellular rejection (ACR), and stable controls based on biopsy and ddcfDNA results. Plasma cfChIP-sequencing was performed to identify peaks, associated genes and pathobiological pathways. Plasma from an external cohort (GTD, NCT01985412) was also analyzed to verify pathways identified. Digital droplet PCR (ddPCR) assays targeting differential regions were constructed to test the diagnostic performance of cfDNA to detect AMR/ACR from stable controls (rejection-specific assays) or AMR from ACR (AMR-specific assays). RESULTS: The cohort included 21 AMR, 28 ACR, and 45 stable controls from GRAfT and GTD, and 23 healthy controls. cfChIP detected expected active genes, including housekeeping genes and gene targets of transplant immunosuppressive drugs but not inactive genes. Unsupervised clustering of the discovery GRAfT cohort assigned 95% of samples correctly as AMR, ACR or stable control. Differential analysis identified pathobiological pathways of AMR such as neutrophil degranulation and complement activation. The pathways were consistent in GTD samples. Rejection-specific assays detected AMR/ACR from controls with AUC of 0.78 - 0.95. AMR-specific assays detected AMR from ACR with AUC of 0.71 - 0.85, sensitivities of 0.73 - 0.94 and specificities of 0.73 - 0.80. CONCLUSION: This study provides valuable preliminary data supporting the use of cfChIP to detect AMR and the associated pathobiological pathways.

Allograft rejection↗

PubMed2026

An alignment-free strategy for circulating tumor DNA detection and tumor fraction estimation from whole-genome sequencing data.

Circulating tumor DNA (ctDNA) is emerging as a promising biomarker for postoperative monitoring of cancer patients. Precise estimation of circulating tumor fraction is crucial for evaluating treatment effects and timely detection of disease recurrence. All current ctDNA detection methods that utilize whole-genome sequencing (WGS) data rely on the reference genome alignment of sequencing reads and often apply separate tools for detecting different variant types. However, various bioinformatic analysis confounders and the application of external variant calling tools could be avoided by analyzing k-mers from unaligned sequencing reads. While k-mer-based methods have successfully been applied for somatic variant validation and detection, the potential of k-mer-based ctDNA detection is unexplored. We have developed a tumor-informed alignment-free ctDNA detection tool called ctDNAmer that detects tumor-specific somatic variation directly from unaligned sequencing data by identifying k-mers unique to the tumor DNA. ctDNAmer detects variant information across the genome by comparing the primary tumor and germline WGS data and accounts for sample-specific germline variability and technical noise in the same framework. We tested the utility of ctDNAmer for tumor fraction estimation on postoperative plasma cfDNA WGS data (mean sequencing depth ~ 28x) from 90 stage III colorectal cancer patients with three years of follow-up. The tumor fraction (TF) estimates agreed with the available clinical information and ctDNA was detected in 77% (17/22) of recurring patients with a median lead time of 8 months compared to radiological imaging. We further validated ctDNAmer's tumor fraction estimates based on a comparison with the mean cfDNA allele frequencies of somatic clonal SNVs identified from aligned primary tumor sequencing data. The TF estimates showed a strong Pearson correlation of 0.897 with the mean allele frequencies and improved ctDNA detection results across samples with an AUC of 0.79 compared to 0.75 if the mean allele frequency of clonal mutations is used.

Circulating Tumor DNA↗

PubMed2006

Circulating cell-free DNA: a novel biomarker for response to therapy in ovarian carcinoma.

INTRODUCTION: Cell-free DNA (CFDNA) is a reflection of both normal and tumor-derived DNA released into the circulation through cellular necrosis and apoptosis. We sought to determine whether tumor-specific plasma DNA could be used as a biomarker for tumor burden and response to therapy in an orthotopic ovarian cancer model. METHODS: Female nude mice injected intraperitoneally with HeyA8 ovarian cancer cells were treated with either docetaxel alone or in combination with anti-angiogenic agents (AEE788-dual VEGFR and EGFR antagonist or EA5-monoclonal antibody against ephrin A2). Following DNA extraction from plasma, quantification of tumor-specific DNA was performed by real-time PCR using human specific beta-actin primers. The number of genome equivalents (GE/ml) were determined from a standard curve. Apoptosis was assessed by TUNEL staining of treated tumors. RESULTS: The levels of tumor-specific DNA in plasma increased progressively with increasing tumor burden (R2=0.8, p<0.01). Additionally, tumor-specific plasma DNA levels varied following treatment with chemotherapy. In mice with established tumors (19 days following tumor injection), tumor-specific plasma DNA levels increased by 63% at 24 hours following a single dose of docetaxel (15 mg/kg), and then declined to 20% below baseline at 72 hours and were 83% lower than baseline 10 days following therapy. In addition, docetaxel treatment resulted in a significant increase in the apoptotic index at 24 hours (p<0.01). Moreover, in two separate therapy experiments using a combination of cytotoxic chemotherapy with anti-angiogenic agents, tumor-specific plasma DNA levels were significantly higher in mice treated with vehicle compared to the treatment groups. The correlation between tumor weight and tumor-specific DNA in these experiments was 0.71-0.76 (p<0.01). CONCLUSIONS: Our results indicate that tumor-specific CFDNA levels correlate with increasing tumor burden and decline following therapy. Thus, tumor-specific DNA may be a useful surrogate biomarker of therapeutic response and should be evaluated in future clinical trials.

Animals↗

PubMed2026

Liquid Biopsy of HPV Cell-Free DNA Enables Blood-Based Early Detection and Molecular Stratification of HPV-Associated Cancer and Precancer Stages.

Liquid biopsies targeting circulating tumor DNA enable noninvasive cancer detection but lack sensitivity in pre- and early- cancer stages, where clinical benefits would be greatest. Human papillomavirus (HPV) causes six cancer types, accounting for 5% of all cancers worldwide. Targeting HPV cell-free (cf)DNA offers a compelling opportunity to overcome current liquid biopsy constraints due to its unique tumor-specific origin, lack of sequence homology to the human genome, and the high viral-to-human copy ratio per cell. Utilizing HPV-associated anal cancer and precancer as a model, here we applied a custom, multi-feature HPV whole-genome liquid biopsy to biobanked and prospective screening cohorts spanning the HPV infection-precancer-cancer continuum. HPV cfDNA was detected years before cancer diagnosis and as early as the infection stage, with increasing detection as stages advanced. Genomic hallmarks of HPV malignancy, including HPV integration, PIK3CA mutations, and 3q amplification, were detected exclusively in cancer, while precancers exhibited distinct HPV genotypes. Fragmentomics analysis of HPV cfDNA revealed stage-informative signatures reflecting viral epigenetic changes during carcinogenesis. A unified classifier incorporating genomic and fragmentomics features achieved a mean AUC of 0.77 for identifying cancer and high-grade precancer, stages requiring clinical intervention. Together, these findings demonstrate the feasibility of blood-based screening and molecular risk stratification for HPV-associated cancer and precancer.

Journal Article↗

PubMed2025

Diffusely metastatic glioblastoma with FGFR3::TACC3 fusion: cell-free DNA fragmentation analyses and molecular characterization of matched primary and metastatic tumor sites.

Extracranial metastasis of IDH-wildtype glioblastoma is very rare and poorly understood at the molecular level. We report a case of FGFR3::TACC3 fusion IDH-wildtype glioblastoma in a 61-year-old male, whose preoperative blood sample showed highly aberrant cfDNA fragmentation patterns, which could be suggestive of early systemic dissemination, undetected by standard-of-care imaging of his body. Eleven months post-resection and adjuvant therapy, he developed widespread extracranial metastases. Comprehensive molecular profiling of matched primary and metastatic tumors revealed broadly conserved genomic, transcriptomic, and copy number landscapes, with the metastasis harboring an additional ERCC6 deletion and enriched expression of receptor tyrosine kinase signaling genes. These findings provide rare insight into the genetic continuity and evolution underlying IDH-wildtype glioblastoma metastasis.

Humans↗

PubMed2026

How advances in machine learning drive early detection and risk prediction of early-onset colorectal cancer.

Early-onset colorectal cancer (EOCRC), defined as colorectal cancer diagnosed before age 50, is rising across high- and middle-income settings whilst organised screening stays anchored to older age thresholds. Blood-based liquid biopsy, combined with machine learning, is the most plausible route to early detection in this group because it does not depend on bowel preparation, endoscopy capacity, or adherence to stool-based testing. The gap is structural: incidence climbs fastest in the population below the age at which any guideline-endorsed modality is offered. The analytical challenge is that early-stage tumour-derived signals in plasma are low in abundance and distributed across heterogeneous molecular layers: circulating tumour DNA mutations, aberrant methylation, cfDNA fragmentomics, and small non-coding RNA. Machine learning converts these into a single calibrated probability. This review examines where artificial intelligence (AI)-driven liquid biopsy genuinely adds diagnostic value in EOCRC, distinguishes components in which learned models are decorative from those in which they are mechanistically necessary, and identifies the validation deficit separating research cohorts from deployable clinical tools. It summarises the first-generation tools used clinically for early detection and post-treatment monitoring, then considers analytes from exosome-bound microRNAs to long-read whole-genome sequencing of circulating plasma DNA, which reads cytosine modification natively, resolves methylation and fragmentation on single molecules, and characterises structural events short reads cannot anchor. Any analyte can feed a learned model, but more diverse input yields better discrimination. The central argument is that approved, guideline-included blood tests were validated in populations aged 45 and above, and their performance in younger patients cannot be assumed.

cfDNA fragmentomics↗

PubMed2022

Direct capture and sequencing reveal ultra-short single-stranded DNA in biofluids.

Cell-free DNA (cfDNA) has become the predominant analyte of liquid biopsy; however, recent studies suggest the presence of subnucleosomal-sized DNA fragments in circulation that are likely single-stranded. Here, we report a method called direct capture and sequencing (DCS) tailored to recover such fragments from biofluids by directly capturing them using short degenerate probes followed by single strand-based library preparation and next-generation sequencing. DCS revealed a new DNA population in biofluids, named ultrashort single-stranded DNA (ussDNA). Evaluation of the size distribution and abundance of ussDNA manifested generality of its presence in humans, animal species, and plants. In humans, red blood cells were found to contain abundant ussDNA; plasma-derived ussDNA exhibited modal size at 50 nt. This work reports the presence of an understudied DNA population in circulation, and yet more work is awaiting to study its generation mechanism, tissue of origin, disease implications, etc.

Biological sciences↗

PubMed2026

Exercise-associated epigenetic remodeling and TCR repertoire dynamics in Lynch syndrome carriers.

Lynch syndrome (LS) carriers are at elevated cancer risk. Emerging evidence suggests that exercise may serve as a non-pharmacologic preventive strategy, yet the epigenetic and immunological mechanisms underlying its protective effects in this population remain unclear. Here, we perform integrative multi-omics profiling of DNA methylation, gene expression, and the T cell receptor (TCR) repertoire in LS carriers undergoing a 52-week aerobic cycling intervention. We identify compartment-specific DNA methylation changes, including innate immune activation in cfDNA and oncogenic pathway repression in tissue. Integrative transcriptomic analysis highlights ISL1 as a key exercise-repressed, epigenetically regulated gene, and identifies FLCN as a colorectal cancer (CRC)-associated methylation target. TCR analysis reveals an exercise-associated increase in systemic repertoire diversity and tissue-specific clonal convergence, thus suggesting antigen-driven recruitment. Collectively, these findings uncover epigenetic and immune remodeling as potential mechanisms of exercise-mediated protection in LS.

Lynch syndrome↗

PubMed2026

fRagmentomics: an R package for integrating cell-free DNA fragment features with mutational status to support liquid biopsy interpretation.

SUMMARY: Liquid biopsy offers a non-invasive approach to study tumor-derived genetic material circulating in plasma. Beyond genetic alterations, the fragmentomic features of cell-free DNA-such as fragment size, genomic position, and end-motifs-provide valuable insights into the biological and clinical context of DNA release. fRagmentomics is a user-friendly R package designed to characterize cfDNA fragments overlapping one or multiple small mutations of any type, starting from an aligned sequencing file (BAM). It supports multiple mutation input formats, accommodates one-based and zero-based genomic conventions, resolves mutation representation ambiguities, and accepts any reference file in FASTA format. For each fragment overlapping a mutation of interest, fRagmentomics outputs fragment-level features including its fragment size, end-motifs, and mutational status, along with additional fragment-level or read-level information. The package implements an indel-aware and optionally soft-clip-preserving fragment size computation that improves accuracy over conventional size estimates based solely on aligned positions. AVAILABILITY AND IMPLEMENTATION: fRagmentomics is licensed under GNU General Public License v3.0 and available at https://github.com/ElsaB-Lab/fRagmentomics, https://anaconda.org/elsab-lab/r-fragmentomics and https://bioconductor.org/packages/fRagmentomics, with documentation and a tutorial. CONTACT: yoann.pradat@gustaveroussy.fr, elsa.bernard@gustaveroussy.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Software↗

PubMed2026

Evidence for the prognostic value of TP53 mutations in circulating tumor DNA across solid malignancies: a systematic review and meta-analysis.

BACKGROUND: The purpose of this meta-analysis study is to provide evidence for the clinical utility of TP53 mutations in circulating tumor DNA (ctDNA) as a prognostic biomarker. METHODS: We searched the PubMed, Embase, Cochrane, and Web of Science databases (last update May 2025) for studies on TP53 mutations in ctDNA or cfDNA as prognosis overall survival and in solid tumors. A total of 21 studies that met the criteria were utilized and data was collected regarding the authors, year of publication, study design, site of the study, number of patients, detection, mutation sample size and outcome measures were collected. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the study, and meta-analysis was done by using STATA 16.0. Effect sizes were in the form of hazard ratios (HR) that had 95% confidence intervals (CI). The models used were fixed-effects and random-effects based on heterogeneity. Funnel plots, and Egger's test was used to measure publication bias, and sensitivity analysis conducted through a leave-one-out method. RESULTS: A total of 21 studies (2,685 TP53-mutated patients, one unreported) showed: Mutated patients had worse progression-free survival (PFS) (HR=2.10, p=0.000; 12 studies, heterogeneity resolved after excluding Yoshida 2023), shorter OS (HR=1.74, p=0.014; 9 studies), and reduced DFS (HR=1.73, p=0.007; 3 studies), but RFS (2 items) showed no statistically significant differences. Subgroup analyses revealed: Prospective studies showed stronger PFS (HR=2.14 vs retrospective 1.90) with Japanese subgroup HR=4.90; Lung/liver cancers had higher HRs than breast. Prospective OS HR=2.25 (lung 3.14, endometrial 0.75). Retrospective DFS HR=1.89 vs Japanese breast RFS HR=4.00. Heterogeneity originated from study design, region, and cancer type variations, with no significant publication bias (Egger's test p>0.05). CONCLUSION: Current evidence suggests that TP53 mutations detected in ctDNA are significantly associated with poor prognosis in various solid tumors, particularly lung cancer. The association is robust for PFS and OS, though high heterogeneity and biological complexity warrant cautious interpretation. These findings support the potential incorporation of ctDNA-based TP53 mutation status into clinical prognostic assessment systems as an adjunctive parameter; however, further standardization of detection protocols, functional annotation of mutation types (e.g., LOF vs. GOF), incorporation of VAF and clonality analysis, and validation in large prospective multicenter cohorts are needed before routine clinical implementation. PROSPERO REGISTRATION NUMBER: CRD420251021095.

Humans↗

PubMed2025

Visualization using NIPTviewer support the clinical interpretation of noninvasive prenatal testing results.

BACKGROUND: Noninvasive prenatal testing (NIPT) is increasingly used to screen for fetal chromosomal aneuploidy by analyzing cell-free DNA (cfDNA) in peripheral maternal blood. The method provides an opportunity for early detection of large genetic abnormalities without an increased risk of miscarriage due to invasive procedures. Commercial applications for use at clinical laboratories often take advantage of DNA sequencing technologies and include the bioinformatic workup of the sequence data. The interpretation of the test results and the clinical report writing, however, remains the responsibility of the diagnostic laboratory. In order to facilitate this step, we developed NIPTviewer, a web-based application to visualize and guide the interpretation of NIPT data results. RESULTS: NIPTviewer has a database functionality to store the NIPT results and a web interface for user interaction and visualization. The application has been implemented as part of a novel analysis pipeline for NIPT in a diagnostic laboratory at Uppsala University Hospital. The validation data set included 84 previously analyzed plasma samples with known results regarding chromosomes 13, 18, 21, X and Y. They were sequenced in six different experiments, uploaded to NIPTviewer and assigned to a clinical laboratory geneticist for interpretation. The results of all previously analyzed samples were replicated. CONCLUSION: NIPTviewer facilitates NIPT results interpretation and has been implemented as part of a NIPT analysis routine that was accredited by the national accreditation body for Sweden (Swedac).

Humans↗

PubMed2005

Optimized real-time quantitative PCR measurement of male fetal DNA in maternal plasma.

BACKGROUND: Circulating fetal DNA (cfDNA) in maternal plasma has been measured to investigate its possible relationship with pregnancy-related disorders, including fetal trisomy 21 and preeclampsia. The circulating concentrations of single-copy fetal genes, however, are close to the detection limits of PCR methods. METHODS: We optimized a protocol for the real-time quantitative PCR amplification of the multicopy sequence DYS14 on the Y-chromosome. This was compared with an established real-time PCR assay for the single-copy SRY gene. RESULTS: By probit regression analysis, the measurements of male DNA by the DYS14 assay had a 10-fold lower detection limit (0.4 genome equivalents) than did measurements of SRY. For plasma samples from women in the first trimester of pregnancy, imprecision (CV) was 2%-22% when amplifying DYS14 compared with 26%-140% for SRY. CONCLUSIONS: The low copy numbers of fetal DNA in plasma of women in the first trimester of pregnancy cannot be measured precisely when targeting single-copy sequences. Better results are obtained by amplifying a sequence that is present in multiple copies per male genome.

Chromosomes, Human, Y↗

PubMed2025

Analytical and clinical performance validation of HPV-SEQ, a novel NGS-based liquid biopsy platform for detection and quantification of human papilloma virus circulating tumor DNA.

BACKGROUND: Human papillomavirus (HPV) is the primary causative driver of oropharyngeal squamous cell carcinoma (OPSCC). Accurate detection of HPV-DNA is critical for risk stratification and management of OPSCC. However, assays designed to detect HPV in primary tumors do not allow monitoring of HPV-DNA over time, whereas commercially available droplet digital PCR-based methods for assessment of circulating cell free (cf)HPV-DNA in plasma remain suboptimal, hindering adaptation into clinical practice. We have developed HPV-SEQ, a novel next-generation-sequencing (NGS) based method for detection and quantification of HPV16/18 DNA in plasma of patients with OPSCC. METHODS: The assay uses primers targeting the L1 gene of HPV16 and HPV18 viral genomes and strain specific calibrators at a defined concentration to determine the ratio of native HPV to a known standard, enabling accurate reporting of patient-derived HPV16/18 viral load in a sample. This study was conducted using two different patient populations in addition to healthy donors and contrived material. All experiments were performed to fulfill several applicable analytical, performance and validation guidelines. RESULTS: A thorough analytical characterization and clinical validation of this platform demonstrates that HPV-SEQ detects cfHPV-DNA with exceptional limit of quantification and high precision, providing a foundation for integrating this platform into clinical settings. CONCLUSIONS: This ultra-sensitive HPV profiling method with optimal analytical performance may represent a significant advancement in risk stratification, treatment management, and post-treatment surveillance for patients with OPSCC.

Humans↗

PubMed2025

Serum, Cell-Free, HPV-Human DNA Junction Detection and HPV Typing for Predicting and Monitoring Cervical Cancer Recurrence.

Almost all cervical cancers are caused by human papillomaviruses (HPVs). In most cases, HPV DNA is integrated into the human genome. We found that tumor-specific, HPV-human DNA junctions are detectable in serum cell-free DNA of a fraction of cervical cancer patients at the time of initial treatment and/or at six months following treatment. Retrospective analysis revealed these junctions were more frequently detectable in women in whom the cancer later recurred. We also found that cervical cancers caused by HPV types outside of phylogenetic clade α9 had a higher recurrence frequency than those caused by α9 types in both our study and The Cancer Genome Atlas cervical cancer database, despite the higher prevalence of α9 types including HPV16 in cervical cancer. Thus, HPV-human DNA junction detection in serum cell-free DNA and HPV type determination in tumor tissue may help predict recurrence risk. Screening serum cell-free DNA for junctions may also offer an unambiguous, non-invasive means to monitor absence of recurrence following treatment.

DNA integration↗