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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↗
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↗
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)↗
PubMed2026

Non-invasive screening in hereditary cancer: a randomized controlled trial to test cell-free DNA-based early detection in the CHARM consortium.

Individuals with hereditary cancer syndromes are born with germline genetic variants that significantly increase their lifetime risk of developing multiple cancers. Cancer rates and overall mortality can be reduced with intensive surveillance to facilitate early cancer detection. However, participating in diagnostic imaging and endoscopy surveillance programs is often time-consuming, overwhelming, inconvenient, and anxiety-inducing. To improve this, multi-cancer early detection tests are being developed using cell-free DNA (cfDNA) sequencing analysis to detect cancers with more sensitivity than conventional screening methods. Our community (the CHARM consortium: Cell-free DNA in Hereditary And high-Risk Malignancies) has been exploring the use of cfDNA sequencing in hereditary cancer, and has launched the CHARM2 prospective randomized controlled trial, which is enrolling 1000 participants with Hereditary Breast and Ovarian Cancer, Lynch syndrome, Li-Fraumeni syndrome, Neurofibromatosis type 1 and Hereditary Diffuse Gastric Cancer to improve equitable access, early detection and surveillance for high-risk individuals. All participants will have screening as per conventional syndrome-specific surveillance recommendations. Half the participants (experimental cohort) will also have cfDNA analysis at least three times a year, with abnormal results triggering dedicated clinical imaging and diagnostic evaluation, and heightened surveillance. Vetted by our patient advisors, validated patient-reported outcome and experience measures assessing participant psychosocial outcomes, engagement, and test preferences will be administered to both arms. Our goal is to inform if and how cfDNA analysis could be implemented into routine clinical care and offer a path to equitable and more convenient cancer screening for all high-risk Canadians.

Female↗
PubMed2026

Detection and classification of lymphoma from cell-free methylome data.

Diagnosing lymphoma traditionally relies on invasive tissue biopsies, which can yield insufficient material for histopathological evaluation and carry a risk of complications. Minimally invasive assessment of cell-free DNA (cfDNA) in plasma offers a promising alternative for lymphoma detection that could aid the rapid evaluation of malignant vs. benign lymphadenopathy. Here, we examine the methylome of plasma samples from 165 lymphoma patients and 47 controls using cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq). Differential methylation analysis of a discovery cohort (142 out of 212 samples) revealed 13,897 hypermethylated genomic regions in lymphoma cases, which were subsequently used for classification using regularized binomial generalized linear models. In a validation cohort (70 samples), we identified lymphomas with an accuracy of 0.89, positive predictive value (PPV) of 0.90 and negative predictive value (NPV) of 0.87. cfDNA methylation scores were significantly associated with orthogonal measures of cfDNA tumor burden, stage, and clinical outcomes. Our results highlight the feasibility of cfDNA methylation profiling as a sensitive and minimally invasive method for detecting lymphoma.

Journal Article↗
PubMed2026

Prenatal cell-free DNA methylome detects association with autism and maternal obesity.

Early identification of autism spectrum disorder (ASD) remains a critical challenge, particularly in utero when non-genetic factors such as maternal obesity (MO) are implicated. Here, we report results of whole-genome bisulfite sequencing of cell-free DNA (cfDNA) from third-trimester maternal plasma in a high-likelihood ASD pregnancy cohort associated with child (3 y) ASD diagnosis and/or MO. Differentially methylated regions (DMRs) between ASD and control cfDNA are strongly enriched for synaptic functions and genes previously implicated in ASD. These cfDNA ASD DMRs recapitulate those observed in ASD placenta and postmortem cortex and significantly overlap with MO DMRs. Our findings establish cfDNA methylation derived from maternal blood as a minimally invasive window into fetal brain ASD etiology, providing a framework for future mechanistic and early intervention studies. Future studies could investigate additional prenatal environmental exposures interacting with genetics during neurodevelopment.

Journal Article↗
PubMed2026

Epigenetic Liquid Biopsy Enables Universal Mutation-Agnostic Molecular Surveillance for High-Risk Neuroblastoma.

PURPOSE: Liquid biopsy monitoring in pediatric solid tumors is limited by low mutational burden and lack of trackable genomic drivers. We sought to develop a mutation-agnostic, methylation-based liquid biopsy framework enabling universal molecular surveillance of high-risk neuroblastoma. EXPERIMENTAL DESIGN: Using whole-genome Oxford Nanopore Technologies sequencing of high-risk neuroblastoma tumors, we compared tumor-derived methylation profiles with a comprehensive atlas of normal human cell types and identified 72 neuroblastoma-specific differentially methylated regions (meNBL) that were reliably detectable in cell-free DNA (cfDNA). Marker robustness and specificity were validated using independent neuroblastoma methylation datasets and assessed against methylation profiles from other cancer types. We established neuroblastoma as a distinct methylation entity within the reference atlas by integrating a panel of 25 meNBLs, enabling quantitative estimation of tumor-derived cfDNA. Assay performance was evaluated across diagnostic, remission, relapse, and healthy control samples and compared with mutation-based and copy number-based approaches. RESULTS: Neuroblastoma-derived cfDNA was consistently detected at diagnosis and relapse but was absent in healthy controls and during confirmed remission. Methylation-based deconvolution demonstrated high specificity, with no detectable background signal in controls, and improved performance relative to copy number-based tumor fraction estimation. Longitudinal profiling enabled early molecular detection of relapse and reliable disease monitoring. CONCLUSIONS: We establish a robust, mutation-independent methylation-based liquid biopsy strategy for neuroblastoma that enables accurate, quantitative disease monitoring across all high-risk patients, including those lacking trackable genomic alterations. This approach supports the clinical translation of methylation-based cfDNA deconvolution as a broadly applicable platform for pediatric precision oncology.

Humans↗
PubMed2006

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

DNA of fetal origin is present in the plasma of pregnant women. The quantitative measurement of circulatory fetal DNA (cfDNA) by real-time quantitative PCR (qPCR) has been applied to investigate a possible correlation between increased levels and pregnancy-related disorders. However, as the levels of cfDNA are close to the detection limit (LOD) of the method used, the measurements may not be reliable. This is also problematic for the evaluation of preanalytical steps, such as DNA extraction and cfDNA enrichment by size separation. We optimized a protocol for the qPCR analysis of the multi-copy sequence DYS14 on the Y chromosome. This was compared with an established assay for the single-copy SRY gene. Probit regression analysis showed that the limit of detection (LOD) of the DYS14 assay, (0.4 genome equivalents (GE)) and limit of quantification (LOQ) were 10-fold lower in comparison to SRY (4 GE). The levels of cfDNA obtained from the first trimester of pregnancy could be quantified with high precision by the DYS14 assay (CV below 25%) as opposed to the SRY measurements (26-140%). Additionally, fetal sex was correctly determined in all instances. The low copy numbers of fetal DNA in plasma of women in the first trimester of pregnancy can be measured reliably, targeting the DYS14 that is present in multiple copies per Y chromosome.

DNA↗
PubMed2026

Non-invasive embryo assessment: Cell-free DNA-based genetic testing and amino acid metabolomics in relation to morphology: A case-control study.

BACKGROUND: Cell-free DNA (cfDNA) in spent culture medium (SCM) offers a non-invasive option for preimplantation genetic testing, but its low concentration and fragmentation reduce clinical reliability. Combining genetic assessment with metabolomic profiling may provide complementary information about embryo competence. OBJECTIVE: This study assessed pre-analytical cfDNA processing workflows and examined whether SCM amino acid metabolic patterns could act as practical markers of embryo quality. MATERIALS AND METHODS: In this case-control study (2021-2023), 90 embryos were evaluated using fluorescence in situ hybridization or array comparative genomic hybridization. SCM samples underwent rapid boiling, silica-based purification, or whole-genome amplification (WGA). Sex determination was performed using quantitative polymerase chain reaction (qPCR). For cfDNA quality control and aneuploidy screening, the multiplex IRFiling kit and quantitative fluorescent polymerase chain reaction (QF-PCR) were used. Amino acid profiles across embryonic developmental stages and quality grades were quantified via liquid chromatography-tandem mass spectrometry. RESULTS: Rapid boiling resulted in complete failure of DNA amplification. Conversely, silica-based purification yielded 70.0% concordance for qPCR-based sexing and 56.7% for QF-PCR. WGA achieved the highest efficacy (73.3% qPCR and 56.7% QF-PCR concordance), although quality control checks flagged occasional misclassifications. LC-MS/MS profiling revealed significantly elevated alanine and arginine levels in tripronuclear embryos. Furthermore, high-quality blastocysts exhibited elevated glutamic acid levels alongside a pronounced overall depletion of extracellular amino acids compared to low-quality counterparts and controls. CONCLUSION: WGA improves cfDNA detectability and qPCR accuracy compared with boiling or purification, but remains inadequate as a standalone screening approach. SCM amino acid profiling provides informative, complementary metabolic signatures of developmental competence, supporting a multimodal strategy for non-invasive embryo assessment.

Amino acid metabolism↗
PubMed2026

Baseline Plasma Cell-Free and Circulating Tumor DNA Across Lymphoma Subtypes and Its Prognostic Impact in Diffuse Large B-Cell Lymphoma.

BACKGROUND: Circulating tumor DNA (ctDNA) analysis enables real‑time assessment of the tumor burden and genomic complexity in lymphomas. However, real‑world evidence across lymphoma subtypes is limited. METHODS: We analyzed cell‑free DNA (cfDNA) and ctDNA data from 336 consecutive patients with newly diagnosed Hodgkin or non-Hodgkin lymphoma in 2022 and evaluated their prognostic impact in diffuse large B‑cell lymphoma (DLBCL). RESULTS: We detected somatic alterations in 248 of 336 patients (73.8%). DLBCL and follicular lymphoma showed the highest variant prevalences and ctDNA burdens. Epigenetic regulators, including KMT2D, CREBBP, TET2, and HIST1H1E, constituted the dominant class of genes with recurrent alterations. Plasma variant profiles closely mirrored publicly available, tissue‑based next-generation sequencing datasets. The baseline ctDNA burden correlated with adverse clinical features, and ctDNA positivity was associated with failure to achieve complete remission. In DLBCL, elevated cfDNA (top quartile) and a high International Prognostic Index (IPI) were independently associated with shorter overall and progression‑free survival. However, the total variant count per patient was not significantly associated with survival after adjustment. CONCLUSIONS: Baseline plasma cfDNA and ctDNA assessments are feasible in routine practice and recapitulate tissue-variant landscapes. Elevated cfDNA concentrations-but not the total variant count-were independently associated with survival in DLBCL, providing prognostic information beyond the IPI and supporting integration of plasma-based biomarkers into multiparameter risk models. Gene‑level ctDNA associations should be regarded as exploratory and hypothesis‑generating.

Cell-free DNA↗
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

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

Cell-free DNA methylation biomarkers for the early detection and tumor burden monitoring of gastric cancer.

Development of sensitive biomarkers is required to achieve early detection and tumor burden monitoring in gastric cancer (GC). We performed genome-wide methylation sequencing on 78 tissue and 241 plasma samples from 171 GC patients and 114 healthy controls from two independent clinical centers. Differentially methylated regions (DMRs) were screened using paired GC and normal tissues, and refined through cfDNA profiles with LASSO regression to construct a cfDNA-based biomarker, the GCML-score. The GCML-score, consisting of 13 DMRs, demonstrated excellent diagnostic performance (AUC: 0.95/0.99/0.95 overall and 0.96/0.99/0.82 in early GC for training/internal validation/external validation cohorts). In 12 patients receiving neoadjuvant chemotherapy, dynamic changes in GCML-score were consistent with radiological tumor burden, highlighting its monitoring potential. The GCML-score, derived from genome-wide cfDNA methylation profiling, provides a robust tool for early GC detection and real-time tumor burden monitoring, facilitating improved prognosis and personalized therapeutic strategies.

Journal Article↗
PubMed2025

Platelets sequester extracellular DNA, capturing tumor-derived and free fetal DNA.

Platelets are anucleate blood cells vital for hemostasis and immunity. During cell death and aberrant mitosis, nucleated cells release DNA, resulting in "cell-free" DNA in plasma (cfDNA). An excess of cfDNA is deleterious. Given their ability to internalize pathogen-derived nucleic acids, we hypothesized that platelets may also clear endogenous cfDNA. We found that, despite lacking a nucleus, platelets contained a repertoire of DNA fragments mapping across the nuclear genome. We detected fetal DNA in maternal platelets and cancer-derived DNA in platelets from patients with premalignant and cancerous lesions. As current liquid biopsy approaches utilize platelet-depleted plasma, important genetic information contained within platelets is being missed. This study establishes a physiological role for platelets that has not previously been highlighted, with broad translational relevance.

Female↗
PubMed2025

Evaluation of a biomarker for amyotrophic lateral sclerosis derived from a hypomethylated DNA signature of human motor neurons.

Amyotrophic lateral sclerosis (ALS) lacks a specific biomarker, but is defined by relatively selective toxicity to motor neurons (MN). As others have highlighted, this offers an opportunity to develop a sensitive and specific biomarker based on detection of DNA released from dying MN within accessible biofluids. Here we have performed whole genome bisulfite sequencing (WGBS) of iPSC-derived MN from neurologically normal individuals. By comparing MN methylation with an atlas of tissue methylation we have derived a MN-specific signature of hypomethylated genomic regions, which accords with genes important for MN function. Through simulation we have optimised the selection of regions for biomarker detection in plasma and CSF cell-free DNA (cfDNA). However, we show that MN-derived DNA is not detectable via WGBS in plasma cfDNA. In support of our experimental finding, we show theoretically that the relative sparsity of lower MN sets a limit on the proportion of plasma cfDNA derived from MN which is below the threshold for detection via WGBS. Our findings are important for the ongoing development of ALS biomarkers. The MN-specific hypomethylated genomic regions we have derived could be usefully combined with more sensitive detection methods and perhaps with study of CSF instead of plasma. Indeed we demonstrate that neuronal-derived DNA is detectable in CSF. Our work is relevant for all diseases featuring death of rare cell-types.

Humans↗
PubMed2026

Detecting Androgenetic Origin of the Genome via Single-Nucleotide Polymorphism-Based Cell-Free DNA Screening in Dichorionic Diamniotic Twin Pregnancies With Complete Hydatidiform Moles and a Coexisting Normal Fetus: A Three-Case Report.

What is already known about this topic? ◦. Complete hydatidiform mole with a coexisting normal fetus (CHMCF) refers to a pregnancy in which a normal fetus and a complete mole coexist. ◦. CHMCF is associated with substantial maternal and fetal morbidity, including hemorrhage, severe anemia, hypertensive disorders, hyperthyroidism, prematurity, fetal loss, and an increased risk of gestational trophoblastic neoplasia. What does this study add? ◦. We report three cases of dichorionic diamniotic (DCDA) twin pregnancies with suspected CHMCF, in which single‐nucleotide polymorphism (SNP)–based cell‐free DNA (cfDNA) analysis detected the androgenetic origin of the genome implying concurrent presence of paternal uniparental diploidy and biparental diploidy in maternal plasma. ◦. To our knowledge, this is among the first case series applying SNP‐based cfDNA prospectively in this specific clinical scenario in twin pregnancy. Its prospective dual‐component detection in twins has a potential clinical decision impact on CHMCF.

Journal Article↗
PubMed2026

DNA methylation biomarkers for early detection of ovarian cancer.

Ovarian cancer (OC) remains difficult to detect at an early stage, and current screening approaches using CA125 and transvaginal ultrasonography have not demonstrated sufficient benefit for population screening. DNA methylation is a promising biomarker class because epigenetic alterations may arise early in tumourigenesis, can be detected in circulating cell-free DNA (cfDNA), and may provide tissue-of-origin information. This review critically evaluates recent evidence on DNA methylation biomarkers for early OC detection. PubMed/MEDLINE, Web of Science, and Scopus were searched for studies published between January 2020 and September 2025, supplemented by selected earlier studies of biological or methodological relevance. Evidence was synthesised across single-gene biomarkers, multi-locus panels, genome-wide signatures, assay platforms, and machine-learning classifiers, with emphasis on early-stage performance, histological representation, comparator populations, analytical methodology, and validation design. Single-gene markers such as BRCA1, RASSF1A, OPCML, HOXA9, and HIC1 show variable performance, while multi-gene and classifier-based approaches generally provide stronger discrimination. However, many studies remain limited by retrospective case-control designs, small FIGO stage I-II subsets, predominance of serous disease, and insufficient prospective validation. Integration with CA125 may improve sensitivity but can reduce specificity, which is critical in low-prevalence screening. Clinical translation will therefore require minimal and reproducible methylation signatures, standardised low-input cfDNA workflows, rigorous external validation, and prospective longitudinal evaluation in intended-use populations.

Humans↗