The Biology of Cell-free DNA Fragmentation and the Roles of DNASE1, DNASE1L3, and DFFB

A standardized framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

Fragmentomics features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. A lack of systematic evaluation of biases in feature quantification hinders the adoption of such applications. We compare features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes and validated in 1182 plasma samples from published studies. Our results clarify the variations from library preparation and feature quantification methods. We design the Trim Align Pipeline and cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualization to standardize multi-modal feature engineering and integration for machine learning.

Liquid biopsy in gynecological cancers: a translational framework from molecular insights to precision oncology and clinical practice

Liquid biopsy offers a noninvasive method to identify and monitor tumor-derived biomarkers, including circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes, microRNAs, and tumor-educated platelets, that provide real-time insights into the biological behavior of gynecological cancers. The detection of these markers has the potential to revolutionize cancer management by enabling earlier detection, providing novel data to personalize treatments, and predicting disease recurrence before clinical imaging and predicting disease recurrence before clinical imaging can confirm progression, thereby also guiding complex clinical decision-making. However, because this new "omics" layer introduces additional complexity, it must be fully understood, from its biological rationale to technical development and clinical integration, to prevent confusion or misapplication. That is why, focusing on 14 critical fields of inquiry, our goal is to map the current state of liquid biopsy from bench to bedside while highlighting practical considerations for clinical integration. Each topic integrates recent advances in assay sensitivity, biomarker variability, and data interpretation, underscoring how standardized protocols and robust analytical methods are pivotal for reliable results. We then translate these findings into disease-specific insights, examining how liquid biopsy could refine early detection, minimal residual disease assessment, and therapy guidance in endometrial, cervical, and ovarian cancers. Although several FDA-approved assays and promising commercial tests illustrate the field's rapid evolution, many translational hurdles remain, including the need for harmonized protocols, larger prospective clinical trials, and cost-effectiveness analyses. Crucially, our synthesis clarifies the pivotal role of interdisciplinary collaboration. Oncologists, laboratory scientists, and industry partners must align on standardized procedures and clinically relevant endpoints. Without such coordination, promising biomarkers may remain confined to research settings, limiting their practical benefit. Taken together, our review offers a translational view designed to contextualize liquid biopsy in gynecological oncology.

Integrating Plasma Cell-Free DNA Fragment End Motif and Size with Genomic Features Enables Lung Cancer Detection

Early detection of lung cancer is important for improving patient survival rates. Liquid biopsy using whole-genome sequencing of cell-free DNA (cfDNA) offers a promising avenue for lung cancer screening, providing a potential alternative or complementary approach to current screening modalities. Here, we aimed to develop and validate an approach by integrating fragment and genomic features of cfDNA to enhance lung cancer detection accuracy across diverse populations. Deep learning-based classifiers were trained using comprehensive cfDNA fragmentomic features from participants in multi-institutional studies, including a Korean discovery dataset (218 patients with lung cancer and 2,559 controls), a Korean validation dataset (111 patients with lung cancer and 1,136 controls), and an independent Caucasian validation cohort (50 patients with lung cancer and 50 controls). In the discovery dataset, classifiers using fragment end motif by size, a feature that captures both fragment end motif and size profiles, outperformed standalone fragment end motif and fragment size classifiers, achieving an area under the curve (AUC) of 0.917. The ensemble classifier integrating fragment end motif by size and genomic coverage achieved an improved performance, with an AUC of 0.937. This performance extended to the Korean validation dataset and demonstrated ethnic generalizability in the Caucasian validation cohort. Overall, the development of a deep learning-based classifier integrating cfDNA fragmentomic and genomic features in this study highlights the potential for accurate lung cancer detection across diverse populations. Significance: Evaluating fragment-based features and genomic coverage in cell-free DNA offers an accurate lung cancer screening method, promising improvements in early cancer detection and addressing challenges associated with current screening methods.

Fragmentomics profiling and quantification of plasma Epstein-Barr virus DNA enhance prediction of future nasopharyngeal carcinoma

Fragmentomics analysis of plasma autosomal DNA has shown promise in cancer diagnostics. Here we evaluated the clinical utility of plasma Epstein-Barr virus (EBV) DNA fragmentomics analysis for nasopharyngeal carcinoma (NPC) screening. Among our prospective cohort of approximately 20,000 subjects that underwent two rounds of screening, we analyzed the first-round blood samples of subjects who tested positive for EBV DNA via polymerase chain reaction (PCR) (n = 558). We found that those who subsequently developed NPC in the second round exhibited a distinctive mononucleosomal size pattern, an NPC-associated end motif (specifically, a depletion of CC-motif) and aberrations in methylation identified through fragmentomics-based methylation analysis (FRAGMA). Subjects with these aberrant fragmentomics features and higher quantity of EBV DNA had a relative risk of 87.1 times greater for developing NPC in the second round compared to subjects tested negative for EBV DNA on PCR. These results demonstrate plasma DNA fragmentomics could predict future cancer risk.

Chromatin accessibility states affect transrenal clearance of plasma DNA: Implications for urine-based diagnostics

BACKGROUND

Urinary cell-free DNA (ucfDNA) is a valuable resource for truly non-invasive liquid biopsy. UcfDNA comprises transrenal ucfDNA passing from the bloodstream through the glomeruli and locally shed urinary-tract ucfDNA. Understanding their differences in characteristics may enable new diagnostic applications.

METHODS

We analyzed 136 ucfDNA samples from healthy controls, pregnant women, patients with chronic kidney diseases (CKDs), and bladder cancer using massively parallel sequencing. Fragmentomic characteristics including fragment sizes and 5' end motifs were deduced. The relationship between ucfDNA and chromatin accessibility was examined by overlapping ucfDNA with open chromatin regions (OCRs, lacking histones) and heterochromatin regions (HCRs, tightly packed with histones).

FINDINGS

Compared with urinary-tract ucfDNA, the transrenal ucfDNA was shorter and enriched for C-ends. The transrenal ucfDNA was over-represented in OCRs but depleted in HCRs, indicating an interplay between the glomerular filtration barrier and the effective cfDNA size. In patients with proteinuria (preeclampsia and CKDs), the amount of ucfDNA from HCRs increased, suggesting elevated glomerular permeability of histone-bound plasma DNA molecules. In oncology, the use of hypomethylation signals in HCRs enhanced bladder cancer detection, with an area under the receiver operating characteristic curve of 0.93.

CONCLUSIONS

Chromatin accessibility states impact the transrenal clearance of plasma DNA, likely through the size restriction of the glomerular barrier. This realization has enabled the rational development of novel approaches for detecting or monitoring renal dysfunction and urological cancers.

FUNDING

The Innovation and Technology Commission of the Hong Kong SAR Government (InnoHK initiative) and the Li Ka Shing Foundation supported this study.

Cell-free DNA from clinical testing as a resource of population genetic analysis

As a noninvasive biomarker, cell-free DNA (cfDNA) has achieved remarkable success in clinical applications. Notably, cfDNA is essentially DNA, and conducting whole-genome sequencing (WGS) can yield a wealth of genetic information. These invaluable data should not be confined to one-time use; instead, they should be leveraged for more comprehensive population genetic analysis, including genetic variation spectrum, population structure and genetic selection, and genome-wide association studies (GWASs), among others. Such research findings can, in turn, facilitate clinical practice, enabling more advanced and accurate disease predictions. This review explores the advantages, challenges, and current research areas of cfDNA in population genetics. We hope that this review can serve as a new chapter in the repurposing of cfDNA sequence data generated from clinical testing in population genetics.

Nucleic acid triggers of autoimmunity and autoinflammation

The key role of nucleic acid sensing receptors in the development of autoimmune and autoinflammatory diseases is becoming increasingly apparent. Activation of these sensors has been attributed to the failure of professional scavenger cells to adequately clear cell debris, in many cases due to defective scavenger receptors. However, as now summarized in this review, numerous gain-of-function mutations in the nucleic acid sensing receptors, or in molecules that regulate sensor activity, have now been evaluated in gene-targeted murine strains, and critical components of their downstream pathways have been identified as therapeutic targets. In addition, we are beginning to understand how DNases and RNases play crucial roles in both generating and eliminating the distinct ligands that engage the various nucleic acid sensors. Murine models of disease have further provided important insights regarding the function of and synergy between individual endosomal and cytosolic receptors, as well as cell type restricted functions.

Dynamic profiling of Cell-free DNA fragmentation uncovers postprandial metabolic and immune alterations

BACKGROUND

Food intake affects body homeostasis and significantly changes circulating cell-free DNA (cfDNA). However, the source and elimination of postprandial cfDNA is difficult to trace, and it is unknown whether these changes can be revealed by cfDNA fragmentomics based on liquid biopsy.

METHODS

We performed shallow whole-genome sequencing of 30 plasma samples from 10 healthy individuals at fasting and postprandial (30-min and 2-h time points). We assessed the effect of postprandial states on cfDNA fragment size distribution and utilized deconvolutional analysis of end motifs to determine the potential roles of DNA nucleases in cfDNA fragmentation. We correlated the fragmentation index (defined as the ratio of short-to-long fragments) with gene expression to estimate the relative contribution of various cellular and tissue sources to cfDNA.

RESULTS

Compared to the fasting state, we observed a significant increase in short cfDNA fragments (70-150 bp) and a decrease in long fragments (151-250 bp) at the 30-minute postprandial state, followed by an inverse trend two hours later. Deconvolutional analysis of cfDNA end motifs showed that DNASE1L3 activity decreased at the 30-minute postprandial state, while DNASE1 and DFFB activities increased at the 2-hour postprandial state. We found that the expression of genes related to cellular metabolism and immune responses was upregulated at the postprandial state. Meanwhile, the contribution of cells and tissues involved in metabolic and immune progress to circulating plasma cfDNA was increased.

CONCLUSIONS

The fragmentation of cfDNA is considerably influenced by postprandial states, highlighting the significance of taking postprandial effects into account when evaluating cfDNA as a biomarker. Furthermore, our study reveals the potential application of cfDNA fragmentation features in monitoring metabolic and immune status changes.

Application of Digital Polymerase Chain Reaction (dPCR) in Non-Invasive Prenatal Testing (NIPT)

This article reviews the current applications of the digital polymerase chain reaction (dPCR) in non-invasive prenatal testing (NIPT) and explores its potential to complement or surpass the capabilities of Next-Generation Sequencing (NGS) in prenatal testing. The growing incidence of genetic disorders in maternal-fetal medicine has intensified the demand for precise and accessible NIPT options, which aim to minimize the need for invasive prenatal diagnostic procedures. Cell-free fetal DNA (cffDNA), the core analyte in NIPT, is influenced by numerous factors such as maternal DNA contamination, placental health, and fragment degradation. dPCR, with its inherent precision and ability to detect low-abundance targets, demonstrates robustness against these interferences. Although NGS remains the gold standard due to its comprehensive diagnostic capabilities, its high costs limit widespread use, particularly in resource-limited settings. In contrast, dPCR provides comparable accuracy with lower complexity and expense, making it a promising alternative for prenatal testing.

Performance of cellulose-based card for direct genetic testing of spinal muscular atrophy

BACKGROUND

Spinal muscular atrophy (SMA) is a devastating neuromuscular condition resulting from the loss of the survival motor neuron 1 (SMN1) gene. Precise genetic testing has become essential after the authorization of several potent medications. To achieve this objective, the use of dried blood spot (DBS) has assured convenient and extensive testing from a distance. Nevertheless, developing countries such as Indonesia sometimes lack access to standard filter papers like FTA or Guthrie cards for DBS processing. Here, we aim to develop a cellulose-based card as an alternative filter paper for DBS preparation suitable for the genetic testing of SMA including but not limited to a direct polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and multiplex allele-specific amplification (multi-ASA).

RESULTS

An in-house paper was developed from a 180 gsm cellulose-based paper and was used for DBS preparation. The performance of dried blood spotted on the cellulose-based card (DBSc) was compared to pure genomic DNA (gDNA) isolate and dried blood spotted on FTA cards (DBSf) for genetic testing. The results of the genetic testing of our cellulose-based card were completely matched with those of gDNA and DBSf in both direct PCR-RFLP and Multi-ASA to separate SMN1 from SMN2. In addition, after three months of storing, the DBSc continued to exhibit a clear result, suggesting its high stability for DNA storage.

CONCLUSION

Our cellulose-based card has the potential to be used for DBS carrier and for further genetic testing using PCR. Our findings can assist physicians in sending DBS samples from SMA suspicion cases to genetic testing centers, thereby preventing diagnosis delay or misdiagnosis.

Cell-free epigenomes enhanced fragmentomics-based model for early detection of lung cancer

BACKGROUND

Lung cancer is a leading cause of cancer mortality, highlighting the need for innovative non-invasive early detection methods. Although cell-free DNA (cfDNA) analysis shows promise, its sensitivity in early-stage lung cancer patients remains a challenge. This study aimed to integrate insights from epigenetic modifications and fragmentomic features of cfDNA using machine learning to develop a more accurate lung cancer detection model.

METHODS

To address this issue, a multi-centre prospective cohort study was conducted, with participants harbouring suspicious malignant lung nodules and healthy volunteers recruited from two clinical centres. Plasma cfDNA was analysed for its epigenetic and fragmentomic profiles using chromatin immunoprecipitation sequencing, reduced representation bisulphite sequencing and low-pass whole-genome sequencing. Machine learning algorithms were then employed to integrate the multi-omics data, aiding in the development of a precise lung cancer detection model.

RESULTS

Cancer-related changes in cfDNA fragmentomics were significantly enriched in specific genes marked by cell-free epigenomes. A total of 609 genes were identified, and the corresponding cfDNA fragmentomic features were utilised to construct the ensemble model. This model achieved a sensitivity of 90.4% and a specificity of 83.1%, with an AUC of 0.94 in the independent validation set. Notably, the model demonstrated exceptional sensitivity for stage I lung cancer cases, achieving 95.1%. It also showed remarkable performance in detecting minimally invasive adenocarcinoma, with a sensitivity of 96.2%, highlighting its potential for early detection in clinical settings.

CONCLUSIONS

With feature selection guided by multiple epigenetic sequencing approaches, the cfDNA fragmentomics-based machine learning model demonstrated outstanding performance in the independent validation cohort. These findings highlight its potential as an effective non-invasive strategy for the early detection of lung cancer.

KEYPOINTS

Our study elucidated the regulatory relationships between epigenetic modifications and their effects on fragmentomic features. Identifying epigenetically regulated genes provided a critical foundation for developing the cfDNA fragmentomics-based machine learning model. The model demonstrated exceptional clinical performance, highlighting its substantial potential for translational application in clinical practice.

Artificial intelligence and machine learning in cell-free-DNA-based diagnostics

The discovery of circulating fetal and tumor cell-free DNA (cfDNA) molecules in plasma has opened up tremendous opportunities in noninvasive diagnostics such as the detection of fetal chromosomal aneuploidies and cancers and in posttransplantation monitoring. The advent of high-throughput sequencing technologies makes it possible to scrutinize the characteristics of cfDNA molecules, opening up the fields of cfDNA genetics, epigenetics, transcriptomics, and fragmentomics, providing a plethora of biomarkers. Machine learning (ML) and/or artificial intelligence (AI) technologies that are known for their ability to integrate high-dimensional features have recently been applied to the field of liquid biopsy. In this review, we highlight various AI and ML approaches in cfDNA-based diagnostics. We first introduce the biology of cell-free DNA and basic concepts of ML and AI technologies. We then discuss selected examples of ML- or AI-based applications in noninvasive prenatal testing and cancer liquid biopsy. These applications include the deduction of fetal DNA fraction, plasma DNA tissue mapping, and cancer detection and localization. Finally, we offer perspectives on the future direction of using ML and AI technologies to leverage cfDNA fragmentation patterns in terms of methylomic and transcriptional investigations.

Analysis of a cell-free DNA-based cancer screening cohort links fragmentomic profiles, nuclease levels, and plasma DNA concentrations

The concentration of circulating cell-free DNA (cfDNA) in plasma is an important determinant of the robustness of liquid biopsies. However, biological mechanisms that lead to inter-individual differences in cfDNA concentrations remain unexplored. The concentration of plasma cfDNA is governed by an interplay between its release and clearance. We hypothesized that cfDNA clearance by nucleases might be one mechanism that contributes toward inter-individual variations in cfDNA concentrations. We performed fragmentomic analysis of the plasma cfDNA from 862 healthy individuals, with a cfDNA concentration range of 1.61-41.01 ng/mL. We observed an increase in large DNA fragments (231-600 bp), a decreased frequencies of shorter DNA fragments (20-160 bp), and an increased frequency of G-end motifs with increasing cfDNA concentrations. End motif deconvolution analysis revealed a decreased contribution of DNASE1L3 and DFFB in subjects with higher cfDNA concentration. The five subjects with the highest plasma DNA concentration (top 0.58%) had aberrantly decreased levels of DNASE1L3 protein in plasma. The cfDNA concentration could be inferred from the fragmentomic profile through machine learning and was well correlated to the measured cfDNA concentration. Such an approach could infer the fractional DNA concentration from particular tissue types, such as the fetal and tumor fraction. This work shows that individuals with different cfDNA concentrations are associated with characteristic fragmentomic patterns of the cfDNA pool and that nuclease-mediated clearance of DNA is a key parameter that affects cfDNA concentration. Understanding these mechanisms has facilitated the enhanced measurement of cfDNA species of clinical interest, including circulating fetal and tumor DNA.

Integrating Donor Derived Cell-Free DNA Fraction and Absolute Quantification for Enhanced Rejection Diagnosis in Kidney Transplant Recipients

Background: This study aimed to assess the diagnostic accuracy of combining donor-derived cell-free DNA (dd-cfDNA) fraction and absolute quantification in detecting kidney allograft rejection. Methods: A prospective study was conducted from December 2019 to April 2021 at the First Affiliated Hospital of Sun Yat-sen University. Kidney transplant recipients who underwent biopsy, including cases of T-cell-mediated rejection (TCMR), antibody-mediated rejection (ABMR), and borderline rejection, were included. dd-cfDNA fraction and absolute concentrations were measured, and diagnostic efficacy was evaluated using receiver operating characteristic (ROC) analysis. The double-positive and double-negative methods were applied to assess performance. Results: A total of 50 kidney transplant recipients were included. The dd-cfDNA fraction cutoff of 1.08% achieved 93.33% sensitivity and 91.43% specificity (AUC = 0.95), with an NPV of 96.97% and a PPV of 82.35%. The absolute dd-cfDNA threshold of 32 cp/mL yielded 80.00% sensitivity and 71.43% specificity (AUC = 0.78), with an NPV of 89.29% and a PPV of 54.55%. The double-positive method provided superior accuracy, with a PPV of 91.67% and an NPV of 89.47%, demonstrating 73.33% sensitivity and 97.14% specificity. The double-negative method achieved 100% NPV and 100% sensitivity. Conclusions: Combining dd-cfDNA fraction and absolute quantification improves diagnostic accuracy for kidney transplant rejection, especially ABMR. The double-positive and double-negative approaches show high predictive value, offering potential clinical value for monitoring kidney transplant recipients.

Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer

Diagnosing lung cancer from indeterminate pulmonary nodules (IPLs) remains challenging. In this multi-institutional study involving 2032 participants with IPLs, we integrate the clinical, radiomic with circulating cell-free DNA fragmentomic features in 5-methylcytosine (5mC)-enriched regions to establish a multiomics model (clinic-RadmC) for predicting the malignancy risk of IPLs. The clinic-RadmC yields an area-under-the-curve (AUC) of 0.923 on the external test set, outperforming the single-omics models, and models that only combine clinical features with radiomic, or fragmentomic features in 5mC-enriched regions (p < 0.050 for all). The superiority of the clinic-RadmC maintains well even after adjusting for clinic-radiological variables. Furthermore, the clinic-RadmC-guided strategy could reduce the unnecessary invasive procedures for benign IPLs by 10.9% ~ 35%, and avoid the delayed treatment for lung cancer by 3.1% ~ 38.8%. In summary, our study indicates that the clinic-RadmC provides a more effective and noninvasive tool for optimizing lung cancer diagnoses, thus facilitating the precision interventions.

Aberrant fragmentomic features of circulating cell-free mitochondrial DNA enable early detection and prognosis prediction of hepatocellular carcinoma

BACKGROUND/AIMS

Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA).

METHODS

Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC).

RESULTS

The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively).

CONCLUSION

We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

"Aging Clocks" Based on Cell-Free DNA

Aging is associated with systemic changes in the physiological and molecular parameters of the body. These changes are referred to as biomarkers of aging. Statistical models that link changes in individual biomarkers to biological age are called aging clocks. These tools facilitate a comprehensive evaluation of bodily health and permit the quantitative determination of the rate of aging. A particularly promising area for the development of aging clocks is the analysis of cell-free DNA (cfDNA), which is present in the blood and contains numerous potential biomarkers. This review explores in detail the fragmentomics, topology, and epigenetic landscape of cfDNA as possible biomarkers of aging. The review further underscores the potential of leveraging single-molecule sequencing of cfDNA in conjunction with long-read technologies to simultaneously profile multiple biomarkers, a strategy that could lead to the development of more precise aging clocks.

Modulating cell-free DNA biology as the next frontier in liquid biopsies

Technical advances over the past two decades have enabled robust detection of cell-free DNA (cfDNA) in biological samples. Yet, higher clinical sensitivity is required to realize the full potential of liquid biopsies. This opinion article argues that to overcome current limitations, the abundance of informative cfDNA molecules - such as circulating tumor DNA (ctDNA) - collected in a sample needs to increase. To accomplish this, new methods to modulate the biological processes that govern cfDNA production, trafficking, and clearance in the body are needed, informed by a deeper understanding of cfDNA biology. Successful development of such methods could enable a major leap in the performance of liquid biopsies and vastly expand their utility across the spectrum of clinical care.

Early detection of colorectal cancer using aberrant circulating cell-free mitochondrial DNA fragmentomics

BACKGROUND

Early detection of colorectal cancer (CRC) is crucial for improving the survival rates of patients.

OBJECTIVE

We aimed to develop a novel strategy for early CRC detection using the fragmentomic features of circulating cell-free mitochondrial DNA (ccf-mtDNA).

DESIGN

Here, a total of 1147 participants, including 478 healthy controls (HCs), 112 patients with advanced adenomas (AAs) and 557 patients with CRC, were enrolled from five hospitals and plasma samples were collected for capture-based ccf-mtDNA sequencing.

RESULTS

Our data analysis revealed significantly aberrant ccf-mtDNA fragmentomic features in patients with CRC and AA when compared with HCs. Then, a CRC detection (CD) model was constructed based on the fragmentomic features of ccf-mtDNA from 246 patients with CRC and 168 HC in the training cohort, showing area under the curve of 0.9863, sensitivity of 92.68% and specificity of 93.45%. Both internal and two external validation cohorts demonstrated the excellent capacity of CD model in distinguishing patients with early-stage CRC from HCs, greatly surpassing the performance of serum biomarkers. Furthermore, our CD model can also detect patients with AA with a sensitivity of 79.35% in AA cohort 1 and 85.00% in AA cohort 2.

CONCLUSION

In conclusion, based on aberrant ccf-mtDNA fragmentomic features, a novel and non-invasive approach was established for the detection of patients with early-stage CRC or AA, with high performance.

A promising application of kidney-specific cell-free DNA methylation markers in real-time monitoring sepsis-induced acute kidney injury

Sepsis-induced acute kidney injury (SI-AKI) is a common clinical syndrome that is associated with high mortality and morbidity. Effective timely detection may improve the outcome of SI-AKI. Kidney-derived cell-free DNA (cfDNA) may provide new insight into understanding and identifying SI-AKI. Plasma cfDNA from 82 healthy individuals, 7 patients with sepsis non-acute kidney injury (SN-AKI), and 9 patients with SI-AKI was subjected to genomic methylation sequencing. We deconstructed the relative contribution of cfDNA from different cell types based on cell-specific methylation markers and focused on exploring the association between kidney-derived cfDNA and SI-AKI.Based on the deconvolution of the cfDNA methylome: SI-AKI patients displayed the elevated cfDNA concentrations with an increased contribution of kidney epithelial cells (kidney-Ep) DNA; kidney-Ep derived cfDNA achieved high accuracy in distinguishing SI-AKI from SN-AKI (AUC = 0.92, 95% CI 0.7801-1); the higher kidney-ep cfDNA concentrations tended to correlate with more advanced stages of SI-AKI; strikingly, SN-AKI patients with potential kidney damage unmet by SI-AKI criteria showed higher levels of kidney-Ep derived cfDNA than healthy individuals. The autonomous screening of kidney-Ep (n = 24) and kidney endothelial (kidney-Endo, n = 12) specific methylation markers indicated the unique identity of kidney-Ep/kidney-Endo compared with other cell types, and its targeted assessment reproduced the main findings of the deconvolution of the cfDNA methylome. Our study first demonstrates that kidney-Ep- and kidney-Endo-specific methylation markers can serve as a novel marker for SI-AKI emergence, supporting further exploration of the utility of kidney-specific cfDNA methylation markers in the study of SI-AKI.

Aberrant fragmentomic features of circulating cell-free mitochondrial DNA as novel biomarkers for multi-cancer detection

Fragmentomic features of circulating cell free mitochondrial DNA (ccf-mtDNA) including fragmentation profile, 5' end base preference and motif diversity are poorly understood. Here, we generated ccf-mtDNA sequencing data of 1607 plasma samples using capture-based next generation sequencing. We firstly found that fragmentomic features of ccf-mtDNA were remarkably different from those of circulating cell free nuclear DNA. Furthermore, region-specific fragmentomic features of ccf-mtDNA were observed, which was associated with protein binding, base composition and special structure of mitochondrial DNA. When comparing to non-cancer controls, six types of cancer patients exhibited aberrant fragmentomic features. Then, cancer detection models were built based on the fragmentomic features. Both internal and external validation cohorts demonstrated the excellent capacity of our model in distinguishing cancer patients from non-cancer control, with all area under curve higher than 0.9322. The overall accuracy of tissue-of-origin was 89.24% and 87.92% for six cancer types in two validation cohort, respectively. Altogether, our study comprehensively describes cancer-specific fragmentomic features of ccf-mtDNA and provides a proof-of-principle for the ccf-mtDNA fragmentomics-based multi-cancer detection and tissue-of-origin classification.

Cell-free placental DNA: What do we really know?

Cell-free placental DNA (cfpDNA) is present in maternal circulation during gestation. CfpDNA carries great potential as a research and clinical tool as it provides a means to investigate the placental (epi)genome across gestation, which previously required invasive placenta sampling procedures. CfpDNA has been widely implemented in the clinical setting for noninvasive prenatal testing (NIPT). Despite this, the basic biology of cfpDNA remains poorly understood, limiting the research and clinical utility of cfpDNA. This review will examine the current knowledge of cfpDNA, including origins and molecular characteristics, highlight gaps in knowledge, and discuss future research directions.

The biological characteristics of long cell-free DNA in spent embryos culture medium as noninvasive biomarker in in-vitro embryo selection

An improved understanding of the cfDNA fragmentomics has proved it as a promising biomarker in clinical applications. However, biological characteristics of cfDNA in spent embryos culture medium (SECM) remain unsolved obstacles before the application in non-invasive in-vitro embryo selection. In this study, we developed a Tn5 transposase and ligase integrated dual-library construction sequencing strategy (TDual-Seq) and revealed the fragmentomic profile of cfDNA of all sizes in early embryonic development. The detected ratio of long cfDNA (>500 bp) was improved from 4.23 % by traditional NGS to 12.80 % by TDual-Seq. End motif analysis showed long cfDNA molecules have a more dominance of fragmentation intracellularly in apoptotic cells with higher predominance of G-end, while shorter cfDNA undergo fragmentation process both intracellularly and extracellularly. Moreover, the mutational pattern of cfDNA and the correlated GO biological process were well differentiated in cleavage and blastocyst embryos. Finally, we developed a multiparametric index (TQI) that employs the fragmentomic profiles of cfDNA, and achieved an area under the ROC curve of 0.927 in screening top quality embryos. TDual-Seq strategy has facilitated characterizing the fragmentomic profile of cfDNA of all sizes in SECM, which are served as a class of non-invasive biomarkers in the evaluation of embryo quality in in-vitro fertilization. And this improved strategy has opened up potential clinical utilities of long cfDNA analysis.

Methylation-Associated Nucleosomal Patterns of Cell-Free DNA in Cancer Patients and Pregnant Women

BACKGROUND

Cell-free DNA (cfDNA) analysis offers an attractive noninvasive means of detecting and monitoring diseases. cfDNA cleavage patterns within a short range (e.g., 11 nucleotides) have been reported to correlate with cytosine-phosphate-guanine (CpG) methylation, allowing fragmentomics-based methylation analysis (FRAGMA). Here, we adopted FRAGMA to the extended region harboring multiple nucleosomes, termed FRAGMAXR.

METHODS

We profiled cfDNA nucleosomal patterns over the genomic regions from -800 to 800 bp surrounding differentially methylated CpG sites, harboring approximately 8 nucleosomes, referred to as CpG-associated cfDNA nucleosomal patterns. Such nucleosomal patterns were analyzed by FRAGMAXR in cancer patients and pregnant women.

RESULTS

We identified distinct cfDNA nucleosomal patterns around differentially methylated CpG sites. Compared with subjects without cancer, patients with hepatocellular carcinoma (HCC) showed reduced amplitude of nucleosomal patterns, with a gradual decrease over tumor stages. Nucleosomal patterns associated with differentially methylated CpG sites could be used to train a machine learning model, resulting in the detection of HCC patients with an area under the receiver operating characteristic curve of 0.93. We further demonstrated the feasibility of multicancer detection using a dataset comprising lung, breast, and ovarian cancers. The tissue-of-origin analysis of plasma cfDNA from pregnant women and cancer patients revealed that the placental DNA and tumoral DNA contributions deduced by FRAGMAXR correlated well with values measured using genetic variants (Pearson r: 0.85 and 0.94, respectively).

CONCLUSIONS

CpG-associated cfDNA nucleosomal patterns of cfDNA molecules are influenced by DNA methylation and might be useful for biomarker developments for cancer liquid biopsy and noninvasive prenatal testing.

Evaluation and integration of cell-free DNA signatures for detection of lung cancer

Cell-free DNA (cfDNA) analysis has shown potential in detecting early-stage lung cancer based on non-genetic features. To distinguish patients with lung cancer from healthy individuals, peripheral blood were collected from 926 lung cancer patients and 611 healthy individuals followed by cfDNA extraction. Low-pass whole genome sequencing and targeted methylation sequencing were conducted and various features of cfDNA were evaluated. With our customized algorithm using the most optimal features, the ensemble stacked model was constructed, called ESim-seq (Early Screening tech with Integrated Model). In the independent validation cohort, the ESim-seq model achieved an area under the curve (AUC) of 0.948 (95 % CI: 0.915-0.981), with a sensitivity of 79.3 % (95 % CI: 71.5-87.0 %) across all stages at a specificity of 96.0 % (95 % CI: 90.6-100.0 %). Specifically, the sensitivity of the ESim-seq model was 76.5 % (95 % CI: 67.3-85.8 %) in stage I patients, 100 % (95 % CI: 100.0-100.0 %) in stage II patients, 100 % (95 % CI: 100.0-100.0 %) in stage III patients and 87.5 % (95 % CI: 64.6%-100.0 %) in stage IV patients in the independent validation cohort. Besides, we constructed LCSC model (Lung Cancer Subtype multiple Classification), which was able to accurately distinguish patients with small cell lung cancer from those with non-small cell lung cancer, achieving an AUC of 0.961 (95 % CI: 0.949-0.957). The present study has established a framework for assessing cfDNA features and demonstrated the benefits of integrating multiple features for early detection of lung cancer.

Nucleic acid liquid biopsies in cardiovascular disease: Cell-free DNA liquid biopsies in cardiovascular disease

Cardiovascular disease (CVD) is the leading cause of death worldwide, and despite treatment efforts, cardiovascular function cannot always be restored, and progression of disease be prevented. Critical insights are oftentimes based on tissue samples. Current knowledge of tissue pathology typically relies on invasive biopsies or postmortem samples. Liquid biopsies, which assess circulating mediators to deduce the histology and pathology of distant tissues, have been advancing rapidly in cancer research and offer a promising approach to be translated to the understanding and treatment of CVD. The widely understood elevations in cell-free DNA during acute and chronic cardiovascular conditions, associate with disease, severity, and offer prognostic value. The role of neutrophil extracellular traps (NETs) and circulating nucleases in thrombosis provide a solid rationale for liquid biopsies in CVD. cfDNA originates from various tissue types and cellular sources, including mitochondria and nuclei, and can be used to trace cell and tissue type lineage, as well as to gain insight into the activation status of cells. This article discusses the origin, structure, and potential utility of cfDNA, offering a deeper and less invasive approach for the understanding of the complexities of CVD.

Cell-free nucleic acid fragmentomics: A non-invasive window into cellular epigenomes

Clinical genomic profiling of cell-free nucleic acids (e.g. cell-free DNA or cfDNA) from blood and other body fluids has ushered in a new era in non-invasive diagnostics and treatment monitoring strategies for health conditions and diseases such as cancer. Genomic analysis of cfDNAs not only identifies disease-associated mutations, but emerging findings suggest that structural, topological, and fragmentation characteristics of cfDNAs reveal crucial information about the location of source tissues, their epigenomes, and other clinically relevant characteristics, leading to the burgeoning field of fragmentomics. The field has seen rapid developments in computational and genomics methodologies for conducting large-scale studies on health conditions and diseases - that have led to fundamental, mechanistic discoveries as well as translational applications. Several recent studies have shown the clinical utilities of the cfDNA fragmentomics technique which has the potential to be effective for early disease diagnosis, determining treatment outcomes, and risk-free continuous patient monitoring in a non-invasive manner. In this article, we outline recent developments in computational genomic methodologies and analysis strategies, as well as the emerging insights from cfNA fragmentomics. We conclude by highlighting the current challenges and opportunities.

GWAS shows the genetics behind cell-free DNA and highlights the importance of p.Arg206Cys in DNASE1L3 for non-invasive testing

The properties of cell-free DNA (cfDNA) are intensely studied for their potential as non-invasive biomarkers. We explored the effect of common genetic variants on the concentration and fragmentation properties of cfDNA using a genome-wide association study (GWAS) based on low-coverage whole-genome sequencing data of 140,000 Dutch non-invasive prenatal tests (NIPTs). Our GWAS detects many genome-wide significant loci, functional enrichments for phagocytes, liver, adipose tissue, and macrophages, and genetic correlations with autoimmune and cardiovascular disease. A common (7%) missense variant in DNASE1L3 (p.Arg206Cys) strongly affects all cfDNA properties. It increases the size of fragments, lowers cfDNA concentrations, affects the distribution of cleave-site motifs, and increases the fraction of circulating fetal DNA during pregnancy. For the application of NIPT, and potentially other cfDNA-based tests, this variant has direct clinical consequences, as it increases the odds of inconclusive results and impairs the sensitivity of NIPT by causing predictors to overestimate the fetal fraction.

DNASE1L3-mediated PANoptosis enhances the efficacy of combination therapy for advanced hepatocellular carcinoma

Rationale: The introduction of combination therapy utilizing tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors for advanced hepatocellular carcinoma (HCC) has significantly altered the management of affected patients. However, the absence of predictive biomarkers to identify those who would derive the greatest benefit from this combination therapy underscores the necessity for further enhancements in its efficacy. Methods: In this study, we performed a proteomic analysis on surgical specimens from patients who either responded to or did not respond to combination therapy with sorafenib and programmed death-1 (PD-1) monoclonal antibody (mAb). We employed in vitro experiments, including immunocytochemistry, co-immunoprecipitation, and transmission electron microscopy, to elucidate the mechanism of DNASE1L3-induced PANoptosis. Additionally, we assessed the function of DNASE1L3 in combination therapy using a mouse liver orthotopic tumor model and clinical samples. Results: Our findings indicated that the levels of deoxyribonuclease 1 like 3 (DNASE1L3) were significantly elevated in the cohort of patients who responded to treatment, correlating with the sorafenib-induced programmed cell death (PCD) of HCC cells. Further experimentation revealed that DNASE1L3 facilitated the generation of double-strand deoxyribonucleic acid (dsDNA) breaks and activated the absent in melanoma 2 (AIM2) pathway during sorafenib-induced HCC cell death, ultimately culminating in PANoptosis. Moreover, DNASE1L3-induced PANoptosis augmented the activation of anti-tumor immunity within the tumor microenvironment (TME), thereby enhancing the efficacy of the combination therapy involving sorafenib and PD-1 mAb. Conclusion: Our findings offer valuable insights into the mechanisms underlying DNASE1L3's role in sorafenib sensitivity and position DNASE1L3 as a promising predictive biomarker and target for improving outcomes in combination therapy for HCC.

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

BACKGROUND

The mortality rate of COVID-19 patients with critical symptoms is reported to be 40.5%. Early identification of patients with poor progression in the critical cohort is essential to timely clinical intervention and reduction of mortality. Although older age, chronic diseases, have been recognized as risk factors for COVID-19 mortality, we still lack an accurate prediction method for every patient. This study aimed to delve into the cell-free DNA fragmentomics of critically ill patients, and develop new promising biomarkers for identifying the patients with high mortality risk.

METHODS

We utilized whole genome sequencing on the plasma cell-free DNA (cfDNA) from 33 COVID-19 patients with critical symptoms, whose outcomes were classified as survival (n = 16) and death (n = 17). Mitochondrial DNA (mtDNA) abundance and fragmentomic properties of cfDNA, including size profiles, ends motif and promoter coverages were interrogated and compared between survival and death groups.

RESULTS

Significantly decreased abundance (~ 76% reduction) and dramatically shorter fragment size of cell-free mtDNA were observed in deceased patients. Likewise, the deceased patients exhibited distinct end-motif patterns of cfDNA with an enhanced preference for "CC" started motifs, which are related to the activity of nuclease DNASE1L3. Several dysregulated genes involved in the COVID-19 progression-related pathways were further inferred from promoter coverages. These informative cfDNA features enabled a high PPV of 83.3% in predicting deceased patients in the critical cohort.

CONCLUSION

The dysregulated biological processes observed in COVID-19 patients with fatal outcomes may contribute to abnormal release and modifications of plasma cfDNA. Our findings provided the feasibility of plasma cfDNA as a promising biomarker in the prognosis prediction in critically ill COVID-19 patients in clinical practice.

Cell-free DNA from nail clippings as source of normal control for genomic studies in hematologic malignancies

Comprehensive genomic sequencing is becoming a critical component in the assessment of hematologic malignancies, with broad implications for patients' management. In this context, unequivocally discriminating somatic from germline events is challenging but greatly facilitated by matched analysis of tumor:normal pairs of samples. In contrast to solid tumors, in hematologic malignancies conventional sources of normal control material (peripheral blood, buccal swabs, saliva) could be highly involved by the neoplastic process, rendering them unsuitable. In this work we describe our real-world experience using cell-free DNA (cfDNA) isolated from nail clippings as an alternate source of normal control material, through the dedicated review of 2,610 tumor:nail pairs comprehensively sequenced by MSK-IMPACT-heme. Overall, we found that nail cfDNA is a robust germline control for paired genomic studies. In a subset of patients, nail DNA may be contaminated by tumor DNA, reflecting unique attributes of the hematologic disease and transplant history. Contamination is generally low level, but significantly more common among patients with myeloid neoplasms (20.5%; 304/1,482) than among those with lymphoid diseases (5.4%; 61/1,128) and particularly enriched in myeloproliferative neoplasms with marked myelofibrosis. When identified in patients with lymphoid and plasma-cell neoplasms, mutations commonly reflected a myeloid profile and correlated with a concurrent/evolving clonal myeloid neoplasm. Donor DNA was identified in 22% (11/50) of nails collected after allogeneic stem-cell transplantation. In this cohort, an association with a recent history of graft-versus-host disease was identified. These findings should be considered as a potential limitation to the use of nails as a source of normal control DNA but could also provide important diagnostic information regarding the disease process.

Application of graft-derived cell-free DNA for solid organ transplantation

Monitoring the status of grafts and the occurrence of postoperative complications, such as rejection, is crucial for ensuring the success and long-term survival of organ transplants. Traditional histopathological examination, though effective, is an invasive procedure and poses risks of complications, making frequent use impractical. In recent years, graft-derived cell-free DNA (gd-cfDNA) has emerged as a promising non-invasive biomarker. It not only provides early warnings of rejection and other types of graft injury but also offers important information about the effectiveness of immunosuppressive therapy and prognosis. gd-cfDNA shows potential in the monitoring of organ transplants. The early, real-time information on graft injury provided by gd-cfDNA facilitates timely individualized treatment and improves patient outcomes. However, the progress of research on gd-cfDNA varies across different organs. Therefore, this article will comprehensively review the application and findings of gd-cfDNA in monitoring various solid organs, discussing the advantages, limitations, and some future research directions to aid in its clinical application.

A novel approach for in vivo DNA footprinting using short double-stranded cell-free DNA from plasma

Here, we present a method for enrichment of double-stranded cfDNA with an average length of ∼40 bp from cfDNA for high-throughput DNA sequencing. This class of cfDNA is enriched at gene promoters and binding sites of transcription factors or structural DNA-binding proteins, so that a genome-wide DNA footprint is directly captured from liquid biopsies. In short double-stranded cfDNA from healthy individuals, we find significant enrichment of 203 transcription factor motifs. Additionally, short double-stranded cfDNA signals at specific genomic regions correlate negatively with DNA methylation, positively with H3K4me3 histone modifications and gene transcription. The diagnostic potential of short double-stranded cell-free DNA (cfDNA) in blood plasma has not yet been recognized. When comparing short double-stranded cfDNA from patient samples of pancreatic ductal adenocarcinoma with colorectal carcinoma or septic with postoperative controls, we identify 136 and 241 differentially enriched loci, respectively. Using these differentially enriched loci, the disease types can be clearly distinguished by principal component analysis, demonstrating the diagnostic potential of short double-stranded cfDNA signals as a new class of biomarkers for liquid biopsies.

DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation

Circulating cell-free DNA (cfDNA) is emerging as an avenue for cancer detection, but the characteristics of cfDNA fragmentation in the blood are poorly understood. We evaluate the effect of DNA methylation and gene expression on genome-wide cfDNA fragmentation through analysis of 969 individuals. cfDNA fragment ends more frequently contained CCs or CGs, and fragments ending with CGs or CCGs are enriched or depleted, respectively, at methylated CpG positions. Higher levels and larger sizes of cfDNA fragments are associated with CpG methylation and reduced gene expression. These effects are validated in mice with isogenic tumors with or without the mutant IDH1, and are associated with genome-wide changes in cfDNA fragmentation in patients with cancer. Tumor-related hypomethylation and increased gene expression are associated with decrease in cfDNA fragment size that may explain smaller cfDNA fragments in human cancers. These results provide a connection between epigenetic changes and cfDNA fragmentation with implications for disease detection.

Chromatin- and nucleosome-associated features in liquid biopsy: implications for cancer biomarker discovery

Cell-free DNA (cfDNA) from the bloodstream has been studied for cancer biomarker discovery, and chromatin-derived epigenetic features have come into the spotlight for their potential to expand clinical applications. Methylation, fragmentation, and nucleosome positioning patterns of cfDNA have previously been shown to reveal epigenomic and inferred transcriptomic information. More recently, histone modifications have emerged as a tool to further identify tumor-specific chromatin variants in plasma. A number of sequencing methods have been developed to analyze these epigenetic markers, offering new insights into tumor biology. Features within cfDNA allow for cancer detection, subtype and tissue of origin classification, and inference of gene expression. These methods provide a window into the complexity of cancer and the dynamic nature of its progression. In this review, we highlight the array of epigenetic features in cfDNA that can be extracted from chromatin- and nucleosome-associated organization and outline potential use cases in cancer management.

Effects of blood-processing protocols on cell-free DNA fragmentomics in plasma: Comparisons of one- and two-step centrifugations

BACKGROUND

Cell-free DNA (cfDNA) fragmentomic characteristics are promising analytes with abundant physiological signals for non-invasive disease diagnosis and monitoring. Previous studies on plasma cfDNA fragmentomics commonly employed a two-step centrifugation process for removing cell debris, involving a low-speed centrifugation followed by a high-speed centrifugation. However, the effects of centrifugation conditions on the analysis of cfDNA fragmentome remain uncertain.

METHODS

We collected blood samples from 10 healthy individuals and divided each sample into two aliquots for plasma preparation with one- and two-step centrifugation processes. We performed whole genome sequencing (WGS) of the plasma cfDNA in the two groups and comprehensively compared the cfDNA fragmentomic features. Additionally, we reanalyzed the fragmentomic features of cfDNA from 16 healthy individuals and 16 COVID-19 patients, processed through one- and two-step centrifugation in our previous study, to investigate the impact of centrifugation on disease signals.

RESULTS

Our results showed that there were no significant differences observed in the characteristics of nuclear cfDNA, including size, motif diversity score (MDS) of end motifs, and genome distribution, between plasma samples treated with one- and two-step centrifugation. The cfDNA size shortening in COVID-19 patients was observed in plasma samples with one- and two-step centrifugation methods. However, we observed a significantly higher relative abundance and longer size of cell-free mitochondrial DNA (mtDNA) in the one-step samples compared to the two-step samples. This difference in mtDNA caused by the one- and two-step centrifugation methods surpasses the pathological difference between COVID-19 patients and healthy individuals.

CONCLUSIONS

Our findings indicate that one-step low-speed centrifugation is a simple and potentially suitable method for analyzing nuclear cfDNA fragmentation characteristics. These results offer valuable guidance for cfDNA research in various clinical scenarios.

Molecular analysis for ovarian cancer detection in patient-friendly samples

BACKGROUND

High ovarian cancer mortality rates motivate the development of effective and patient-friendly diagnostics. Here, we explored the potential of molecular testing in patient-friendly samples for ovarian cancer detection.

METHODS

Home-collected urine, cervicovaginal self-samples, and clinician-taken cervical scrapes were prospectively collected from 54 patients diagnosed with a highly suspicious ovarian mass (benign n = 25, malignant n = 29). All samples were tested for nine methylation markers, using quantitative methylation-specific PCRs that were verified on ovarian tissue samples, and compared to non-paired patient-friendly samples of 110 age-matched healthy controls. Copy number analysis was performed on a subset of urine samples of ovarian cancer patients by shallow whole-genome sequencing.

RESULTS

Three methylation markers are significantly elevated in full void urine of ovarian cancer patients as compared to healthy controls (C2CD4D, P = 0.008; CDO1, P = 0.022; MAL, P = 0.008), of which two are also discriminatory in cervical scrapes (C2CD4D, P = 0.001; CDO1, P = 0.004). When comparing benign and malignant ovarian masses, GHSR shows significantly elevated methylation levels in the urine sediment of ovarian cancer patients (P = 0.024). Other methylation markers demonstrate comparably high methylation levels in benign and malignant ovarian masses. Cervicovaginal self-samples show no elevated methylation levels in patients with ovarian masses as compared to healthy controls. Copy number changes are identified in 4 out of 23 urine samples of ovarian cancer patients.

CONCLUSIONS

Our study reveals increased methylation levels of ovarian cancer-associated genes and copy number aberrations in the urine of ovarian cancer patients. Our findings support continued research into urine biomarkers for ovarian cancer detection and highlight the importance of including benign ovarian masses in future studies to develop a clinically useful test.

Tumor- and Fibroblast-Derived Cell-Free DNAs Differently Affect the Progression of B16 Melanoma In Vitro and In Vivo

It is widely postulated that the majority of pathologically elevated extracellular or cell-free DNA (cfDNA) in cancer originates from tumor cells; however, evidence has emerged regarding the significant contributions of other cells from the tumor microenvironment. Here, the effect of cfDNA originating from murine B16 melanoma cells and L929 fibroblasts on B16 cells was investigated. It was found that cfDNAL929 increased the viability and migration properties of B16 cells in vitro and their invasiveness in vivo. In contrast, cfDNAB16 exhibited a negative effect on B16 cells, reducing their viability and migration in vitro, which in vivo led to decreased tumor size and metastasis number. It was shown that cell treatment with both cfDNAs resulted in an increase in the expression of genes encoding DNases and the oncogenes Braf, Kras, and Myc. cfDNAL929-treated cells were shown to experience oxidative stress. Gene expression changes in the case of cfDNAB16 treatment are well correlated with the observed decrease in proliferation and migration of B16 cells. The obtained data may indicate the possible involvement of fibroblast DNA in the tumor microenvironment in tumor progression and, potentially, in the formation of new tumor foci due to the transformation of normal cells.

Effect of a 12-Week Walking Program Monitored by Global Physical Capacity Score (GPCS) on Circulating Cell-Free mtDNA and DNase Activity in Patients with Irritable Bowel Syndrome

Irritable bowel syndrome (IBS) involves low-grade mucosal inflammation. Among the various approaches capable of managing the symptoms, physical activity is still under investigation. Despite its benefits, it promotes oxidative stress and inflammation. Mitochondria impacts gut disorders by releasing damage-associated molecular patterns, such as cell-free mtDNA (cf-mtDNA), which support inflammation. This study evaluated the effects of a 12-week walking program on the cf-mtDNA and DNase in 26 IBS and 17 non-IBS subjects. Pro- and anti-inflammatory cytokines were evaluated by ELISA. Digital droplet PCR was used to quantify cf-mtDNA; DNase activity was assessed using a single radial enzyme diffusion assay. PCR-RFLP was used to genotype DNASE1 rs1053874 SNP. Significantly lower IL-10 levels were found in IBS than in non-IBS individuals. Exercise reduced cf-mtDNA in non-IBS subjects but not in IBS patients. DNase activity did not correlate with the cf-mtDNA levels in IBS patients post-exercise, indicating imbalanced cf-mtDNA clearance. Different rs1053874 SNP frequencies were not found between groups. The study confirms the positive effects of regular moderate-intensity physical activity in healthy subjects and its role in cf-mtDNA release and clearance. Walking alone might not sufficiently reduce subclinical inflammation in IBS, based on imbalanced pro- and anti-inflammatory molecules. Prolonged programs are necessary to investigate their effects on inflammatory markers in IBS.

Genomic origin, fragmentomics, and transcriptional properties of long cell-free DNA molecules in human plasma

Recent studies have revealed an unexplored population of long cell-free DNA (cfDNA) molecules in human plasma using long-read sequencing technologies. However, the biological properties of long cfDNA molecules (>500 bp) remain largely unknown. To this end, we have investigated the origins of long cfDNA molecules from different genomic elements. Analysis of plasma cfDNA using long-read sequencing reveals an uneven distribution of long molecules from across the genome. Long cfDNA molecules show overrepresentation in euchromatic regions of the genome, in sharp contrast to short DNA molecules. We observe a stronger relationship between the abundance of long molecules and mRNA gene expression levels, compared with short molecules (Pearson's r = 0.71 vs. -0.14). Moreover, long and short molecules show distinct fragmentation patterns surrounding CpG sites. Leveraging the cleavage preferences surrounding CpG sites, the combined cleavage ratios of long and short molecules can differentiate patients with hepatocellular carcinoma (HCC) from non-HCC subjects (AUC = 0.87). We also investigated knockout mice in which selected nuclease genes had been inactivated in comparison with wild-type mice. The proportion of long molecules originating from transcription start sites are lower in Dffb-deficient mice but higher in Dnase1l3-deficient mice compared with that of wild-type mice. This work thus provides new insights into the biological properties and potential clinical applications of long cfDNA molecules.

A review on the impact of single-stranded library preparation on plasma cell-free diversity for cancer detection

In clinical oncology, cell-free DNA (cfDNA) has shown immense potential in its ability to noninvasively detect cancer at various stages and monitor the progression of therapy. Despite the rapid improvements in cfDNA liquid biopsy approaches, achieving the required sensitivity to detect rare tumor-derived cfDNA still remains a challenge. For next-generation sequencing, the perceived presentation of cfDNA is strongly linked to the extraction and library preparation protocols. Conventional double-stranded DNA library preparation (dsDNA-LP) focuses on assessing ~167bp double-stranded mononucleosomal (mncfDNA) and its other oligonucleosomal cell-free DNA counterparts in plasma. However, dsDNA-LP methods fail to include short, single-stranded, or nicked DNA in the final library preparation, biasing the representation of the actual cfDNA populations in plasma. The emergence of single-stranded library preparation (ssDNA-LP) strategies over the past decade has now allowed these other populations of cfDNA to be studied from plasma. With the use of ssDNA-LP, single-stranded, nicked, and ultrashort cfDNA can be comprehensively assessed for its molecular characteristics and clinical potential. In this review, we overview the current literature on applications of ssDNA-LP on plasma cfDNA from a potential cancer liquid biopsy perspective. To this end, we discuss the molecular principles of single-stranded DNA adapter ligation, how library preparation contributes to the understanding of native cfDNA characteristics, and the potential for ssDNA-LP to improve the sensitivity of circulating tumor DNA detection. Additionally, we review the current literature on the newly reported species of plasma ultrashort single-stranded cell-free DNA plasma, which appear biologically distinct from mncfDNA. We conclude with a discussion of future perspectives of ssDNA-LP for liquid biopsy endeavors.

Deoxyribonuclease 1-like 3 inhibits colorectal malignancy through antagonizing NEDD4-triggered CDKN1A ubiquitination

Deoxyribonuclease 1-like 3 (DNASE1L3) has been shown to play nonnegligible roles in several types of carcinomas. Nevertheless, the biological function, clinical relevance, and influence of DNASE1L3 in colorectal cancer (CRC) remain obscure. Immunohistochemistry was adopted to examine DNASE1L3 and CDKN1A expression in CRC tissue, and the clinical significance of DNASE1L3 was assessed. Cell counting kit-8, colony formation, and transwell assays were employed for assessing tumor proliferation and migration. The mechanisms underlying the impact of DNASE1L3 were explored via western blot analysis, co-immunoprecipitation, and ubiquitination assay. It was observed that DNASE1L3 was downregulated in CRC tissues and was tightly associated with patient prognosis. DNASE1L3 impaired CRC cell proliferation and migration through elevating CDKN1A via suppressing CDKN1A ubiquitination. Meanwhile, DNASE1L3 was positively related to CDKN1A. In mechanism, DNASE1L3 and CDKN1A interacted with the E3 ubiquitin ligase NEDD4. Moreover, DNASE1L3 was competitively bound to NEDD4, thus repressing NEDD4-mediated CDKN1A ubiquitination and degradation. These discoveries implied the potential mechanisms of DNASE1L3 during tumorigenesis, suggesting that DNASE1L3 may serve as a new potential therapeutic agent for CRC.

Comprehensive Analysis Reveals Deoxyribonuclease 1 as a Potential Prognostic and Diagnostic Biomarker in Human Cancers

BACKGROUND

Deoxyribonuclease 1 (DNASE1) is an important gene associated with several cancers, including liver, bladder, and gastric cancer. It has been linked to autoimmune illnesses, including systemic lupus erythematosus, which may lead to cancer formation. However, the role of DNASE1 in cancer has not been studied.

MATERIALS AND METHODS

We performed a pan-cancer analysis using bioinformatics tools, including Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), and University of Alabama at Birmingham Cancer Data Analysis Portal (UALCAN) databases, Kaplan-Meier plotter, and cBioPortal, to investigate the expression of DNASE1 across various cancers as well as its association with immune infiltration and genetic alterations. Public datasets were used to validate DNASE1 expression in kidney renal clear cell carcinoma (KIRC) and kidney papillary renal cell carcinoma (KIRP) samples.

RESULTS

DNASE1 was found to be highly expressed in many cancers, such as bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), head and neck squamous cell carcinoma (HNSC), and was lowly expressed in other cancers, including KIRC, KIRP, and thyroid carcinoma (THCA). Additionally, TIMER results showed an association of DNASE1 with immune cell infiltration in KIRC and KIRP. Survival analysis indicated that high DNASE1 expression was associated with poor prognosis in KIRC. We also discovered that altered DNASE1 expression was related to poor prognosis in The Cancer Genome Atlas (TCGA) tumors.

CONCLUSION

DNASE1 could potentially be used as a prognostic and diagnostic biomarker for KIRC and as a diagnostic biomarker for KIRP.

Cell-free DNA fragmentomics and second malignant neoplasm risk in patients with PTEN hamartoma tumor syndrome

Individuals with PTEN hamartoma tumor syndrome (PHTS) harbor pathogenic germline PTEN variants that confer a significantly increased lifetime risk of various organ-specific cancers including second primary malignant neoplasms (SMNs). Currently, there are no reliable biomarkers that can predict individual-level cancer risk. Despite the highly promising value of cell-free DNA (cfDNA) as a biomarker for underlying sporadic cancers, the utility of cfDNA in individuals with known cancer-associated germline variants and subclinical cancers remains poorly understood. We perform ultra-low-pass whole-genome sequencing (ULP-WGS) of cfDNA from plasma samples from patients with PHTS and cancer as well as those without cancer. Analysis of cfDNA reveals that patients with PHTS and SMNs have distinct cfDNA size distribution, aberrant genome-wide fragmentation, and differential fragment end motif frequencies. Our work provides evidence that cfDNA profiles may be used as a marker for SMN risk in patients with PHTS.

Pre-Analytical Factors Affecting Extracellular DNA in Saliva

Salivary DNA is widely used for genetic analyses because of its easy collection. However, its extracellular fraction in particular, similar to the extracellular DNA (ecDNA) in plasma, could be a promising biomarker for oral or systemic diseases. In contrast to genetics, the quantity of salivary ecDNA is of importance and can be affected by the pre-analytical processing of samples, but the details are not known. The aim of our study was to analyze the effects of centrifugation and freezing of saliva on the concentration of ecDNA in saliva. Fifteen healthy volunteers, free of any known systemic or oral diseases, were asked to collect unstimulated saliva samples. Aliquots were centrifuged at 1600× g and frozen or directly processed. The fresh or thawed cell-free saliva samples underwent subsequent centrifugation at 16,000× g. The supernatants were used for DNA isolation and quantification using fluorometry and real-time PCR. While freezing had minimal effects on the salivary ecDNA concentration, another centrifugation step decreased ecDNA considerably in both fresh and frozen samples (by 97.8% and 98.4%, respectively). This was mirrored in the quantitative PCR targeting a nuclear (decrease by 93.5%) and mitochondrial (decrease by 97.7%) ecDNA sequence. In conclusion, in this first study focusing on the technical aspects of salivary ecDNA quantitation, we show that, regardless of its subcellular origin, the concentration of ecDNA in saliva is mainly affected by additional centrifugation and not by the freezing of centrifuged cell-free saliva samples. This suggests that most salivary ecDNA likely is associated with cell debris and apoptotic bodies. Which fraction is affected by a particular disease should be the focus of further targeted studies.

Integration of Cell-Free DNA End Motifs and Fragment Lengths Can Identify Active Genes in Liquid Biopsies

Multiple studies have shown that cell-free DNA (cfDNA) from cancer patients differ in both fragment length and fragment end motif (FEM) from healthy individuals, yet there is a lack of understanding of how the two factors combined are associated with cancer and gene transcription. In this study, we conducted cfDNA fragmentomics evaluations using plasma from lung cancer patients (n = 12) and healthy individuals (n = 7). A personal gene expression profile was established from plasma using H3K36me3 cell-free chromatin immunoprecipitation sequencing (cfChIP-seq). The genes with the highest expression displayed an enrichment of short cfDNA fragments (median = 19.99%, IQR: 16.94-27.13%, p < 0.0001) compared to the genes with low expression. Furthermore, distinct GC-rich FEMs were enriched after cfChIP. Combining the frequency of short cfDNA fragments with the presence of distinct FEMs resulted in an even further enrichment of the most expressed genes (median = 37.85%, IQR: 30.10-39.49%, p < 0.0001). An in vitro size selection of <150 bp cfDNA could isolate cfDNA representing active genes and the size-selection enrichment correlated with the cfChIP-seq enrichment (Spearman r range: 0.499-0.882, p < 0.0001). This study expands the knowledge regarding cfDNA fragmentomics and sheds new light on how gene activity is associated with both cfDNA fragment lengths and distinct FEMs.

Multi-modal cell-free DNA genomic and fragmentomic patterns enhance cancer survival and recurrence analysis

The structure of cell-free DNA (cfDNA) is altered in the blood of patients with cancer. From whole-genome sequencing, we retrieve the cfDNA fragment-end composition using a new software (FrEIA [fragment end integrated analysis]), as well as the cfDNA size and tumor fraction in three independent cohorts (n = 925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% cancer samples using at least one cfDNA measure, including 64% early-stage cancer (n = 220). cfDNA detection correlates with a shorter overall (p = 0.0086) and recurrence-free (p = 0.017) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n = 396 cancer, 90 controls) achieve a detection accuracy of 82% and area under the receiver operating characteristic curve of 0.96. In conclusion, harnessing the biological features of cfDNA can improve, at no extra cost, the diagnostic performance of liquid biopsies.

Heat inactivation does not alter host plasma cell-free DNA characteristics in infectious disease research

BACKGROUND

Cell-free DNA (cfDNA) is a promising analyte for non-invasive liquid biopsy, carrying abundant signatures for disease diagnosis and monitoring. In infectious disease researches, blood plasma samples are routinely heat-inactivated before proceeding with downstream analyses. However, the effects of heat inactivation on cfDNA fragmentomic analysis remain largely unclear, potentially introducing biases or altering the characteristics of cfDNA.

METHODS

We performed a comprehensive investigation of cfDNA concentrations and fragmentomics in 21 plasma samples from 7 healthy individuals, by comparing the sample group without the heat inactivation to those exposed to once or twice heat-inactivation at 56 °C for 30 min and following freeze-thaw.

RESULTS

Plasma samples with once and twice heat inactivation displayed no significant deviations in primary characteristics, including cfDNA concentrations, size profiles, end motif features, and genome-wide distributions, compared to samples without heat treatment.

CONCLUSIONS

Heat-inactivated cfDNA can be utilized for liquid biopsy in infectious disease researches, without substantial impact on cfDNA concentrations and fragmentomic properties. This study provides essential insights into the effects of heat inactivation on cfDNA properties and will contribute to the development of reliable non-invasive biomarkers for infectious disease.

An ultrasonic biosample disruptor with two triangular teeth on its radiation face

Ultrasound has been used in biosample disruption such as disruption of algal cell and DNA. New structure of ultrasonic biosample disruptor (UBD) needs to be explored to increase the energy efficiency. In this study, an UBD with two triangular teeth on the bottom radiation face of the water tank has been proposed, to concentrate the acoustic energy into the slot between the two neighboring triangular teeth, in order to raise the acoustic energy utilization and fragmentation performance. The acoustic energy concentration into the slot is verified by the FEM computation, and the improvement of fragmentation performance is experimentally confirmed with spirulina and tribonema, compared to the traditional UBD which has a flat radiation face. The number proportion of fragment in the length range of 10-20 μm generated by the UBD proposed in this work is 17.08% and 10.82% more than that generated by the traditional UBD for the two samples, respectively. Besides, the UBD proposed in this work has a much smaller standard deviation of DNA fragment length (47 bp) than the traditional UBD (249 bp), with a similar mean length of fragments. Moreover, the maximum weight proportion of fragment in the range of 100-300 bp, generated by the UBD proposed in this work, is 71.4%.

Distinct Hodgkin lymphoma subtypes defined by noninvasive genomic profiling

The scarcity of malignant Hodgkin and Reed-Sternberg cells hampers tissue-based comprehensive genomic profiling of classic Hodgkin lymphoma (cHL). By contrast, liquid biopsies show promise for molecular profiling of cHL due to relatively high circulating tumour DNA (ctDNA) levels1-4. Here we show that the plasma representation of mutations exceeds the bulk tumour representation in most cases, making cHL particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumours, we demonstrate Hodgkin and Reed-Sternberg ctDNA shedding to be shaped by DNASE1L3, whose increased tumour microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R mutations that are dependent on IL-13 signalling and therapeutically targetable with IL-4Rα-blocking antibodies. Finally, using PhasED-seq5, we demonstrate the clinical value of pretreatment and on-treatment ctDNA levels for longitudinally refining cHL risk prediction and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL, as well as capturing molecularly distinct subtypes with diagnostic, prognostic and therapeutic potential.