bims-fragic 2026-10-18 papers

Issue of 2026–10–18
three papers selected by
Laura Mannarino, Humanitas Research

Genome Med. 2026 Oct 15. pii: 154. [Epub ahead of print]18(1):

Decoding coupled epigenetic-fragmentomic signals in circulating cell-free DNA for interpretable cancer diagnosis.

Yunze Wang, Yuying Hou, Xinyu Liu, Qingjiao Li, Wen Zhang, Xionghui Zhou.

BACKGROUND: Plasma cell-free DNA (cfDNA) whole-genome methylation sequencing enables simultaneous characterization of DNA methylation and fragmentomic features for cancer detection. However, it remains unclear whether methylation library preparation faithfully preserves fragmentomic signals, how methylation and fragmentation are biologically coupled, and how these two modalities can be systematically integrated.
METHODS: We systematically evaluated the preservation of cfDNA fragmentomic features in whole-genome bisulfite sequencing (WGBS) and enzymatic methyl sequencing (EM-seq) relative to conventional whole-genome sequencing (WGS). We next investigated the biological relationship between methylation and fragmentation and delineated methylation haplotype blocks (MHBs) directly from plasma cfDNA as biologically interpretable units for organizing multimodal cfDNA signals. Guided by these findings, we developed multimodal diagnostic models integrating complementary methylation and fragmentomic features.
RESULTS: Canonical cfDNA fragmentomic patterns were partially preserved across methylation sequencing protocols, although the degree of preservation varied among individual features. DNA methylation levels were associated with characteristic fragment length and end-motif patterns. Plasma-derived MHBs exhibited tissue-associated regulatory features and distinct patterns of chromatin accessibility, repeat enrichment, and methylation heterogeneity, providing biologically interpretable units for integrated cfDNA analysis. Within these regions, methylation and fragmentomic signals exhibited coordinated yet complementary patterns. Leveraging this framework, we developed Fragmentomics And Methylation Ensemble (FAME), an interpretable multimodal model integrating MHB-centered methylation and fragmentomic features for cancer detection and tissue-of-origin prediction, and further extended it with complementary genome-wide methylation and fragmentomic features to generate a genome-wide-augmented FAME model (FAME-GW). Across cross-validation, independent validation, and comparisons with THEMIS (THorough Epigenetic Marker Integration Solution), SPOT-MAS (screening for the presence of tumor by methylation and size), and DELFI (DNA evaluation of fragments for early interception), FAME-based models achieved robust diagnostic performance, with FAME providing a compact and interpretable representation and FAME-GW delivering the strongest overall predictive performance.
CONCLUSIONS: Our study demonstrates that cfDNA whole-genome methylation sequencing partially preserves informative fragmentomic signals and establishes plasma-derived MHBs as biologically interpretable units for organizing and integrating complementary methylation and fragmentomic information. This framework provides insight into the coupling of epigenetic and fragmentomic information and an effective strategy for interpretable cfDNA-based cancer diagnosis.

Keywords: Cancer detection; Cell-free DNA; DNA methylation; Fragmentomics; Liquid biopsy; Methylation haplotype blocks

DOI: https://doi.org/10.1186/s13073-026-01793-w

AJOG Glob Rep. 2026 Nov;6(4): 100692

First-trimester non-invasive prediction of preterm birth using cell-free DNA fragmentomics.

My-Diem Nguyen Pham, Minh-Tam Thi Phan, Nhat-Thang Tran, Ta-Son Vo, Hong-Thinh Le, Thu-Ha Thi Nguyen, Quoc-Huy Vu Nguyen, Minh-Thi Thi Ha, Tam Minh Le, Diem-Tuyet Thi Hoang, Khanh-Trang Nguyen Huynh, Nhan Viet Nguyen, Chuong Canh Nguyen, Thuong Chi Bui, Xuan Thanh Nguyen, Sa Viet Le, Vinh Dinh Tran, My-Nhi Ba Nguyen, Thong Van Nguyen, Tuyet-Anh Thi Nguyen, Ba Phuoc Hoang, Trong Van Nguyen, Thuy-Ai Thuy Nguyen, Toa Tri Nguyen, Thang Duc Duong, Cuong Huy Pham, Kim-Oanh Thi Luong, Cuong Ngoc Dao, Khanh Van Hoang, Thu-Thanh Thi Huynh, Khuong Manh Nguyen, Son-Tra Thi Tran, Hoanh Trung Tran, Son Canh Nguyen, Thuy Dinh Tran, Phương Thi Lan Nguyen, Thanh Viet Pham, Kong Chi Pham, Minh Doan Thai, Thanh-Thuy Thi Do, Hoa Thi Dao, Yen-Linh Thi Van, Sang Hung Tang, Hoai-Nghia Nguyen, Minh-Duy Phan, Hoa Giang, Cuong Thach Nguyen, Quang Thinh Trac.

Background: Spontaneous preterm birth (PTB) remains a leading cause of neonatal morbidity and mortality, yet accurate prediction in asymptomatic women during early gestation remains a critical unmet clinical need. Cell-free DNA (cfDNA) obtained through the same maternal blood collection used for routine first-trimester non-invasive prenatal testing (NIPT) represents an underutilized substrate for early PTB risk identification.
Objective: To develop and validate a cell-free DNA (cfDNA) fragmentomic classifier for the early prediction of spontaneous preterm birth (PTB) using routine first-trimester non-invasive prenatal testing (NIPT) data.
Study design: A case-control study was conducted within a multicenter Vietnamese cohort comprising 286 pregnancies, including 82 spontaneous PTB cases and 204 term controls. Maternal plasma cfDNA collected during routine first-trimester NIPT (median gestational age, 12 weeks) was sequenced to a depth of approximately 20 million reads per sample. Five fragmentomic feature categories including copy number alterations, end-motif composition, nucleosome distance, fragment length, and joint fragment-length × end-motif were evaluated for PTB prediction. Machine learning classifiers were developed in a training cohort (n=228, 65 PTB vs 163 TB) and tested in an internal held-out validation cohort (n=58, 17 PTB vs 41 TB).
Results: Among the 5 fragmentomic feature classes evaluated, 4-mer end-motif (EM) profiles exhibited the most pronounced differences between PTB and term control samples. Consistent with these findings, the EM-based classifier demonstrated the highest discriminative performance in the internal validation cohort, achieving an AUC of 0.970 (95% CI, 0.912-1.000). At a specificity >90%, the model achieved a sensitivity of 94% (95% CI, 78%-100%).
Conclusion: These findings demonstrate that cfDNA EM signatures derived from routine first-trimester NIPT can accurately identify pregnancies at risk of spontaneous preterm birth, using only a routine maternal blood sample, supporting the potential to extend the clinical utility of existing prenatal screening infrastructure pending prospective validation at production sequencing depths.

Keywords: NIPT preterm birth; cell-free DNA; early prediction; fragmentomics; machine learning

DOI: https://doi.org/10.1016/j.xagr.2026.100692

Transl Oncol. 2026 Oct 16. pii: S1936-5233(26)00416-X. [Epub ahead of print]74 103080

Cell-free DNA fragmentomics and epigenomic profiling in hematologic malignancies: current evidence, translational limitations, and future directions.

Amr Ali Mohamed Abdelgawwad El-Sehrawy, Sarmad S Abdullah, Guzalya Mamedova, Jasur Rizaev, Ihab M Abdelrahim, Shrey Kumar Srivastav, Zeina T Khaleel, Majid S Jabir, Neeraj Bainsal, Aseel Smerat.

Mutation-based liquid biopsy supports diagnosis and disease monitoring in hematologic malignancies, but interpretation of plasma variants may be complicated by clonal hematopoiesis, treatment-related changes, and nonmalignant blood-cell turnover. This structured narrative review evaluates whether cell-free DNA (cfDNA) fragmentomics, DNA methylation, and 5-hydroxymethylcytosine (5hmC) provide complementary information beyond mutation detection. Direct plasma evidence is most developed for selected fragmentomic and 5hmC applications, although most studies remain retrospective, internally validated, or proof of concept. Fragmentomic studies have reported associations with lymphoma classification, outcome assessment, and longitudinal tumor-effector profiling during chimeric antigen receptor T-cell therapy, but routine clinical utility and decision thresholds are not established. Plasma 5hmC studies have reported associations with lymphoma classification, treatment response, prognosis, and measurable residual disease in acute myeloid leukemia, whereas pharmacodynamic monitoring during Bruton's tyrosine kinase inhibition remains hypothesis-generating. DNA methylation may support source-cell or lineage inference, but lineage assignment does not establish malignant fraction, and key disease-assessment studies remain largely tissue-based, cellular-DNA-based, cross-cancer, or methodological. The novelty of this review is a structured evidence map that distinguishes direct plasma evidence from indirect support and compares the three modalities by biological information, assay compatibility, and validation maturity. We also propose a hypothesis-generating framework for sample-level integration using separate assay-specific aliquots and computational combination of outputs. No universal analytical order or clinically validated integrated workflow has been established. Fragmentomic and epigenomic profiling should therefore be regarded as investigational complements to mutation-based testing, requiring independent prospective validation against established genomic, cellular, imaging, and tissue-based methods.

Keywords: 5-Hydroxymethylcytosine; DNA methylation; Hematologic malignancies; Liquid biopsy; cfDNA fragmentomics

DOI: https://doi.org/10.1016/j.tranon.2026.103080