bims-fragic 2025-09-28 papers

Issue of 2025–09–28
three papers selected by
Laura Mannarino, Humanitas Research

Am J Clin Exp Immunol. 2025 ;14(4): 237-240

Cell-free DNA fragmentomics: a universal framework for early cancer detection and monitoring.

Wanyu Dong, Wenshi Hu, Yaojuan Lu, Qiping Zheng.

Cell-free DNA (cfDNA) fragmentomics has emerged as a powerful and noninvasive approach for cancer detection, characterization, and monitoring. By analyzing genome-wide fragmentation patterns - including fragment length distributions, end motifs, nucleosome footprints, and copy number variations - cfDNA fragmentomics provides high-resolution insights into tumor-specific biological signals even at low tumor burden. This technology offers advantages over conventional mutation-based assays by capturing aggregate structural and epigenomic alterations without requiring prior knowledge of driver mutations. In non-small cell lung cancer (NSCLC), cfDNA fragmentomics enables early detection, discrimination of malignant pulmonary nodules, and post-surgical monitoring of minimal residual disease. Recent studies have demonstrated that fragmentomic risk scores can accurately stratify recurrence risk and improve prognostic sensitivity beyond traditional genomic assays. In hepatocellular carcinoma (HCC), integration of fragment size selection, CNV profiling, and end-motif analysis has led to high-performing models for early diagnosis, particularly in high-risk populations. Moreover, cfDNA fragmentomics has proven effective in detecting malignant transformation in patients with neurofibromatosis-associated peripheral nerve sheath tumors, distinguishing benign from premalignant or malignant lesions with high precision. Expanding beyond these major cancers, fragmentomic approaches have demonstrated diagnostic potential in gastric, urological, hematologic, and pediatric malignancies. Notably, the DELFI-TF (DNA Evaluation of Fragments for early Interception-Tumor Fraction) framework has shown prognostic relevance by correlating pre-treatment cfDNA features with survival outcomes in colorectal and lung cancer patients, outperforming conventional imaging. All of these results highlight the translational importance of cfDNA fragmentomics as a cutting-edge precision oncology tool. Its continued integration into clinical workflows may redefine early cancer detection, facilitate subtype-specific interventions, and enable real-time, individualized treatment monitoring.

Keywords: Cell-free DNA; early cancer detection; fragmentomics; liquid biopsy

DOI: https://doi.org/10.62347/EBRY4326

ESMO Open. 2025 Sep 23. pii: S2059-7029(25)01639-4. [Epub ahead of print]10(10): 105770

Early detection, clinicopathological subtyping, and prognosis prediction for endometrial cancer patients using fragmentomics liquid biopsy assay.

Q Rao, H Zhou, W Weng, Y He, N Li, P He, W Tang, M He, X Zhu, D Zhu, H Bao, X Wu, H Wang, Z Lin, B Zhang.

BACKGROUND: Endometrial cancer (EC) is among the most prevalent gynecological malignancies worldwide. This study explores the use of cell-free DNA (cfDNA) fragmentomics to develop a non-invasive liquid biopsy assay, aiming to improve early detection, subtyping, and prognostication of EC, thereby enhancing therapeutic outcomes and reducing associated mortality.
MATERIALS AND METHODS: A cohort of 120 patients with diagnosed EC and 120 healthy volunteers was used to develop a novel non-invasive liquid biopsy assay for EC. Five distinct fragmentomic features were analyzed from preoperative plasma samples using low-pass whole-genome sequencing. Ensemble models were created by integrating base models that utilized four different machine learning algorithms for early cancer detection, clinicopathological subtyping, and prediction of recurrence-free survival. An independent test cohort of 62 EC patients and 62 healthy controls was used to assess the final ensemble model's performance.
RESULTS: The liquid biopsy assay demonstrated high efficacy in early EC detection, achieving an area under the curve (AUC) of 0.96, with 75.8% sensitivity and 96.8% specificity in the independent test cohort. Consistent sensitivities were observed across EC stages I-IV at 74.4%, 85.7%, 75%, and 75%, respectively. The assay moderately predicted clinicopathological features including stage (AUC = 0.72), histological subtypes (AUC = 0.73), and microsatellite instability status (AUC = 0.77). The model also effectively predicted recurrence-free survival, identifying high-risk patients [hazard ratio (HR) 8.6, P < 0.001]. Additionally, similarity network fusion stratified patients into high- and low-risk clusters, with high-risk individuals exhibiting a notably increased recurrence risk (HR 6.2, P = 0.049). Patients identified as high-risk by both methods exhibited an even greater risk (HR 10.1, P < 0.0001) for recurrence.
CONCLUSIONS: This DECIPHER-UCEC-2 study (Detecting Early Cancer by Inspecting ctDNA Features) demonstrates that by integrating cfDNA fragmentomics with machine learning, our liquid biopsy assay shows significant promise for EC's early detection, subtyping, and prognosis, potentially paving the way for enhanced patient outcomes.

Keywords: cell-free DNA; early diagnosis; endometrial cancer; fragmentomics; whole-genome sequencing

DOI: https://doi.org/10.1016/j.esmoop.2025.105770

Clin Chim Acta. 2025 Sep 23. pii: S0009-8981(25)00506-6. [Epub ahead of print] 120627

Analysis of urine cell-free DNA copy number and fragment size from healthy individuals.

Jufen Wang, Zilong Wu, Bingyu Wu, Xinghao Lin, Wenhe Wu, Jun Li.

OBJECTIVE: This study characterizes urine cell-free DNA (cfDNA) copy number and fragment size in healthy individuals and explores their associations with routine clinical parameters.
METHODS: Sixty healthy subjects were enrolled, providing paired blood and urine samples. Six primer pairs targeting nuclear (GAPDH-61/168/241) and mitochondrial DNA (ND1-57/167/240) were designed for absolute qPCR. Optimal urine collection, pre-treatment, and cfDNA detection protocols were evaluated. Correlations between cfDNA characteristics (fragment size and copy number) and clinical parameters (complete blood count, urinalysis, hepatic/renal function biomarkers) were analyzed.
RESULTS: Non-extracted urine retained a higher proportion of fragments <100 bp and > 2000 bp than extracted samples. The optimal pre-treatment involved immediate EDTA addition, centrifugation at 4 °C, and storage at -80 °C. Urine cfDNA comprised short, medium, and long fragments. Cell-free mitochondrial DNA (cf-mtDNA) showed the highest copy numbers in short fragments, decreasing with length, whereas cell-free nuclear DNA (cf-nDNA) peaked in medium fragments. ND1-57 Cq values correlated negatively with neutrophil percentage (P < 0.01) and positively with lymphocyte percentage (P < 0.05). Lymphocyte percentage was moderately correlated with ND1 short fragment (ND1-S, P < 0.01) and weakly with the ND1-S to ND1 medium fragment (ND1-M) ratio (P < 0.05). Absolute lymphocyte count correlated weakly with ND1-S (P < 0.01) and ND1-M (P < 0.05). Neutrophil percentage correlated weakly with ND1-S (P < 0.01) and ND1-S to ND1 long fragment (ND1-L) ratio (P < 0.05).
CONCLUSION: Urine cfDNA displays three distinct fragment sizes, with cf-mtDNA predominantly found in short fragments and showing stronger associations with physiological parameters than cf-nDNA.

Keywords: Biomarker; Cell-free mtDNA; Cell-free nDNA; Pre-treatment conditions; Urine

DOI: https://doi.org/10.1016/j.cca.2025.120627