bims-fragic 2026-07-05 papers

Issue of 2026–07–05
five papers selected by
Laura Mannarino, Humanitas Research

Cell Commun Signal. 2026 Jul 01.

Integration of breaking-point transition probabilities and specific open chromatin region features for early cancer detection.

Jinwen Ji, Ke Xu, Yanru Li, Liangyun Zhang, Zhihui Xu, Cong Pian.

BACKGROUND: Early detection of cancer using cell-free DNA (cfDNA) remains challenging due to the limited release of circulating tumor DNA (ctDNA) in early-stage disease. This study aimed to enhance detection sensitivity by integrating cfDNA fragmentation features with epigenomic context related to chromatin accessibility.
METHODS: We performed low-pass whole-genome sequencing (LP-WGS) on cfDNA samples from 506 participants, including lung cancer patients, benign cases, and healthy controls. Fragmentation patterns were characterized by calculating 16-bp breakpoint transition probabilities and extracting features within tissue-specific open chromatin regions (OCRs). These features were combined into an model termed SOTP_BP16_OCR, and its performance in multi-cancer classification on additional datasets was further evaluated.
RESULTS: cfDNA fragments exhibited strong sequence bias within 16 bp around breakpoints, extending beyond the conventional 5'-end motif window. The selected lung cancer-specific OCRs were enriched in biologically meaningful regions and showed clear differences between healthy and malignant samples. The SOTP_BP16_OCR model achieved an AUC of 0.96 (95% CI: 0.94-0.99) for distinguishing lung cancer patients from healthy individuals, including those with benign nodules, and maintained an AUC of 0.95 (95% CI: 0.92-0.98) for early-stage cases. Using features derived from two external datasets (n = 129 and n = 225), the SOTP_BP16_OCR model achieved AUCs of 0.94 and 0.99 for case-control classification. Tissue-of-origin prediction, which could only be performed in one dataset, reached an accuracy of 0.802.
CONCLUSION: By integrating sequence transition probabilities and open chromatin features, our model captures biologically relevant fragmentation signals under limited ctDNA release, providing a sensitive, affordable, and scalable approach for cfDNA-based cancer early screening.

Keywords: Cell-free DNA; Early-stage detection; Lung cancer; Open chromatin regions; Second-order transition probabilities; Tissue-of-origin (TOO)

DOI: https://doi.org/10.1186/s12964-026-03024-6

Sci Rep. 2026 Jun 30.

A comprehensive urine workflow enables robust methylation and fragmentation analysis of cell-free DNA.

Florence Mauger, Nouara Oussada, Caroline Horgues, Anna Eberhard, Leandra Oman, Mélanie Gou, Kamély Lumière, Daniela Mancarella-Langer, Thorsten Voss, Steven McGinn, Peter M Abuja, Ellen Heitzer, Jean-François Deleuze.

Urine cell-free DNA (cfDNA) holds great promise as a non-invasive biomarker for diagnosis, prognosis and treatment monitoring of diseases. However, its clinical utility is challenged by high nuclease activity and rapid degradation, necessitating an optimized urine cfDNA workflow. We evaluated our workflow for urine cfDNA methylation and fragmentation profiling, comparing a closed, non-crosslinking urine stabilization system (PAXgene Urine Technology), with a crosslinking reagent (Streck Urine Preserve) and unstabilized urine, using enzymatic methyl sequencing of cfDNA from 20 healthy individuals, across three urine storage time points (immediate, 6 h, and 72 h). Urine stabilization significantly improved cfDNA yield and preserved cfDNA fragment sizes, while unstabilized samples exhibited marked degradation and reduced sequencing quality. Methylation analysis revealed high concordance between stabilized samples, with subtle divergence after 72 h. In contrast, unstabilized samples showed widespread methylation changes. Stabilized urine cfDNA retained key biological patterns including donor-, sex-, and tissue- methylation signatures and fragment coverage profiles around transcription start sites and exon-intron junctions, consistent with underlying chromatin features. Our study underscores the importance of well-designed (pre)analytical urine workflows to allow urine cfDNA (epi)genomic analyses. These findings align with emerging standards for pre-examination processes and support clinically compatible urine cfDNA workflows.

Keywords: (pre)analytical cfDNA workflow; Fragmentation; Liquid biopsy; Methylation; Non-invasive biomarkers; Urine cell-free DNA

DOI: https://doi.org/10.1038/s41598-026-60021-y

Mol Pharmacol. 2026 Jun 12. pii: S0026-895X(26)00038-6. [Epub ahead of print]108(7): 100138

Emerging roles of platelet DNA in cancer detection and noninvasive prenatal testing.

Manli Ding, Xiaohui Huang, Xueqian Ouyang, Fengting Guo, Lanfang Li.

Cell-free DNA (cfDNA) level is a core liquid biopsy biomarker. However, it exhibits low detection sensitivity in early-stage diseases and carries a risk of information loss. Traditionally regarded as anucleate and DNA-deficient, platelets have recently been confirmed to actively take up and carry extracellular DNA-termed platelet DNA (pDNA). We summarized pDNA uptake mechanisms, including clathrin-mediated endocytosis of DNA-loaded extracellular vesicles and direct internalization of free DNA, as well as its pharmacological regulation. Compared with plasma cfDNA levels, pDNA shows superior stability, higher mutant allele frequencies, and resistance to nucleases. We elaborated its clinical potential for early cancer detection by capturing low-abundance tumor mutations and for noninvasive prenatal testing by overcoming the scarcity of fetal cfDNA in early pregnancy. Finally, we discussed integrating pDNA analysis using multiomics and artificial intelligence to advance precision liquid biopsy. SIGNIFICANCE STATEMENT: Platelet DNA level reshapes platelets' role from hemostatic cells to genetic carriers, resolving plasma cell-free DNA level's limitations. It enables early cancer detection and prenatal testing, advancing liquid biopsy toward precision medicine for better diagnostic outcomes.

Keywords: Cancer detection; Circulating cell-free DNA; Liquid biopsy; Noninvasive prenatal testing; Platelet DNA

DOI: https://doi.org/10.1016/j.molpha.2026.100138

Front Immunol. 2026 ;17 1854718

Liquid biopsy, multi-cancer early detection, and artificial intelligence: new frontiers in cancer screening from a technological and immunological perspective.

Dong Wu, Qing Yu, Qixiang Wu, Xiaoying Wang, Haojie Wei, Fengli Li, Guangli Li, Xiaowu Wang, Xiaojuan Wang.

Early cancer detection remains a central challenge in oncology because many lethal tumors are diagnosed after curative opportunities have narrowed, whereas current organ-specific screening methods cover only a limited number of cancer types and may be constrained by invasiveness, cost, accessibility or stage-dependent sensitivity. Liquid biopsy, multi-cancer early detection (MCED) and artificial intelligence (AI) are rapidly reshaping this field, but their clinical implications require careful interpretation. This review critically evaluates major liquid-biopsy analytes, including circulating tumor DNA, cell-free DNA methylation and fragmentomics, circulating tumor cells, extracellular vesicles, non-coding RNAs, tumor-educated platelets and multi-omics signatures, with emphasis on intended use, clinical maturity, tissue-of-origin value and translational limitations. A distinctive feature of this review is the integration of tumor-derived signals with host-response and immunological readouts, including peripheral blood mononuclear cell-based monitoring, immune-cell-derived extracellular vesicles, exosomal immune-checkpoint molecules and inflammatory confounders, thereby framing liquid biopsy as both a cancer-detection tool and a window into tumor-immune interactions. We further discuss MCED as a clinical care pathway rather than an isolated blood test, highlighting the importance of positive and negative predictive values, cancer prevalence, diagnostic-resolution pathways, false-positive workup, overdiagnosis, mortality benefit, cost-effectiveness and equitable access. The role of AI is examined in relation to model development, multimodal fusion, tissue-of-origin prediction, calibration, interpretability, bias, generalizability and clinical implementation. Across these technologies, a key translational message is that technical detectability is not equivalent to clinical readiness. While selected assays have entered defined clinical or guideline-supported settings, many emerging biomarkers and AI-enabled models remain investigational or translational. Future progress will depend on standardized workflows, prospective validation in representative populations, evidence of clinical utility, regulatory and ethical oversight, and integration with established screening and diagnostic systems.

Keywords: artificial intelligence; clinical validation; early cancer detection; liquid biopsy; multi-cancer early detection; tumor immune interactions

DOI: https://doi.org/10.3389/fimmu.2026.1854718

Front Oncol. 2026 ;16 1850041

Early detection of multiple cancers: the era of methylation-based liquid biopsy.

Yajie Lin, Zekai Hu, Leyao Shuai, Zhaowei Tong, Hainv Gao, Junsheng Zhao.

Liquid biopsy based on circulating cell-free DNA (cfDNA) methylation has become a leading non-invasive strategy for multi-cancer early detection (MCED). Aberrant DNA methylation arises at the early stage of tumorigenesis and displays cancer-type-specific signatures, enabling early capture of tumor-derived epigenetic signals. High-throughput sequencing, digital PCR and machine learning algorithms have greatly improved the sensitivity and specificity of methylation-based assays. Large-scale clinical trials including CCGA, PATHFINDER, THUNDER and GUIDE have validated that MCED tests achieve high specificity (>99%) and reliable accuracy for tissue of origin prediction. Integrating methylomics with fragmentomics further boosts early detection performance, especially for early-stage tumors with low ctDNA shedding. Nevertheless, clinical translation still faces notable hurdles, including technical standardization, biological confounding factors, high cost and the demand for large-scale prospective mortality endpoint validation. Future development will rely on multi-omics integration, optimized bioinformatic pipelines and standardized interventional trials to lower cancer-specific mortality. In summary, methylation liquid biopsy is poised to reshape cancer screening from single-organ late diagnosis to multi-cancer early intervention, offering profound prospects for precision oncology.

Keywords: DNA methylation; biomarker; circulating tumor DNA (ctDNA); liquid biopsy; multi-cancer early detection

DOI: https://doi.org/10.3389/fonc.2026.1850041