bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2026–05–24
two papers selected by
Sergio Marchini, Humanitas Research
  1. Genome-wide variation in cell-free DNA end motif entropy predicts immunotherapy response in head and neck cancer.
  2. Early detection of gastric cancer with the assistance of cell-free DNA fragmentomics.
  1. J Clin Invest. 2026 May 19. pii: e196284. [Epub ahead of print]
    Genome-wide variation in cell-free DNA end motif entropy predicts immunotherapy response in head and neck cancer.
    Ravi Bandaru, Hailu Fu, Haizi Zheng, Jocelyn Liang, Li Wang, Shuchi Gulati, Benjamin H Hinrichs, Mingxiang Teng, Bin Zhang, Masha Kocherginsky, De-Chen Lin, David A Hildeman, Francis P Worden, Matthew O Old, Neal E Dunlap, John M Kaczmar, Maura L Gillison, Dalia El-Gamal, Trisha Wise Draper, Yaping Liu.
       BACKGROUND: Minimally invasive biomarkers predicting immunotherapy response in head and neck squamous cell carcinoma (HNSCC) remain an unmet clinical need.
    METHODS: Using patients from a prospective, multi-institutional phase II trial, we performed whole-genome sequencing of 185 longitudinal plasma cell-free DNA (cfDNA) samples from 68 patients with locally advanced, surgically resectable HNSCC who received neoadjuvant and adjuvant pembrolizumab. We developed the regional motif diversity score (rMDS), a fragmentomic metric that quantifies the entropy of cfDNA 5'-end motifs across genomic regions.
    RESULTS: Unsupervised analysis showed rMDS robustly distinguished responders from non-responders, outperforming established fragmentomic metrics and copy number alterations while remaining independent of technical confounders. Longitudinal rMDS changes localized to regions enriched for immune-, lectin-, and keratinization-related genes - hallmarks of squamous cell carcinoma - reflecting tumor-peripheral immunity interplay during treatment. The most dynamic regions clustered at telomere-proximal loci, suggesting a link between telomere biology and cfDNA fragmentation. An rMDS-based machine learning classifier achieved AUC 0.89-0.99 across validation settings, with the highest accuracy post-treatment, outperforming PD-L1 expression and tumor fraction in matched samples. Predicted responders showed improved disease-free survival (log-rank P = 0.035; HR 2.67, 95% CI 1.03-6.92).
    CONCLUSION: rMDS represents a biologically meaningful, clinically actionable biomarker for immunotherapy response in HNSCC, supporting integration into future risk assessment frameworks.
    TRIAL REGISTRATION:
    CLINICALTRIALS: gov NCT02641093.
    FUNDING: NHGRI R56HG012360 and startup funds from Cincinnati Children's Hospital Medical Center, Northwestern University, and Robert H. Lurie Comprehensive Cancer Center (Y.L.); Science Olympiad Alumni Research Grant, Science Olympiad USA Foundation (R.B.); Merck Sharp & Dohme Corp. (T.W.D.).
    Keywords:  Cancer immunotherapy; Epigenetics; Genetics; Head and neck cancer; Oncology
    DOI:  https://doi.org/10.1172/JCI196284
  2. Clin Epigenetics. 2026 May 22.
    Early detection of gastric cancer with the assistance of cell-free DNA fragmentomics.
    Xiaoli Huang, Zhengxiang Han, Ying Zhang, Hongmei Wang, Xuqi Li, Chenxi Bai, Ying Pan, Jingwen Huang, Jiaojiao Xie, Xiaohan Qian, Xuan Wang, Tao Ding, Jinpeng Zhang, Shanshan Yang, Xinyue Hong, Qifan Jing, Gang Li, Xiaohua Li.
       BACKGROUND: Gastric cancer remains one of the most prevalent malignancies globally. As early-stage gastric cancer is typically asymptomatic or presents with non-specific symptoms, most patients are diagnosed at advanced stages, leading to poor survival outcomes. Effective early detection strategies are important for reducing gastric cancer-related mortality. In this study, we developed a non-invasive assay utilizing cell-free DNA to distinguish patients with early-stage gastric cancer from healthy individuals.
    RESULTS: We performed low-depth whole genome sequencing to profile cell-free DNA and extracted three distinct features: fragment size patterns, coverage at transcription factor binding sites, and methylation-based profiles. These features were integrated via machine learning to construct a stacked ensemble model. The study included a training cohort (108 gastric cancer patients and 108 healthy controls), a temporally independent validation cohort (79 patients and 79 healthy controls), and an external validation cohort recruited from two independent centers (136 patients and 136 healthy controls). The ensemble model demonstrated robust performance, achieving area under the curve values of 0.986, 0.978, and 0.967 in the training, validation, and external cohorts, respectively. Specificity and sensitivity were 98.1% and 89.8% in the training cohort, 97.5% and 87.6% in the validation cohort, and 96.3% and 87.5% in the external cohort. Notably, the sensitivity for detecting stage I gastric cancer exceeded 85% across all cohorts.
    CONCLUSIONS: By integrating multi-dimensional cell-free DNA fragmentomic features, this assay provides accurate, non-invasive detection of gastric cancer, particularly at early stages. While its performance was high, the specificity reported here may be overestimated due to the use of a strictly screened healthy control group. Nevertheless, this fragmentomic-based approach represents a promising tool to complement existing screening strategies, potentially improving early diagnosis rates.
    Keywords:  Cell-free DNA; Early detection; Fragmentomics; Gastric cancer
    DOI:  https://doi.org/10.1186/s13148-026-02150-9
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