bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2026–01–25
seven papers selected by
Sergio Marchini, Humanitas Research
  1. Cancer-Like Fragmentomic Characteristics of Somatic Variants in Cell-Free DNA.
  2. Mismatch Repair Deficiency Profiling and Its Impact on Management and Prognosis in Endometrial Cancer Patients: A Comprehensive Update.
  3. Enhancing interpretation of clinical disease-associated copy number variations from multiple sequencing strategies with CNVSeeker.
  4. Sacituzumab Govitecan plus Pembrolizumab for Advanced Triple-Negative Breast Cancer.
  5. Robust characterization and interpretation of rare pathogenic cell populations from spatial omics using GARDEN.
  6. Liquid biopsy in Oncology: Results of a Delphi consensus study endorsed by the AIOM-SIAPEC/IAP-SIBioC-SIF Italian scientific societies.
  7. Impact and correction of segmentation errors in spatial transcriptomics.
  1. Adv Sci (Weinh). 2026 Jan 22. e14819
    Cancer-Like Fragmentomic Characteristics of Somatic Variants in Cell-Free DNA.
    Zhenyu Zhang, Yunyun An, Mengqi Yang, Yuqi Pan, Xiaoyi Liu, Fanglei Gong, Huizhen Lin, Bianbian Tang, Yunxia Bai, Xin Zhao, Yu Zhao, Changzheng Du, Kun Sun.
      Cell-free DNA (cfDNA) in plasma consists of short DNA fragments resulting from a non-random fragmentation process, with distinct fragmentomic characteristics that are related with their cellular origins. Here, we report that somatic variant signatures in cfDNA markedly differ between non-cancerous controls and cancer patients, indicating that tumor-associated signals are retained in these variants. Surprisingly, even in controls, cfDNA molecules harboring somatic variants exhibit cancer-like fragmentomic characteristics, such as reduced size, decreased DNA methylation, and altered end motif usages and distributions in the nucleosome structure. Further investigations suggest that such cancer-like traits are associated with somatic variants derived from clonal hematopoiesis. Importantly, these somatic variants-associated fragmentomic aberrations are more pronounced in cancer patients, enabling cancer diagnosis. In a large pan-cancer cohort, we utilize AI to integrate genomic, fragmentomic, and epigenomic features to develop diagnostic models named FreeSV and FreeSV+. Leveraging somatic variant-associated features alone, the FreeSV model achieved area under the ROC curves (AUCs) between 0.81-0.92 across cancer types; however, when genomewide features are also included, the AUCs of FreeSV+ model substantially increased to 0.93-0.99 across cancer types, highlighting the significance of integrative genomic and fragmentomic analyses in cfDNA for cancer liquid biopsy.
    Keywords:  artificial intelligence; cancer diagnosis; end motif; epigenomics; liquid biopsy
    DOI:  https://doi.org/10.1002/advs.202514819
  2. Cureus. 2025 Dec;17(12): e99364
    Mismatch Repair Deficiency Profiling and Its Impact on Management and Prognosis in Endometrial Cancer Patients: A Comprehensive Update.
    Emmanouela-Aliki Almperi, Chrysoula Margioula-Siarkou, Aristarchos Almperis, Georgia Margioula-Siarkou, Stefanos Flindris, Alexandros I Daponte, Theodora Papamitsou, Konstantinos Dinas, Stamatios Petousis.
      With an increasing incidence, endometrial cancer (EC) is the most prevalent gynecologic cancer in developed countries. Although histological classification has been used traditionally, its usage in forecasting clinical behavior was less effective. A molecular classification of EC has been introduced by the Cancer Genome Atlas (TCGA), which has separated it into four subgroups: p53-abnormal (p53abn), mismatch repair deficiency (MMRd), polymerase epsilon (POLE)-mutated (POLEmut), and no specific molecular profile (NSMP). The prognostic value of this molecular subtyping is superior. This narrative review analyzes the clinicopathological features of MMRd tumors, highlighting their intermediate prognosis relative to other molecular subtypes, while also noting associations with high-grade, lymphovascular space invasion, and lymph node metastasis. For this purpose, relevant studies were retrieved from PubMed, Scopus, and Web of Science up to 2025, focusing on clinicopathological correlations and treatment outcomes. Furthermore, we analyze the important therapeutic implications of MMR status. About 25%-30% of cases are classified as MMRd EC and are associated with an intermediate prognosis. The increased mutational burden in MMRd tumors enhances their susceptibility to immune checkpoint inhibitors such as pembrolizumab and dostarlimab, which have demonstrated considerable efficacy and altered the treatment approach for patients with advanced or recurrent MMRd EC. This review highlights the significance of MMR testing in risk stratification, prognosis, and planning of personalized treatment, ultimately improving patient outcomes.
    Keywords:  cancer immunotherapy; endometrial cancer (ec); mmr deficient; molecular profile; platinum based chemotherapy
    DOI:  https://doi.org/10.7759/cureus.99364
  3. Bioinformatics. 2026 Jan 19. pii: btag034. [Epub ahead of print]
    Enhancing interpretation of clinical disease-associated copy number variations from multiple sequencing strategies with CNVSeeker.
    Xudong Xiang, Xinxin Mao, Tengfei Luo, Chenbin Liu, Bozhao Li, Pei Yu, Yu Zhang, Dai Wu, Yijing Wang, Qiao Zhou, Yixiao Zhu, Bin Li, Kun Xia, Guihu Zhao, Jinchen Li.
       MOTIVATION: DNA copy number variations (CNVs) exert a profound impact on major genetic disorders in humans. Although multiple sequencing technologies have become the first line of molecular diagnosis for CNVs, existing tools are unable to resolve the pathogenicity of CNVs directly from raw sequencing data.
    RESULTS: We developed CNVSeeker, a one-stop and easy-to-use pipeline that provides comprehensive analysis from raw sequencing data to variant interpretation reports, and supports multiple types of sequencing data including short-read data such as whole genome sequencing (WGS) data and whole exome sequencing (WES) data, and long-read sequencing data from Pacific Biosciences HiFi (PacBio) platform or Oxford Nanopore Technologies (ONT) platform. Through extensive benchmarking, CNVSeeker demonstrated comparable enhancement over the state-of-the-art methods for CNV calling. Moreover, CNVSeeker enables significantly precise variant classification with an accuracy of ∼87%. By applying CNVSeeker to 1946 individuals with autism spectrum disorder (ASD), a total of 133 ASD-associated CNVs in 122 patients were identified, yielding a diagnostic yield of ∼6.3%. Additionally, we have also provided a user-friendly webserver for intuitive visualization of results. This study highlights the potential of CNVSeeker to benefit clinicians and geneticists with limited bioinformatic skill by aiding them interpret CNVs directly from various types of raw sequencing data for auxiliary disease diagnosis.
    AVAILABILITY: The web server is freely available at https://genemed.tech/cnvseeker and the open-source code can be found at https://github.com/lovelycatZ/CNVSeeker.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btag034
  4. N Engl J Med. 2026 Jan 22. 394(4): 354-366
    Sacituzumab Govitecan plus Pembrolizumab for Advanced Triple-Negative Breast Cancer.
    ASCENT-04/KEYNOTE-D19 Clinical Trial Investigators
       BACKGROUND: Triple-negative breast cancer is an aggressive breast cancer subtype, and there remains an unmet need to improve outcomes in patients with previously untreated, programmed death ligand 1 (PD-L1)-positive, locally advanced unresectable or metastatic triple-negative breast cancer.
    METHODS: In this phase 3, open-label, international trial, we randomly assigned patients in a 1:1 ratio to receive sacituzumab govitecan plus pembrolizumab or chemotherapy plus pembrolizumab. The primary end point was progression-free survival as assessed by blinded independent central review. Secondary end points included overall survival, objective response (complete or partial response) and duration of response as assessed by blinded independent central review, and safety.
    RESULTS: A total of 443 patients were randomly assigned to receive sacituzumab govitecan plus pembrolizumab (221 patients) or chemotherapy plus pembrolizumab (222 patients). The median progression-free survival was 11.2 months (95% confidence interval [CI], 9.3 to 16.7) with sacituzumab govitecan plus pembrolizumab and 7.8 months (95% CI, 7.3 to 9.3) with chemotherapy plus pembrolizumab (hazard ratio for disease progression or death, 0.65; 95% CI, 0.51 to 0.84; two-sided P<0.001). Data for overall survival were immature. The percentage of patients with an objective response was 60% (95% CI, 53 to 66) with sacituzumab govitecan plus pembrolizumab and 53% (95% CI, 46 to 60) with chemotherapy plus pembrolizumab; among patients with a response, the median duration of response was 16.5 months (95% CI, 12.7 to 19.5) and 9.2 months (95% CI, 7.6 to 11.3), respectively. Adverse events of grade 3 or higher occurred in 71% of the patients receiving sacituzumab govitecan plus pembrolizumab and in 70% of those receiving chemotherapy plus pembrolizumab; the incidence of treatment discontinuation due to adverse events was 12% and 31%, respectively. Adverse events leading to death occurred in 3% of the patients in each group.
    CONCLUSIONS: Sacituzumab govitecan plus pembrolizumab led to significantly longer progression-free survival than chemotherapy plus pembrolizumab among patients with previously untreated, PD-L1-positive, advanced triple-negative breast cancer. (Funded by Gilead Sciences; ASCENT-04/KEYNOTE-D19 ClinicalTrials.gov number, NCT05382286.).
    DOI:  https://doi.org/10.1056/NEJMoa2508959
  5. Nat Commun. 2026 Jan 17.
    Robust characterization and interpretation of rare pathogenic cell populations from spatial omics using GARDEN.
    Xinming Zhang, Zhuohan Yu, Gaoyang Hao, Qi Yao, Yanmei Hu, Fuzhou Wang, Xingjian Chen, Linjing Liu, Ka-Chun Wong, Xiangtao Li.
      Spatial omics links molecular measurements to their positions in tissue, revealing cellular organization and interactions. Yet most computational tools highlight common cell types and overlook rare populations that can drive disease. Here we show GARDEN, a computational framework that identifies and characterizes these pathogenic cells or regions in spatial omics by embedding graph-based dynamic attention into a spatially-aware graph fusion contrastive model. GARDEN works consistently across tissues, species and resolution scales, and aligns consecutive sections to reconstruct 3D anatomy. In an Alzheimer's disease model, GARDEN localizes C1qa/C1qb-marked microglia in amyloid-β regions and reveals key immune pathways. In nasopharyngeal carcinoma it identifies tiny tertiary lymphoid structures, and in breast cancer it uncovers inflammatory M1-like macrophages near ductal carcinoma in situ and links them to pro-metastatic signaling. An interpretation module pinpoints key immune signatures, and GARDEN extends to spatial chromatin accessibility, providing insight into epigenetic regulation and informing diagnostics and therapeutic targeting.
    DOI:  https://doi.org/10.1038/s41467-026-68500-6
  6. J Liq Biopsy. 2026 Mar;11 100453
    Liquid biopsy in Oncology: Results of a Delphi consensus study endorsed by the AIOM-SIAPEC/IAP-SIBioC-SIF Italian scientific societies.
    Valerio Gristina, Umberto Malapelle, Gennaro Daniele, Giovanni Maria Iannantuono, Tancredi Didier Bazan Russo, Rossana Berardi, Giordano Domenico Beretta, Ettore Domenico Capoluongo, Marcello Ciaccio, Romano Danesi, Marzia Del Re, Matteo Fassan, Giuseppe Giuffrè, Stefania Gori, Lorena Incorvaia, Antonio Marchetti, Nicola Normanno, Carmine Pinto, Daniele Santini, Andrea Sartore Bianchi, Nicola Silvestris, Pierosandro Tagliaferri, Giancarlo Troncone, Massimo Di Maio, Francesco Perrone, Antonio Galvano, Christian Rolfo, Antonio Russo.
      Liquid biopsy (LB) offers a minimally invasive alternative to tissue biopsy by detecting tumor-derived analytes in biological fluids. Nonetheless, its adoption is limited by variability in methodologies. Therefore, this study used a modified RAND/UCLA approach involving 23 experts of the field, providing two questionnaires that assessed agreement on 22 items. Consensus was reached for all the pre- and post-analytical phase items, agreeing on the pivotal role of plasma cfDNA. Conversely, opinions varied regarding other biomarkers and biological samples. Furthermore, turnaround time and disease setting resulted as two of the most important analytical parameters for choosing testing methodology. Particularly, a complementary tissue-liquid approach with sampling interval ≤2 weeks was preferred. To conclude, a strong consensus on sample handling, biomarker prioritization, and clinical applications is achieved. However, significant heterogeneity remains regarding novel biomarkers, sampling strategies, and costs. Standardization and validation are needed to enhance the clinical adoption of LB.
    Keywords:  Clinical practice; Delphi; Liquid biopsy; Solid tumors; ctDNA
    DOI:  https://doi.org/10.1016/j.jlb.2025.100453
  7. Nat Genet. 2026 Jan 20.
    Impact and correction of segmentation errors in spatial transcriptomics.
    Jonathan Mitchel, Teng Gao, Viktor Petukhov, Eli Cole, Peter V Kharchenko.
      Spatial transcriptomics aims to elucidate how cells coordinate within tissues by connecting cellular states to their native microenvironments. Imaging-based assays are especially promising, capturing molecular and cellular features at subcellular resolution in three dimensions. Interpretation of such data, however, hinges on accurate cell segmentation. Assigning individual molecules to the correct cells remains challenging. Here we re-analyze data from multiple tissues and platforms to find that segmentation errors currently confound most downstream analysis of cellular state, including differential expression, neighbor influence and ligand-receptor interactions. The extent to which misassigned molecules impact the results can be striking, frequently dominating the results. Thus, we show that matrix factorization of local molecular neighborhoods can effectively identify and isolate such molecular admixtures, thereby reducing their impact on downstream analyses, in a manner analogous to doublet filtering in single-cell RNA sequencing. As the applications of spatial transcriptomics assays become more widespread, accounting for segmentation errors will be important for resolving molecular mechanisms of tissue biology.
    DOI:  https://doi.org/10.1038/s41588-025-02497-4
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