bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2025–11–02
ten papers selected by
Sergio Marchini, Humanitas Research
  1. Biomarkers in High-Grade Serous Ovarian Cancer: Context is everything.
  2. Clinical validation of a DNA methylation biomarker associated with overall survival of relapsed ovarian cancer patients.
  3. Real-world data and clinical experience from over 100,000 multi-cancer early detection tests.
  4. Advances in Epigenomic Sequencing and Their Applications in Cancer Diagnostics.
  5. ZIPcnv: accurate and efficient inference of copy number variations from shallow whole-genome sequencing.
  6. Artificial Intelligence and Multi-modality Data Integration Deciphers Tertiary Lymphoid Structure Maturity in Gastric Cancer.
  7. A multi-center study for colorectal cancer early detection in high-risk disease patients using cell-free fragmentomics assay.
  8. Annotating the genome at single-nucleotide resolution with DNA foundation models.
  9. Single-cell and spatial transcriptomics reveal intratumor heterogeneity and immune evasion in natural killer/T cell lymphoma.
  10. Acquired high tumor mutational burden and activity of immunotherapy after targeted therapy in microsatellite stable colorectal cancer.
  1. Clin Cancer Res. 2025 Oct 30.
    Biomarkers in High-Grade Serous Ovarian Cancer: Context is everything.
    Laura Venegas, Anjelica Hodgson, Amit M Oza.
      The Oxford Classic Epithelial-Mesenchymal Transition (OxC-EMT) score identifies a high-risk subgroup of High-Grade Serous Carcinoma (HGSC) patients with inferior survival. This commentary discusses the evaluation of HGSC biomarkers in context and the important steps in transition from a prognostic to a validated predictive biomarker to inform clinical utility.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-25-2851
  2. Int J Cancer. 2025 Nov 01.
    Clinical validation of a DNA methylation biomarker associated with overall survival of relapsed ovarian cancer patients.
    Muhammad Habiburrahman, Nahal Masrour, Naina Patel, Anna M Piskorz, Robert Brown, James D Brenton, Iain A McNeish, James M Flanagan.
      Approximately 70% of ovarian cancer (OC) patients relapse after chemotherapy, underscoring the need to assess survival before second-line treatment. We previously identified PLAT-M8, an 8-CpG blood-based methylation signature linked to chemoresistance. This study validates its correlation with clinicopathological features and treatment profiles in additional cohorts. Extracted DNA from whole blood was provided from the BriTROC-1 (n = 47) and OV04 cohorts (n = 57) upon the first relapse. Additional samples from Hammersmith Hospital (n = 100) were collected during first-line chemotherapy (Cycles 3-4 and 6). Bisulphite pyrosequencing was used to quantify DNA methylation at the previously identified 8 CpG sites. The methylation data obtained were combined with previous data from ScoTROC-1D and 1V (n = 141) and OCTIPS (n = 46). Cox regression was used to assess OS after relapse concerning clinicopathological characteristics. The DNA methylation Class (Class 1 vs. 2) was determined by consensus clustering. As for results, blood DNA methylation at relapse correlates with clinical outcomes, but it has no impact during first-line treatment. Class 1 is linked to shorter survival (summary OS: HR 2.50, 1.64-3.79) and poorer prognosis on carboplatin monotherapy (OS: aHR 9.69, 95% CI: 2.38-39.47). It is associated with older (>75 years), advanced-stage, platinum-resistant patients, residual disease, and shorter PFS. In contrast, Class 2 is linked to platinum sensitivity, higher complete response rates (RECIST), and better prognosis but shows no correlation with CA-125. These findings highlight PLAT-M8's potential in guiding second-line chemotherapy decisions. The PLAT-M8 methylation biomarker is associated with survival in relapsed OC patients and may potentially predict their response to second-line platinum treatment.
    Keywords:  DNA methylation; epigenetic biomarker; ovarian cancer; platinum‐based chemotherapy; survival
    DOI:  https://doi.org/10.1002/ijc.70217
  3. Nat Commun. 2025 Oct 31. 16(1): 9625
    Real-world data and clinical experience from over 100,000 multi-cancer early detection tests.
    Marc Matrana, Vershalee Shukla, Dallas Kingsbury, Martin Poliak, Jordan Lipton, Matthew McMillin, Louis B Malinow, Oliver Venn, John F Beausang, Geoff Stanley, Earl Hubbell, Kathryn N Kurtzman, Jeffrey M Venstrom, Rita Shaknovich, Candace Westgate.
      Blood-based multi-cancer early detection (MCED) has the potential to simultaneously screen for multiple deadly cancers with high positive predictive value. To assess real-world performance, we evaluated the Galleri® MCED test (GRAIL, Inc.) across 111,080 individuals (median age 58 years, 55.5% males). This MCED test analyzes methylation patterns of cell-free DNA to detect presence of a cancer signal and predict the anatomical cancer signal origin (CSO) to facilitate diagnostic evaluation. Cancer signal detection rate was 0.91% (1011/111,080), consistent with clinical studies and independent modeled values. Providers reported clinical outcome for 459 of 1011 individuals with cancer signal detected MCED tests. Of these, 258 had an invasive cancer diagnosis, spanning 32 cancer types. The MCED test correctly predicted the CSO in 87% of cases with a reported cancer type, consistent with previous clinical studies. CSO enabled efficient workup in most patients, with a median 39.5 days from result receipt to cancer diagnosis.
    DOI:  https://doi.org/10.1038/s41467-025-64094-7
  4. Precis Chem. 2025 Oct 27. 3(10): 581-603
    Advances in Epigenomic Sequencing and Their Applications in Cancer Diagnostics.
    Liyun Lin, Yang Liu.
      Cancer, a globally prevalent and life-threatening disease, remains a major area of focus in biomedical research. However, its substantial heterogeneity and complex pathogenesis continue to pose significant challenges for accurate diagnosis and effective treatment. The rapid advancement of epigenomic sequencing technologies has opened avenues by uncovering the epigenetic hallmarks and underlying pathology of cancer. As a result, these technologies have become invaluable tools in advancing cancer diagnostics and connecting research with clinical applications. This review briefly overviews epigenomic modifications and their significance in cancer diagnostics, highlighting potential epigenomic biomarkers with clinical applicability. We also examine emerging techniques in bulk and single-cell sequencing approaches, alongside spatial tools, highlighting their integration with multiomics technologies for cancer diagnostics. Particular attention is given to the analysis of key epigenetic characteristics, such as DNA methylation, histone modifications, and chromatin accessibility. Additionally, we summarize the diagnostic applications of these technologies and evaluate their current adoption in clinical settings. Challenges, limitations, and future directions for advancing epigenomic sequencing toward routine clinical diagnostics are also discussed. This review aims to provide scientists and clinicians with a comprehensive resource, encouraging further exploration and adoption of epigenomic sequencing technologies to drive progress in precision medicine.
    Keywords:  DNA methylation; cancer diagnostics; chromatin accessibility; epigenomics; histone modifications; sequencing; single-cell; spatial
    DOI:  https://doi.org/10.1021/prechem.5c00014
  5. Bioinformatics. 2025 Oct 25. pii: btaf592. [Epub ahead of print]
    ZIPcnv: accurate and efficient inference of copy number variations from shallow whole-genome sequencing.
    Zhengfa Xue, Jingyu Zeng, Xuwen Wang, Jiajing Yuan, Tianci Wang, Xin Lai, Lin Wang, Yu Wang, Huanhuan Zhu, Xin Jin, Jiayin Wang.
       MOTIVATION: Shallow whole-genome sequencing (sWGS), a rapid and cost-effective sequencing technology, has gradually been widely adopted for CNV analyses. However, with genome‑wide coverage of only 0.1-5X, sWGS data display a pronounced zero‑inflation phenomenon-a large fraction of loci has zero sequencing reads. Zero‑inflation causes read counts to fluctuate by several‑fold between adjacent windows. As a result, random upward blips in coverage can be misinterpreted as copy‑number gains (false positives), and true deletions often become indistinguishable from pervasive zero‑coverage noise. In addition, existing CNV detection tools developed for sWGS data often struggle to adapt across different CNV sizes. These combined effects severely constrain the accuracy of CNV inference.
    RESULTS: To address above challenges, we propose ZIPcnv, a novel CNV detection tool specifically designed for sWGS data. First, we apply a segment sliding window to smooth the raw read depth signal, which transforms the original zero-inflated statistical characteristics into approximately normal distribution characteristics. We then design a statistical process model that robustly detects persistent shifts under high background noise using a cumulative sum strategy, classifying genomic regions into candidate and non-candidate CNV regions. Finally, dynamic sliding windows are used for one-pass detection of CNVs of varying lengths, with window size adapting to the CNV region size. We evaluated the performance of ZIPcnv on simulated data and 190 real whole-genome sequencing samples. Experimental results show that ZIPcnv consistently outperforms currently popular CNV detection tools.
    AVAILABILITY: The ZIPcnv source code is freely available at https://github.com/Nevermore233/ZIPcnv.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    Keywords:  Copy number variations; Genomics; Low coverage; Shallow whole-genome sequencing; Zero-inflated
    DOI:  https://doi.org/10.1093/bioinformatics/btaf592
  6. Cancer Res. 2025 Oct 28.
    Artificial Intelligence and Multi-modality Data Integration Deciphers Tertiary Lymphoid Structure Maturity in Gastric Cancer.
    Wenxuan Wu, Zhenzhen Xun, Yaxuan Han, Qimiao Chen, Shaojun Yu, Yikai Luo, Zhixing Hao, Jing Chen, Yewei Xu, Xiaying Han, Jia Qi, Kai Song, Xiaojing Ma, Yongyuan Yhen, Guofeng Chen, Muxing Kang, Xiaoli Jin, Yuan Ding, Zhiqiang Zhu, Can Hu, Xiangdong Cheng, Lie Wang, Pin Wu, Han Liang, Jian Chen.
      Tertiary lymphoid structures (TLSs) are critical components of the tumor microenvironment in gastric cancer (GC), but clinical assessment of TLS is challenging. The development of automated annotation tools for histopathological slide analysis could facilitate the identification of TLSs and enhance our understanding of the mechanisms driving TLS maturation. Here, we generated a transformer-based deep learning model that enables quantitative characterization of TLS maturity from whole-slide images. Application of the model to a large GC cohort (n = 253) showed that higher TLS maturity correlated with improved patient survival. Integration of single-cell RNA sequencing data from 17 GC patients combined with multiplex immunohistochemistry, flow cytometry, and functional co-culture assays identified a key immune circuit in mature TLSs involving CD8⁺ tissue-resident memory T cells (TRM), which recruit activated B cells via the CXCL13-CXCR5 axis to enhance TRM cytotoxicity through granzyme B upregulation. Overall, this study established a clinically applicable AI tool and uncovered key immune interactions that regulate TLS maturation and anti-tumor immunity in GC.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-25-1793
  7. Cancer Cell Int. 2025 Oct 29. 25(1): 382
    A multi-center study for colorectal cancer early detection in high-risk disease patients using cell-free fragmentomics assay.
    Jierong Chen, Zhongwen Zheng, Linjie Zhang, Waiting Lam, Qingxin Xie, Lishu Xu, Jing Zhou, Guansheng Zheng, Feng Zhu, Kai Wang, Zejian Lyu, Qinggang Yuan, Ruowei Yang, Xiuxiu Xu, Dongqin Zhu, Lingling Yang, Hua Bao, Deqing Wu, Yong Li, Chao Ding, Bing Gu.
       BACKGROUND: Early detection of colorectal cancer (CRC) is crucial for improving patient survival. This innovative multi-center study aims to develop a non-invasive blood-based assay using cell-free DNA (cfDNA) fragmentomics to differentiate CRC from advanced colorectal adenomas and non-cancerous colorectal and other digestive diseases.
    METHODS: A total of 167 CRC patients and 227 with benign colorectal conditions were divided into training and validation cohorts (1:1 ratio). Plasma cfDNA underwent Low-depth whole-genome sequencing to profile three fragmentomics features, which were integrated into a stacked ensemble model. The model was validated on 69 CRC patients and 96 benign controls, with an additional cohort of 31 advanced adenoma patients included to assess its performance in differentiating advanced adenomas from benign cases.
    RESULTS: The model achieved an AUC of 0.926, with sensitivity of 91.3% and specificity of 82.3% in validation. Sensitivities were consistently high across CRC stages (I: 94.4%, II: 86.4%, III: 91.3%, IV: 100%). Notably, the model demonstrated exceptional accuracy in distinguishing advanced adenomas from benign cases, achieving an AUC of 0.846 and sensitivity of 67.7%, outperforming traditional blood tests.
    CONCLUSIONS: This multi-center study underscores a significant advancement in liquid biopsy technology, offering a highly accurate and non-invasive approach for early CRC detection and differentiation of advanced colorectal adenomas.
    Keywords:  Advanced colorectal adenoma; Cell-free DNA fragmentomics; Colorectal cancer; Early- detection; Liquid biopsy
    DOI:  https://doi.org/10.1186/s12935-025-03967-9
  8. Nat Methods. 2025 Oct 29.
    Annotating the genome at single-nucleotide resolution with DNA foundation models.
    Bernardo P de Almeida, Hugo Dalla-Torre, Guillaume Richard, Christopher Blum, Lorenz Hexemer, Maxence Gélard, Javier Mendoza-Revilla, Ziqi Tang, Frederikke I Marin, David M Emms, Priyanka Pandey, Stefan Laurent, Marie Lopez, Alexandre Laterre, Maren Lang, Uğur Şahin, Karim Beguir, Thomas Pierrot.
      Genome annotation models that directly analyze DNA sequences are indispensable for modern biological research, enabling rapid and accurate identification of genes and other functional elements. Current annotation tools are typically developed for specific element classes and trained from scratch using supervised learning on datasets that are often limited in size. Here we frame the genome annotation problem as multilabel semantic segmentation and introduce a methodology for fine-tuning pretrained DNA foundation models to segment 14 different genic and regulatory elements at single-nucleotide resolution. We leverage the self-supervised pretrained model Nucleotide Transformer to develop a general segmentation model, SegmentNT, capable of processing DNA sequences up to 50-kb long and that achieves state-of-the-art performance on gene annotation, splice site and regulatory elements detection. We also integrated in our framework the foundation models Enformer and Borzoi, extending the sequence context up to 500 kb and enhancing performance on regulatory elements. Finally, we show that a SegmentNT model trained on human genomic elements generalizes to different species, and a multispecies SegmentNT model achieves strong generalization across unseen species. Our approach is readily extensible to additional models, genomic elements and species.
    DOI:  https://doi.org/10.1038/s41592-025-02881-2
  9. iScience. 2025 Oct 17. 28(10): 113626
    Single-cell and spatial transcriptomics reveal intratumor heterogeneity and immune evasion in natural killer/T cell lymphoma.
    Shuyun Ma, Biaojie Huang, Jiahui Wang, Ru Lv, Dan-Ling Dai, Qian Zhong, Yi Xia, Panpan Liu, Youqiong Ye, Kui Wu, Shichen Dong, Jun Cai, Qihua Zou, Yuchen Zhang, Lirong Li, Guibo Li, Wenlong Zhong, Lei Wang, Qingqing Cai.
      Natural killer/T cell lymphoma (NKTCL), an Epstein-Barr virus-associated malignancy, is a highly aggressive subtype of non-Hodgkin lymphoma. However, the intratumoral heterogeneity and the interaction within the tumor microenvironment (TME) remain insufficiently understood. Here, we utilized single-cell and spatial transcriptomics to analyze tissues from NKTCL patients, identifying five malignant meta-programs (MPs) with distinct functional pathways, differentiation trajectories, and spatial distributions. Notably, the MP3 subgroup emerges at the early stages of tumor differentiation, characterized by the hyperactivation of MYC signaling and an association with poor prognosis. Intriguingly, pharmacologic inhibition of fatty acid-binding protein 5 (FABP5) leads to the downregulation of c-Myc and significantly impairs tumor growth both in vitro and in vivo. Furthermore, ligand-receptor interaction analysis reveals that tumor-associated macrophages (TAMs) may facilitate immune evasion and suppress T cell activity within the TME. Collectively, our findings elucidate the cellular heterogeneity and immune landscape of NKTCL, offering potential targets for therapeutic intervention.
    Keywords:  Cancer; Microenvironment; Transcriptomics
    DOI:  https://doi.org/10.1016/j.isci.2025.113626
  10. Clin Cancer Res. 2025 Oct 30.
    Acquired high tumor mutational burden and activity of immunotherapy after targeted therapy in microsatellite stable colorectal cancer.
    Celine Yeh, Oliver Artz, Haochen Zhang, Elias-Ramzey Karnoub, Peter Ntiamoah, Caroline Weipert, Henry Walch, Emily Harrold, Fergus Keane, Sree Chalasani, Neil H Segal, Michael B Foote, Andrea Cercek, Andrew Pagano, Steven B Maron, Luis A Diaz, Christine A Iacobuzio-Donahue, Jinru Shia, Benoit Rousseau, Rona Yaeger.
       PURPOSE: Microsatellite stable (MSS) colorectal cancers (CRCs), in contrast to microsatellite instability-high (MSI-H) CRCs, have few mutations and are insensitive to immune checkpoint blockade (ICB). CRCs treated with targeted agents often acquire a high number of genomic alterations at progression. We asked if targeted therapy could be used to generate a high tumor mutational burden (TMB) in MSS CRC and sensitize these tumors to ICB.
    PATIENTS AND METHODS: In patients with MSS metastatic CRC treated with targeted therapy, we evaluated baseline and progression TMB and response to ICB for patients whose tumors developed high TMB. We determined types of alterations, mutational signatures, neoantigenicity, and clonality associated with emergent genomic alterations in cases of acquired high TMB.
    RESULTS: Among 26 cases, nine acquired high TMB at progression. Three of these patients received ICB but none had a response. In the TMB-high cases, we found no induction of tumor-infiltrating lymphocytes or programmed death-ligand 1 expression. Acquired genomic alterations consisted predominantly of single nucleotide variants, were enriched for single-base substitution 17a/b mutational signature, and did not enhance predicted major histocompatibility complex class I binding. TMB was higher in plasma, driven by highly subclonal acquired alterations, compared to tissue samples which harbored few resistance alterations.
    CONCLUSION: A substantial number of MSS CRCs acquire high TMB following targeted therapy. However, this change is not associated with sensitization to ICB. The high TMB is due to subclonal alterations unique to individual disease sites that are inadequate to elicit a robust antitumor immune response.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-25-2566
This page is being maintained by Thomas Krichel. It was last updated on 2025‒12‒01 at 8:24.