bims-tumhet 2025-09-21 papers

bims-tumhet

Biomed News

on Tumor heterogeneity

Issue of 2025–09–21
nine papers selected by
Sergio Marchini, Humanitas Research

Cancer subclone detection based on DNA copy number in single-cell and spatial omic sequencing data.
A subset of serous tubal intraepithelial carcinoma (STIC)-like lesions and concurrent high-grade endometrial carcinoma are genomically related entities.
The application and prospects of spatial omics technologies in clinical medical research and molecular diagnostics.
AACR Cancer Progress Report 2025: Unifying Cancer Science and Medicine: A Continuum of Innovation for Impact.
CNSistent integration and feature extraction from somatic copy number profiles.
Clinical relevance of circulating tumor DNA in HER2-positive advanced gastric cancer: a collaborative study of a phase Ib trial of dual HER2 and PD-1 targeted therapy (Ni-High).
Epigenetic paradigm of DNA methylation for understanding the pathophysiology, diagnostics, and therapeutics in sarcomas.
Precision epigenetic therapies in oncology.
The Approaching Darwinian Era in Oncology.

Nat Methods. 2025 Sep;22(9): 1846-1856

Cancer subclone detection based on DNA copy number in single-cell and spatial omic sequencing data.

Chi-Yun Wu, Jiazhen Rong, Anuja Sathe, Paul R Hess, Billy T Lau, Susan M Grimes, Sijia Huang, Hanlee P Ji, Nancy R Zhang.

Somatic mutations such as copy number alterations accumulate during cancer progression, driving intratumor heterogeneity that impacts therapy effectiveness. Understanding the characteristics and spatial distribution of genetically distinct subclones is essential for unraveling tumor evolution and improving cancer treatment. Here we present Clonalscope, a subclone detection method using copy number profiles, applicable to spatial transcriptomics and single-cell sequencing data. Clonalscope implements a nested Chinese Restaurant Process to identify de novo tumor subclones, which can incorporate prior information from matched bulk DNA sequencing data for improved subclone detection and malignant cell labeling. On single-cell RNA sequencing and single-cell assay for transposase-accessible chromatin using sequencing data from gastrointestinal tumors, Clonalscope successfully labeled malignant cells and identified genetically different subclones with thorough validations. On spatial transcriptomics data from various primary and metastasized tumors, Clonalscope labeled malignant spots, traced subclones and identified spatially segregated subclones with distinct differentiation levels and expression of genes associated with drug resistance and survival.

DOI: https://doi.org/10.1038/s41592-025-02773-5
Mod Pathol. 2025 Sep 12. pii: S0893-3952(25)00188-7. [Epub ahead of print] 100890

A subset of serous tubal intraepithelial carcinoma (STIC)-like lesions and concurrent high-grade endometrial carcinoma are genomically related entities.

Edaise M da Silva, Arnaud Da Cruz Paula, Kimberly Dessources, Sushmita Gordhandas, Pier Selenica, Nadeem R Abu-Rustum, Britta Weigelt, Rajmohan Murali.

  In patients with high-grade endometrial carcinoma (HG-EC), concurrent isolated serous tubal intraepithelial carcinoma (STIC) or STIC-like lesions (STIC-LLs) in the fallopian tube(s) may be found. We sought to determine whether concurrently diagnosed HG-ECs and STIC-LLs are genetically related. Six HG-ECs, including serous carcinomas (n=4) and carcinosarcomas with serous epithelial component (n=2), with co-occurring STIC-LLs were identified, and subjected to microdissection, DNA extraction and panel sequencing targeting 468 cancer-related genes, or, if DNA quantities were limited, to Sanger sequencing. WT1 and p53 protein expression was assessed by immunohistochemistry (IHC). We found that three HG-ECs and concurrent STIC-LLs shared pathogenic mutations, such as TP53 hotspot, NF2, FBXW7 and PIK3CA mutations. IHC analysis revealed that the HG-EC of case 5 lacked WT1 expression and had p53 aberrant expression, while the matched STIC-LL displayed diffuse WT1 expression. Of the remaining three cases that did not show evidence of genetic relatedness based on the targeted sequencing panel, one STIC-LL harbored a clonal TP53 missense mutation, whereas the matched HG-EC had a distinct clonal TP53 hotspot mutation, a clonal FBXW7 hotspot mutation, and ERBB2 amplification. At the protein level, the p53 expression patterns of the HG-ECs and STIC-LLs were concordant in these three cases. Here we demonstrate that co-occurring HG-ECs and STIC-LLs are genetically related in a subset of cases.

Keywords:  carcinosarcomas; genetic relatedness; sequencing; serous endometrial carcinoma; serous tubal intraepithelial carcinoma

DOI:  https://doi.org/10.1016/j.modpat.2025.100890
J Genet Genomics. 2025 Sep 12. pii: S1673-8527(25)00237-1. [Epub ahead of print]

The application and prospects of spatial omics technologies in clinical medical research and molecular diagnostics.

Xiaofeng Wu, Weize Xu, Da Lin, Leqiang Sun, Lit-Hsin Loo, Jinxia Dai, Gang Cao.

  While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information, spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments. These technologies are emerging as transformative tools in molecular diagnostics and medical research. By integrating histopathological morphology with spatial multi-omics profiling (genome, transcriptome, epigenome, and proteome), spatial omics technologies open an avenue for understanding disease progression, therapeutic resistance mechanisms, and precise diagnosis. It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states, which may greatly facilitate tumor molecular subtyping, prognostic assessment, and predicting the efficacy of radiotherapy and chemotherapy. Despite the substantial advancements in spatial omics, the translation of spatial omics into clinical applications remains challenging due to robustness, efficacy, clinical validation, and cost constraints. In this review, we will summarize the current progress and prospects of spatial omics technologies, particularly in medical research and diagnostic applications.

Keywords:  Clinical medical research; Molecular diagnostics; Multi-omics; Precise medicine; Spatial omics

DOI:  https://doi.org/10.1016/j.jgg.2025.09.003
Clin Cancer Res. 2025 Sep 17. OF1-OF5

AACR Cancer Progress Report 2025: Unifying Cancer Science and Medicine: A Continuum of Innovation for Impact.

Brett M Sansbury, Elizabeth Blackman, Kristin M Primm, Sayyed Kaleem Zaidi, Rajarshi Sengupta.

DOI: https://doi.org/10.1158/1078-0432.CCR-25-3366
Gigascience. 2025 Jan 06. pii: giaf104. [Epub ahead of print]14

CNSistent integration and feature extraction from somatic copy number profiles.

Adam Streck, Roland F Schwarz.

   BACKGROUND: Most cancers exhibit somatic copy number alterations (SCNAs)-gains and losses of variable regions of DNA. SCNAs play a key role in cancer adaptation through modulation of gene expression, deletion of tumor suppressor genes, or amplification of oncogenes. Systematic analysis of SCNAs is now a routine task in both the clinic and research and can help identify novel cancer genes, improve our understanding of cancer gene regulation, and enable us to accurately reconstruct cancer phylogenies. However, to conduct such analyses, SCNA profiles have to be integrated between samples, patients, and cohorts-often a nontrivial task, for which dedicated toolkits are lacking.
RESULTS: To fill this gap, we developed CNSistent, a Python package for imputation, filtering, consistent segmentation, feature extraction, and visualization of cancer copy number profiles from heterogeneous datasets. We demonstrate the utility of CNSistent by applying it to the following publicly available cohorts: The Cancer Genome Atlas, Pan-Cancer Analysis of Whole Genomes, and TRAcking Cancer Evolution through therapy (Rx). We compare the effect of sample preprocessing and different segmentation and aggregation strategies on cancer type and subtype classification tasks using various classification models. We also evaluate how well a classifier trained on one cohort generalizes to another. Lastly, we introduce 2 segment-based peak and outlier scores to investigate relationships between segments, between samples, and between cancer types. Using these scores, we investigate non-small cell lung cancer samples, highlighting that SOX2 amplification is the dominant copy number alteration in lung squamous cell carcinoma and the main distinction to lung adenocarcinoma.
CONCLUSIONS: CNSistent is a general-purpose toolkit for integrated processing of SCNA profiles across many patients and cohorts. It is available at https://bitbucket.org/schwarzlab/cnsistent. The Research Resource Identifier for CNSistent is SCR_027025.

Keywords:  SCNA; cancer; cancer classification; data processing; deep learning

DOI:  https://doi.org/10.1093/gigascience/giaf104
Ther Adv Med Oncol. 2025 ;17 17588359251367344

Clinical relevance of circulating tumor DNA in HER2-positive advanced gastric cancer: a collaborative study of a phase Ib trial of dual HER2 and PD-1 targeted therapy (Ni-High).

Hiroki Osumi, Takeru Wakatsuki, Akira Ooki, Keisho Chin, Hirokazu Shoji, Mariko Ogura, Izuma Nakayama, Noriko Yamamoto, Hidekazu Hirano, Hiroki Hara, Keiko Minashi, Eiji Shinozaki, Ken Kato, Naoki Ishizuka, Shigehisa Kitano, Kengo Takeuchi, Narikazu Boku, Kensei Yamaguchi, Daisuke Takahari.

   Background: The combination of anti-programmed cell death-1 antibody with human epidermal growth factor receptor 2 (HER2)-targeted therapy and chemotherapy is widely used in the United States and Europe for HER2-positive advanced gastric cancer (AGC). Molecular profiles that predict the efficacy of this dual-target therapy are unclear.
Objectives: To explore the clinical utility of circulating tumor DNA (ctDNA) as a predictive marker of the efficacy of standard chemotherapy plus HER2 and programmed death-ligand 1 dual-targeted therapy in patients with HER2-positive AGC.
Design: Collaborative study of the Ni-High phase Ib clinical trial.
Methods: A total of 21 patients with tissue-confirmed HER2-positive AGC who received chemotherapy with dual-targeted therapy (capecitabine/S-1, oxaliplatin, trastuzumab, and nivolumab) in a phase Ib clinical trial (UMIN000034222) were enrolled. The association of genomic profiles in plasma ctDNA with tissue HER2 amplification status and their correlation with clinical outcomes was investigated.
Results: Among the 21 patients studied, 20 (95.2%) showed somatic alterations in ctDNA. ERBB2 amplifications and single-nucleotide variants (SNVs)/indels were found in 12 (57.1%) and 3 (14.3%) patients, respectively. Significant associations between maximum mutant allele frequency (mMAF) and tumor size and between ctDNA and tissue ERBB2 copy numbers were found. Patients without ERBB2 SNV/indels showed longer median progression-free survival (PFS) and overall survival (OS) than those with these alterations. Patients with focal ERBB2 amplification in ctDNA showed better outcomes than those with aneuploidy (median PFS: 20.8 vs 8.4 months, hazard ratio (HR) = 0.08; median OS: NA vs 14.8 months, HR = 0.077). Lower mMAF at cycle 2 was associated with a better response to chemotherapy with dual-targeted therapy.
Conclusion: ERBB2 genetic status and mMAF changes in ctDNA may, respectively, predict and reflect the efficacy of chemotherapy with dual-targeted therapy in HER2-positive AGC.
Trial registration: UMIN000034222.

Keywords:  circulating tumor DNA; epidermal growth factor receptor; gastric cancer; liquid biopsy; programmed cell death-1

DOI:  https://doi.org/10.1177/17588359251367344
Epigenomics. 2025 Sep 19. 1-12

Epigenetic paradigm of DNA methylation for understanding the pathophysiology, diagnostics, and therapeutics in sarcomas.

Sujata Bhattacharya, Harshita Makkar, Jagdish Prasad Meena, Aditya Kumar Gupta, Rachna Seth.

  Sarcomas are heterogeneous malignant tumors originating from mesenchymal tissues, presenting substantial diagnostic and therapeutic challenges. The diverse genetic and epigenetic landscape provides significant heterogeneity and complexity to the disease, ultimately leading to poor outcomes for affected individuals, especially in metastatic diseases. As research in this field evolves, incorporating methylation profiling into routine clinical practice could significantly enhance the early diagnosis, risk stratification, and personalized treatment strategies for sarcoma patients. Moreover, the integration of advanced genetic techniques and ongoing upgradation in treatment strategies, predominantly those targeting methylation modifications, may lead to improved survival outcomes in sarcomas. We conducted a structured literature review using PubMed, Scopus, Embase, Google Scholar, and Web of Science, encompassing publications up to 30 November 2024. The search focused on DNA methylation in sarcoma pathogenesis, diagnostics, and therapeutics. Relevant articles were screened, and key findings were synthesized thematically. In this review, we provide a comprehensive insight into the role of DNA methylation in promoting sarcomas. We emphasize subtype-associated methylation patterns in sarcomas and their value as prognostic and diagnostic biomarkers, revealing their synergistic effects with the existing treatment regimens. Despite having preclinical outcomes, the translation of these therapies into clinical practice remains a challenge.

Keywords:  DNA methylation; Sarcomas; diagnostic and prognostic biomarkers; epigenetics; therapeutic targets

DOI:  https://doi.org/10.1080/17501911.2025.2563500
Cancer Metastasis Rev. 2025 Sep 19. 44(4): 71

Precision epigenetic therapies in oncology.

Arundhati Chaudhary, Kayleigh J A Orchard, Francesca Salani, Theodora Partsou, Mark Eccleston, Guido Bocci, Antoine Italiano, Francesco Crea.

  Phenotypic plasticity is a key mechanism of metastatic progression and cancer therapy resistance. This hallmark of human malignancies is enabled by highly conserved epigenetic mechanisms that control gene expression. Functional alterations in DNA methylation and histone post-translational modifications have been extensively described as drivers of metastatic dissemination and therapy resistance. Pharmacological inhibitors of epigenetic enzymes can revert these alterations, thereby stopping cancer progression and counteracting the emergence of resistant clones. Despite promising pre-clinical evidence, the clinical implementation of epigenetic therapies in solid cancers has led to disappointing results. Several factors can explain these challenges, including the lack of rational combinations. Notably, response to epigenetic treatments can be heterogeneous and short-lived. A liquid biopsy technology that allows the measure of specific epigenetic alterations enables patient selection and therapy monitoring, leading to the development of precision epigenetic therapies. In this review, we discuss the state of the art of this emerging treatment modality, and we identify key challenges that need to be overcome to reach the full potential of this new therapeutic concept.

Keywords:  Cancer; Epigenetics; HPTMs; Metastasis; Prognosis; Solid tumours

DOI:  https://doi.org/10.1007/s10555-025-10288-w
Cancer Res. 2025 Sep 15. 85(18): 3373-3375

The Approaching Darwinian Era in Oncology.

Robert A Gatenby.

Through most of medical history, treatments for metastatic cancers were ineffective, and rapid patient death was inevitable. Over the past five decades, a worldwide drug development effort has introduced a remarkable range of new cancer treatment strategies and agents so that virtually all metastatic cancers have one or more effective therapeutic options to prolong life. Yet most metastatic cancers remain fatal, and increasingly, the proximate cause of death is evolution. Local or systemic therapies applied to large, heterogeneous cancer populations elicit complex short- and long-term adaptive responses. Cells already possessing the molecular machinery of resistance obtain a stepwise fitness benefit relative to treatment-sensitive cells, allowing increased proliferation. Cells, otherwise sensitive to the treatment, may survive when in epigenetic states resistant to the treatment-induced death pathway or microenvironmental conditions that reduce drug delivery/efficacy, followed by a transition to "hard-wired" resistance allowing proliferation. These dynamics, enabled by the vast information content of the human genome, can produce diverse adaptive strategies in response to virtually all available treatments. Thus, oncology is rapidly approaching an era in which patient death is caused not by the absence of effective therapies but rather by eco-evolutionary dynamics that defeat initially successful treatments. Emerging evidence suggests that explicit integration of evolutionary principles to control or eliminate resistant populations can improve outcomes. In this issue of Cancer Research, Hockings and colleagues present an important evolutionary strategy to delay or prevent the evolution of resistance in ovarian cancer, with broad potential application. See related article by Hockings et al., p. 3503.

DOI: https://doi.org/10.1158/0008-5472.CAN-25-1878