bims-tumhet 2025-12-07 papers

Cell Commun Signal. 2025 Nov 29.

DECIPHER-PRAD: an advanced fragmentomics-based cell-free DNA assay for prostate cancer early detection.

Shun Zhang, Guanchen Zhu, Linfeng Xu, Qing Zhang, Xuefeng Qiu, Hua Bao, Min Wu, Xiaotian Zhao, Tao Ding, Fufeng Wang, Shuang Chang, Yang Shao, Junlong Zhuang, Hongqian Guo.

Early detection of prostate cancer is limited by the poor specificity of prostate-specific antigen (PSA)-based screening. Cell-free DNA (cfDNA) fragmentomics offers a promising non-invasive approach to improve screening accuracy and risk stratification. In this study, we enrolled 106 prostate cancer patients and 114 high-risk non-cancer individuals to develop a cfDNA fragmentomics-based screening assay using plasma whole-genome sequencing. Two fragmentomic features-copy number variation and fragment size profile-were incorporated into machine learning models for training and evaluated in an independent validation cohort of 83 cancer patients and 76 non-cancer individuals. The fragmentomics-based model achieved an area under the curve (AUC) of 0.933 in the training cohort (66.0% sensitivity at 95.6% specificity; 51.9% sensitivity at 98.2% specificity) with good calibration (slope: 0.957; intercept: 0.001), and maintained strong performance in the validation cohort (AUC: 0.887; 57.8% sensitivity at 92.1% specificity), showing rising predictive probabilities and sensitivity across advancing stages (Stage I-IV: 27.3% to 77.8%). Importantly, the model performed well in the PSA grey zone (4-10 ng/mL) with an AUC of 0.865 (69.0% sensitivity at 81.8% specificity). When integrated with total PSA levels, the combined algorithm achieved an AUC of 0.915 in the validation cohort and improved sensitivity at 98% specificity (Stage I-IV: 30.0% to 87.5%). These findings support the clinical potential of our cfDNA fragmentomic assay, particularly when combined with PSA, as a highly accurate and non-invasive tool for early prostate cancer detection.

Keywords: Cell-free DNA; Early detection; Fragmentomics; Prostate cancer

DOI: https://doi.org/10.1186/s12964-025-02522-3

JAMA. 2025 Dec 04.

What Is Ovarian Cancer?

Rebecca Voelker.

DOI: https://doi.org/10.1001/jama.2025.18446

Trends Cancer. 2025 Dec 02. pii: S2405-8033(25)00284-5. [Epub ahead of print]

Epigenetic drivers of chromosomal instability.

Ilio Vitale, Matteo Cereda, Lorenzo Galluzzi.

Chromosomal instability (CIN) fuels phenotypic cancer heterogeneity through heritable epigenetic defects, hence driving disease initiation, progression, and resistance to therapy. Two recent studies, by Bai et al. and Salinas-Luypaert et al., demonstrate that imbalanced histone or DNA methylation actively promotes CIN by disrupting centrosome homeostasis or centromere integrity, globally linking epigenetic dysregulation to mitotic failure and genome instability.

Keywords: cell cycle checkpoints; chromosome missegregation; epitranscriptomic; intratumoral heterogeneity; micronuclei; mitotic catastrophe

DOI: https://doi.org/10.1016/j.trecan.2025.11.010

Transl Oncol. 2025 Nov 29. pii: S1936-5233(25)00352-3. [Epub ahead of print]63 102621

Evaluation of the 1021-HRD assay compared to established HRD testing platforms in ovarian cancer.

PARP inhibitors have revolutionized ovarian cancer treatment, with benefits strongly linked to the presence of Homologous Recombination Deficiency (HRD). Although HRD testing was originally conducted on centralized platforms, there is growing demand for scalable, accessible, and robust solutions capable of supporting expanded clinical utilization. In the present study, a decentralized NGS-based assay was compared for its ability to effectively identify HRD positive patients when compared to the reference assay as well as other testing platforms. Eighty-two cases of ovarian cancer patients previously tested using the reference HRD assay (Myriad MyChoice® CDx assay) were evaluated by an NGS based HRD assay, the 1021-HRD assay (GenePlus), that provides genomic instability (GI) analysis along with tumor molecular profiling. HRD status, GI status (referred to as HRD-score), and even BRCA1/2 mutation detection were assessed for concordance with the reference test and the analytical accuracy of the assay was calculated. Additionally, GI alignment across alternative HRD testing platforms was examined. Finally, the association between key tumor alterations and the HRD status was evaluated. The 1021-HRD assay demonstrated an overall HRD classification agreement of approximately 92.68 % (κ = 0.841) in comparison to the reference method, as evidenced by the results, with 81.25 % specificity and 100 % sensitivity. These features generally suggest consistent performance, with only minor discrepancies observed. The BRCA1/2 alterations detected were 97.56 % in agreement with the approved assay. The Pearson r value of 0.878 indicates a strong correlation between the GI values obtained. The assay's capacity to detect non-BRCA1/2 HRD phenotypes was verified by the observation that 55.56 % of BRCA-wildtype malignancies were HRD-positive. Of particular interest, combining molecular profiling with GI analysis, the assay identified additional actionable alterations in 65 % of the cases, revealing clinically relevant biomarkers beyond the homologous recombination pathway. This wide-ranging approach may provide more diagnostic and therapeutic insight than HRD testing alone. In conclusion, the 1021-HRD assay is a dependable, decentralized alternative for HRD testing. It can provide a more comprehensive genomic characterization and exhibits remarkable analytical concordance with current standards. Its combined format and accessibility render it well-suited for real-world use in personalized ovarian cancer care. Its additional capacity to reveal more extensive tumor genomic alterations improves clinical decision-making and underscores the importance of integrating HRD scoring with comprehensive molecular profiling in personalized oncology.

Keywords: Genomic instability; Homologous recombination deficiency; Next generation sequencing; Ovarian cancer; PARP inhibitors

DOI: https://doi.org/10.1016/j.tranon.2025.102621

Nat Rev Cancer. 2025 Dec 02.

A guide to transcriptomic deconvolution in cancer.

Yaoyi Dai, Shuai Guo, Yidan Pan, Carla Castignani, Matthew D Montierth, Peter Van Loo, Wenyi Wang.

Cancer tissues are heterogeneous mixtures of tumour, stromal and immune cells, where each component comprises multiple distinct cell types and/or states. Mapping this heterogeneity and understanding the unique contributions of each cell type to the tumour transcriptome is crucial for advancing cancer biology, yet high-throughput expression profiles from tumour tissues only represent combined signals from all cellular sources. Computational deconvolution of these mixed signals has emerged as a powerful approach to dissect both cellular composition and cell-type-specific expression patterns. Here, we provide a comprehensive guide to transcriptomic deconvolution, specifically tailored for cancer researchers, presenting a systematic framework for selecting and applying deconvolution methods, considering the unique complexities of tumour tissues, data availability and method assumptions. We detail 43 deconvolution methods and outline how different approaches serve distinctive applications in cancer research: from understanding tumour-immune surveillance to identifying cancer subtypes, discovering prognostic biomarkers and characterizing spatial tumour architecture. By examining the capabilities and limitations of these methods, we highlight emerging trends and future directions, particularly in addressing tumour cell plasticity and dynamic cell states.

DOI: https://doi.org/10.1038/s41568-025-00886-9

Cancer Metastasis Rev. 2025 Dec 04. 44(4): 88

Circulating tumour cells and circulating tumour DNA in head and neck cancer: from molecular insights to clinical impact.

Sreedevi Damodaran, Chameera Ekanayake Weeramange, Lizbeth Kenny, Sarju Vasani, Brett G M Hughes, Omar Breik, Chamindie Punyadeera.

Head and neck squamous cell cancers (HNSCC) are a clinically and biologically diverse group of malignancies with limited tools for real-time monitoring and early detection of recurrence. Liquid biopsy strategies-particularly the analysis of circulating tumour cells (CTCs) and circulating tumour DNA (ctDNA)-have emerged as promising, minimally invasive biomarkers to capture real-time tumour dynamics. This review explores cellular and molecular processes that facilitate the release and survival of CTCs and ctDNA in the circulation in HNSCC. We also address the clinical relevance of CTCs and ctDNA in the prognosis, treatment response, and detection of minimal residual disease in HNSCC. Although integrating liquid biopsies into clinical care is limited by lack of standardisation, biological variability, and workflow challenges, CTCs and ctDNA have great potential to revolutionise HNSCC patient care with real-time and tailored interventions.

Keywords: Biomarkers; Circulating tumour DNA; Circulating tumour cells; Head and neck cancer; Liquid biopsy; Minimal residual disease; Precision oncology

DOI: https://doi.org/10.1007/s10555-025-10305-y

Nature. 2025 Dec;648(8092): 31

David Baltimore obituary: virologist whose enzyme discovery transformed understanding of cancer and HIV/AIDS.

Stephen Goff.

Keywords: History; Molecular biology; Virology

DOI: https://doi.org/10.1038/d41586-025-03862-3

Nat Biotechnol. 2025 Dec 03.

Standardized metrics for assessment and reproducibility of imaging-based spatial transcriptomics datasets.

Spatial transcriptomics lacks standardized metrics for evaluating imaging-based in situ hybridization technologies across sites. In this study, we generated the Spatial Touchstone (ST) dataset from six tissue types across several global sites with centralized sectioning, analyzed on both Xenium and CosMx platforms. These platforms were selected for their widespread use and distinct chemistries. We assessed reproducibility, sensitivity, dynamic ranges, signal-to-noise ratio, false discovery rates, cell type annotation and congruence with single-cell profiling. This study offers ST standardized operating procedures (STSOPs) and an open-source software, SpatialQM, enabling evaluation of samples across all technical metrics and direct imputation of cell annotations. The generated imaging-based spatial transcriptomics data repository comprises 254 spatial profiles, incorporating both public and newly generated ST datasets in a web-based application, which enables analysis and comparison of user data against an extensive collection of imaging-based datasets. Finally, we establish best practices and metrics to evaluate and integrate imaging-based multi-omics data from single cells into spatial transcriptomics to spatial proteomics.

DOI: https://doi.org/10.1038/s41587-025-02811-9