bims-enbcad Biomed News
on Engineering biology for causal discovery
Issue of 2025–11–23
eleven papers selected by
Xiao Qin, University of Oxford
  1. Multi-Omics Meets Premalignancy: Paving the Way for Early Prevention of Cancer.
  2. Colonoscopy Quality and Strategies for Improvement.
  3. Collagen-Based Tumor Spheroid Model for Investigating Tumor-Macrophage Interactions through Extracellular Matrix Remodeling.
  4. Semantic design of functional de novo genes from a genomic language model.
  5. A set cover algorithm identifies minimal circulating tumour DNA sequencing targets for colorectal cancer detection.
  6. A Review of Early-Onset Gastrointestinal Cancers-Reply.
  7. scGPD: single-cell informed gene panel design for targeted spatial transcriptomics.
  8. Inferring differential dynamics from multi-lineage, multi-omic, and multi-sample single-cell data with MultiVeloVAE.
  9. The inflammation-aging axis: Shared and distinct mechanisms in physiological gut aging and IBD-associated accelerated gut aging.
  10. Stem cell-based approach to identify regulatory TFs during mammalian cell differentiation.
  11. The gut microbiome and gastrointestinal cancers: mechanisms, biomarkers and therapeutic opportunities.
  1. Research (Wash D C). 2025 ;8 0930
    Multi-Omics Meets Premalignancy: Paving the Way for Early Prevention of Cancer.
    Feiran Zhang, Ziyi Zhou, Peng Zhang, Shao Li.
      Comprehensive understanding of premalignant lesions (PMLs) represents a pivotal opportunity for cancer early detection and interception. Recently, advances in multi-omics technologies and artificial intelligence (AI) methods have provided unprecedented insights into PML-induced tumorigenesis. In this paper, we firstly catalog clinically recognized PMLs across 15 cancer types, emphasizing their epidemiological profiles and malignant transformation potentials. Then, we summarize recent intriguing discoveries and remaining challenges from bulk, single-cell, and spatial omics studies, highlighting how these omics technologies reveal the dynamic molecular, cellular, and spatial evolution from precancerous states to invasive malignancies. We further discuss network-based computational strategies for multi-omics integration and tumorigenesis trajectory inference, with applications of recent deep learning-based AI approaches. Finally, we highlight translational implications for PMLs, including developing high-precision early-diagnosis biomarkers and targeted pharmacological preventive strategies. Collectively, this paper underscores how the convergence of high-resolution multi-omics with sophisticated AI is poised to redefine PML research, enabling pan-cancer exceedingly-early risk stratification and pharmacological prevention.
    DOI:  https://doi.org/10.34133/research.0930
  2. Gut Liver. 2025 Nov 17.
    Colonoscopy Quality and Strategies for Improvement.
    Hyun Jung Lee, Uri Ladabaum.
      Colonoscopy plays a pivotal role in colorectal cancer (CRC) screening and reduces CRC incidence and mortality. Its effectiveness depends on colonoscopist performance, which can vary. Missed lesions during colonoscopy can lead to post-colonoscopy CRC (PCCRC), making high-quality colonoscopy essential for maximizing the preventive benefit of CRC screening. This review highlights the significance of colonoscopy quality indicators and practices for improvement. Bowel preparation, cecal intubation, and withdrawal time are key process indicators for procedure quality and are closely associated with the adenoma detection rate (ADR) and PCCRC risk. Given the role of colonoscopy in preventing CRC through the removal of precancerous lesions, the ADR serves as the core quality metric and the most reliable predictor of PCCRC. Serrated polyps have gained attention in colonoscopy quality research, as 15% to 30% of CRCs arise from serrated lesions, with an increased detection rate inversely associated with PCCRC risk. This emphasizes the critical need for continuous efforts by colonoscopists to enhance performance quality. Systemic interventions, audits and feedback during endoscopist education, basic and enhanced withdrawal and inspection techniques, and technologies such as mucosal exposure devices and computer-aided detection have demonstrated efficacy in increasing the ADR. While artificial intelligence has shown promise in increasing the ADR, inconsistent outcomes in real-world studies underscore the continued importance of the fundamental aspects of high-quality colonoscopy techniques, including complete mucosal exposure. Understanding quality indicators and ensuring high-performance quality in daily practice will ultimately lead to better CRC prevention outcomes.
    Keywords:  Colonoscopy; Colorectal neoplasms; Quality; Screening
    DOI:  https://doi.org/10.5009/gnl250301
  3. bioRxiv. 2025 Oct 03. pii: 2025.10.01.679587. [Epub ahead of print]
    Collagen-Based Tumor Spheroid Model for Investigating Tumor-Macrophage Interactions through Extracellular Matrix Remodeling.
    Luna Zhang, Sanab Abdi, Hannah M Szafraniec, Paolo P Provenzano, Kathryn L Schwertfeger, David K Wood.
      Macrophages in the tumor microenvironment (TME) can constitute up to 50% of tumor mass and play a critical role in cancer cell proliferation, invasion, and metastasis. While their contribution to extracellular matrix (ECM) degradation through matrix metalloproteinases (MMPs) has been explored, the role of other macrophage-derived factors in ECM remodeling and their impacts beyond degradation remain poorly understood. Here, we describe the development of a 3D collagen-based tumor spheroid model to investigate the impact of peripheral blood mononuclear cell (PBMC)-derived macrophages on cancer cell-ECM and cancer cell-macrophage interactions within the TME. We observed that cancer cells stimulated PBMC-derived macrophages into an M2-like phenotype and that tumor spheroid conditioned macrophages (TSCMs) shifted cancer cell populations toward phenotypes with greater invasion distances and reduced circularity, indicative of increased malignancy. Such observations can be explained by macrophage-mediated ECM remodeling. Specifically, we demonstrate that TSCMs secreted a variety of soluble factors that are known to contribute to ECM remodeling, including ECM degradation and fiber realignment. These processes collectively create a tumor-favoring environment by loosening the collagen matrix and aligning fibers that serve as invasion tracks for migrating tumor cells that facilitate cancer cell migration and invasion. This model provides a robust platform to study the interactions between cellular and non-cellular components in the TME and to identify the molecular mechanisms underlying cancer progression. These insights may aid in the development of novel therapeutic strategies targeting macrophage-mediated processes in cancer.
    Keywords:  ECM remodeling; Macrophages; Tumor microenvironment; Tumor spheroid model
    DOI:  https://doi.org/10.1101/2025.10.01.679587
  4. Nature. 2025 Nov 19.
    Semantic design of functional de novo genes from a genomic language model.
    Aditi T Merchant, Samuel H King, Eric Nguyen, Brian L Hie.
      Generative genomic models can design increasingly complex biological systems1. However, controlling these models to generate novel sequences with desired functions remains challenging. Here, we show that Evo, a genomic language model, can leverage genomic context to perform function-guided design that accesses novel regions of sequence space. By learning semantic relationships across prokaryotic genes2, Evo enables a genomic 'autocomplete' in which a DNA prompt encoding genomic context for a function of interest guides the generation of novel sequences enriched for related functions, which we refer to as 'semantic design'. We validate this approach by experimentally testing the activity of generated anti-CRISPR proteins and type II and III toxin-antitoxin systems, including de novo genes with no significant sequence similarity to natural proteins. In-context design of proteins and non-coding RNAs with Evo achieves robust activity and high experimental success rates even in the absence of structural priors, known evolutionary conservation or task-specific fine-tuning. We then use Evo to complete millions of prompts to produce SynGenome, a database containing over 120 billion base pairs of artificial intelligence-generated genomic sequences that enables semantic design across many functions. More broadly, these results demonstrate that generative genomics with biological language models can extend beyond natural sequences.
    DOI:  https://doi.org/10.1038/s41586-025-09749-7
  5. Sci Rep. 2025 Nov 20. 15(1): 40949
    A set cover algorithm identifies minimal circulating tumour DNA sequencing targets for colorectal cancer detection.
    Kit Moloney-Geany, Michael A Black, Robert C Day, Parry Guilford, Michael J Dunnet.
      Advances in high-throughput sequencing and decreasing costs have made cell-free DNA sequencing a promising approach for cancer detection. Sequencing assays require high read depth to detect low-frequency somatic mutations, so cell-free DNA panels must support deep sequencing while still assaying broadly enough to detect as many malignancies as possible. We developed OPTIC (Oncogene Panel Tester for Identifying Cancers), a pipeline employing a set cover algorithm, to identify the minimal set of genomic targets capturing the maximal proportion of tumours. Using three cohorts totalling 2,940 colorectal cancer samples, OPTIC was utilized to design a targeted sequencing panel spanning just 10,975 bases across APC, TP53, KRAS, BRAF, NRAS, PIK3CA, CTNNB1, RNF43, and ACVR2A. Collectively, these loci contain pathogenic mutations in 96.3% of cases. Our pipeline enables compact panel design without compromising sample coverage. This enables higher throughput, greater sequencing depth, and lower costs per-sample in early colorectal cancer detection from cell-free DNA.
    Keywords:  Cell-free DNA; Colorectal cancer; Coverage; Gene panel; Sequencing; Somatic mutation detection
    DOI:  https://doi.org/10.1038/s41598-025-24719-9
  6. JAMA. 2025 Nov 19.
    A Review of Early-Onset Gastrointestinal Cancers-Reply.
    Thejus Jayakrishnan, Kimmie Ng.
      
    DOI:  https://doi.org/10.1001/jama.2025.18243
  7. bioRxiv. 2025 Oct 02. pii: 2025.10.02.680117. [Epub ahead of print]
    scGPD: single-cell informed gene panel design for targeted spatial transcriptomics.
    Yunshan Guo, Jia Zhao, Rui B Chang, Hongyu Zhao.
      In targeted spatial transcriptomics technologies, a key challenge is to select an informative gene panel that captures the complexity of cellular and spatial heterogeneity within tissues. Many existing methods use prior knowledge or heuristic selection rules, such as selecting highly variable genes, which overlook gene-gene correlations and may consequently result in suboptimal coverage. To address the limitations of the existing methods, we introduce scGPD, a deep learning-based framework for gene panel design that leverages single-cell RNA-seq data to identify compact, nonredundant sets of genes for spatial profiling. scGPD uses a gene-gene correlation-aware gating mechanism to extract informative features from data, encouraging diversity among selected genes and eliminating redundancy. Across diverse single-cell datasets, scGPD outperforms existing gene panel design methods in recovering transcriptome-wide expression using a limited number of genes. When applied to spatial transcriptomics data, it achieves superior cell type classification accuracy, demonstrating strong generalization across modalities. The gene panels selected by scGPD further exhibit well-defined spatial expression patterns, highlighting their robustness and relevance for spatial analysis. The scGPD framework is flexible and can be adapted to multiple use cases, enabling the prioritization of genes relevant to specific diseases or phenotypes. Together, these results demonstrate that scGPD provides a robust and adaptable solution to design efficient gene panels for spatial transcriptomics, with broad applicability to tissue mapping and disease characterization.
    DOI:  https://doi.org/10.1101/2025.10.02.680117
  8. Nat Commun. 2025 Nov 20.
    Inferring differential dynamics from multi-lineage, multi-omic, and multi-sample single-cell data with MultiVeloVAE.
    Chen Li, Yichen Gu, Maria C Virgilio, Kun H Lee, Kathleen L Collins, Joshua D Welch.
      Understanding how cells differentiate to their final specialized fates is a fundamental problem in biomedical science. Single-cell multi-omic profiling provides an opportunity to identify dynamic molecular changes, but new computational approaches are needed to realize this potential. In particular, previous methods for RNA velocity inference lack support for multi-lineage, multi-sample, and multi-omic single-cell data and cannot be used to identify differential dynamics. To overcome these challenges, we introduce MultiVeloVAE, a probabilistic framework for multi-sample RNA velocity inference that integrates single-cell RNA and multi-omic data. MultiVeloVAE models gene expression and chromatin accessibility on a shared time scale, performs multi-sample inference from datasets with partially overlapping modalities, accounts for lineage bifurcations, and enables statistical testing of velocity parameters among cell types and over time. Using newly generated 10X Multiome datasets from human embryoid bodies and differentiating macrophage cells, we demonstrate that MultiVeloVAE provides novel insights into chromatin accessibility and gene expression dynamics during development.
    DOI:  https://doi.org/10.1038/s41467-025-66287-6
  9. Biosci Trends. 2025 Nov 20.
    The inflammation-aging axis: Shared and distinct mechanisms in physiological gut aging and IBD-associated accelerated gut aging.
    Lichao Yang, Zhixian Jiang, Qi Sun, Kenji Karako, Lianwen Yuan, Peipei Song.
      Inflammatory bowel disease (IBD) and physiological gut aging present with overlapping clinical features, including impaired barrier functioning, decreased nutrient absorption, and intestinal frailty. Emerging evidence indicates that even young IBD patients can exhibit gut phenotypes akin to those seen with aging. However, the two processes differ substantially in their underlying mechanisms. Gut aging is characterized by low-grade, chronic inflammation and gradual cellular senescence, whereas IBD involves persistent immune activation, cyclical tissue damage, and accelerated degenerative changes. This review systematically contrasts physiological gut aging and IBD-associated accelerated gut aging across several dimensions: cellular senescence and programmed cell death, immune cell remodeling, alterations in gut microbiota, changes in mesenteric adipose tissue, and the evolving role of the appendix. By integrating current advances in basic and translational research, this article highlights both the shared and distinct pathways driving gut dysfunction in aging and IBD, and underscores the importance of early recognition and targeted intervention for premature gut aging in clinical practice.
    Keywords:  cellular senescence; gut aging; immune dysregulation; inflammatory bowel disease; intestinal barrier
    DOI:  https://doi.org/10.5582/bst.2025.01279
  10. Stem Cell Reports. 2025 Nov 20. pii: S2213-6711(25)00320-0. [Epub ahead of print] 102716
    Stem cell-based approach to identify regulatory TFs during mammalian cell differentiation.
    Yingzhen Pei, Siyi Li, Görkem Garipler, Kenji Kamimoto, Esteban O Mazzoni.
      Cell differentiation is regulated by transcription factors (TFs), but specific TFs needed for mammalian differentiation pathways are not fully understood. For example, during spinal motor neuron (MN) differentiation, 1,370 TFs are transcribed, yet only 55 have reported functional relevance. We developed a method combining pluripotent stem cell differentiation, single-cell transcriptomics, and a CRISPR-based TF loss-of-function screen and applied it to MN differentiation. The CRISPR screen identified 245 genes important for mouse MN differentiation, including 116 TFs. This screen uncovered important genes not showing differential transcription and identified a regulatory hub at the MN progenitor (pMN) stage. A secondary human screen of 69 selected candidates revealed a conservation between mouse pMN and human pMN and ventral pMN (vpMN) regulations. The validation of three hits required for efficient human MN differentiation supported the effectiveness of our approach. Collectively, our strategy offers a framework for identifying important TFs in various differentiation pathways.
    Keywords:  CRISPR screen; development; differentiation; motor neuron; scRNA-seq; spinal cord; transcription factors; zinc finger
    DOI:  https://doi.org/10.1016/j.stemcr.2025.102716
  11. Front Physiol. 2025 ;16 1676796
    The gut microbiome and gastrointestinal cancers: mechanisms, biomarkers and therapeutic opportunities.
    Sarbjeet Kaur Makkar, Kumar S Bishnupuri.
      Gastrointestinal (GI) cancers remain a leading global cause of cancer-related mortality, significantly impacting public health and healthcare systems worldwide. Emerging evidence underscores the critical role of gut microbiome dysbiosis-characterized by disrupted microbial diversity and function-in GI carcinogenesis. Utilizing recent advancements in multi-omics technologies and sophisticated computational biology, researchers have elucidated distinct microbial signatures associated with colorectal, gastric, hepatobiliary, pancreatic, and esophageal cancers. This review comprehensively analyzes the primary mechanisms through which gut microbes contribute to cancer development and progression, encompassing genotoxicity, chronic inflammation, metabolic dysregulation, epigenetic modifications, and immunomodulation. Moreover, we explore innovative microbiome-derived biomarkers for potential clinical applications, including early diagnosis, prognosis assessment, and therapeutic response prediction. The intricate interactions between microbiota and standard cancer therapies-chemotherapy, immunotherapy, and radiation therapy-are discussed, highlighting microbiome influences on therapeutic efficacy and adverse effect profiles. We also critically assess the impact of modifiable factors such as diet, medications, lifestyle, and environmental exposures on microbiome composition and cancer risk. The review evaluates emerging therapeutic interventions, including dietary modifications, probiotics, prebiotics, fecal microbiota transplantation (FMT), and engineered live biotherapeutics. Despite notable advancements, significant hurdles remain, including clarifying causality, methodological standardization, and equitable global research representation. Addressing these challenges, we propose a strategic research agenda aimed at harnessing microbiome insights to advance precision oncology and improve GI cancer outcomes globally.
    Keywords:  cancerimmunotherapy; gastrointestinal cancers; gut microbiome; microbial dysbiosis; microbiome-derived biomarkers; microbiota-targeted therapy
    DOI:  https://doi.org/10.3389/fphys.2025.1676796
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