bims-enbcad 2025-12-21 papers

bims-enbcad

Biomed News

on Engineering biology for causal discovery

Issue of 2025–12–21
seventeen papers selected by
Xiao Qin, University of Oxford

Advances in colorectal cancer screening: technological innovations, guideline discrepancies, and individualized strategies.
Intratumoral microbiome: a crucial regulating factor in development and progression of colorectal cancer.
Beyond colonoscopy, faecal DNA mutation screening provides a potential and viable path to early colorectal cancer detection.
SpaceBar enables single-cell-resolution clone tracing with imaging-based spatial transcriptomics.
Improving Colorectal Cancer Detection with AI-Assisted Colonoscopy: A Systematic Review and Meta-Analysis of 38 RCTs with GRADE Assessment.
Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA.
Dissecting how morphogens shape cell fates in human neural organoids.
Gene-specific selective sweeps are pervasive across human gut microbiomes.
Query-driven generative AI synthesizes multi-modal spatial omics from histology.
Integrating synthetic biology to understand and engineer the heart, lung, blood, and sleep systems.
Early mutational events and clonal dynamics in normal crypts: implications for colorectal tumorigenesis.
Metabolic Adaptation in Colorectal Cancer Microenvironment: Focus on Cancer-Associated Fibroblasts (CAFs) and Tumor-Associated Macrophages (TAMs).
Regulatory element modules as universal features for single-cell chromatin analysis.
LARIS enables accurate and efficient ligand and receptor interaction analysis in spatial transcriptomics.
FastCCC: a permutation-free framework for scalable, robust, and reference-based cell-cell communication analysis in single cell transcriptomics studies.
Nucleophosmin supports WNT-driven hyperproliferation and tumor initiation.
Bacterial population dynamics during colonization of solid tumors.

Front Oncol. 2025 ;15 1723546

Advances in colorectal cancer screening: technological innovations, guideline discrepancies, and individualized strategies.

Li Tang, Xiaoyong Zhao, Guohong Wang, Jiehao Huang, Mu Zhang, Wei Xu.

  Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide. Numerous clinical and epidemiological studies have demonstrated that early screening can significantly reduce both the incidence and mortality of CRC. This review systematically summarizes recent advances in CRC screening technologies. It first reviews the current applications of traditional screening tools such as colonoscopy and fecal occult blood tests, then focuses on emerging molecular detection techniques based on DNA, RNA, proteins, and metabolites, as well as representative multi-omics integration approaches. Furthermore, it discusses the innovative use of artificial intelligence (AI) and image recognition technologies in CRC screening. At the guideline level, we compare recent updates and implementation differences among major national screening guidelines, including those of the U.S. Preventive Services Task Force (USPSTF), and analyze key challenges in current screening practices. Finally, we propose directions for future development. By integrating existing evidence, this review aims to provide clinical reference for transforming CRC screening from population-based to precision-based individualized prevention, promoting its wide, efficient, and sustainable implementation.

Keywords:  Early detection; Molecular diagnostics; Screening technology; artificial intelligence; colorectal cancer; guideline discrepancies

DOI:  https://doi.org/10.3389/fonc.2025.1723546
Mol Biomed. 2025 Dec 15. 6(1): 138

Intratumoral microbiome: a crucial regulating factor in development and progression of colorectal cancer.

Yating Fan, Xiangshuai Gu, Hua Yang, Ye Chen, Chao Fang, Hongxin Deng, Lei Dai.

  Colorectal cancer (CRC) is one of the most malignant cancers, and studies have indicated that microbes within tumors play a crucial role in CRC. Advanced methodologies, including single-cell and spatial technologies, high-resolution sequencing, and multi-omic integration, are now unraveling the complex composition and function of the intratumoral microbiome. Mechanistically, these microbial communities contribute to CRC initiation by serving as direct mutagens that induce genomic instability, perpetuating a state of chronic inflammation, and activating specific carcinogenic pathways. Furthermore, they actively promote tumor progression and metastatic dissemination through multiple means, including the modulation of key oncogenic signaling pathways, extensive remodeling of the tumor immune microenvironment, and facilitation of a pro-metastatic niche. Given these profound and multifaceted influences, the intratumoral microbiome shows significant promise as a source of diagnostic and prognostic biomarkers, offering considerable potential for non-invasive monitoring and improved risk stratification in clinical practice. Therapeutically, intervention strategies are rapidly evolving, encompassing approaches such as microbiome modulation to enhance conventional therapies, precise clearance of pathogenic bacteria, utilization of intrinsically antitumor microbes, and the engineering of synthetic bacteria as targeted living therapeutics. This review comprehensively outlines the current research methods, elaborates on the mechanistic insights, and discusses the therapeutic targeting of the intratumoral microbiome, aiming to provide a foundational framework for developing new and effective strategies in CRC precision medicine.

Keywords:  Biomarkers; Colorectal cancer; Engineered bacteria; Immune modulation; Intratumoral microbiome; Tumor microenvironment

DOI:  https://doi.org/10.1186/s43556-025-00376-2
Sci Rep. 2025 Dec 13.

Beyond colonoscopy, faecal DNA mutation screening provides a potential and viable path to early colorectal cancer detection.

Alonzo Alfaro-Núñez, Stina Christensen, Jette Ellehauge, Jens Ole Eriksen, Gitte Andersen, Esther A Jensen.

  Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide, with early detection critical for improving clinical outcomes. In Denmark's CRC screening program, nearly 60% of patients undergoing colonoscopy do not have polyps requiring treatment, highlighting the need for more sensitive and less invasive screening methods to improve early detection and reduce unnecessary procedures. In this study, we assessed the potential of two faecal DNA-based methods for detecting CRC-related mutations. Extracted DNA was analysed using next-generation sequencing (NGS) and digital PCR (dPCR). NGS targeted a gene panel covering the most frequently mutated sites in CRC, while dPCR focused on six specific CRC-associated mutations. A common limitation across both methods was the low abundance of human DNA in faecal samples, which reduced the reliability of variant detection. Nevertheless, both NGS and dPCR showed promise, particularly when DNA input was sufficient. Significant associations were observed between mutation counts and clinical diagnosis, with key CRC mutations reliably detected. The findings suggest that, with further implementation, these methods could serve as a less invasive and more cost-effective alternative to colonoscopy, especially for high-risk individuals. However, the sensitivity of both methods was limited in samples with low DNA yield, likely due to inhibitory effects during sample preservation or extraction. While faecal samples may be better suited for gut microbiome profiling, our findings underscore the potential of human DNA-based faecal screening in CRC and highlight the need for optimized extraction protocols to improve diagnostic accuracy, minimize unnecessary procedures, and provide personalized care for high-risk populations.

Keywords:  Colonoscopy alternative; Colorectal cancer (CRC); Early detection; Gastrointestinal bleeding; Gut microbiome; Molecular markers; Non-invasive screening

DOI:  https://doi.org/10.1038/s41598-025-30802-y
Nat Methods. 2025 Dec 18.

SpaceBar enables single-cell-resolution clone tracing with imaging-based spatial transcriptomics.

Grant Kinsler, Caitlin Fagan, Haiyin Li, Jessica Kaster, Maggie Dunne, Robert J Vander Velde, Ryan H Boe, Sydney Shaffer, Meenhard Herlyn, Arjun Raj, Yael Heyman.

Imaging-based spatial transcriptomics methods allow for the measurement of spatial determinants of cellular phenotypes but are incompatible with random barcode-based clone-tracing methods, preventing the simultaneous detection of clonal and spatial drivers. Here we report SpaceBar, which enables simultaneous clone tracing and spatial gene expression profiling with standard imaging-based spatial transcriptomics pipelines. Our approach uses a library of 96 synthetic barcode sequences that combinatorially labels each cell. Thus, SpaceBar can distinguish between clonal dynamics and environmentally driven transcriptional regulation in complex tissue contexts.

DOI: https://doi.org/10.1038/s41592-025-02968-w
J Gastrointest Cancer. 2025 Dec 19. 56(1): 240

Improving Colorectal Cancer Detection with AI-Assisted Colonoscopy: A Systematic Review and Meta-Analysis of 38 RCTs with GRADE Assessment.

Israa Ahmed Qutob, Asmaa Soliman, Rayhana Trabelsi, Mohamed Karam Allah Elkholy, Ali Salah Elgahamy, Maha Abuismail, Mohamed Nabil Hamouda, Islam Elhaddad, Ahmed Abdelaziz Eldaly, Abdullrahman Elgarawany, Sohaila O Boshirtela, Sumaya Mohammed, Sally Seliem.

   BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide. Early detection of precancerous lesions such as adenomas and polyps is vital for prevention, yet standard colonoscopy may miss up to 26% of adenomas. Artificial intelligence (AI)-assisted colonoscopy has emerged as a promising tool to enhance lesion detection. This meta-analysis provides an updated synthesis of randomized controlled trials (RCTs) evaluating the diagnostic performance of AI-assisted versus standard colonoscopy.
METHODS: Following PRISMA guidelines, a comprehensive search of PubMed, Cochrane, Web of Science, and Scopus identified 38 RCTs including 29,745 participants. Pooled risk ratios (RRs) or mean differences (MDs) with 95% confidence intervals (CIs) were calculated using random-effects models. Subgroup analyses by geographical region and AI manufacturer were performed to explore heterogeneity. Certainty of evidence was rated using the GRADE approach, and publication bias was assessed through funnel plots and Egger's test.
RESULTS: AI-assisted colonoscopy significantly improved adenoma detection rate (ADR: RR = 1.19, 95% CI 1.14-1.25) and polyp detection rate (PDR: RR = 1.19, 95% CI 1.13-1.25), while reducing adenoma miss rate (AMR: RR = 0.52, 95% CI 0.38-0.72) and polyp miss rate (PMR: RR = 0.53, 95% CI 0.33-0.88). The mean number of adenomas per colonoscopy increased (MD = 0.20, 95% CI 0.14-0.25). AI modestly prolonged withdrawal time (MD = 0.46 min, 95% CI 0.26-0.66). No significant difference was observed for carcinoma detection (RR = 1.12) or advanced adenoma miss rate (RR = 0.67). Sessile serrated lesion detection showed a nonsignificant trend toward improvement (RR = 1.13), becoming significant after outlier exclusion (RR = 1.23). Subgroup analyses revealed higher ADR improvement in East Asian studies and with specific AI systems (e.g., Wision AI). Egger's test suggested minor small-study effects for ADR and withdrawal time.
CONCLUSIONS: AI-assisted colonoscopy substantially enhances adenoma and polyp detection while reducing miss rates. However, its benefit for carcinoma and sessile serrated lesion detection remains uncertain. Further standardized RCTs with long-term follow-up are warranted to confirm its role in colorectal cancer screening.

Keywords:  Adenoma detection rate (ADR); Artificial intelligence (AI); Colonoscopy; Colorectal cancer (CRC) prevention; Polyp detection

DOI:  https://doi.org/10.1007/s12029-025-01353-2
Nat Commun. 2025 Dec 18.

Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA.

Hanaé Carrié, Ngak Leng Sim, Pui Mun Wong, Anna Gan, Yi Ting Lau, Polly Poon, Saranya Thangaraju, Iain Tan, Yoon Sim Yap, Kiran Krishnamachari, Limsoon Wong, Anders Skanderup.

Detection of somatic mutations in cell-free DNA (cfDNA) is challenging due to low variant allele frequencies and extensive DNA degradation. Here we develop a benchmarking strategy using longitudinal patient-matched cfDNA samples from individuals with colorectal and breast cancer. Samples with high and ultra-low levels of tumor-derived DNA are combined into controlled dilution series that preserve the properties of authentic cell-free DNA, including each patient's germline and blood-cell mutation backgrounds. Using deep whole-genome (150x) and exome (2,000x) sequencing, we define a reference set of ~37,000 single nucleotide variants and ~58,000 indels to benchmark nine somatic variant callers across varying ctDNA levels and sequencing depths. We also explore machine learning-based tuning of individual callers and identify features that improve accuracy in cfDNA. This benchmarking resource clarifies the detection limits of current approaches and provides practical guidance for selecting somatic variant calling methods in liquid biopsy applications.

DOI: https://doi.org/10.1038/s41467-025-67842-x
Nat Methods. 2025 Dec 16.

Dissecting how morphogens shape cell fates in human neural organoids.

DOI: https://doi.org/10.1038/s41592-025-02959-x
Nature. 2025 Dec 17.

Gene-specific selective sweeps are pervasive across human gut microbiomes.

Richard Wolff, Nandita R Garud.

The human gut microbiome is composed of a highly diverse consortia of species that are continually evolving within and across hosts1,2. The ability to identify adaptations common to many human gut microbiomes would show not only shared selection pressures across hosts but also key drivers of functional differentiation of the microbiome that may affect community structure and host traits. However, the extent to which adaptations have spread across human gut microbiomes is relatively unknown. Here we develop a new selection scan statistic named the integrated linkage disequilibrium score (iLDS) that can detect sweeps of adaptive alleles spreading across host microbiomes by migration and horizontal gene transfer. Specifically, iLDS leverages signals of hitchhiking of deleterious variants with a beneficial variant. Application of the statistic to around 30 of the most prevalent commensal gut species from 24 human populations around the world showed more than 300 selective sweeps across species. We find an enrichment for selective sweeps at loci involved in carbohydrate metabolism, indicative of adaptation to host diet, and we find that the targets of selection differ significantly between industrialized populations and non-industrialized populations. One of these sweeps is at a locus known to be involved in the metabolism of maltodextrin-a synthetic starch that has recently become a widespread component of industrialized diets. In summary, our results indicate that recombination between strains fuels pervasive adaptive evolution among human gut commensal bacteria, and strongly implicate host diet and lifestyle as critical selection pressures.

DOI: https://doi.org/10.1038/s41586-025-09798-y
bioRxiv. 2025 Dec 13. pii: 2025.12.11.693669. [Epub ahead of print]

Query-driven generative AI synthesizes multi-modal spatial omics from histology.

Minxing Pang, Tarun Kanti Roy, Xiaodong Wu, Kai Tan.

Spatial omics technologies offer unprecedented insights into the cellular organization of tissues; however, they are not yet scalable for routine clinical use. In contrast, images of histological staining remain the foundation of pathological diagnosis despite lacking molecular information. Bridging this gap requires computational methods that can accurately infer spatial molecular data from histology alone. Here, we introduce TissueCraftAI, a generative artificial intelligence framework that predicts multi-modal spatial omics maps directly from standard histology images using natural language prompts. To train and validate our model, we created PRISM-12M, a large-scale dataset comprising over twelve million spatially registered histology and spatial omics image patches across fourteen tissue types from humans and mice. TissueCraftAI significantly outperforms existing methods in generating realistic histology images and predicting spatial proteomics and transcriptomics data with high fidelity. We demonstrated its utility in various downstream applications, including improving cell type annotation and enhancing the accuracy of patient survival predictions across multiple cancer types. By enabling flexible, query-driven in silico spatial molecular analysis using routine histology images, TissueCraftAI opens up new research avenues in computational pathology.

DOI: https://doi.org/10.64898/2025.12.11.693669
Cell Syst. 2025 Dec 17. pii: S2405-4712(25)00279-0. [Epub ahead of print]16(12): 101446

Integrating synthetic biology to understand and engineer the heart, lung, blood, and sleep systems.

Elliot L Chaikof, Jichao Chen, Martha U Gillette, Laurie A Boyer, Tara L Deans, Pulin Li, Isaac B Hilton, Kyle Daniels, Yogesh Goyal, Ying Mei, Changyang Linghu, Theresa B Loveless, David M Truong, Michael R Blatchley, Mingxia Gu, Caleb J Bashor, Jason H Yang, Ritu Raman, Akhilesh B Reddy, Krishanu Saha, Jennifer Davis, Kalpna Gupta, Xiaojing J Gao, Kate E Galloway.

Synthetic biology offers control over cellular and tissue functions. As it moves beyond microbes into humans, synthetic biology enables precise control over gene expression, cell fate, and tissue organization across heart, lung, blood, and sleep systems. By integrating genome engineering, dynamic gene circuits, and high-dimensional biosensors, these advances support scalable, quantitative models of multicellular biology, expanding the need for systems-level models and integration. We highlight emerging systems such as tunable transcriptional regulators, synthetic organizers, and feedback circuits that bridge molecular control with functional outcomes. Furthermore, by combining omics data with artificial intelligence (AI)-guided circuit design, synthetic biology enables high-resolution cellular and tissue-scale models of development, cellular interactions, drug development, gene therapy, and therapeutic response. Key challenges remain-including delivery, transgene stability, and robust spatiotemporal control in physiologically relevant models. This perspective synthesizes field-spanning progress and defines shared priorities for engineering cells and tissues that function reliably across dynamic, multi-organ environments.

DOI: https://doi.org/10.1016/j.cels.2025.101446
Hum Genomics. 2025 Dec 15. 19(1): 146

Early mutational events and clonal dynamics in normal crypts: implications for colorectal tumorigenesis.

Charlie Marvalim, Dedrick Kok Hong Chan.



Keywords:  Cell-autonomous effects; Clonal evolution; Colorectal cancer; Intratumoral heterogeneity; Microenvironmental interactions; Somatic driver mutations; Tumor-initiating events

DOI:  https://doi.org/10.1186/s40246-025-00889-5
Exp Cell Res. 2025 Dec 15. pii: S0014-4827(25)00467-7. [Epub ahead of print] 114867

Metabolic Adaptation in Colorectal Cancer Microenvironment: Focus on Cancer-Associated Fibroblasts (CAFs) and Tumor-Associated Macrophages (TAMs).

Chou-Yi Hsu, Amr Ali Mohamed Abdelgawwad El-Sehrawy, Mirza R Baig, Zahraa Khudhair, Saidmurodkhon Murtazaev, Pareshkumar N Patel, Subbulakshmi Ganesan, Vimal Arora, Sandeep Kumar Shukla, Priya Priyadarshini Nayak.

  Metabolic reprogramming within the tumor microenvironment (TME) is a critical driver of colorectal cancer (CRC) progression, influencing tumor growth, immune evasion, and metastatic dissemination. Cancer-associated fibroblasts (CAFs) undergo adaptive shifts toward aerobic glycolysis, a process often termed the "reverse Warburg effect," producing high levels of lactate and pyruvate that are shuttled to adjacent CRC cells to fuel oxidative phosphorylation and anabolic biosynthesis. CAFs additionally secrete cytokines and growth factors, including TGF-β, IL-6, and VEGF, which integrate metabolic and signaling networks to stimulate epithelial-mesenchymal transition (EMT), angiogenesis, and metastatic potential. Similarly, tumor-associated macrophages (TAMs) exhibit remarkable metabolic plasticity that correlates with their functional heterogeneity. Beyond the classical M1/M2 dichotomy, TAM subsets display differential reliance on oxidative phosphorylation, fatty acid oxidation, or glycolysis depending on local oxygen and nutrient availability. M2-like TAMs, for example, preferentially use oxidative phosphorylation and fatty acid metabolism to sustain survival in hypoxic niches while secreting immunosuppressive metabolites such as arginase, polyamines, and lactate, which inhibit cytotoxic T-cell function. Crosstalk between CAFs and TAMs amplifies these metabolic adaptations: CAF-derived lactate promotes M2 polarization, while TAMs enhance glycolysis and biosynthetic activity in tumor cells. This study aims to systematically investigate the metabolic reprogramming of CAFs and TAMs within the CRC tumor microenvironment. Specifically, we seek to characterize the metabolic adaptations and heterogeneity of these stromal populations, elucidate their reciprocal interactions with tumor cells, and identify potential metabolic vulnerabilities that can be therapeutically targeted to disrupt tumor growth, immune evasion, and metastatic progression.

Keywords:  CAF; Colorectal cancer; Immune cell; TAM; TME

DOI:  https://doi.org/10.1016/j.yexcr.2025.114867
bioRxiv. 2025 Dec 12. pii: 2025.12.10.692786. [Epub ahead of print]

Regulatory element modules as universal features for single-cell chromatin analysis.

Chrysania Lim, Javen Tan Yih Ruay, Tim Stuart.

Single-cell chromatin accessibility data provide important insights into the activity of DNA regulatory elements in health and disease. However, the analysis of these data is made challenging by the lack of a common set of features for use in downstream analysis. This results in individual studies quantifying dataset-specific peak regions that cannot be directly compared to other studies. To address this challenge, we developed a comprehensive set of DNA regulatory element modules (REMO) for the human genome. Here we show how REMO can be applied to single-cell chromatin data to better separate cell states in a low-dimensional space compared to peak matrix quantification, greatly improve the scalability of dimension reduction steps, and enable automated annotation of cell types. This is accompanied by new memory-efficient and scalable software for the quantification of single-cell chromatin accessibility data.
Abstract Figure:

DOI: https://doi.org/10.64898/2025.12.10.692786
bioRxiv. 2025 Nov 28. pii: 2025.11.26.690796. [Epub ahead of print]

LARIS enables accurate and efficient ligand and receptor interaction analysis in spatial transcriptomics.

Min Dai, Tivadar Török, Dawei Sun, Vallari Shende, Grace Wang, Yuesang Lin, Sherry Jingjing Wu, Alyssa Rukshin, Gord Fishell, Fei Chen.

Advances in spatially resolved transcriptomics provide unprecedented opportunities to characterise intercellular communication pathways. However, robust and computationally efficient incorporation of spatial information into intercellular communication inference remains challenging. Here, we present LARIS ( L igand A nd R eceptor Interaction analysis in S patial transcriptomics), an accurate and scalable method that identifies cell type-specific and spatially restricted ligand-receptor (LR) interactions at single-cell or bead resolution. LARIS is compatible with all spatial transcriptomic technologies and quantifies specificity, infers sender-receiver directionality, and detects how differential interactions vary across time and space. To compare LARIS with existing methods, we established a simulation framework to generate ground truth of LR interactions with defined tissue architecture and gene expression patterns. LARIS demonstrates superior performances over other methods in accuracy and scalability. We further applied LARIS to human tonsil and developing mouse cortex spatial transcriptomics datasets collected from various spatial techniques. This uncovered the signalling mechanisms shaping tissue organisation and their changes over time. LARIS reveals cell type-, niche-, and condition-specific signalling and scales to hundreds of thousands of cells in minutes. This provides an efficient and direct method for discovering the molecular interplay between apposed cells across development.

DOI: https://doi.org/10.1101/2025.11.26.690796
Nat Commun. 2025 Dec 13.

FastCCC: a permutation-free framework for scalable, robust, and reference-based cell-cell communication analysis in single cell transcriptomics studies.

Siyu Hou, Wenjing Ma, Xiang Zhou.

Detecting cell-cell communications (CCCs) in single-cell transcriptomics studies is fundamental for understanding the function of multicellular organisms. Here, we introduce FastCCC, a permutation-free framework that enables scalable, robust, and reference-based analysis for identifying critical CCCs and uncovering biological insights. FastCCC relies on fast Fourier transformation-based convolution to compute p-values analytically without permutations, introduces a modular algebraic operation framework to capture a broad spectrum of CCC patterns, and can leverage atlas-scale single cell references to enhance CCC analysis on user-collected datasets. To support routine reference-based CCC analysis, we constructed the first human CCC reference panel, encompassing 19 distinct tissue types, over 450 unique cell types, and approximately 16 million cells. We demonstrate the advantages of FastCCC across multiple datasets, most of which exceed the analytical capabilities of existing CCC methods. In real datasets, FastCCC reliably captures biologically meaningful CCCs, even in highly complex tissue environments, including differential interactions between endothelial and immune cells linked to COVID-19 severity, dynamic communications in thymic tissue during T-cell development, as well as distinct interactions in reference-based CCC analysis.

DOI: https://doi.org/10.1038/s41467-025-66272-z
Nat Genet. 2025 Dec 18.

Nucleophosmin supports WNT-driven hyperproliferation and tumor initiation.

Georgios Kanellos, Chiara Giacomelli, Alexander Raven, Nikola Vlahov, Hu Jin, Pauline Herviou, Sudhir B Malla, Nadia Nasreddin, Patricia P Centeno, Constantinos Alexandrou, Kathryn Gilroy, Rachel L Baird, Kathryn Pennel, June Munro, Joseph A Waldron, Holly Hall, Leah Officer-Jones, Sheila Bryson, Douglas Strathdee, Sergio Lilla, Sara Zanivan, Vivienne Morrison, Colin Nixon, Rachel A Ridgway, Crispin Miller, John R P Knight, Andrew D Campbell, Philip D Dunne, John Le Quesne, Joanne Edwards, Peter J Park, Martin Bushell, Owen J Sansom.

Nucleophosmin (NPM1), a nucleolar protein frequently mutated in hematopoietic malignancies, is overexpressed in several solid tumors with poorly understood functional roles. Here, we demonstrate that Npm1 is upregulated after APC loss in WNT-responsive tissues and supports WNT-driven intestinal and liver tumorigenesis. Mechanistically, NPM1 loss induces ribosome pausing and accumulation at the 5'-end of coding sequences, triggering a protein synthesis stress response and p53 activation, which mediate this antitumorigenic effect. Collectively, our data identify NPM1 as a critical WNT effector that sustains WNT-driven hyperproliferation and tumorigenesis by attenuating the integrated stress response and p53 activation. Notably, NPM1 expression correlates with elevated WNT signaling and proliferation in human colorectal cancer (CRC), while CRCs harboring NPM1 deletions exhibit preferential TP53 inactivation, underscoring the clinical relevance of our findings. Being dispensable for adult epithelial homeostasis, NPM1 represents a promising therapeutic target in p53-proficient WNT-driven tumors, including treatment-refractory KRAS-mutant CRC, and hepatic cancers.

DOI: https://doi.org/10.1038/s41588-025-02408-7
Mol Syst Biol. 2025 Dec 15.

Bacterial population dynamics during colonization of solid tumors.

Serkan Sayin, Motasem ElGamel, Brittany Rosener, Michael Brehm, Andrew Mugler, Amir Mitchell.

  Bacterial colonization of tumors is widespread, yet the dynamics during colonization remain underexplored. Here we discover strong variability in the sizes of intratumor bacterial clones and use this variability to infer the mechanisms of colonization. We monitored bacterial population dynamics in murine tumors after introducing millions of genetically barcoded Escherichia coli cells. Results from intravenous injection revealed that roughly a hundred bacteria seeded a tumor and that colonizers underwent rapid, yet highly nonuniform growth. Within a day, bacteria reached a steady-state and then sustained load and clone diversity. Intratumor injections, circumventing colonization bottlenecks, revealed that the nonuniformity persists and that the sizes of bacterial progenies followed a scale-free distribution. Theory suggested that our observations are compatible with a growth model constrained by a local niche load, global resource competition, and noise. Our work provides the first dynamical model of tumor colonization and may allow distinguishing genuine tumor microbiomes from contamination.

Keywords:   E. coli ; Colonization; Microbiome; Tumor; Zipf’s Law

DOI:  https://doi.org/10.1038/s44320-025-00175-5