bims-gerecp Biomed News
on Gene regulatory networks of epithelial cell plasticity
Issue of 2026–05–10
fourteen papers selected by
Xiao Qin, University of Oxford
  1. Non-invasive profiling of the tumour microenvironment with spatial ecotypes.
  2. A tumor-intrinsic WNT-inhibitory NOTUM program drives immune resistance in microsatellite stable colorectal cancer.
  3. CellFuse enables Multi-modal Integration of Single-cell and Spatial Proteomics Data for Systems-level Analysis in Cancer.
  4. Transcription factor collaboration enables precise T cell state engineering.
  5. How ever-expanding organoids from epithelial stem cells were developed: A hypothesis-free approach.
  6. Single-nucleus multiome sequencing identifies candidate regulators of mouse gastric epithelial homeostasis.
  7. Powerful tools are revealing the 'control knobs' of the genome.
  8. Advances in Massive Parallel Sequencing: From Genomics to Spatial Transcriptomics.
  9. Bioengineered systems to exploit tumor microenvironment metabolism.
  10. Integrated Single-Cell and Spatial Profiling of MMP Gene Expression in Colorectal Cancer.
  11. A high-MAPK, low-WNT cell state drives metastatic dissemination in colorectal cancer.
  12. Mass spectrometry-based single-cell proteomics technologies, trends, and biological insights.
  13. RegFormer: a single-cell foundation model powered by gene regulatory hierarchies.
  14. Genetic manipulation technologies for precise cellular control: a comparative review of five approaches.
  1. Nature. 2026 May 06.
    Non-invasive profiling of the tumour microenvironment with spatial ecotypes.
    Wubing Zhang, Erin L Brown, Abul Usmani, Noah Earland, Minji Kang, Chibuzor Olelewe, Anushka Viswanathan, Pradeep S Chauhan, Chloé B Steen, Hyun Soo Jeon, Susanna Avagyan, Irfan Alahi, Nicholas P Semenkovich, Janella C Schwab, Chloe M Sachs, Faridi Qaium, Peter K Harris, Qingyuan Cai, Andrew J Gentles, James Knight, Rondell P Graham, Antonietta Bacchiocchi, Peter C Lucas, Ryan C Fields, Mario Sznol, Ruth Halaban, David Y Chen, Aadel A Chaudhuri, Aaron M Newman.
      Multicellular programs in the tumour microenvironment (TME) drive cancer pathogenesis and response to therapy but remain challenging to identify and profile clinically1-3. Here, we present a machine-learning framework for multi-analyte profiling of spatially dependent cell states and multicellular ecosystems, termed spatial ecotypes (SEs). By integrating over 10 million single-cell and spot-level spatial transcriptomes from diverse human carcinomas and melanomas, we identified nine SEs with broad conservation, each of which has unique biology, geospatial features and clinical outcome associations, including several linked to immunotherapy response. Notably, SEs were distinguishable by DNA methylation profiling and were recoverable from plasma cell-free DNA (cfDNA) using deep learning. In cfDNA from nearly 100 patients with melanoma, SE levels exhibited striking associations with immunotherapy response. Our data reveal fundamental units of TME organization and demonstrate a multimodal platform for profiling solid and liquid TMEs, with implications for improved risk stratification and therapy personalization.
    DOI:  https://doi.org/10.1038/s41586-026-10452-4
  2. Cell Rep Med. 2026 May 06. pii: S2666-3791(26)00193-X. [Epub ahead of print] 102776
    A tumor-intrinsic WNT-inhibitory NOTUM program drives immune resistance in microsatellite stable colorectal cancer.
    Julian Chua, Arshdeep Kaur, Fynnis Mitchell, Anneke Korver, Parnika Sakthivel, Elleine Allapitan, Mahdin Uddin, Areeba Maqsood, Naomi Chege, Aralia Leon-Coria, Constance A M Finney, Oliver F Bathe, Parham Minoo, Arshad Ayyaz.
      Immunotherapy remains largely ineffective in colorectal cancer (CRC), particularly in microsatellite stable (MSS) tumors, which represent the majority of cases. However, the complexity of intratumoral heterogeneity has made it difficult to define tumor-intrinsic programs that drive immune resistance. Here, we identify a cancer cell population that emerges predominantly in advanced-stage MSS CRCs. These cells exhibit stem-like features but aberrantly activate a WNT-inhibitory transcriptional program marked by high NOTUM expression. We term these cells WNT/β-catenin inhibitory cancer cells (WICCs). WICCs are enriched in immune-excluded tumors, correlate with reduced CD8+ T cell infiltration, and are induced in both primary human CRC tumors and patient-derived tumoroids. Selective ablation of WICCs or genetic knockout of NOTUM enhances CD8+ T-cell-mediated cytotoxicity, uncovering a tumor-intrinsic mechanism of immune evasion and nominating the WICC-NOTUM axis as a selective and tractable therapeutic target to overcome immunotherapy resistance in CRC.
    Keywords:  CD8(+) T cells; NOTUM; WNT signaling; cancer-stem-like cells; colorectal cancer; immunosuppression; immunotherapy; microsatellite stable; single-cell genomics; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.xcrm.2026.102776
  3. Cancer Res. 2026 May 05.
    CellFuse enables Multi-modal Integration of Single-cell and Spatial Proteomics Data for Systems-level Analysis in Cancer.
    Abhishek Koladiya, Zinaida Good, Sricharan Reddy Varra, Pablo Domizi, Sean C Bendall, Kara L Davis.
      Analysis of tumors using single-cell and spatial modalities is critical to advance our understanding of cancer. The growth of technologies that enable these studies provides an increasing number of single cell datasets. Integrating such data across studies will increase the impact of individual studies and speed cancer research. Most existing integration approaches are tailored to transcriptomic data and assume large sets of shared features, an assumption that fails for lower-dimensional proteomic measurements. Here, we developed CellFuse, a deep learning-based integration framework that unifies antibody-based proteomic datasets including high-dimensional cytometry, CITE-seq, and spatial proteomics data. Leveraging supervised contrastive learning, CellFuse learned a shared embedding space that enabled accurate cross-modality cell type prediction and robust label transfer across tumor samples and experimental conditions. Applied to datasets spanning peripheral blood, bone marrow, and lymphoma, CellFuse consistently outperformed existing approaches in recovering clinically relevant populations, including rare malignant and immune subsets. In solid tumors, it reconstructed spatially resolved microenvironments, capturing interactions between malignant, stromal, and immune cells that correlated with treatment response. By enabling scalable, modality-agnostic integration, CellFuse provides a powerful tool to uncover prognostic cell states and delineate the architecture of the tumor-immune ecosystem with translational relevance, driving cancer discoveries.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-25-3699
  4. bioRxiv. 2026 Apr 22. pii: 2026.04.20.718569. [Epub ahead of print]
    Transcription factor collaboration enables precise T cell state engineering.
    Rachel E Savage, Christian D McRoberts Amador, Conrad T Hock, Ruochi Zhang, Hung-Che Kuo, Aretha R Gao, Max A Horlbeck, Charles A Gersbach, Jason D Buenrostro.
      Transcription factors (TFs) collaborate to regulate gene expression programs that define cell fate. In CD8 + T cells, this coordinated regulation underlies exhaustion, a dysfunctional state that constrains immunity in chronic infection and cancer. Here, we screen for cell state-specific TFs by performing pooled overexpression screens of 3,548 TF and TF isoforms in primary T cells across multiple CD8 + T cell states. We identify 82 regulators that collaborate with exhaustion-specific programs and profile their effects using perturb-SHARE-seq, connecting perturbations to changes in chromatin accessibility and gene expression across 702,314 single cells. We identify 38 reproducible regulatory programs and construct a map of 12,616 TF-program connections that shape CD8 + T cell states, nominating KLF2 as predictive of positive response to CAR-T therapy. Using seq2PRINT, a deep learning framework that predicts functional TF interactions, we identify RUNX as a "master collaborator", a TF that broadly collaborates with other factors, and uncover a RUNX2:KLF2 interaction that specifies exhaustion-associated programs. Mutation of the RUNX2:KLF2 protein interface attenuates KLF2-mediated repression of exhaustion, while synthetic tethering of RUNX2 to KLF2 leads to an amplification of the phenotype. More broadly, we identify the collaborative action of RUNX as a driver in CD8 + T cell states, and show that tethering TFs enables the rational engineering of cell state identity for cell and gene therapies.
    DOI:  https://doi.org/10.64898/2026.04.20.718569
  5. Cell Stem Cell. 2026 May 07. pii: S1934-5909(26)00141-4. [Epub ahead of print]33(5): 722-725
    How ever-expanding organoids from epithelial stem cells were developed: A hypothesis-free approach.
    Hans Clevers.
      
    DOI:  https://doi.org/10.1016/j.stem.2026.04.001
  6. bioRxiv. 2026 Apr 27. pii: 2026.04.23.720450. [Epub ahead of print]
    Single-nucleus multiome sequencing identifies candidate regulators of mouse gastric epithelial homeostasis.
    Maithê Rocha Monteiro de Barros, Katharina Bosch, Salima Soualhi, Shirin Issa Bhaloo, Thomas Chu, Tanya Hemrajani, Jin Cho, Kurtay Ozuner, Rui Fu, Heather Geiger, Nicolas Robine, Jade E B Carter, Silas Maniatis, Sandra Ryeom, Simon Tavaré, Karol Nowicki-Osuch.
       Background & Aims: Gastric epithelial cells maintain homeostasis through dynamic self-renewal mechanisms involving stem and progenitor cells; however, identifying them has been challenging. This study aims to identify stem cells of healthy gastric epithelium and cell type-specific regulators defining gastric epithelial homeostasis via single-nucleus multiome analysis.
    Methods: Ten unique gastric samples were collected from 8-12 week old wildtype mice. Isolated nuclei were subjected to simultaneous profiling of gene expression and chromatin accessibility. After quality control, 31,598 cells were analyzed with Seurat and Signac using weighted-nearest neighbors analysis for joint RNA and ATAC clustering. Furthermore, SCENIC+, MultiVelo, EpiCHAOS and Cell plasticity score were used to uncover gene regulatory networks, cell state dynamics and lineage trajectories.
    Results: Our analyses were validated by the identification of known regulators of stem-cell differentiation into mature cell types. More importantly, it revealed previously uncharacterized regulatory networks comprising novel transcription factor combinations that define cell identities, including Ppara , Pparg , Arid5b and Sox5 as candidate regulators of parietal, foveolar, chief and neck cells, respectively. Further, our data support the identity of isthmus cells as stem-like cells of healthy gastric epithelium, as evidenced by epigenetic plasticity that simultaneously contains open chromatin states of all differentiated cell types in the absence of transcriptional reprogramming.
    Conclusion: Consistent with Waddington's epigenetic landscape hypothesis, gastric epithelial homeostasis is controlled by orchestrated epigenetic and transcriptional programs. Contrary to the prevailing hypothesis, stem cells can be defined not by a separate epigenetic state but by epigenetic superposition of differentiated cell states. Future work is needed to define the universality of these results.
    DOI:  https://doi.org/10.64898/2026.04.23.720450
  7. Nature. 2026 May;653(8113): 318-320
    Powerful tools are revealing the 'control knobs' of the genome.
    Michael Eisenstein.
      
    Keywords:  Gene therapy; Genomics; Machine learning; Technology
    DOI:  https://doi.org/10.1038/d41586-026-01410-1
  8. Adv Exp Med Biol. 2026 ;1504 43-67
    Advances in Massive Parallel Sequencing: From Genomics to Spatial Transcriptomics.
    Tomás Araújo, Margarida Gama-Carvalho.
      The ability to decode nucleic acids has reshaped biological research and biotechnology, enabling systematic analysis of genome structure, gene regulation, and cellular heterogeneity. This chapter reviews the major technological advances that have driven this transformation. We begin with the historical development of Sanger sequencing and its role in establishing the first genome-scale analyses. We then examine the emergence of next-generation sequencing, highlighting the conceptual innovations-massive parallelization, clonal amplification, and cyclic detection chemistries-that enabled high-throughput, cost-effective sequencing. Building on these foundations, we discuss the shift toward single-cell and spatial transcriptomics, which extend sequencing from bulk measurements to the resolution of individual cells and their tissue contexts. Together, these developments illustrate how sequencing technologies have progressed from early linear workflows to multimodal, high-resolution platforms that now support comprehensive interrogation of biological systems.
    Keywords:  Library preparation; Massive parallel sequencing; Next-generation sequencing (NGS); Single-cell RNA-seq (scRNA-seq); Spatial transcriptomics
    DOI:  https://doi.org/10.1007/978-3-032-18966-0_3
  9. Trends Cancer. 2026 May 07. pii: S2405-8033(26)00078-6. [Epub ahead of print]
    Bioengineered systems to exploit tumor microenvironment metabolism.
    Christine Sanganoo, Ilaria Caturegli, Zachary Mattes, Jordan Ryan, Wilson W Wong, Mark W Grinstaff.
      Our understanding of cancer metabolism has afforded the opportunity to develop therapies specific to tumor metabolic dysregulation. While molecular therapeutics targeting cancer metabolism have found success in the clinic, bioengineering approaches are nascent. Here, we describe key metabolic pathways and their genetic dysregulations in the tumor microenvironment (TME) that are ripe for intervention. We examine bioengineered biomaterial and cellular systems that harness the metabolic and immune landscape of the TME to target metabolic dependencies of tumor growth. These therapeutic strategies include, for example, preventing the uptake of essential metabolites, delivering metabolic inhibitors, and restoring an immunostimulating environment. With a focus toward clinical applications and tolerability, we identify key limitations and conclude with future directions.
    Keywords:  antimetabolite delivery; biomaterials; cancer metabolism; immunosuppressive metabolite modulation; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.trecan.2026.04.003
  10. bioRxiv. 2026 Apr 22. pii: 2026.04.17.719089. [Epub ahead of print]
    Integrated Single-Cell and Spatial Profiling of MMP Gene Expression in Colorectal Cancer.
    Nicholas A Danese, Shan Kurkcu, Marina Bleiler, Klea Nito, Alan Kuo, Daniel W Rosenberg, Masako Nakanishi, Charles Giardina.
      Increased matrix metalloproteinase (MMP) expression has long been recognized as a common feature of colorectal cancers (CRCs), yet less is known about how these enzymes interact to impact cancer progression. Taking advantage of single-cell and spatial transcriptomic data, we analyzed the cell-type-specific and spatial expression of MMPs in CRCs. Distinct colon cancer-associated fibroblast (CAF) subtypes were found to express different MMP combinations, including MMP1/3-expressing and MMP11-expressing CAFs. Conversely, myeloid cells (monocytes, macrophages, and dendritic cells) expressed varying levels of the "myeloid MMPs" 9, 12, and 14, which correlated closely with secretory gene expression. Finally, a small population of cancer cells expressed high levels of MMP7. The MMP7-expressing cancer cells frequently co-expressed MMP1, MMP14, and several Wnt-related genes, consistent with a cancer cell type at high risk of malignancy and metastasis. Spatial transcriptomic data showed MMP expression in discernible clusters driven in part by cell-type localization, including fibroblast-heavy stromal regions and inflammatory cell hubs. Epithelial-rich areas showed subregions of MMP7-expressing cancer cells, including areas where cancer cell and myeloid MMP expression overlap. Tumors showed a wide variation in MMP1-expressing CAFs, a variation reflected in primary CAF cell lines. In vitro, MMP1 expression was a stable phenotype that persisted through multiple rounds of division. MMP1-expressing CAFs were frequently positioned at the stromal interface, suggesting a role in facilitating cell movement across the tumor boundary. Our analysis indicates that cell-type and positional MMP expression varies between tumors and may play a role in determining lesion progression and cancer spread.
    DOI:  https://doi.org/10.64898/2026.04.17.719089
  11. Nat Cancer. 2026 May 07.
    A high-MAPK, low-WNT cell state drives metastatic dissemination in colorectal cancer.
    Melanie Heinlein, Ginny X Li, Noelyn Kljavin, Amanda R Moore, Brian Biehs, Liming Tao, Soufiane Boumahdi, Farnaz Mohammadi, Minyi Shi, Yuxin Liang, Hartmut Koeppen, Nicolò Riggi, Robert Piskol, Frederic J de Sauvage.
      Colorectal cancer (CRC), a leading cause of cancer-related mortality due to distant metastases, is largely driven by activating mutations in the WNT and mitogen-activated protein kinase (MAPK) pathways. Understanding the mechanism underlying the metastatic process is essential for developing effective treatments. Using serial in vivo orthotopic passaging, we developed an immunocompetent mouse model of metastatic CRC. Highly metastatic tumor cells exhibited chromosomal amplifications in MAPK pathway genes, resulting in increased MAPK pathway activity and suppression of WNT-associated transcriptional programs, including stem cell genes. Pharmacological inhibition of mutant KRASG12D led to a reduction in the MAPK-high-WNT-low transcriptional state and decreased both lung and liver metastases. Analysis of CRC patient data revealed that the metastatic gene signature associated with the MAPK-high-WNT-low state correlated with poorer survival outcomes. These findings underscore the plasticity of metastasis-initiating cells in CRC driven by the opposing roles of MAPK and WNT signaling, despite their synergy observed during colon tumorigenesis.
    DOI:  https://doi.org/10.1038/s43018-026-01155-w
  12. Trends Biochem Sci. 2026 May 07. pii: S0968-0004(26)00111-8. [Epub ahead of print]
    Mass spectrometry-based single-cell proteomics technologies, trends, and biological insights.
    Rui Hu, Christian Montes, Justin W Walley.
      Single-cell proteomics (SCP) has emerged as a transformative approach for characterizing cellular heterogeneity at the protein level. Recent advances in mass spectrometry workflows, with improvements spanning sample preparation, peptide separation, data acquisition, and data interpretation, have enabled unprecedented proteome depth and throughput at single-cell resolution. Beyond technological innovations, SCP is now addressing complex biological questions in oncology, developmental biology, and neuroscience, revealing dynamic cellular states and regulatory mechanisms. Integration with other single-cell omics is bridging the gap between genotype-phenotype relationships and uncovering multilayered regulation. In this review, we summarize recent progress in SCP technologies and highlight emerging applications and integrative strategies that mark a transition from technological development to broad biological understanding.
    Keywords:  cellular heterogeneity; mass spectrometry; multiomics; single-cell proteomics
    DOI:  https://doi.org/10.1016/j.tibs.2026.04.011
  13. Nat Commun. 2026 May 05.
    RegFormer: a single-cell foundation model powered by gene regulatory hierarchies.
    Luni Hu, Hua Qin, Yilin Zhang, Yi Lu, Ping Qiu, Zhihan Guo, Lei Cao, Wenjian Jiang, Yixin Shen, Qianqian Chen, Yanbang Shang, Tianyi Xia, Ziqing Deng, Hansheng Zhao, Xun Xu, Shuangsang Fang, Yuxiang Li, Yong Zhang.
      Single-cell RNA sequencing (scRNA-seq) enables high-resolution profiling of cellular diversity, but current computational models often fail to incorporate regulatory priors, handle data sparsity, or efficiently process long gene sequences. Here, we present RegFormer, a foundation model that integrates gene regulatory networks (GRNs) with Mamba-based state-space modeling, overcoming the scalability and context-length limitations of Transformer architectures. RegFormer encodes each gene through dual embeddings, a value embedding for quantitative expression and a token embedding for regulatory identity, organized within a GRN-guided gene order to capture both expression dynamics and hierarchical regulation. Pretrained on 25 million human single cells spanning 45 tissues and diverse biological contexts, RegFormer achieves superior scalability and biological fidelity. Across comprehensive benchmarks, it consistently outperforms state-of-the-art single-cell foundation models (scGPT, Geneformer, scFoundation, and scBERT), delivering higher clustering accuracy, improved batch integration, and more precise cell type annotation. RegFormer also reconstructs biologically coherent GRNs, accurately models transcriptional responses to genetic perturbations, and enhances drug response prediction across cancer cell lines. By combining regulatory priors with efficient long-sequence Mamba modeling, RegFormer establishes a biologically grounded and scalable framework for single-cell representation learning, enabling deeper mechanistic insight into gene regulation and cellular state transitions.
    DOI:  https://doi.org/10.1038/s41467-026-72198-x
  14. Front Bioeng Biotechnol. 2026 ;14 1818170
    Genetic manipulation technologies for precise cellular control: a comparative review of five approaches.
    Qin Xiao, Panpan Sun, Jing Liu, Jia Li, Xueqin Xu, Ying Cao, Yanqiong Wu, Changbin Ke.
      Genetic manipulation technologies have revolutionized our ability to control cellular activities with high precision. Five major approaches-chemogenetics, optogenetics, odorgenetics, magnetogenetics, and sonogenetics-offer distinct advantages for different research and therapeutic scenarios. However, a unified framework for systematic comparison across these technologies has been lacking.This review provides a comprehensive analysis of these five genetic manipulation technologies from three perspectives: molecular mechanisms, quantitative performance metrics, and application scenarios. We first dissect the signaling pathways and key molecular components underlying each technology. We then establish a seven-dimensional evaluation framework encompassing spatiotemporal resolution, tissue penetration, cell-type specificity, reversibility, multiplexing capability, biosafety, and technical accessibility. Using this framework, we systematically score and compare the five technologies, revealing that optogenetics excels in spatiotemporal precision (millisecond/micrometer scale), chemogenetics offers superior clinical translatability, while sonogenetics and magnetogenetics provide advantages for non-invasive deep tissue applications. We further analyze optimal application scenarios for each technology, including neural circuit dissection, chronic disease management, and deep tissue intervention.This comparative analysis provides researchers with an evidence-based guide for technology selection. We propose that future developments should focus on hybrid approaches combining the strengths of multiple technologies, and on addressing current limitations in delivery efficiency and long-term biosafety for clinical translation.
    Keywords:  chemogenetics; genetic manipulation; magnetogenetics; neuromodulation; odorgenetics; optogenetics; sonogenetics
    DOI:  https://doi.org/10.3389/fbioe.2026.1818170
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