🧪 Technology & Methods Development
Reconstructing single-cell resolution from spatial transcriptomics with CellRefiner.
This study introduces CellRefiner, a physical model-based framework that integrates scRNA-seq with lower-resolution spatial transcriptomics to computationally reconstruct single-cell spatial maps. By modeling cells as interacting particles and optimizing positions based on proximity, expression similarity, and ligand–receptor interactions, CellRefiner robustly recovers realistic spatial cell patterns across multiple platforms and tissues, improving downstream spatial analyses such as cell–cell communication.
Impact: A powerful computational tool to upgrade non–single-cell spatial data to effective single-cell resolution for richer biological discovery.
Bourgain-Chang E et al., https://doi.org/10.1038/s41467-026-70090-2
CEMUSA: a graph-based integrative metric for evaluating clusters in spatial transcriptomics.
CEMUSA is presented as a graph-based evaluation metric for spatial clustering that jointly considers label agreement, spatial organization, and the severity of clustering errors. By overcoming biases of traditional metrics that ignore spatial structure, CEMUSA enables more accurate benchmarking and comparison of spatial clustering algorithms.
Impact: A dedicated, spatially aware quality metric to objectively assess and optimize spatial clustering methods.
Hu J et al., https://doi.org/10.1093/bioinformatics/btag056
Metabolic RNA Labeling-Enabled Time-Resolved Single-Cell RNA Sequencing.
This Account reviews the evolution of metabolic RNA labeling–based time-resolved scRNA-seq, from single to dual nucleoside labeling and from in vitro systems to in vivo applications. The authors highlight methods such as Well-TEMP-seq, scDUAL-seq, and Dyna-vivo-seq, and discuss recent efforts to couple temporal RNA dynamics with spatial transcriptomics to capture spatiotemporal gene regulation at single-cell resolution.
Impact: A comprehensive overview and conceptual roadmap for integrating time-resolved and spatial transcriptomics to study dynamic gene regulation.
Yin K et al., https://doi.org/10.1021/acs.accounts.6c00010
🧬 Cancer Research & Tumor Microenvironment
A hormetic transcriptional program coregulates invasion, proliferation and dormancy to define metastatic potential.
By integrating spatial transcriptomics, single-cell RNA-seq, and chromatin profiling in breast cancer models and patient cohorts, this study shows that tumor cells disseminate with pre-set metastatic potential. The transcription factor Prrx1 emerges as a master regulator that balances invasion, proliferation, and dormancy in a hormetic fashion, with intermediate expression driving maximal metastatic burden and combined invasion–proliferation signatures strongly stratifying patient prognosis.
Impact: Reveals a unified transcriptional program controlling metastatic competence and offers prognostic signatures for breast cancer stratification.
Jiménez-Castaño R et al., https://doi.org/10.1038/s41467-026-70242-4
Macrophage-rich niches regulate T cell dynamics at the liver invasive margin during gallbladder cancer progression.
Single-cell and spatial transcriptomics of the tumor–liver interface in gallbladder cancer uncover CXCL9⁺ macrophage-rich immune niches at the invasive margin. Distinct CXCL9⁺TRAC⁺ and CXCL9⁺C1QB⁺ niches differentially regulate CD8⁺ T cell recruitment and exhaustion, and patient data show that high CXCL9 and low LGALS4 levels at this margin predict better prognosis and response to anti–PD-1 therapy.
Impact: Identifies spatially defined immune niches that shape T cell behavior and provide actionable biomarkers for immunotherapy in gallbladder cancer.
Li M et al., https://doi.org/10.1172/JCI193672
Acinar Metaplastic Cells Generate Semi-Homogeneous Niches and Interact With Immune Cells.
Focusing on early pancreatic transformation, this study dissects how heterogeneous acinar metaplastic cell subtypes are spatially distributed across premalignant lesions. Using spatial and single-cell profiling, the authors show that these metaplastic populations form semi-homogeneous niches with distinct patterns of stromal and immune cell crosstalk that may set the stage for progression to pancreatic ductal adenocarcinoma.
Impact: Maps the early spatial ecology of pancreatic metaplasia, highlighting micro-niches and immune interactions that could be targeted to prevent cancer development.
Arcila-Barrera S et al., https://doi.org/10.1053/j.gastro.2025.12.014
🧫 Infectious Disease & Immunopathology
Single-cell and spatial profiling highlights TB-induced myofibroblasts as drivers of lung pathology.
Combining scRNA-seq and spatial transcriptomics on human TB and control lungs, this work identifies 30 cellular subsets and pinpoints MMP1⁺CXCL5⁺ myofibroblast-like fibroblasts as key drivers of granuloma-associated tissue destruction and fibrosis. Network analyses reveal strong crosstalk between these fibroblasts and SPP1⁺ macrophages within the granuloma cuff, a circuit linked to severe disease and higher bacterial burden in nonhuman primate models.
Impact: Uncovers pathogenic fibroblast–macrophage interactions as central to TB lung damage, suggesting new cellular targets for host-directed therapies.
Mbano IM et al., https://doi.org/10.1084/jem.20251067
🧠 Immunology & Hematopoiesis
Single-cell multiomic atlas of healthy pediatric bone marrow reveals age-dependent differences in lineage differentiation driven by stromal signaling.
This study builds a multimodal single-cell atlas of pediatric bone marrow, integrating transcriptomic and surface protein data from over 90,000 cells across infancy to young adulthood. Spatial transcriptomics on biopsies validates a developmental shift from B cell–biased hematopoiesis in young children to myeloid and T cell bias in adolescents and young adults, driven by age-dependent stromal signaling and distinct lymphoid progenitor subsets.
Impact: Provides a spatially anchored reference atlas of pediatric bone marrow maturation, informing age-specific vulnerability to hematologic disease and immunotherapies.
Hanemaaijer ES et al., https://doi.org/10.1038/s41590-026-02422-9
🩺 Liver Disease & Fibrosis
Activation of the Integrin αV-YAP-CTGF Axis in Liver Sinusoidal Endothelial Cells Promotes Liver Fibrogenesis, Leading to Portal Hypertension and Liver Carcinogenesis in Congestive Hepatopathy.
Investigating congestive hepatopathy, this study focuses on liver sinusoidal endothelial cells (LSECs) and implicates activation of the integrin αV–YAP–CTGF signaling axis in driving fibrogenesis. Through molecular and spatial analyses, the authors link this endothelial program to progressive fibrosis, portal hypertension, and an increased risk of liver cancer in the context of chronic congestion.
Impact: Identifies an endothelial integrin–YAP–CTGF pathway as a mechanistic driver and potential therapeutic target in congestive liver fibrosis and carcinogenesis.
Kato S et al., https://doi.org/10.1053/j.gastro.2025.11.014
Clusterin Drives Fiber Endocytosis by Mesothelial Cells to Resolve Liver Fibrosis.
This work reveals that the secreted glycoprotein clusterin (CLU) promotes endocytosis of fibrotic extracellular matrix fibers by mesothelial cells, facilitating remodeling and resolution of liver fibrosis. The study challenges the notion that advanced fibrosis is irreversibly fixed and positions CLU-mediated pathways as promising levers to therapeutically reverse chronic liver scarring.
Impact: Demonstrates a CLU-driven mesothelial clearance mechanism that could be harnessed to actively reverse liver fibrosis.
Wang M et al., https://doi.org/10.1053/j.gastro.2025.08.022