Research Radar — 2026-07-28
Methods & AI
Computational
Full-length single-cell spatial transcriptomics reveals spatial and cell-type-specific transcript isoforms in the primate brain
Nature Methods Published 2026-07-24 Research Article DOI: 10.1038/s41592-026-03174-y
spatial transcriptomics single-cell long-read sequencing isoform detection Stereo-seq
Summary: Fullscope-seq combines Stereo-seq with long-read sequencing to achieve single-cell isoform-level resolution in spatial transcriptomics on macaque brain slices, unlocking a new layer of transcriptome complexity.
Why it matters: Combines Stereo-seq with long-read sequencing to achieve single-cell isoform-level resolution in spatial transcriptomics, enabling full-length transcript isoform detection across large tissue areas.
Why for Yiru: Directly relevant to spatial transcriptomics research. The single-cell isoform resolution approach could inspire new analytical strategies in your work.
RETROFIT: Reference-free deconvolution of cell-type mixtures in spatial transcriptomics
Nature Communications Published 2026-07-24 Research Article DOI: 10.1038/s41467-026-74928-7
spatial transcriptomics deconvolution Bayesian method reference-free cell-type composition
Summary: Introduces RETROFIT, a reference-free Bayesian method that infers cell-type composition and expression from spatial transcriptomics data without relying on external references.
Why it matters: Solves a key bottleneck in spatial transcriptomics by enabling reference-free deconvolution of mixed cell populations, making spatial analysis more widely applicable.
Why for Yiru: Deconvolution is core to spatial transcriptomics analysis. This reference-free approach could be immediately useful in your spatial data analysis workflow.
A benchmark study of vision and pathology foundation models for computational pathology
Nature Communications Published 2026-07-24 Research Article DOI: 10.1038/s41467-026-76004-6
foundation model computational pathology benchmarking AI deep learning
Summary: Benchmarks 32 pathology and vision AI foundation models on large-scale cancer datasets, showing that generalisation is heterogeneous and task-dependent, but ensemble approaches can combine the strengths of different models.
Why it matters: Provides the most comprehensive comparison of pathology and vision foundation models to date, revealing critical insights about when domain-specific pretraining matters.
Why for Yiru: Foundation models are a key interest. Understanding when pathology-specific models outperform general vision models is valuable for tool selection.
Spatialproteomics: an interoperable toolbox for analyzing highly multiplexed fluorescence image data
Nature Methods Published 2026-07-24 Research Article DOI: 10.1038/s41592-026-03155-1
spatial proteomics multiplexed imaging Python toolbox image analysis bioinformatics
Summary: Spatialproteomics is a Python-based toolbox that supports end-to-end analysis of highly multiplexed imaging data, standardizing workflows in the growing spatial proteomics field.
Why it matters: Provides a unified Python framework for end-to-end analysis of highly multiplexed imaging data, standardizing previously fragmented analysis workflows.
Why for Yiru: Spatial proteomics complements spatial transcriptomics. This toolbox could streamline your multiplexed imaging analysis pipeline.
Deep interpretable learning of sample representations for characterizing disease states in single-cell transcriptomics
bioRxiv Published 2026-07-22 Preprint DOI: 10.1101/2026.07.21.738207
deep learning single-cell transcriptomics interpretability representation learning disease states
Summary: Introduces Phenoverse, an interpretable deep learning framework that learns sample-level disease state representations through cell type-aware residual encoding, prototype learning, and Perceiver-based aggregation for single-cell transcriptomics.
Why it matters: Makes deep learning interpretable in single-cell analysis, providing biological insights rather than just predictions.
Why for Yiru: Interpretable AI in single-cell analysis aligns with your interest in making ML models biologically meaningful.
IOBRpy enables agentic multi-omics decoding of anti-tumor immunity
bioRxiv Published 2026-07-22 Preprint DOI: 10.1101/2026.07.17.739055
multi-omics tumor immunity AI agent immunotherapy computational pipeline
Summary: IOBRpy is a Python toolkit driven by an innovative AI dual-agent layer for automated, highly standardized immuno-oncology workflows. It enables agentic multi-omics decoding from raw data to TME characterization.
Why it matters: Brings AI agent technology to immuno-oncology bioinformatics, automating complex multi-omics workflows for tumor immunity analysis.
Why for Yiru: Directly relevant to your multi-omics and immunotherapy interests. The agentic approach could also inspire your own computational workflows.
Biomedical discoveries
Biomedicine
Single-nucleus multimodal spatial transcriptomics reveals spatial colocalization of neoantigen-expressing tumor cells and cognate T cells
Nature Biotechnology Published 2026-07-22 Research Article DOI: 10.1038/s41587-026-03194-1
spatial transcriptomics neoantigen T cell tumor microenvironment single-nucleus TCR sequencing
Summary: Combines single-nucleus multimodal spatial transcriptomics with TCR sequencing to directly visualize spatial colocalization of neoantigens and cognate T cells in the tumor microenvironment.
Why it matters: First direct visualization of spatial relationships between neoantigen-expressing tumor cells and cognate T cells using multimodal spatial transcriptomics at single-nucleus resolution.
Why for Yiru: Directly aligns with your spatial transcriptomics and tumor immunology interests. The multimodal approach to studying T cell-tumor interactions is highly relevant.
Blocking the m6Am methyltransferase PCIF1 releases STAT1-mediated Th1 immunity to potentiate cancer immunotherapy
Nature Communications Published 2026-07-22 Research Article DOI: 10.1038/s41467-026-75269-1
immunotherapy epitranscriptomics m6A modification PCIF1 T cell activation STAT1 Th1 immunity
Summary: Shows that deleting PCIF1 in T cells releases STAT1-mediated Th1 immunity, identifying a new epitranscriptomic mechanism for potentiating cancer immunotherapy.
Why it matters: Discovers PCIF1 as an epitranscriptomic checkpoint in T cells, revealing that m6Am methylation regulates STAT1 translation and T cell activation with therapeutic implications.
Why for Yiru: Connects epitranscriptomics with immunotherapy — your interest in immune mechanisms plus a novel therapeutic target. Highly relevant.
Disease-associated microglia adopt stage-specific phenotypes that regulate T cell fate and immunity in glioma
Immunity Published 2026-07-24 Research Article DOI: 10.1016/j.immuni.2026.07.015
microglia glioma T cell immunity tumor microenvironment brain tumor myeloid cells
Summary: Disease-associated microglia (DAMs) in glioma are not static suppressors but evolve with tumor stage, transitioning through antigen-presenting, checkpoint-regulatory, and T cell-clearing programs.
Why it matters: Reveals that brain-resident microglia dynamically reprogram their phenotypes during glioma progression, directly shaping local T cell responses and immunity in the brain.
Why for Yiru: Your interest in macrophage biology and tumor microenvironment makes this highly relevant. Dynamic microglia phenotypes could inform myeloid-targeting strategies.
A self-amplifying nerve-fibroblast circuit drives colorectal cancer progression
Cancer Cell Published 2026-07-24 Research Article DOI: 10.1016/j.ccell.2026.07.006
colorectal cancer cancer-associated fibroblast cholinergic signaling NTN1 tumor microenvironment nerve-tumor crosstalk
Summary: Demonstrates a self-amplifying circuit where cholinergic signaling induces NTN1 secretion from colorectal CAFs, which enhances intratumoral cholinergic innervation, accelerating cancer growth through CHRM3 and UNC5B.
Why it matters: Reveals a previously unknown self-amplifying nerve-CAF-cancer circuit that drives colorectal cancer progression, identifying CHRM3 and NTN1 as potential therapeutic targets.
Why for Yiru: Tumor microenvironment interactions are central to your research. This nerve-CAF-cancer axis reveals a new dimension of TME crosstalk.
Routine FFPE sections support clinically compatible single-nucleus transcriptomics across six human cancer types
bioRxiv Published 2026-07-24 Preprint DOI: 10.1101/2026.07.23.740343
FFPE tissue single-nucleus transcriptomics clinical translation cancer genomics tumor profiling
Summary: Presents a clinically compatible sample-to-report workflow for tumor composition profiling from routine FFPE sections, combining low-input single-nucleus RNA-seq with foundation model-based automated cell annotation across six cancer types.
Why it matters: Demonstrates that routine FFPE sections are compatible with clinically scalable single-nucleus transcriptomics, bridging the gap between research and clinical use.
Why for Yiru: Directly relevant to your interest in translating spatial/single-cell methods to clinical applications. FFPE compatibility is key for real-world impact.
Macrophage-instructed GSDME couples glioblastoma cell-state plasticity with inflammatory cell death
bioRxiv Published 2026-07-23 Preprint DOI: 10.1101/2026.07.22.740157
macrophage glioblastoma GSDME pyroptosis cell-state plasticity inflammatory cell death
Summary: Using COMET spatial proteomics and multiplex spatial profiling, shows that macrophages instruct GSDME-dependent pyroptosis in glioblastoma, coupling inflammatory cell death with tumor cell-state plasticity.
Why it matters: Identifies GSDME as a macrophage-instructed regulator of glioblastoma cell plasticity, linking innate immune signaling to tumor cell fate decisions.
Why for Yiru: Your interest in macrophage biology and cancer makes this highly relevant. The intersection of macrophage function and tumor cell plasticity is fascinating.
An immune-stimulating antibody conjugate spatiotemporally targeting CD47 and TLR9 elicits macrophage-dependent tumor clearance and durable anti-cancer adaptive immunity
bioRxiv Published 2026-07-23 Preprint DOI: 10.1101/2026.07.22.739359
CD47 TLR9 macrophage antibody conjugate cancer immunotherapy tumor clearance
Summary: Engineers aCD47-CpG, an immune-stimulating antibody conjugate coupling CD47 blockade with TLR9 agonism, which reprograms macrophages and elicits durable anti-cancer adaptive immunity.
Why it matters: Demonstrates that combining CD47 blockade with TLR9 stimulation in a single conjugate can transition innate immune activation into durable adaptive anti-tumor immunity.
Why for Yiru: Macrophage-targeting immunotherapies are highly relevant. The dual CD47-TLR9 approach represents a creative strategy in macrophage checkpoint modulation.
Cross-disciplinary watchlist
Other Fields
Genetic background sets the trajectory of experimental cancer evolution
Nature Published 2026-07-22 Research Article DOI: 10.1038/s41586-026-10821-z
cancer evolution genetic background mouse models tumor initiation genetic diversity
Summary: Experimentally replaying tumour evolution in divergent mouse strains reveals that interactions between genetic ancestry and acquired cancer-driving mutations shape the earliest stages of cancer development.
Why it matters: Provides direct experimental evidence that genetic background fundamentally shapes cancer evolutionary trajectories, interacting with somatic mutations.
Why for Yiru: Understanding how genetic background influences cancer evolution provides context for interpreting tumor heterogeneity in your studies.
Prospective validation of imaging and serum diagnostic biomarkers of steatohepatitis and fibrosis in MASLD: the LITMUS Imaging Study
Nature Medicine Published 2026-07-24 Research Article DOI: 10.1038/s41591-026-04496-2
MASLD biomarker imaging steatohepatitis fibrosis clinical validation
Summary: The LITMUS study prospectively validates that serum biomarkers outperform imaging for identifying patients at risk of MASH, while elastography is superior for staging advanced fibrosis and cirrhosis.
Why it matters: Provides the largest prospective validation of multi-modal biomarkers for MASLD, offering evidence-based guidance for clinical diagnostic strategies.
Why for Yiru: Biomarker validation methodology and multi-modal diagnostic comparison are relevant to your interest in translational biomarkers.
FcRH5×CD3 bispecific antibody cevostamab in relapsed or refractory multiple myeloma: a phase 1 trial
Nature Medicine Published 2026-07-22 Research Article DOI: 10.1038/s41591-026-04522-3
bispecific antibody multiple myeloma cevostamab phase 1 trial T cell engager
Summary: Phase 1 trial of the FcRH5×CD3 bispecific T cell engager cevostamab shows the maximum tolerated dose was not reached with encouraging response rates in relapsed/refractory multiple myeloma.
Why it matters: Provides clinical evidence for a novel bispecific T cell engager targeting FcRH5 in multiple myeloma, expanding the toolkit of T cell-redirecting therapies.
Why for Yiru: Bispecific T cell engagers are central to modern immunotherapy. This clinical data adds to your understanding of T cell-redirecting therapies.
A Synthetic Microbial Therapy Rewires Antitumor Immunity Across Multiple Cancer Types
bioRxiv Published 2026-07-22 Preprint DOI: 10.1101/2026.07.19.735925
synthetic biology microbiome cancer immunotherapy antitumor immunity microbial therapy
Summary: Introduces SPIKE 1.0, a metabolically engineered bacterium that converts tryptophan into immunomodulatory hydroxyindoles to remodel the TME, eliciting durable antitumor responses across multiple murine models.
Why it matters: Represents a novel immunotherapeutic modality that combines synthetic biology with cancer immunotherapy, showing efficacy across multiple cancer types.
Why for Yiru: While not your core focus, the intersection of microbiome engineering and cancer immunotherapy is a rapidly evolving area worth monitoring.
Mechanisms regulating combination effect of antibody-drug conjugates and cancer immunotherapy
bioRxiv Published 2026-07-22 Preprint DOI: 10.1101/2026.07.17.738956
antibody-drug conjugate cancer immunotherapy combination therapy ADC mechanism of action
Summary: Investigates the mechanistic basis of ADC combinations with T cell engagers and checkpoint inhibitors, revealing that ADC-induced TNF production enhances T cell engagement and overcomes resistance.
Why it matters: Provides a mechanistic framework for rationally combining ADCs with immunotherapy, identifying key pathways that drive synergy and resistance.
Why for Yiru: Combination therapy strategies are increasingly important in cancer treatment. Understanding ADC-IO mechanisms helps contextualize emerging therapeutic paradigms.