Research Radar — 2026-05-21
Methods & AI
Computational
A Deep-Learning Framework Reveals Whole-Body Perturbations at Cell Level
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10535-2
deep learning foundation model whole-body imaging multi-organ disease modeling systems biology
Summary: Presents MouseMapper, a suite of foundation-model-based deep learning algorithms enabling multi-system analysis of disease across the entire mouse body. MouseMapper performs whole-body quantitative analysis of disease-associated changes at cellular resolution, mapping perturbations across multiple organ systems simultaneously. The framework addresses the long-standing challenge of comprehensive, high-resolution whole-body disease phenotyping, which has been limited by tools that analyze individual organs in isolation. Published in Nature, this represents a landmark application of foundation model architectures to organism-scale biology.
Why it matters: Diseases like obesity and cancer have systemic effects that perturb multiple organ systems, yet tools for whole-body analysis at cellular resolution have been lacking. MouseMapper provides a transformative platform for understanding how diseases propagate across organ systems, with implications for drug development, toxicity screening, and systems-level disease modeling.
Why for Yiru: The TME does not exist in isolation — systemic factors including metabolism, endocrine signaling, and immune system status shape tumour biology. A whole-body perturbation mapping framework could reveal how systemic disease states influence the TME across organs, providing a more holistic view of cancer as a systemic disease.
Multi-Scale Tri-Modal Histology Dataset Integrating Tumor Morphology, Immune Patterns, and Clinical Outcomes
bioRxiv Published 2026-05-19 preprint DOI: 10.1101/2026.05.15.725535
histology multimodal prostate cancer immune infiltration deep learning spatial biology dataset
Summary: Introduces Prostate-TriMod, a novel tri-modal histology dataset from the Cell DIVE multiplexed imaging platform, designed to integrate high-resolution visual morphology with spatial tissue maps, immune infiltration patterns, and clinical outcomes for prostate cancer. The dataset consists of three synchronized modalities: multiscale virtual H&E tiles at multiple resolutions (224–2040 px), spatial tissue maps identifying cancerous/non-cancerous epithelial cells, stroma and immune populations via TOPAZ and CAT models, and text captions generated from single-cell data and spatial patterns. Includes comprehensive clinical annotations including Grade Groups and biochemical recurrence status, enabling multimodal AI framework development.
Why it matters: Multimodal histology datasets that bridge visual morphology, spatial molecular data, and clinical outcomes are critical for developing clinically deployable AI models in pathology. Prostate-TriMod provides a standardized benchmark that could accelerate the development of foundation models for computational pathology by providing aligned visual, spatial, and textual modalities with ground-truth clinical outcomes.
Why for Yiru: Multimodal integration of histology with spatial molecular and immune data is directly relevant to TME analysis. A dataset that aligns morphological features with immune infiltration patterns and clinical outcomes provides a template for similar multimodal resources in other cancer types and for TME-focused AI model development.
Genetic Analysis of Circulating Metabolic Traits in 619,372 Individuals
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10532-5
GWAS metabolomics biobank genetics metabolic traits population genomics Estonian Biobank UK Biobank
Summary: Performs a GWAS meta-analysis for 249 circulating metabolic traits combining the Estonian Biobank and UK Biobank, totaling 619,372 individuals — the largest metabolic GWAS to date. The study identifies thousands of genetic loci associated with circulating metabolite levels, providing a comprehensive map of the genetic architecture of human metabolism. Integrates metabolomic, genomic, and proteomic data to interpret how genetic variants influence metabolic traits through molecular intermediates, advancing the understanding of how genetic variation shapes systemic metabolism at population scale.
Why it matters: Circulating metabolites are key intermediate phenotypes linking genetic variation to complex diseases including cancer, cardiovascular disease, and metabolic disorders. A GWAS of this scale provides an unparalleled resource for understanding the genetic basis of human metabolism and identifying causal metabolic pathways in disease.
Why for Yiru: Systemic metabolism shapes the TME through circulating nutrients, hormones, and metabolites that influence tumour cell metabolism, immune cell function, and therapy response. Understanding the genetic architecture of circulating metabolites could reveal host genetic factors that influence TME composition and cancer outcomes.
A Critical Initialization for Biological Neural Networks
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10528-1
neural networks theoretical neuroscience criticality population dynamics eigenvalue spectrum brain dynamics
Summary: Investigates how macroscopic coordination in large neural populations emerges from microscopic, short-lived pairwise neural interactions. Shows that the eigenvalue spectrum and dynamical properties of large-scale neural recordings in mice resemble those of networks poised near a critical initialization point — analogous to the critical initialization regime known in artificial neural network theory. This suggests that biological neural networks may operate near a dynamical phase transition that optimizes information processing capacity, providing a theoretical bridge between artificial and biological neural computation.
Why it matters: The observation that biological neural networks share fundamental dynamical properties with optimally initialized artificial networks suggests deep theoretical connections between natural and artificial intelligence. This could inform both our understanding of brain computation and the design of more brain-like AI systems.
Why for Yiru: Theoretical frameworks connecting biological and artificial neural computation are broadly relevant to the computational biology community. Understanding the principles of optimal neural network initialization in biological systems may inspire new approaches to modeling complex biological systems, including cellular interaction networks in the TME.
De Novo Design of Quasisymmetric Two-Component Protein Cages
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10464-0
protein design de novo design nanocages computational biology synthetic biology self-assembly
Summary: Reports the computational de novo design of quasisymmetric two-component protein cages — hollow, self-assembling protein nanostructures built from two distinct protein subunits that co-assemble with near-perfect symmetry. The design pipeline combines Rosetta-based protein interface design with geometric principles of icosahedral symmetry, enabling the creation of protein cages with tunable sizes, porosities, and interior volumes. These designed nanocages represent a major advance in the ability to computationally program protein self-assembly into functional nanostructures.
Why it matters: De novo protein cage design opens the door to programmed nanomaterials for drug delivery, vaccine design, enzyme encapsulation, and synthetic biology. The ability to design multi-component assemblies greatly expands the functional complexity accessible to computational protein design.
Why for Yiru: Computational protein design is a rapidly advancing field with implications for therapeutic development, including engineered protein cages for targeted drug delivery to the TME. Understanding the principles of multi-component protein assembly design is broadly relevant to protein engineering.
Early Terminated Transcripts and Missing Proteins Reflect Artifacts in Bacterial Proteomes
bioRxiv Published 2026-05-20 preprint DOI: 10.1101/2026.05.19.725897
proteomics quality control MMseqs2 bacterial genomics sequencing artifacts protein clustering
Summary: Uses MMseqs2 clustering to systematically examine the uniformity and heterogeneity of proteomes from 20 bacterial species, revealing that short-outlier proteins in clusters are predominantly artifacts from sequencing errors and initiation codon misannotation. At least 80% of short-outlier genomes contain mode-length copies of the protein, with ~40% of artifacts from frameshifts/termination codons and another ~40% from initiation codon choice. Missing proteins in core clusters are also explained by frameshifts in genome sequences over 98% of the time, highlighting the importance of proteome quality control for downstream analyses.
Why it matters: Proteome quality directly impacts all downstream computational analyses from functional annotation to comparative genomics. This systematic characterization of artifact sources provides practical guidance for proteome quality filtering and highlights the hidden impact of genome sequencing errors on protein-level analyses.
Why for Yiru: Quality control in large-scale biological data analysis is essential for generating reliable results. The methodological approach of using clustering-based outlier detection to identify artifacts is broadly applicable to other high-throughput biological data types, including single-cell and spatial transcriptomics QC.
Biomedical discoveries
Biomedicine
STN1 Upregulation Promotes PARPi Resistance in BRCA2-Deficient Cancer Cells via Replication Fork Protection and Suppression of ssDNA Gap Formation
bioRxiv Published 2026-05-19 preprint DOI: 10.1101/2026.05.15.725290
PARP inhibitor drug resistance BRCA2 replication fork ssDNA gaps DNA repair CST complex
Summary: Identifies STN1, a component of the CTC1/STN1/TEN1 (CST) complex, as a key modulator of PARP inhibitor (PARPi) resistance in BRCA2-deficient cancers. RNA-seq analysis of PARPi-resistant BRCA2-mutant cancer cells reveals STN1 as consistently upregulated across resistant lines despite largely distinct transcriptomic profiles. STN1 overexpression enhances Olaparib resistance by increasing RAD51 loading to stalled replication forks while restricting MRE11 recruitment, protecting stalled forks from nascent-strand degradation. Crucially, STN1 also rescues the accumulation of ssDNA gaps — a major determinant of PARPi sensitivity in BRCA2-deficient cells — providing a resistance mechanism independent of homologous recombination restoration.
Why it matters: PARPi resistance is a major clinical challenge in BRCA-mutant breast, ovarian, pancreatic, and prostate cancers. STN1 represents a novel resistance mechanism operating through replication fork protection rather than HR restoration, highlighting a new therapeutic vulnerability and a potential biomarker for identifying patients likely to develop PARPi resistance.
Why for Yiru: DNA damage response and replication stress are fundamental to cancer biology and intersect with the TME through genomic instability, immune activation (cGAS-STING), and therapeutic response. Understanding PARPi resistance mechanisms is particularly relevant given the expanding clinical use of PARP inhibitors and their potential combination with immunotherapy.
CDK12 and CDK13 Suppress Distinct Intronic Polyadenylation Sites
bioRxiv Published 2026-05-19 preprint DOI: 10.1101/2026.05.15.725461
CDK12 CDK13 intronic polyadenylation neoantigens transcription cancer genomics ovarian cancer
Summary: Dissects the distinct roles of CDK12 and CDK13 in suppressing early transcriptional termination using a CRISPR-engineered CDK12 C1039S mutation conferring THZ531 resistance. Poly(A) Click-seq across a dose-response curve reveals thousands of intronic polyadenylation (IPA) sites with distinct CDK12- and CDK13-dependent behaviors. Oxford Nanopore long-read sequencing confirms premature termination events and reveals full-length isoform switches that truncate protein domains and produce novel intronically encoded peptide sequences. Integration with mass spectrometry identifies peptides derived from IPA isoforms, confirming that intronic sequences are translationally competent and represent a source of tumor-specific neoantigens in CDK12/13-deficient cancers.
Why it matters: CDK12/13 mutations occur across multiple cancer types and are associated with genomic instability and immune infiltration. The demonstration that IPA-derived peptides are translated and detectable by mass spectrometry provides direct evidence for IPA-derived neoantigens as immunotherapy targets in CDK12/13-mutant cancers, opening a new therapeutic axis for these tumors.
Why for Yiru: CDK12/13-deficient cancers exhibit increased neoantigen burden and enhanced immunotherapy response — linking transcriptional dysregulation directly to TME immunogenicity. The concept of splicing-derived neoantigens expands our understanding of tumour antigen sources beyond traditional non-synonymous mutations, with implications for personalized immunotherapy design.
HDAC Inhibition Sensitizes Pancreatic Tumors to DNA Damage by Global Redistribution of the Transcriptional Machinery
bioRxiv Published 2026-05-19 preprint DOI: 10.1101/2026.05.18.726071
HDAC inhibitor pancreatic cancer DNA damage entinostat nanoparticle BRD4 epigenetics
Summary: Identifies Class I HDACs (HDAC1/2) as critical regulators of the DNA damage response (DDR) in pancreatic ductal adenocarcinoma (PDAC). HDAC1/2 directs H3K27ac distribution to maintain sufficient BRD4 and RNA Polymerase II occupancy at DDR gene promoters. HDAC inhibition by entinostat shifts H3K27 acetylation toward intergenic regions, diverting BRD4 and Pol II from DDR gene promoters and thereby suppressing DDR gene expression. This sensitizes PDAC to diverse DNA-damaging agents. To overcome systemic HDAC inhibitor toxicity, the authors develop bottlebrush prodrug nanoparticles (entinostat-BPD) for tumor-selective delivery, achieving potent efficacy with reduced toxicity in preclinical PDAC models.
Why it matters: Pancreatic cancer remains one of the deadliest malignancies with limited therapeutic options, and DDR-targeting strategies have shown only modest single-agent activity. The identification of an HDAC-dependent DDR vulnerability, combined with a tumor-selective nanoparticle delivery strategy, provides both a mechanistic rationale and a translational path for HDAC inhibitor combination therapy in PDAC.
Why for Yiru: Epigenetic regulation of DNA damage response intersects with TME biology through multiple mechanisms including genomic instability-driven immune activation and therapeutic sensitization. The nanoparticle delivery approach for tumor-selective epigenetic targeting is relevant to reducing systemic toxicity while modulating the TME.
Pharmacological Inhibition of UCH-L1 by LDN57444 Sensitises Hepatocellular Carcinoma to Sorafenib by Reverting Drug-Induced Adaptive Responses
bioRxiv Published 2026-05-19 preprint DOI: 10.1101/2026.05.15.725527
hepatocellular carcinoma sorafenib UCH-L1 drug resistance deubiquitinase MAPK combination therapy
Summary: Demonstrates that the deubiquitinase UCH-L1 is upregulated in hepatocellular carcinoma (HCC) and associated with poor survival. Low-dose sorafenib paradoxically upregulates UCH-L1 in HCC cells while promoting invasiveness and sustaining MEK1/2-ERK1/2 pathway activation. Combining sorafenib with the UCH-L1 inhibitor LDN57444 produces strong synergistic cytotoxicity in vitro, reverts MAPK activation, and suppresses invasion. In an orthotopic xenograft HCC model, low-dose sorafenib plus LDN57444 completely inhibits tumour growth and enhances sorafenib efficacy, presenting UCH-L1 as a key mediator of adaptive drug resistance.
Why it matters: Sorafenib resistance limits its clinical efficacy in advanced HCC, and adaptive responses to kinase inhibitors commonly involve feedback activation of parallel signaling pathways. UCH-L1 represents a druggable node in this adaptive response, and its inhibition may enable lower, better-tolerated sorafenib dosing while maintaining anti-tumour efficacy.
Why for Yiru: Adaptive drug resistance through feedback signaling is a general phenomenon across cancer types with relevance to both targeted therapy and immunotherapy. Understanding how tumour cells dynamically rewire signaling networks under therapeutic pressure connects to TME plasticity and treatment-induced immune evasion.
STRIP2 Stabilizes LCN2 to Suppress Ferroptosis and Drives Colorectal Cancer Malignancy
bioRxiv Published 2026-05-19 preprint DOI: 10.1101/2026.05.16.725308
colorectal cancer ferroptosis STRIP2 LCN2 ubiquitination oxidative stress cell death
Summary: Identifies STRIP2 as overexpressed in colorectal cancer (CRC), driving malignant phenotypes in vitro and in vivo. Mechanistically, STRIP2 stabilizes the IL-17 downstream effector LCN2 by blocking its K48-linked ubiquitination and degradation, enhancing anti-ferroptosis defense in CRC cells. STRIP2 overexpression suppresses ferroptosis while boosting proliferation and reducing oxidative stress; siRNA-mediated STRIP2 knockdown induces the opposite effect. This establishes a STRIP2–LCN2 axis that promotes ferroptosis resistance and CRC progression, linking ferroptosis regulation to CRC malignancy.
Why it matters: Ferroptosis is an iron-dependent form of regulated cell death with emerging relevance to cancer therapy, particularly in treatment-resistant cancers and in the context of immunotherapy where ferroptosis can enhance immunogenic cell death. STRIP2-mediated ferroptosis resistance represents both a mechanism of CRC progression and a potential therapeutic vulnerability.
Why for Yiru: Ferroptosis regulation in the TME is an emerging area — ferroptotic cancer cells can release DAMPs that shape anti-tumour immunity, and T cell-derived IFNγ can induce ferroptosis in tumour cells. Understanding ferroptosis resistance mechanisms in CRC connects to interests in immunogenic cell death and TME modulation.
Basal Gland Localization and Focal Distribution of OLFM4-Expressing Cells in Increasing Severity of Gastric Intestinal Metaplasia
bioRxiv Published 2026-05-20 preprint DOI: 10.1101/2026.05.14.725297
gastric cancer intestinal metaplasia OLFM4 spatial biology stem cells precancerous multiplex IF
Summary: Uses multiplex immunofluorescence and whole-slide image analysis on 100 tissue biopsies annotated for metaplasia severity to evaluate protein-level expression and spatial organization of three markers (ANPEP, CPS1, OLFM4) previously identified by single-cell and spatial transcriptomics as associated with high-risk gastric intestinal metaplasia (GIM). OLFM4 expression is largely restricted to epithelial glands and shows strong association with increased GIM severity. OLFM4-positive cells are present in discrete glandular foci that expand with increasing metaplasia severity, and within individual glands, OLFM4 is highest at the gland base — suggesting a stem cell-like compartment driving GIM progression toward gastric cancer.
Why it matters: Gastric cancer interception requires identifying which precancerous lesions will progress. The spatial organization of OLFM4+ stem-like cells at gland bases provides a candidate protein-level biomarker for high-risk GIM, connecting spatial molecular features to clinically actionable risk stratification.
Why for Yiru: Spatial organization of stem-like compartments driving disease progression has conceptual parallels to cancer stem cell niches in the TME. The approach of combining single-cell transcriptomic discovery with spatial protein validation is directly relevant to TME biomarker studies.
Cross-disciplinary watchlist
Other Fields
Mitochondrial l-2-Hydroxyglutarate Is a Physiological Signalling Metabolite
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10564-x
metabolism oncometabolite mitochondria 2-hydroxyglutarate signalling physiology
Summary: Reveals that l-2-hydroxyglutarate (l-2HG), previously known primarily as an oncometabolite produced by mutant isocitrate dehydrogenase in cancers, is also a physiological signalling metabolite produced in mitochondria under normal conditions. The study characterizes the mitochondrial production, regulation, and signalling functions of l-2HG in non-cancer contexts, demonstrating that this metabolite plays homeostatic roles in cellular signalling beyond its pathological accumulation in IDH-mutant tumours. This redefines l-2HG as a bona fide physiological metabolite with context-dependent functions rather than solely a disease-associated molecule.
Why it matters: The reclassification of l-2HG from an exclusively pathological oncometabolite to a physiological signalling molecule fundamentally changes our understanding of its biology. This has implications for interpreting IDH inhibitor effects in cancer patients and for understanding how normal metabolic signalling is co-opted in malignancy.
Why for Yiru: Oncometabolites like 2HG shape the TME through effects on immune cell function, including T cell and macrophage activity. Understanding the physiological functions of 2HG provides context for its pathological roles in IDH-mutant cancers and its potential contribution to TME immunosuppression.
Dopamine Drives Persistent Remodelling of the Maternal Brain
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10509-4
neuroscience dopamine maternal brain plasticity hippocampus transcriptomics epigenetics
Summary: Uses brain-wide transcriptomic profiling to define the molecular landscape of neuroplasticity induced by reproductive experience, identifying the dorsal hippocampal formation as a key site of persistent maternal brain remodelling. Reveals that dopamine signaling is a critical driver of long-lasting transcriptional and epigenetic changes in the maternal hippocampus, mediating enduring adaptations in learning, memory, and behavior that persist long after pregnancy. The study establishes a molecular framework for understanding how reproductive experience produces lifelong neural changes.
Why it matters: Pregnancy induces some of the most dramatic and persistent physiological changes in adult mammals, yet the molecular mechanisms underlying lifelong maternal brain adaptations have remained poorly understood. This study identifies dopamine as a key mediator, connecting reproductive biology to fundamental mechanisms of long-term neural plasticity.
Why for Yiru: The concept of persistent, experience-driven molecular remodelling of tissues connects to how chronic disease states and therapeutic interventions produce lasting changes in the TME. Dopamine signaling is also relevant to cancer biology, as dopaminergic pathways can influence tumour growth and immune function.
Astrocyte Glucocorticoid Receptor Signalling Restricts Neuronal Plasticity
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10512-9
neuroscience astrocytes glucocorticoid critical period plasticity single-cell chromatin
Summary: Examines the experience-dependent maturation of the mouse primary visual cortex using paired single-cell transcriptomic and chromatin accessibility sequencing, revealing that astrocyte glucocorticoid receptor (GR) signaling is a key mechanism that restricts neuronal plasticity as animals mature. GR activation in astrocytes during the closure of critical periods orchestrates transcriptional programs that stabilize mature neural circuits, limiting the capacity for experience-dependent rewiring. This identifies astrocytes — not just neurons — as active regulators of developmental plasticity closure through stress hormone signaling.
Why it matters: Critical periods of developmental plasticity are fundamental to brain wiring, and understanding how plasticity is restricted as animals mature could enable strategies to reopen plasticity windows for treating neurological and psychiatric conditions. The finding that astrocyte GR signaling controls plasticity closure shifts the focus from neuron-intrinsic to glial-mediated mechanisms.
Why for Yiru: The concept of plasticity windows being actively closed by microenvironmental signals has parallels in the TME, where tissue-resident stromal cells (akin to astrocytes in the brain) can restrict or permit immune cell plasticity and function. Glucocorticoid signaling is also a potent modulator of immune responses relevant to TME biology.
Neural Representation of Action Symbols in Primate Frontal Cortex
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10297-x
neuroscience primate frontal cortex symbolic representation motor control cognitive neuroscience
Summary: Investigates how the primate frontal cortex represents action symbols — discrete units that can be recombined into composite actions — during goal-directed problem solving. Using neural recordings in monkeys performing novel behavioral tasks, the study reveals that frontal cortical neurons encode abstract action symbols that can be flexibly combined to generate diverse behaviors, supporting the hypothesis that symbolic representations underlie cognitive flexibility and creative problem-solving. Identifies specific neural populations and coding schemes that enable compositional action generation.
Why it matters: The ability to flexibly combine learned actions to solve novel problems is a hallmark of intelligent behavior. Understanding how the brain represents and manipulates action symbols at the neural level addresses fundamental questions about the neural basis of cognition and could inform the design of more flexible AI systems.
Why for Yiru: The concept of compositional representations — where complex behaviors are built from reusable primitives — has conceptual parallels in systems biology, where complex cellular phenotypes arise from combinations of simpler regulatory and signaling modules. This abstract principle connects neuroscience to the modular organization of biological systems.
Design of One-Component Quasisymmetric Protein Nanocages
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10554-z
protein design nanocages de novo design computational biology synthetic biology self-assembly
Summary: Reports the computational design of one-component quasisymmetric protein nanocages — hollow protein nanostructures that self-assemble from a single protein building block yet achieve near-icosahedral symmetry through quasi-equivalent interactions. Published alongside the two-component cage design in the same Nature issue, this complementary approach simplifies nanocage construction by requiring only a single designed subunit while maintaining the structural complexity of multi-component assemblies, representing a milestone in the programmable design of self-assembling protein nanomaterials.
Why it matters: One-component nanocages are simpler to produce and more scalable than multi-component assemblies, making them more tractable for therapeutic and industrial applications. The ability to computationally design single-component protein cages with defined sizes, shapes, and interior volumes dramatically expands the nanomaterial design toolkit.
Why for Yiru: Protein nanocages have potential applications in targeted drug delivery to the TME, vaccine design, and biosensing. Understanding the design principles enabling single-component assembly of complex symmetric structures advances the frontier of what is programmable in protein-based therapeutics.
A Pathogen lncRNA Secreted into Rice Sequesters a Host miRNA for Virulence
Nature Published 2026-05-20 research article DOI: 10.1038/s41586-026-10572-x
plant biology lncRNA miRNA host-pathogen RNA biology virulence
Summary: Discovers that a long non-coding RNA (lncRNA) from a rice pathogen is secreted into host plant cells, where it sequesters a host miRNA to promote virulence. This cross-kingdom RNA-based virulence strategy reveals a novel mechanism of host manipulation through direct RNA-RNA interactions between pathogen and host molecules, expanding the known repertoire of pathogen effector strategies beyond protein-based mechanisms to include regulatory RNA molecules.
Why it matters: Cross-kingdom RNA interactions represent an emerging frontier in host-pathogen biology with potential parallels in microbiome-host communication, intercellular RNA trafficking in cancer, and RNA-based therapeutic strategies. The discovery of a pathogen lncRNA that directly sequesters a host miRNA establishes a new paradigm for molecular host manipulation.
Why for Yiru: RNA-based intercellular communication is increasingly recognized in the TME, where tumor-derived exosomal RNAs can reprogram immune and stromal cells. Understanding cross-kingdom lncRNA–miRNA interactions in plant pathology may reveal generalizable principles of RNA-mediated intercellular signaling relevant to TME biology.