Biology subjects

Hu, Y.

Publications and source records attributed to Hu, Y..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

In-situ glial cell-surface proteomics identifies pro-longevity factors in Drosophila

Much focus has shifted towards understanding how glial dysfunction contributes to age-related neurodegeneration due to the critical roles glial cells play in maintaining healthy brain function. Cell-cell interactions, which are largely mediated by cell-surface proteins, control many critical aspects of development and physiology; as such, dysregulation of glial cell-surface proteins in particular is hypothesized to play an important role in age-related neurodegeneration. However, it remains technically difficult to profile glial cell-surface proteins in intact brains. Here, we applied a cell-surface proteomic profiling method to glial cells from intact brains in Drosophila, which enabled us to fully profile cell-surface proteomes in-situ, preserving native cell-cell interactions that would otherwise be omitted using traditional proteomics methods. Applying this platform to young and old flies, we investigated how glial cell-surface proteomes change during aging. We identified candidate genes predicted to be involved in brain aging, including several associated with neural development and synapse wiring molecules not previously thought to be particularly active in glia. Through a functional genetic screen, we identified one surface protein, DIP-{beta}, which is down-regulated in old flies and can increase fly lifespan when overexpressed in adult glial cells. We further performed whole-head single-nucleus RNA-seq and revealed that DIP-{beta} overexpression mainly impacts glial and fat cells. We also found that glial DIP-{beta} overexpression was associated with improved cell-cell communication, which may contribute to the observed lifespan extension. Our study is the first to apply in-situ cell-surface proteomics to glial cells in Drosophila, and to identify DIP-{beta} as a potential glial regulator of brain aging.

neuroscience↗

bioRxiv2025

OT-RMSD: A Generalization of the Root-Mean-Square Deviation for Aligning Unequal-Length Protein Structures

The Root-Mean-Square Deviation (RMSD) metric, coupled with the Kabsch algorithm for optimal superposition, represents a cornerstone of quantitative structural biology. However, its application is fundamentally limited to the comparison of structures with a pre-defined, one-to-one correspondence of equal length, precluding its direct use for the vast majority of biologically relevant comparisons involving proteins of different lengths or unknown equivalences. To overcome this limitation, we introduce OT-RMSD, a novel, parameter-light method that generalizes the RMSD for comparing unequal-length protein structures without a pre-defined alignment. Our approach recasts the correspondence problem as an Optimal Transport (OT) task, utilizing a fundamental, distance-based cost function to identify the most economical mapping between two protein structures. This transport plan is then used as a soft-weighting scheme within an iterative Sinkhorn-Kabsch framework to simultaneously solve for correspondence and optimal superposition. We test our method on a benchmark dataset of 40 challenging protein pairs and demonstrate its superiority over both the widely-used PyMOL align command and a more complex, heuristic-driven variant of our own framework. On average, OT-RMSD identifies larger and more accurate alignment cores, achieving a significantly lower RMSD. We conclude that OT-RMSD provides a mathematically principled, robust, and effective extension of the classic RMSD concept, offering a powerful tool for modern structural analysis.

bioinformatics↗

bioRxiv2025

Neurotype matching in monogamous rodents is modulated by early-life sleep experience

Studies of human sociability indicate stronger social affinity in matched-neurotype dyads (e.g., two individuals with autism or two without) compared to mixed-neurotype dyads (e.g., one individual with autism paired with one without). Is this neurotype matching phenomenon also quantifiable in non-human animals? Using deep learning tools, we analyzed dyadic male-female interactions in prairie voles, a highly social rodent species. To simulate "neurotypes", voles were exposed to either control conditions or early-life sleep disruption (ELSD) during a critical neurodevelopmental period (postnatal days 14-21), recapitulating two features of human autism: developmental sleep disruption and later-life atypical sociability. Analogous to human studies, voles showed signs of reduced social affinity in mixed dyads compared to matched dyads, including sex-specific changes in aggression and body orientation toward the conspecific. These findings advance our understanding of social affinity, providing a framework for new studies in both animal models and humans.

animal behavior and cognition↗

bioRxiv2025

Dual effects of nicotinamide on aging-related arrhythmia: protective at low dose, proarrhythmic at high doses

BackgroundCardiac arrhythmia and dysfunction progressively increase with age, both of which are closely associated with a decline in NAD+. Supplementation with nicotinamide (NAM), a critical NAD+ precursor, has shown protection in experimental models of aging-related cardiac diseases, including atrial fibrillation (AF) and heart failure, especially heart failure with preserved ejection fraction. With the potential rise of NAM in treatment of various cardiometabolic diseases, its dose-dependent cardiac-specific adverse effects and underlying mechanisms warrant investigation. MethodsThe effects of NAM on aging-related arrhythmia and cardiac dysfunction were assessed using ex vivo Langendorff mouse hearts and adult Drosophila heart preparations. Different doses of NAM (10-100 mM) were tested for their impact on the contractility of HL-1 cardiomyocytes, lifespan and cardiac function of Drosophila, as well as arrhythmia susceptibility of ex vivo mouse hearts. Acetylation of sarcoplasmic/endoplasmic reticulum Ca{superscript 2} ATPase 2a (SERCA2a) was measured by immunoprecipitation followed by Western blotting. ResultsAcute perfusion with 10 mM NAM had limited influence on aging-related AF susceptibility in ex vivo mouse hearts. Short-term dietary intervention with 10 mM NAM in late-life protected against aging-induced cardiac arrhythmia and contractile dysfunction exclusively in male Drosophila. In contrast, life-long exposure or NAM concentrations above 20 mM led to dose-dependent adverse cardiac effects, including impaired contractility in HL-1 cardiomyocyte and shortened lifespan in Drosophila, with increased arrhythmia observed in both models. In ex vivo mouse hearts, 100 mM NAM increased SERCA2a acetylation, suggesting inhibition of sirtuin1 and impaired calcium handling, which likely underlies the observed effects of high-dose NAM on arrhythmia and cardiac dysfunction. ConclusionsNAM exhibits a narrow therapeutic window in aging-related cardiac dysfunction and arrhythmia, with its efficacy highly dependent on dose, duration, and biological context. While a moderate dose in late-life may be protective, chronic or excessive intake of NAM can induce arrythmia and impair cardiac function, likely through disruption of the SERCA2a activity. These findings underscore the importance of cautious and context-specific application of NAM in clinical settings.

physiology↗

bioRxiv2025

OTMalign: A Fast and Robust TM-score-driven Protein Structure Alignment Algorithm using Optimal Transport

Protein structure alignment is a fundamental task in computational biology. While the TM-score is a gold standard for evaluating structural similarity, its direct optimization is challenging. Many algorithms, therefore, rely on heuristic or combinatorial approaches. In this work, we present OTMalign, a novel algorithm that iteratively optimizes the TM-score in a fast and robust manner. OTMalign leverages the theory of Optimal Transport (OT) to establish a soft correspondence between protein structures, guided by a TM-score-inspired reward matrix. This avoids the pitfalls of combinatorial searches and provides a global perspective at each iteration. The optimal rigid body transformation is then determined analytically using a weighted Kabsch algorithm, where the weights are derived from the OT correspondence matrix (the P matrix). We demonstrate that this P matrix effectively captures the structural similarity, and its use in a weighted covariance matrix allows for a direct SVD-based solution for the rotation and translation. We evaluated OTMalign on the RPIC benchmark dataset, demonstrating its rapid convergence and ability to produce high-quality alignments. OTMalign offers a practical and theoretically sound framework for TM-score optimization, distinguished by its speed and iterative nature.

bioinformatics↗

bioRxiv2025

GUANACO: A Unified Web-Based Platform for Single-Cell Multi-Omics Data Visualization

While single-cell multi-omics has advanced our understanding of cellular heterogeneity, the complexity of these datasets remains a barrier for non-computational users. Here, we introduce GUANACO, a Dash-based Python package for interactive, code-free visualization of single-cell RNA-seq and ATAC-seq data. GUANACO integrates matrix- and genome-track views, supporting flexible cell/gene selection, statistical testing, and transcription factor binding site exploration. Its user-friendly interface offers colorblind-friendly palettes, intuitive controls, and options for generating publication-ready figures. With a low memory requirement and cost-effective deployment, GUANACO facilitates seamless sharing and reproducible research, empowering researchers to explore, interpret, and communicate single-cell insights without extra coding.

bioinformatics↗

bioRxiv2025

LieOTMap-FFT: A Differentiable Fitting Framework Combining Lie Algebra and FFT-accelerated Optimal Transport for Cryo-EM Maps

Interpreting cryo-electron microscopy (cryo-EM) density maps often requires the accurate placement of atomic models, a challenging high-dimensional fitting problem. We introduce LieOTMap-FFT, a novel, fully differentiable framework for rigid body map-to-map alignment. Our framework synergistically combines four key mathematical and computational techniques. First, we parameterize the SE(3) rigid body transformation using Lie algebra, ensuring a continuous and singularity-free optimization landscape suitable for gradient descent. Second, we treat the mobile and target density maps as probability distributions on a 3D grid and measure their similarity using an Optimal Transport (OT) score based on the Sinkhorn algorithm. Third, to make this computationally feasible for large maps, we leverage the Fast Fourier Transform (FFT) to accelerate the core convolution operations within the Sinkhorn iterations from O(N 2) to O(N log N). Finally, a TM-align-inspired similarity kernel provides a robust score landscape for global search. We demonstrate the power of LieOTMap-FFT by fitting a large ribosomal subunit (PDB: 1AON) into a cryo-EM map (EMD-1046), refining a random initial placement to a final RMSD of 4.81 [A]. This result showcases the frameworks ability to achieve high-accuracy global convergence by effectively integrating these four core technologies.

bioinformatics↗

bioRxiv2025

LieOTMap: A Differentiable Approach to Cryo-EM Fitting via Lie-Theoretic Optimal Transport

MotivationThe integration of high-resolution atomic models with lower-resolution cryo-electron microscopy (cryo-EM) maps is a fundamental task in structural biology. However, this rigid-body fitting problem is challenged by complex scoring landscapes and the non-differentiable nature of standard structural similarity metrics like TM-score, precluding their direct use in modern gradient-based optimization pipelines. MethodWe present LieOTMap, a novel, fully differentiable framework for cryo-EM fitting. Our approach introduces two key innovations. First, we parameterize rigid-body transformations on the Lie algebra se(3), which provides a minimal, singularity-free representation of the motion. Second, we formulate a loss function based on the Sinkhorn divergence, a differentiable proxy for the Optimal Transport (Wasserstein) distance. This loss function serves as a robust, geometrically meaningful surrogate for non-differentiable scores, allowing us to leverage powerful gradient descent optimizers to navigate the search space. ResultsWe demonstrate the effectiveness of LieOTMap by fitting the apo-state structure of E. coli GroEL (PDB: 1aon) into the ATP-bound state cryo-EM map (EMD-1046). Our method successfully navigates a large-scale conformational change, achieving a highly accurate final RMSD of 3.08 [A] with respect to the ground-truth structure (PDB: 1GRU). This result showcases the power of combining Lie-theoretic representations with differentiable geometric loss functions for complex structural alignment tasks. AvailabilityThe source code is available at https://github.com/YueHuLab/LieOTMap.

bioinformatics↗

bioRxiv2025

LieMap: A Fast and Transparent Gradient-Based Method for Cryo-EM Structure Fitting

Fitting high-resolution atomic models into lower-resolution cryo-electron microscopy (cryo-EM) maps is a critical yet challenging step in structural biology. We present LieMap, a straightforward, fast, and transparent gradient-based fitting protocol designed for practical applications. Our method parameterizes rigid-body motion on the Lie algebra se(3) to provide a minimal and singularity-free representation. The optimization objective is to directly maximize a real-space cross-correlation score, calculated as the mean density value sampled from the map at the atomic coordinates. This score is computed differentiably using trilinear interpolation and optimized with the Adam optimizer in a multi-stage fashion. We demonstrate the effectiveness of LieMap by fitting the apo-state structure of E. coli GroEL (PDB: 1aon) into its ATP-bound state cryo-EM map (EMD-1046). The protocol successfully navigates the large conformational change, achieving a final RMSD of 3.23 [A]. LieMaps simplicity, computational efficiency, and transparent optimization process make it a valuable and practical tool for structural biologists.

bioinformatics↗

bioRxiv2025

Siglec-F Protects Against Elastase-induced Lung Inflammation and Emphysema in Mice

Respiratory surfaces are exposed daily to billions of inhaled particles that could cause injury to alveolar tissues where gas exchange occurs. Accordingly, robust defense is essential but must involve minimal physiologic disruption. Airspace macrophages (AMs) protect lung surfaces while also maintaining tissue integrity through non-inflammatory homeostatic responses in health. However, in chronic obstructive pulmonary disease (COPD), AMs contribute to emphysematous alveolar destruction through mechanisms that are poorly understood. We hypothesized that damaging effects of AMs in emphysema result from loss of mechanisms that normally restrain homeostatic AMs. We found that Siglec-F, a common marker of AMs, exerts suppressive effects on tissue resident AMs (RAMs), thereby supporting alveolar integrity in mouse lungs during health and in a model of elastase-induced alveolar destruction. Siglec-F-deficient mice exhibited decreased alveolar numbers at baseline, and they had worsened alveolar damage after elastase challenge that was unexpectedly RAM-mediated. Transcriptomic profiling revealed dysregulation of key pathways involved in tissue remodeling and repair, including extracellular matrix degradation, TGF-{beta} signaling, and phagocytosis. These findings uncover previously unrecognized roles for RAMs and Siglec-F in preserving alveolar integrity. Our findings implicate RAMs and Siglecs as potential therapeutic targets for preserving alveolar integrity in health and for limiting alveolar damage in COPD.

immunology↗

bioRxiv2025

Targeting p16INK4a reverses alveolar epithelial cell dysfunction and induces lung regeneration in emphysema

Pulmonary emphysema involves impaired regenerative capacity of alveolar type 2 epithelial cells (AT2), the main progenitor cells in alveoli. However, the mechanisms underlying dysfunctional epithelial repair remain unclear. In a mouse model of elastase-induced emphysema, we observed an accumulation of activated AT2s in the lung, associated with an overexpression of p16INK4a (p16), a cell cycle inhibitor known to influence stem cell fate. Deletion of p16 promoted the transition of AT2 into alveolar type 1 (AT1) cells, resulting in tissue regeneration in both mice and alveolar organoids. Pharmacological targeting of the p16 pathway using senolytic agents recapitulate this regenerative effect, further supporting the role of p16 as a key brake on epithelial plasticity. These findings demonstrate that alveolar epithelial cell dysfunction can be reversed by p16 deletion or by eliminating p16+ cells, thereby reactivating the AT2-to-AT1 transition and promoting endogenous alveolar regeneration. This work identifies the p16 pathway as a promising therapeutic target for restoring damaged alveoli in emphysema.

cell biology↗

bioRxiv2025

LieOTDock: A Protein Docking Framework via Lie Group Optimization and Optimal Transport

Protein-protein interactions (PPIs) are fundamental to cellular function, and structurally characterizing them is a key goal in molecular biology. Computational docking, a crucial tool for predicting the structure of protein complexes, faces significant challenges in search efficiency and scoring accuracy. Here, we introduce LieOTDock, a novel framework that leverages the mathematics of Lie groups and Optimal Transport (OT) for highly efficient protein docking pose generation. The core of our method is a data-driven surface sampling technique that identifies salient geometric features for initial pairing. These initial poses are then refined via a gradient-based optimization directly on the Lie group SE(3), the natural space of rigid-body motions. This optimization is guided by a differentiable score based on Sinkhorn-regularized Optimal Transport, which measures the geometric complementarity of surface patches. We tested LieOTDock on the 1AVW benchmark, where it successfully generated a near-native pose of 3.43 [A] RMSD from a 5000-candidate run in under three minutes on a consumer-grade Apple M4 Mini. Our results demonstrate that LieOTDock, by its principled use of Lie theory and OT, provides a powerful and efficient framework for generating high-quality candidate structures. This work decouples the challenge of geometric sampling from final scoring, offering a robust and modular approach to the protein docking problem, though future work is needed to integrate more physically realistic scoring functions for improved candidate ranking.

bioinformatics↗

bioRxiv2025

Automated analysis of C. elegans behavior by LabGym: an open-source, AI-powered platform

The genetic tractability, well-mapped circuitry, and diverse behavioral repertoire of the nematode C. elegans make it an ideal model for physiological and behavioral studies. A wide range of methods has been developed for analyzing C. elegans behaviors, evolving with advances in technology such as videography and computer-assisted analysis. Here, we introduce LabGym--an open-source, artificial intelligence (AI)-based platform we recently developed--to the C. elegans research community. We trained deep learning models in LabGym capable of automatically categorizing and quantifying multiple user-defined parameters of worm locomotion behavior in multi-worm videos with high accuracy. Furthermore, we demonstrated their efficacy in quantifying locomotion changes in aging worms. Our work offers a cost-effective, user-accessible approach to behavioral analysis in C. elegans.

animal behavior and cognition↗

bioRxiv2025

Reprogramming Factors Activate a Non-Canonical Oxidative Resilience Pathway That Can Rejuvenate RPEs and Restore Vision

Oct4, Sox2, and Klf4 (OSK) Yamanaka factors induce pluripotency and reverse age-related epigenetic changes, yet the mechanisms by which they promote rejuvenation remain poorly explored. Oxidative stress contributes to CNS aging and retinal pigmented epithelium (RPE) degeneration in age-related macular degeneration. We find that OSK expression in RPE restores retinal structure and visual function in aged mice and promotes oxidative resilience through a non-canonical, Tet2-independent pathway. Integrative functional genomics identifies GSTA4, a detoxifying enzyme that clears the lipid peroxidation byproduct 4-HNE, as a necessary and sufficient OSK effector. Dynamic GSTA4 regulation by OSK recapitulates a stem cell derived stress resilience program. GSTA4 overexpression alone enhances mitochondrial resilience, rejuvenates the aged RPE transcriptome, and reverses visual decline. GSTA4 is consistently upregulated across diverse lifespan-extending interventions suggesting a broader pro-longevity role. These findings uncover a previously unrecognized protective axis driven by Yamanaka factors that circumvents reprogramming, providing therapeutic insights for age-related diseases. HIGHLIGHTSO_LIOSK-GSTA4 provides a dynamic, Tet2-independent stress-resilience axis. C_LIO_LIFunctional genomics pinpoints GSTA4 as a direct downstream effector activated by OSK. C_LIO_LIRPE aging involves progressive accumulation of 4-HNE that can be detoxified by GSTA4. C_LIO_LIEnhancing GSTA4 rejuvenates RPE cells, restores vision and is associated with lifespan-extending interventions. C_LI

genetics↗

bioRxiv2025

Evolutionary innovation within conserved gene regulatory networks underlying biomineralized skeletons in Bilateria

Biomineralized skeletons have evolved convergently across animals, yet exhibit remarkable diversity in structure and development. However, the evolutionary origins of gene regulatory networks underlying biomineralized skeletons remains elusive. Here, we report comprehensive developmental profiling of transcriptomic and chromatin dynamics in a bivalve mollusc, Crassostrea nippona. We provide evidence for a biphasic regulatory program orchestrating larval and adult shell formation, involving the coordinated activity of ancient transcription factors and dynamic chromatin remodeling. Comparative analyses suggest a conserved developmental toolkit was co-opted for larval exoskeleton formation in the common lophotrochozoan ancestor. In contrast, limited regulatory conservation was observed between lophotrochozoans and echinoderms with regards to the formation of biomineralized skeletons, despite both relying on a heterochronic activation of ancestral regulators. Together, our findings support a hierarchical model where dynamic chromatin decouples rapidly evolving effectors from deeply conserved regulators, allowing modular innovations within conserved gene regulatory networks. This study highlights how epigenetic dynamics bridge evolutionary conservation and novelty, offering a framework for understanding the independent evolution of biomineralization across Bilateria through combinatorial regulatory evolution.

evolutionary biology↗

bioRxiv2025

Contrasting genomic trajectories of Bartonellaceae symbionts of planthoppers

Symbioses with microorganisms have shaped the nutritional biology and evolution of many insects. For example, several ant clades have adapted to nutrient-poor diets through symbiosis with a specific clade of bacteria in the family Bartonellaceae (Hyphomicrobiales), notorious for also including virulent vertebrate pathogens. Here we show that Bartonellaceae phylogenetically placed within the clade that has only encompassed ant symbionts to date - Candidatus genus Tokpelaia - have established as symbionts in four different clades of planthoppers (Insecta: Hemiptera: Fulgoromorpha). Genome size and contents indicate different levels of integration of these strains into the planthopper host biology and their diverse roles. Symbionts infecting one of the clades have some of the largest genomes among Bartonellaceae, at ca. 2 Mb, two others are under 700 kb, and the fourth is reduced to barely 158 kb. The planthopper-associated Tokpelaia strains with larger genomes, similarly to ant symbionts, encode multiple amino acid and vitamin biosynthesis genes, complementing the degraded nutritional capabilities of their hosts ancient heritable endosymbionts. Strikingly, the smallest Tokpelaia genome lacks any genes linked to essential amino acid biosynthesis, in contrast to all other known insect-associated bacteria with genomes of comparable size. We identified a single vitamin biosynthesis gene and iron-sulfur cluster assembly genes as its only putative contributions to the host biology. Our results broaden the host spectrum of non-pathogenic Bartonellaceae, indicating that they have contributed to nutrition and symbiotic consortium function in diverse diet-restricted host clades. They also highlight an unexpectedly broad range of evolutionary outcomes for this important bacterial group. SignificanceMany insects rely on bacterial partners to overcome nutrient-poor diets, yet the diversity and evolutionary trajectories and outcomes for these associations remain unclear. Our discovery of Bartonellaceae bacteria in planthoppers improves the understanding of the host range of these broadly relevant bacteria best-known as vertebrate pathogens. The finding that these planthopper symbionts generally have the capacity to produce essential amino acids and vitamins relevant to hosts and likely form long-term symbiotic associations agree with the expectations for sap-sucking hemipteran symbionts. However, the breadth of sizes and functions of the newly assembled genomes substantially expand the known range of states for Bartonellaceae, and their evolutionary trajectories. In particular, the identification of a strain with an ultra-reduced genome of only 158kb with no amino acid biosynthetic functions contrasts with all other known insect-symbiotic bacteria with genomes in a similar size range. This study also indicates how symbionts may enable the degeneration, functional loss, and evolution of other bacteria residing in the same host.

ecology↗

bioRxiv2025

LieOTAlign: A Differentiable Protein Structure Alignment Framework Combining Optimal Transport and Lie Algebra

The comparison of protein structures is fundamental to understanding biological function and evolutionary relationships. Existing methods, while powerful, often rely on heuristic search algorithms and non-differentiable scoring functions, which limits their direct integration into end-to-end deep learning pipelines. This paper introduces LieOTAlign1, a novel and fully differentiable protein structure alignment framework built on the mathematical principles of Lie algebra and Optimal Transport (OT). LieOTAlign represents rigid body transformations within the Lie algebra of SE(3), which intrinsically preserves the geometric validity of rotations and translations during optimization. We formulate the alignment task as an optimal transport problem, seeking the most efficient mapping between two protein structures. This approach leads to a differentiable version of the TM-score, the Sinkhorn score, which is derived from the entropically regularized OT solution computed via the Sinkhorn algorithm. The entire LieOTAlign pipeline is differentiable, enabling the use of gradient-based optimizers like AdamW to maximize structural similarity. Benchmarking against the official TM-align on the RPIC dataset shows that LieOTAlign can identify longer, topologically significant alignments, achieving higher TM-scores. While the current RMSD is higher, LieOTAlign provides a powerful and flexible framework for protein structure alignment, paving the way for its integration into next-generation deep learning models for diverse bioinformatics challenges.

bioinformatics↗

bioRxiv2025

Screening of Cellular Senescence Related Genes as Biomarkers and Therapeutic Targets for Glioblastoma by Integrated Machine Learning

Glioblastoma (GBM) is an aggressive brain tumor with limited prognostic biomarkers and therapeutic targets. This study applied an integrated machine learning (IML) framework to discover cellular senescence (CS)-related gene biomarkers and candidate therapeutic targets in GBM. Using Gene Expression Omnibus (GEO) training and validation cohorts, 113 machine learning models across 11 algorithms were integrated to pinpoint CS-associated gene signatures. Differential expression analysis combined with overlap of a CellAge senescence gene set yielded 129 CS-related differentially expressed genes (DEGs). Functional enrichment of these DEGs highlighted pathways related to cellular senescence and cell cycle regulation (Gene Ontology and KEGG). A multivariate classifier constructed via stepwise generalized linear modeling (GLM) and LASSO achieved high diagnostic performance (area under the ROC curve 0.92 in training, each independent validation set is over 0.85). Seven top-ranked genes from this model were validated, with TGF{beta}I emerging as the most robust biomarker (AUC > 0.85) and its elevated expression was associated with significantly shorter overall survival. Spatial transcriptomics and single-cell RNA sequencing localized TGF{beta}I expression to tumor cell clusters harboring high copy number variation (CNV) burdens. Immune microenvironment profiling linked TGF{beta}I expression with increased macrophage infiltration. Finally, single-cell gene set enrichment (scGSEA) and AUCell analyses indicated enrichment of ECM-receptor interaction signaling in TGF{beta}I-expressing cells. In summary, IML combined with spatial and single-cell transcriptomics identified TGF{beta}I as a potent CS-related biomarker and a promising therapeutic target in GBM.

cancer biology↗