Objective: Hypoxia is a significant feature of solid tumors, including pancreatic ductal adenocarcinoma(PDAC). It is associated with tumor invasion, metastasis, and drug resistance. However, the spatial distribution o...Objective: Hypoxia is a significant feature of solid tumors, including pancreatic ductal adenocarcinoma(PDAC). It is associated with tumor invasion, metastasis, and drug resistance. However, the spatial distribution of hypoxia-related heterogeneity in PDAC remains unclear.Methods: Spatial transcriptomics(STs), a new technique, was used to investigate the ST features of engrafted human PDAC in the ischemic hind limbs of nude mice. Transcriptomes from ST spots in the hypoxic tumor and the control were clustered using differentially-expressed genes. These data were compared to determine the spatial organization of hypoxia-induced heterogeneity in PDAC. Clinical relevance was validated using the Tumor Cancer Genome Atlas and KM-plotter databases. The CMAP website was used to identify molecules that may serve as therapeutic targets for PDAC.Results: ST showed that the tumor cell subgroups decreased to 7 subgroups in the hypoxia group, compared to 9 subgroups in the control group. Different subgroups showed positional characteristics and different gene signatures. Subgroup 6 located at the invasive front showed a higher proliferative ability under hypoxia. Subgroup 6 had active functions including cell proliferation, invasion, and response to stress. Expressions of hypoxia-related genes, LDHA, TPI1, and ENO1, induced changes. CMAP analysis indicated that ADZ-6482, a PI3 K inhibitor, was targeted by the invasive subgroup in hypoxic tumors.Conclusions: This study is the first to describe hypoxic microenvironment-induced spatial transcriptome changes in PDAC, and to identify potential treatment targets for PDAC. These data will provide the basis for further investigations of the prognoses and treatments of hypoxic tumors.展开更多
Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other...Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.展开更多
The secondary vascular tissue emanating from meristems is central to understanding how vascular plants such as forest trees evolve,grow,and regulate secondary radial growth.However,the overall molecular characterizati...The secondary vascular tissue emanating from meristems is central to understanding how vascular plants such as forest trees evolve,grow,and regulate secondary radial growth.However,the overall molecular characterization of meristem origins and developmental trajectories from primary to secondary vascular tissues in woody tree stems is technically challenging.In this study,we combined high-resolution anatomic analysis with a spatial transcriptome(ST)technique to define features of meristematic cells in a developmental gradient from primary to secondary vascular tissues in poplar stems.The tissue-specific gene expression of meristems and derived vascular tissue types were accordingly mapped to specific anatomical domains.Pseudotime analyses were used to track the origins and changes of meristems throughout the development from primary to secondary vascular tissues.Surprisingly,two types of meristematic-like cell pools within secondary vascular tissues were inferred based on high-resolution microscopy combined with ST,and the results were confirmed by in situ hybridization of,transgenic trees,and single-cell sequencing.The rectangle shape procambium-like(PCL)cells develop from procambium meristematic cells and are located within the phloem domain to produce phloem cells,whereas fusiform shape cambium zone(CZ)meristematic cells develop from fusiform metacambium meristematic cells and are located inside the CZ to produce xylem cells.The gene expression atlas and transcriptional networks spanning the primary transition to secondary vascular tissues generated in this work provide new resources for studying the regulation of meristem activities and the evolution of vascular plants.A web server(https://pgx.zju.edu.cn/stRNAPal/)was also established to facilitate the use of ST RNA-seq data.展开更多
Primary and secondary growth of the tree stem are responsible for corresponding increases in trunk height and diameter.However,our molecular understanding of the biological processes that underlie these two types of g...Primary and secondary growth of the tree stem are responsible for corresponding increases in trunk height and diameter.However,our molecular understanding of the biological processes that underlie these two types of growth is incomplete.In this study,we used single-cell RNA sequencing and spatial transcriptome sequencing to reveal the transcriptional landscapes of primary and secondary growth tissues in the Populus stem.Comparison between the cell atlas and differentiation trajectory of primary and secondary growth revealed different regulatory networks involved in cell differentiation from cambium to xylem precursors and phloem precursors.These regulatory networks may be controlled by auxin accumulation and distribution.Analysis of cell differentiation trajectories suggested that vessel and fiber development followed a sequential pattern of progressive transcriptional regulation.This research provides new insights into the processes of cell identity and differentiation that occur throughout primary and secondary growth of tree stems,increasing our understanding of the cellular differentiation dynamics that occur during stemgrowth in trees.展开更多
BACKGROUND Hemorrhoids,a prevalent chronic condition globally,significantly impact patients'quality of life.While various surgical interventions,such as external stripping and internal ligation,procedure for prola...BACKGROUND Hemorrhoids,a prevalent chronic condition globally,significantly impact patients'quality of life.While various surgical interventions,such as external stripping and internal ligation,procedure for prolapse and hemorrhoids,and tissue selecting technique,are employed for treatment,they are often associated with postoperative complications,including unsatisfactory defecation,bleeding,and anal stenosis.In contrast,Xiaozhiling injection,a traditional Chinese medicine-based therapy,has emerged as a minimally invasive and effective alternative for internal hemorrhoids.This treatment offers distinct advantages,such as reduced dietary restrictions,broad applicability,and minimal induction of systemic inflammatory responses.Additionally,Xiaozhiling injection effectively eliminates hemorrhoid nuclei,prevents local tissue necrosis,preserves anal cushion integrity,and mitigates postoperative complications,including bleeding and prolapse.Despite its clinical efficacy,the molecular mechanisms underlying its therapeutic effects remain poorly understood,warranting further investigation.AIM To investigate the molecular mechanism underlying the therapeutic effect of Xiaozhiling injection in the treatment of internal hemorrhoids.METHODS An internal hemorrhoid model was established in rats,and the rats were randomly divided into a modeling group[control group(CK group)]and a treatment group.One week after injection,Stereo-seq and electron microscopy were used to study the changes in gene expression and subcellular structures in fibroblasts.RESULTS Single-cell sequencing revealed differences in the expression and transcript levels of the genes collagen 3 alpha 1,decorin,and actin alpha 2 in fibroblasts between the CK group and the treatment group.Spatial transcriptome analysis revealed that genes of the sphingosine kinase 1(Sphk1)/sphingosine-1-phosphate(S1P)pathway spatially overlapped with key genes of the transforming growth factor beta 1 pathway,namely,Sphk1,S1P receptor,and transforming growth factor beta 1,in the treatment group.The proportion of fibroblasts was lower in the treatment group than in the CK group,and Xiaozhiling treatment had a significant effect on the proportion of fibroblasts in hemorrhoidal tissue.Immunohistochemistry revealed a significant increase in the expression of a fibroblast marker.Electron microscopy showed that the endoplasmic reticulum of fibroblasts contained a large amount of glycogen,indicating cell activation.Fibroblast activation and the expression of key genes of the Sphk1-S1P pathway could be observed at the injection site,suggesting that after Xiaozhiling intervention,the Sphk1-S1P pathway could be activated to promote fibrosis.CONCLUSION Xiaozhiling injection exerts its therapeutic effects on internal hemorrhoids by promoting collagen synthesis and secretion in fibroblasts.After Xiaozhiling intervention,the Sphk1-S1P pathway can be activated to promote fibrosis.展开更多
Background:Studies have reported the special value of PANoptosis in cancer,but there is no study on the prognostic and therapeutic effects of PANoptosis in bladder cancer(BLCA).This study aimed to explore the role of ...Background:Studies have reported the special value of PANoptosis in cancer,but there is no study on the prognostic and therapeutic effects of PANoptosis in bladder cancer(BLCA).This study aimed to explore the role of PANoptosis in BLCA heterogeneity and its impact on clinical outcomes and immunotherapy response while establishing a robust prognostic model based on PANoptosis-related features.Methods:Gene expression profiles and clinical data were collected from public databases.Spatial heterogeneity of cell death pathways in BLCA was evaluated.Consensus clustering was performed based on identified PANoptosis genes.Cell death pathway scores,molecular,and pathway activation differences between different groups were compared.Protein-protein interaction(PPI)network construction was constructed,and immune-related gene sets,tumor immune dysfunction and exclusion(TIDE)scores,and SubMap analysis were used to evaluate immunomodulator expression and immunotherapy efficacy.Ten machine learning algorithms were utilized to develop the most accurate predictive risk model,and a nomogram was created for clinical application.Results:BLCA demonstrated a spatially heterogeneous distribution of pyroptosis,apoptosis,and necroptosis.Notably,T effector cells significantly colocalized with total apoptosis.Two PANoptosis modes were identified:high PANoptosis(high.PANO)and low PANoptosis(low.PANO).High.PANO was associated with worse clinical outcomes and advanced tumor stage,and increased activation of immune-related and cell death pathways.It also showed increased infiltration of immune cells,elevated expression of immunomodulatory factors,and enhanced responsiveness to the immunotherapy.The PANoptosis-related machine learning prognostic signature(PMLS)exhibited strong predictive power for outcomes in BLCA.CSPG4 was identified as a key gene underlying prognostic and therapeutic differences.Conclusion:PANoptosis shapes distinct prognostic and immunological phenotypes in BLCA.PMLS offers a reliable prognostic tool.CSPG4 may represent a potential therapeutic target in PANoptosis-driven BLCA.展开更多
Recent studies have explored the spatial transcriptomics patterns of Alzheimer's disease(AD)brain by spatial sequencing in mouse models,enabling the identification of unique genome-wide transcriptomic features ass...Recent studies have explored the spatial transcriptomics patterns of Alzheimer's disease(AD)brain by spatial sequencing in mouse models,enabling the identification of unique genome-wide transcriptomic features associated with different spatial regions and pathological status.However,the dynamics of gene interactions that occur during amyloid-βaccumulation remain largely unknown.In this study,we performed analyses on ligand-receptor communication,transcription factor regulatory network,and spot-specific network to reveal the dependence and the dynamics of gene associations/interactions on spatial regions and pathological status with mouse and human brains.We first used a spatial transcriptomics dataset of the AppNL-G-F knock-in AD and wild-type mouse model.We revealed 17 ligand-receptor pairs with opposite tendencies throughout the amyloid-βaccumulation process and showed the specific ligand-receptor interactions across the hippocampus layers at different extents of pathological changes.We then identified nerve function related transcription factors in the hippocampus and entorhinal cortex,as well as genes with different transcriptomic association degrees in AD versus wild-type mice.Finally,another independent spatial transcriptomics dataset from different AD mouse models and human single-nuclei RNA-seq data/AlzData database were used for validation.This is the first study to identify various gene associations throughout amyloid-βaccumulation based on spatial transcriptomics,establishing the foundations to reveal advanced and in-depth AD etiology from a novel perspective based on the comprehensive analyses of gene interactions that are spatio-temporal dependent.展开更多
The preexistence of immune cells in the tumor microenvironment substantiates the efficacy of immunotherapy in cancer patients.Although the complex intratumoral immune heterogeneity has been extensively studied in sing...The preexistence of immune cells in the tumor microenvironment substantiates the efficacy of immunotherapy in cancer patients.Although the complex intratumoral immune heterogeneity has been extensively studied in single cell resolution,hi-res spatial investigations are limited.In this study,we performed a spatial transcriptome analysis of 4 colorectal adenocarcinoma specimens and 2 paired distant normal specimens to identify the molecular pattern involved in a discontinuous inflammatory response in pathologically annotated cancer regions.Based on the location of spatially varied gene expression,we unmasked the spatially-varied immune ecosystem and identified the locoregional“warmed-up”immune response in predefined“cold”tumor with substantial infiltration of immune components.This“warmed-up”immune profile was found to be associated with the in-situ copy number variance and the tissue remodeling process.Further,“warmed-up”signature genes indicated improved overall survival in CRC patients obtained from TCGA database.展开更多
Microwave thermochemotherapy(MTC)has been applied to treat lip squamous cell carcinoma(LSCC),but a deeper understanding of its therapeutic mechanisms and molecular biology is needed.To address this,we used single-cell...Microwave thermochemotherapy(MTC)has been applied to treat lip squamous cell carcinoma(LSCC),but a deeper understanding of its therapeutic mechanisms and molecular biology is needed.To address this,we used single-cell transcriptomics(scRNA-seq)and spatial transcriptomics(ST)to highlight the pivotal role of tumor-associated neutrophils(TANs)among tumor-infiltrating immune cells and their therapeutic response to MTC.MNDA+TANs with anti-tumor activity(N1-phenotype)are found to be abundantly infiltrated by MTC with benefit of increased blood perfusion,and these TANs are characterized by enhanced cytotoxicity,ameliorated hypoxia,and upregulated IL1B,activating T&NK cells and fibroblasts via IL1B-IL1R.In this highly anti-tumor immunogenic and hypoxia-reversed microenvironment under MTC,fibroblasts accumulated in the tumor front(TF)can recruit N1-TANs via CXCL2-CXCR2 and clear N2-TANs(pro-tumor phenotype)via CXCL12-CXCR4,which results in the aggregation of N1-TANs and extracellular matrix(ECM)deposition.In addition,we construct an N1-TANs marker,MX2,which positively correlates with better prognosis in LSCC patients,and employ deep learning techniques to predict expression of MX2 from hematoxylin-eosin(H&E)-stained images so as to conveniently guide decision making in clinical practice.Collectively,our findings demonstrate that the N1-TANs/fibroblasts defense wall formed in response to MTC effectively combat LSCC.展开更多
Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocyt...Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocytes,microglia,and oligodendrocytes in the central nervous system,and satellite glial cells and Schwann cells in the peripheral nervous system.Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models,few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord.Here,we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes,microglia,and oligodendrocytes in the human spinal cord.To explore the conservation and divergence across species,we compared these findings with those from mice.In the human spinal cord,astrocytes,microglia,and oligodendrocytes were each divided into six distinct transcriptomic subclusters.In the mouse spinal cord,astrocytes,microglia,and oligodendrocytes were divided into five,four,and five distinct transcriptomic subclusters,respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice.Additionally,we detected sex differences in gene expression in human spinal cord glial cells.Specifically,in all astrocyte subtypes,the levels of NEAT1 and CHI3L1 were higher in males than in females,whereas the levels of CST3 were lower in males than in females.In all microglial subtypes,all differentially expressed genes were located on the sex chromosomes.In addition to sex-specific gene differences,the levels of MT-ND4,MT2A,MT-ATP6,MT-CO3,MT-ND2,MT-ND3,and MT-CO_(2) in all spinal cord oligodendrocyte subtypes were higher in females than in males.Collectively,the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cordrelated illnesses,including chronic pain,amyotrophic lateral sclerosis,and multiple sclerosis.展开更多
Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technolo...Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.展开更多
Smoking is a well-established risk factor for periodontitis,yet the precise mechanisms by which smoking contributes to periodontal disease remain poorly understood.Recent advances in spatial transcriptomics have enabl...Smoking is a well-established risk factor for periodontitis,yet the precise mechanisms by which smoking contributes to periodontal disease remain poorly understood.Recent advances in spatial transcriptomics have enabled a deeper exploration of the periodontal tissue microenvironment at single-cell resolution,offering new opportunities to investigate these mechanisms.In this study,we utilized Visium HD single-cell spatial transcriptomics to profile gingival tissues from 12 individuals,including those with periodontitis,those with smoking-associated periodontitis,and healthy controls.Our analysis revealed that smoking disrupts the epithelial barrier integrity,induces fibroblast alterations,and dysregulates fibroblast–epithelial cell communication,thereby exacerbating periodontitis.The spatial analysis showed that endothelial cells and macrophages are in close proximity and interact,which further promotes the progression of smoking-induced periodontal disease.Importantly,we found that targeting the endothelial CXCL12 signalling pathway in smoking-associated periodontitis reduced the proinflammatory macrophage phenotype,alleviated epithelial inflammation,and reduced alveolar bone resorption.These findings provide novel insights into the pathogenesis of smoking-associated periodontitis and highlight the potential of targeting the endothelial–macrophage interaction as a therapeutic strategy.Furthermore,this study establishes an essential information resource for investigating the effects of smoking on periodontitis,providing a foundation for future research and therapeutic development for this prevalent and debilitating disease.展开更多
While bulk RNA sequencing and single-cell RNA sequencing have shed light on cellular heterogeneity and potential molecular mechanisms in the musculoskeletal system in both physiological and various pathological states...While bulk RNA sequencing and single-cell RNA sequencing have shed light on cellular heterogeneity and potential molecular mechanisms in the musculoskeletal system in both physiological and various pathological states,the spatial localization of cells and molecules and intercellular interactions within the tissue context require further elucidation.Spatial transcriptomics has revolutionized biological research by simultaneously capturing gene expression profiles and in situ spatial information of tissues,gradually finding applications in musculoskeletal research.This review provides a summary of recent advances in spatial transcriptomics and its application to the musculoskeletal system.The classification and characteristics of data acquisition techniques in spatial transcriptomics are briefly outlined,with an emphasis on widely-adopted representative technologies and the latest technological breakthroughs,accompanied by a concise workflow for incorporating spatial transcriptomics into musculoskeletal system research.The role of spatial transcriptomics in revealing physiological mechanisms of the musculoskeletal system,particularly during developmental processes,is thoroughly summarized.Furthermore,recent discoveries and achievements of this emerging omics tool in addressing inflammatory,traumatic,degenerative,and tumorous diseases of the musculoskeletal system are compiled.Finally,challenges and potential future directions for spatial transcriptomics,both as a field and in its applications in the musculoskeletal system,are discussed.展开更多
KanCell is a deep learning model based on Kolmogorov-Arnold networks(KAN)designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing and spatial transcriptomics(ST)data.ST technologie...KanCell is a deep learning model based on Kolmogorov-Arnold networks(KAN)designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing and spatial transcriptomics(ST)data.ST technologies provide insights into gene expression within tissue context,revealing cellular interactions and microenvironments.To fully leverage this potential,effective computational models are crucial.We evaluate KanCell on both simulated and real datasets from technologies such as STARmap,Slide-seq,Visium,and Spatial Transcriptomics.Our results demonstrate that KanCell outperforms existing methods across metrics like PCC,SSIM,COSSIM,RMSE,JSD,ARS,and ROC,with robust performance under varying cell numbers and background noise.Real-world applications on human lymph nodes,hearts,melanoma,breast cancer,dorsolateral prefrontal cortex,and mouse embryo brains confirmed its reliability.Compared with traditional approaches,KanCell effectively captures non-linear relationships and optimizes computational efficiency through KAN,providing an accurate and efficient tool for ST.By improving data accuracy and resolving cell type composition,KanCell reveals cellular heterogeneity,clarifies disease microenvironments,and identifies therapeutic targets,addressing complex biological challenges.展开更多
Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear....Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear.Using spatial transcriptomics and single-cell RNA-sequencing data from multi-regional LUAD biopsies consisting of tumor core,tumor edge,and normal area,we sought to delineate the spatial heterogeneity and driving factors of cell colocalization.Two cancer cell sub-clusters(Cancer_c1 and Cancer_c2),associated with LUAD initiation and metastasis,respectively,exhibit distinct spatial distributions and immune cell colocalizations.In particular,Cancer_c1,enriched within the tumor core,could directly interact with B cells or indirectly recruit B cells through macrophages.Conversely,Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8^(+)T cells.Collectively,our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD,providing insights for developing therapeutic strategies for cancer intervention.展开更多
Diabetic kidney disease(DKD),a primary cause of end-stage renal disease,results from progressive tissue remodeling and loss of kidney function.While single-cell RNA sequencing has significantly accelerated our underst...Diabetic kidney disease(DKD),a primary cause of end-stage renal disease,results from progressive tissue remodeling and loss of kidney function.While single-cell RNA sequencing has significantly accelerated our understanding of cellular diversity and dynamics in DKD,its lack of spatial resolution limits insights into tissue-specific dysregulation and the microenvironment.Spatial transcriptomics(ST)is an innovative technology that combines gene expression with spatial localization,offering a powerful approach to dissect the molecular mechanisms of DKD.This mini-review introduces how ST has transformed DKD research by enabling spatially resolved analysis of cell interactions and identifying localized molecular alterations in glomeruli and tubules.ST has revealed dynamic intercellular communication within the renal microenvironment,lesion-specific gene expression patterns,and immune infiltration profiles.For example,SlideseqV2 has highlighted disease-specific cellular neighborhoods and associated signaling networks.Furthermore,ST has pinpointed key genes implicated in disease progression,such as fibrosis-related proteins and transcription factors in tubular damage.By integration of ST with computational tools such as machine learning and network-based analysis can help uncover gene regulatory mechanisms and potential therapeutic targets.However,challenges remain in limited spatial resolution,high data complexity,and computational demands.Addressing these limitations is essential for advancing precision medicine in DKD.展开更多
As a common malignant tumor,the heterogeneity of colorectal cancer plays an important role in tumor progression and treatment response.In recent years,the rapid development of single-cell transcriptomics and spatial t...As a common malignant tumor,the heterogeneity of colorectal cancer plays an important role in tumor progression and treatment response.In recent years,the rapid development of single-cell transcriptomics and spatial transcriptomics technologies has provided new perspectives for resolving the heterogeneity of colorectal cancer.These techniques can reveal the complexity of cellular composition and their interactions in the tumor microenvironment,and thus facilitate a deeper understanding of tumor biology.However,in practical applications,researchers still face technical challenges such as data processing and result interpretation.The aim of this paper is to explore how to use artificial intelligence(AI)technology to enhance the research efficiency of single-cell and spatial transcriptomics,analyze the current research progress and its limitations,and explore how combining AI approaches can provide new ideas for decoding the heterogeneity of colorectal cancer,and ultimately provide theoretical basis and practical guidance for the clinical precision treatment.展开更多
Spatial transcriptomics technology provides novel insights into the spatial organization of gene expression during embryonic development.In this study,we propose a method that integrates analysis across both temporal ...Spatial transcriptomics technology provides novel insights into the spatial organization of gene expression during embryonic development.In this study,we propose a method that integrates analysis across both temporal and spatial dimensions to investigate spatial transcriptomics data from mouse embryos at different developmental stages.We quantified the spatial expression pattern of each gene at various stages by calculating its Moran’s I.Furthermore,by employing time-series clustering to identify dynamic co-expression modules,we identified several developmentally stage-specific regulatory gene modules.A key finding was the presence of distinct,stage-specific gene network modules across different developmental periods:Early modules focused on morphogenesis,mid-stage on organ development,and late-stage on neural and tissue maturation.Functional enrichment analysis further confirmed the core biological functions of each module.The dynamic,spatially-resolved gene expression model constructed in this study not only provides new biological insights into the programmed spatiotemporal reorganization of gene regulatory networks during embryonic development but also presents an effective approach for analyzing complex spatiotemporal omics data.This work provides a new perspective for understanding developmental biology,regenerative medicine,and related fields.展开更多
Recent data suggest that vascular endothelial growth factor receptor inhibitor(VEGFRi)can enhance the anti-tumor activity of the anti-programmed cell death-1(anti-PD-1)antibody in colorectal cancer(CRC)with microsatel...Recent data suggest that vascular endothelial growth factor receptor inhibitor(VEGFRi)can enhance the anti-tumor activity of the anti-programmed cell death-1(anti-PD-1)antibody in colorectal cancer(CRC)with microsatellite stability(MSS).However,the comparison between this combination and standard third-line VEGFRi treatment is not performed,and reliable biomarkers are still lacking.We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi(combination group,n=54)or VEGFRi alone(VEGFRi group,n=32),and their efficacy and safety were evaluated.We additionally examined the immune characteristics of the MSS CRC tumor microenvironment(TME)through single-cell and spatial transcriptomic data,and an MSS CRC immune cell-related signature(MCICRS)that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort.Compared with VEGFRi alone,the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit(median progression-free survival:4.4 vs.2.0 months,P=0.0024;median overall survival:10.2 vs.5.2 months,P=0.0038)and a similar adverse event incidence.Through single-cell and spatial transcriptomic analysis,we determined ten MSS CRC-enriched immune cell types and their spatial distribution,including naive CD4+T,regulatory CD4+T,CD4+Th17,exhausted CD8+T,cytotoxic CD8+T,proliferated CD8+T,natural killer(NK)cells,plasma,and classical and intermediate monocytes.Based on a systemic meta-analysis and ten machine learning algorithms,we obtained MCICRS,an independent risk factor for the prognosis of MSS CRC patients.Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation,and hence a significant relation with the superior efficacy of pan-cancer immunotherapy.More importantly,the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort.Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity.MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.展开更多
Recent advances in spatially resolved transcriptomics(SRT)have provided new opportunities for characterizing spatial structures of various tissues.Graph-based geometric deep learning has gained widespread adoption for...Recent advances in spatially resolved transcriptomics(SRT)have provided new opportunities for characterizing spatial structures of various tissues.Graph-based geometric deep learning has gained widespread adoption for spatial domain identification tasks.Currently,most methods define adjacency relation between cells or spots by their spatial distance in SRT data,which overlooks key biological interactions like gene expression similarities,and leads to inaccuracies in spatial domain identification.To tackle this challenge,we propose a novel method,SpaGRA(https://github.com/sunxue-yy/SpaGRA),for automatic multi-relationship construction based on graph augmentation.SpaGRA uses spatial distance as prior knowledge and dynamically adjusts edge weights with multi-head graph attention networks(GATs).This helps SpaGRA to uncover diverse node relationships and enhance message passing in geometric contrastive learning.Additionally,SpaGRA uses these multi-view relationships to construct negative samples,addressing sampling bias posed by random selection.Experimental results show that SpaGRA presents superior domain identification performance on multiple datasets generated from different protocols.Using SpaGRA,we analyze the functional regions in the mouse hypothalamus,identify key genes related to heart development in mouse embryos,and observe cancer-associated fibroblasts enveloping cancer cells in the latest Visium HD data.Overall,SpaGRA can effectively characterize spatial structures across diverse SRT datasets.展开更多
基金supported by grants from the National Natural Science Key Foundation of China (Grants Nos. 82030092 and 81230050)。
文摘Objective: Hypoxia is a significant feature of solid tumors, including pancreatic ductal adenocarcinoma(PDAC). It is associated with tumor invasion, metastasis, and drug resistance. However, the spatial distribution of hypoxia-related heterogeneity in PDAC remains unclear.Methods: Spatial transcriptomics(STs), a new technique, was used to investigate the ST features of engrafted human PDAC in the ischemic hind limbs of nude mice. Transcriptomes from ST spots in the hypoxic tumor and the control were clustered using differentially-expressed genes. These data were compared to determine the spatial organization of hypoxia-induced heterogeneity in PDAC. Clinical relevance was validated using the Tumor Cancer Genome Atlas and KM-plotter databases. The CMAP website was used to identify molecules that may serve as therapeutic targets for PDAC.Results: ST showed that the tumor cell subgroups decreased to 7 subgroups in the hypoxia group, compared to 9 subgroups in the control group. Different subgroups showed positional characteristics and different gene signatures. Subgroup 6 located at the invasive front showed a higher proliferative ability under hypoxia. Subgroup 6 had active functions including cell proliferation, invasion, and response to stress. Expressions of hypoxia-related genes, LDHA, TPI1, and ENO1, induced changes. CMAP analysis indicated that ADZ-6482, a PI3 K inhibitor, was targeted by the invasive subgroup in hypoxic tumors.Conclusions: This study is the first to describe hypoxic microenvironment-induced spatial transcriptome changes in PDAC, and to identify potential treatment targets for PDAC. These data will provide the basis for further investigations of the prognoses and treatments of hypoxic tumors.
文摘Alzheimer’s disease(AD)is the most common form of dementia.In addition to the lack of effective treatments,there are limitations in diagnostic capabilities.The complexity of AD itself,together with a variety of other diseases often observed in a patient’s history in addition to their AD diagnosis,make deciphering the molecular mechanisms that underlie AD,even more important.Large datasets of single-cell RNA sequencing,single-nucleus RNA-sequencing(snRNA-seq),and spatial transcriptomics(ST)have become essential in guiding and supporting new investigations into the cellular and regional susceptibility of AD.However,with unique technology,software,and larger databases emerging;a lack of integration of these data can contribute to ineffective use of valuable knowledge.Importantly,there was no specialized database that concentrates on ST in AD that offers comprehensive differential analyses under various conditions,such as sex-specific,region-specific,and comparisons between AD and control groups until the new Single-cell and Spatial RNA-seq databasE for Alzheimer’s Disease(ssREAD)database(Wang et al.,2024)was introduced to meet the scientific community’s growing demand for comprehensive,integrated,and accessible data analysis.
基金supported by the National Natural Science Foundation of China(32071792)to J.D.,Zhejiang UniversityNational Key Program on 2016YFD0600103 to J.D.,Zhejiang University+2 种基金The Key program of the National Science Foundation of Zhejiang province(LZ22C160002)to J.D.,Zhejiang UniversityNational Key R&D Program of China(2021YFF1200404)to R.H.Z.,Zhejiang UniversityStarry Night Science Fund of Zhejiang University Shanghai Institute for Advanced Study(SNZJU-SIAS-003/011)to R.H.Z.,Zhejiang University.
文摘The secondary vascular tissue emanating from meristems is central to understanding how vascular plants such as forest trees evolve,grow,and regulate secondary radial growth.However,the overall molecular characterization of meristem origins and developmental trajectories from primary to secondary vascular tissues in woody tree stems is technically challenging.In this study,we combined high-resolution anatomic analysis with a spatial transcriptome(ST)technique to define features of meristematic cells in a developmental gradient from primary to secondary vascular tissues in poplar stems.The tissue-specific gene expression of meristems and derived vascular tissue types were accordingly mapped to specific anatomical domains.Pseudotime analyses were used to track the origins and changes of meristems throughout the development from primary to secondary vascular tissues.Surprisingly,two types of meristematic-like cell pools within secondary vascular tissues were inferred based on high-resolution microscopy combined with ST,and the results were confirmed by in situ hybridization of,transgenic trees,and single-cell sequencing.The rectangle shape procambium-like(PCL)cells develop from procambium meristematic cells and are located within the phloem domain to produce phloem cells,whereas fusiform shape cambium zone(CZ)meristematic cells develop from fusiform metacambium meristematic cells and are located inside the CZ to produce xylem cells.The gene expression atlas and transcriptional networks spanning the primary transition to secondary vascular tissues generated in this work provide new resources for studying the regulation of meristem activities and the evolution of vascular plants.A web server(https://pgx.zju.edu.cn/stRNAPal/)was also established to facilitate the use of ST RNA-seq data.
基金supported by the National Natural Science Foundation of China(32130072)the Chinese Academy of Sciences’Strategic Priority Research Program(XDB27020104)the National Key Research and Development Program(2021YFD2200204).
文摘Primary and secondary growth of the tree stem are responsible for corresponding increases in trunk height and diameter.However,our molecular understanding of the biological processes that underlie these two types of growth is incomplete.In this study,we used single-cell RNA sequencing and spatial transcriptome sequencing to reveal the transcriptional landscapes of primary and secondary growth tissues in the Populus stem.Comparison between the cell atlas and differentiation trajectory of primary and secondary growth revealed different regulatory networks involved in cell differentiation from cambium to xylem precursors and phloem precursors.These regulatory networks may be controlled by auxin accumulation and distribution.Analysis of cell differentiation trajectories suggested that vessel and fiber development followed a sequential pattern of progressive transcriptional regulation.This research provides new insights into the processes of cell identity and differentiation that occur throughout primary and secondary growth of tree stems,increasing our understanding of the cellular differentiation dynamics that occur during stemgrowth in trees.
基金Supported by the National Natural Science Foundation of China,No.81774118the Foreign Cooperation Project of Science and Technology Department of Fujian Province,No.2023I0021the Medical Innovation Project of Fujian Province,No.2024CXB013.
文摘BACKGROUND Hemorrhoids,a prevalent chronic condition globally,significantly impact patients'quality of life.While various surgical interventions,such as external stripping and internal ligation,procedure for prolapse and hemorrhoids,and tissue selecting technique,are employed for treatment,they are often associated with postoperative complications,including unsatisfactory defecation,bleeding,and anal stenosis.In contrast,Xiaozhiling injection,a traditional Chinese medicine-based therapy,has emerged as a minimally invasive and effective alternative for internal hemorrhoids.This treatment offers distinct advantages,such as reduced dietary restrictions,broad applicability,and minimal induction of systemic inflammatory responses.Additionally,Xiaozhiling injection effectively eliminates hemorrhoid nuclei,prevents local tissue necrosis,preserves anal cushion integrity,and mitigates postoperative complications,including bleeding and prolapse.Despite its clinical efficacy,the molecular mechanisms underlying its therapeutic effects remain poorly understood,warranting further investigation.AIM To investigate the molecular mechanism underlying the therapeutic effect of Xiaozhiling injection in the treatment of internal hemorrhoids.METHODS An internal hemorrhoid model was established in rats,and the rats were randomly divided into a modeling group[control group(CK group)]and a treatment group.One week after injection,Stereo-seq and electron microscopy were used to study the changes in gene expression and subcellular structures in fibroblasts.RESULTS Single-cell sequencing revealed differences in the expression and transcript levels of the genes collagen 3 alpha 1,decorin,and actin alpha 2 in fibroblasts between the CK group and the treatment group.Spatial transcriptome analysis revealed that genes of the sphingosine kinase 1(Sphk1)/sphingosine-1-phosphate(S1P)pathway spatially overlapped with key genes of the transforming growth factor beta 1 pathway,namely,Sphk1,S1P receptor,and transforming growth factor beta 1,in the treatment group.The proportion of fibroblasts was lower in the treatment group than in the CK group,and Xiaozhiling treatment had a significant effect on the proportion of fibroblasts in hemorrhoidal tissue.Immunohistochemistry revealed a significant increase in the expression of a fibroblast marker.Electron microscopy showed that the endoplasmic reticulum of fibroblasts contained a large amount of glycogen,indicating cell activation.Fibroblast activation and the expression of key genes of the Sphk1-S1P pathway could be observed at the injection site,suggesting that after Xiaozhiling intervention,the Sphk1-S1P pathway could be activated to promote fibrosis.CONCLUSION Xiaozhiling injection exerts its therapeutic effects on internal hemorrhoids by promoting collagen synthesis and secretion in fibroblasts.After Xiaozhiling intervention,the Sphk1-S1P pathway can be activated to promote fibrosis.
基金supported by grants from the National Natural Science Foundation of China(No.82172741)Shanghai Municipal Health Bureau(No.2020CXJQ03).
文摘Background:Studies have reported the special value of PANoptosis in cancer,but there is no study on the prognostic and therapeutic effects of PANoptosis in bladder cancer(BLCA).This study aimed to explore the role of PANoptosis in BLCA heterogeneity and its impact on clinical outcomes and immunotherapy response while establishing a robust prognostic model based on PANoptosis-related features.Methods:Gene expression profiles and clinical data were collected from public databases.Spatial heterogeneity of cell death pathways in BLCA was evaluated.Consensus clustering was performed based on identified PANoptosis genes.Cell death pathway scores,molecular,and pathway activation differences between different groups were compared.Protein-protein interaction(PPI)network construction was constructed,and immune-related gene sets,tumor immune dysfunction and exclusion(TIDE)scores,and SubMap analysis were used to evaluate immunomodulator expression and immunotherapy efficacy.Ten machine learning algorithms were utilized to develop the most accurate predictive risk model,and a nomogram was created for clinical application.Results:BLCA demonstrated a spatially heterogeneous distribution of pyroptosis,apoptosis,and necroptosis.Notably,T effector cells significantly colocalized with total apoptosis.Two PANoptosis modes were identified:high PANoptosis(high.PANO)and low PANoptosis(low.PANO).High.PANO was associated with worse clinical outcomes and advanced tumor stage,and increased activation of immune-related and cell death pathways.It also showed increased infiltration of immune cells,elevated expression of immunomodulatory factors,and enhanced responsiveness to the immunotherapy.The PANoptosis-related machine learning prognostic signature(PMLS)exhibited strong predictive power for outcomes in BLCA.CSPG4 was identified as a key gene underlying prognostic and therapeutic differences.Conclusion:PANoptosis shapes distinct prognostic and immunological phenotypes in BLCA.PMLS offers a reliable prognostic tool.CSPG4 may represent a potential therapeutic target in PANoptosis-driven BLCA.
基金supported by grants from the National Natural Science Foundation of China (No.81902277)the National Key R&D Program of China (No.2017YFC1001100).
文摘Recent studies have explored the spatial transcriptomics patterns of Alzheimer's disease(AD)brain by spatial sequencing in mouse models,enabling the identification of unique genome-wide transcriptomic features associated with different spatial regions and pathological status.However,the dynamics of gene interactions that occur during amyloid-βaccumulation remain largely unknown.In this study,we performed analyses on ligand-receptor communication,transcription factor regulatory network,and spot-specific network to reveal the dependence and the dynamics of gene associations/interactions on spatial regions and pathological status with mouse and human brains.We first used a spatial transcriptomics dataset of the AppNL-G-F knock-in AD and wild-type mouse model.We revealed 17 ligand-receptor pairs with opposite tendencies throughout the amyloid-βaccumulation process and showed the specific ligand-receptor interactions across the hippocampus layers at different extents of pathological changes.We then identified nerve function related transcription factors in the hippocampus and entorhinal cortex,as well as genes with different transcriptomic association degrees in AD versus wild-type mice.Finally,another independent spatial transcriptomics dataset from different AD mouse models and human single-nuclei RNA-seq data/AlzData database were used for validation.This is the first study to identify various gene associations throughout amyloid-βaccumulation based on spatial transcriptomics,establishing the foundations to reveal advanced and in-depth AD etiology from a novel perspective based on the comprehensive analyses of gene interactions that are spatio-temporal dependent.
基金This work was supported by grants from the National Natural Science Foundation of China(82002628)Natural Science Foundation of Guangdong Province(2021A1515010096)+3 种基金China Postdoctoral Science Foundation(2019M660227)Chinese Society of Clinical Oncology Foundation(Y-HR2018-319,Y-L2017-002,and Y-JS2019-009)Sun Yat-sen University Basic Research Fund(19ykpy180)the open research funds from the Sixth Affiliated Hospital of Guangzhou Medical University,Qingyuan People’s Hospital(202011-103)。
文摘The preexistence of immune cells in the tumor microenvironment substantiates the efficacy of immunotherapy in cancer patients.Although the complex intratumoral immune heterogeneity has been extensively studied in single cell resolution,hi-res spatial investigations are limited.In this study,we performed a spatial transcriptome analysis of 4 colorectal adenocarcinoma specimens and 2 paired distant normal specimens to identify the molecular pattern involved in a discontinuous inflammatory response in pathologically annotated cancer regions.Based on the location of spatially varied gene expression,we unmasked the spatially-varied immune ecosystem and identified the locoregional“warmed-up”immune response in predefined“cold”tumor with substantial infiltration of immune components.This“warmed-up”immune profile was found to be associated with the in-situ copy number variance and the tissue remodeling process.Further,“warmed-up”signature genes indicated improved overall survival in CRC patients obtained from TCGA database.
基金supported by National Natural Science Foundation of China grants(Nos.82173326 and 82473058)Key Research and Development Project of Sichuan Province(Nos.2024YFFK0374 and 2024YFFK0198)Interdisciplinary Innovation Project of West China College of Stomatology,Sichuan University(RD-03-202004).
文摘Microwave thermochemotherapy(MTC)has been applied to treat lip squamous cell carcinoma(LSCC),but a deeper understanding of its therapeutic mechanisms and molecular biology is needed.To address this,we used single-cell transcriptomics(scRNA-seq)and spatial transcriptomics(ST)to highlight the pivotal role of tumor-associated neutrophils(TANs)among tumor-infiltrating immune cells and their therapeutic response to MTC.MNDA+TANs with anti-tumor activity(N1-phenotype)are found to be abundantly infiltrated by MTC with benefit of increased blood perfusion,and these TANs are characterized by enhanced cytotoxicity,ameliorated hypoxia,and upregulated IL1B,activating T&NK cells and fibroblasts via IL1B-IL1R.In this highly anti-tumor immunogenic and hypoxia-reversed microenvironment under MTC,fibroblasts accumulated in the tumor front(TF)can recruit N1-TANs via CXCL2-CXCR2 and clear N2-TANs(pro-tumor phenotype)via CXCL12-CXCR4,which results in the aggregation of N1-TANs and extracellular matrix(ECM)deposition.In addition,we construct an N1-TANs marker,MX2,which positively correlates with better prognosis in LSCC patients,and employ deep learning techniques to predict expression of MX2 from hematoxylin-eosin(H&E)-stained images so as to conveniently guide decision making in clinical practice.Collectively,our findings demonstrate that the N1-TANs/fibroblasts defense wall formed in response to MTC effectively combat LSCC.
基金supported by the National Natural Science Foundation of China,No.82301403(to DZ)。
文摘Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocytes,microglia,and oligodendrocytes in the central nervous system,and satellite glial cells and Schwann cells in the peripheral nervous system.Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models,few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord.Here,we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes,microglia,and oligodendrocytes in the human spinal cord.To explore the conservation and divergence across species,we compared these findings with those from mice.In the human spinal cord,astrocytes,microglia,and oligodendrocytes were each divided into six distinct transcriptomic subclusters.In the mouse spinal cord,astrocytes,microglia,and oligodendrocytes were divided into five,four,and five distinct transcriptomic subclusters,respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice.Additionally,we detected sex differences in gene expression in human spinal cord glial cells.Specifically,in all astrocyte subtypes,the levels of NEAT1 and CHI3L1 were higher in males than in females,whereas the levels of CST3 were lower in males than in females.In all microglial subtypes,all differentially expressed genes were located on the sex chromosomes.In addition to sex-specific gene differences,the levels of MT-ND4,MT2A,MT-ATP6,MT-CO3,MT-ND2,MT-ND3,and MT-CO_(2) in all spinal cord oligodendrocyte subtypes were higher in females than in males.Collectively,the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cordrelated illnesses,including chronic pain,amyotrophic lateral sclerosis,and multiple sclerosis.
基金supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI)the Ministry of Health&Welfare,Republic of Korea (HR22C1734)+2 种基金the National Research Foundation (NRF) of Korea (2020R1A6A1A03043539,2020M3A9D8037604,2022R1C1C1004756)(to SBL)the NRF of Korea (2022R1C1C1005741 and RS-2023-00217595)the new faculty research fund of Ajou University School of Medicine (to EJL)。
文摘Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.
基金supported by grants from the National Natural Science Foundation of China(Grant nos.82201011,82370958 and 81870770).
文摘Smoking is a well-established risk factor for periodontitis,yet the precise mechanisms by which smoking contributes to periodontal disease remain poorly understood.Recent advances in spatial transcriptomics have enabled a deeper exploration of the periodontal tissue microenvironment at single-cell resolution,offering new opportunities to investigate these mechanisms.In this study,we utilized Visium HD single-cell spatial transcriptomics to profile gingival tissues from 12 individuals,including those with periodontitis,those with smoking-associated periodontitis,and healthy controls.Our analysis revealed that smoking disrupts the epithelial barrier integrity,induces fibroblast alterations,and dysregulates fibroblast–epithelial cell communication,thereby exacerbating periodontitis.The spatial analysis showed that endothelial cells and macrophages are in close proximity and interact,which further promotes the progression of smoking-induced periodontal disease.Importantly,we found that targeting the endothelial CXCL12 signalling pathway in smoking-associated periodontitis reduced the proinflammatory macrophage phenotype,alleviated epithelial inflammation,and reduced alveolar bone resorption.These findings provide novel insights into the pathogenesis of smoking-associated periodontitis and highlight the potential of targeting the endothelial–macrophage interaction as a therapeutic strategy.Furthermore,this study establishes an essential information resource for investigating the effects of smoking on periodontitis,providing a foundation for future research and therapeutic development for this prevalent and debilitating disease.
基金supported by The National Natural Science Youth Foundation of China(Grant No.82102584).
文摘While bulk RNA sequencing and single-cell RNA sequencing have shed light on cellular heterogeneity and potential molecular mechanisms in the musculoskeletal system in both physiological and various pathological states,the spatial localization of cells and molecules and intercellular interactions within the tissue context require further elucidation.Spatial transcriptomics has revolutionized biological research by simultaneously capturing gene expression profiles and in situ spatial information of tissues,gradually finding applications in musculoskeletal research.This review provides a summary of recent advances in spatial transcriptomics and its application to the musculoskeletal system.The classification and characteristics of data acquisition techniques in spatial transcriptomics are briefly outlined,with an emphasis on widely-adopted representative technologies and the latest technological breakthroughs,accompanied by a concise workflow for incorporating spatial transcriptomics into musculoskeletal system research.The role of spatial transcriptomics in revealing physiological mechanisms of the musculoskeletal system,particularly during developmental processes,is thoroughly summarized.Furthermore,recent discoveries and achievements of this emerging omics tool in addressing inflammatory,traumatic,degenerative,and tumorous diseases of the musculoskeletal system are compiled.Finally,challenges and potential future directions for spatial transcriptomics,both as a field and in its applications in the musculoskeletal system,are discussed.
基金supported by the National Natural Science Foundation of China(52361145714,21673252)the Beijing Municipal Education Commission(2019821001)+1 种基金Climbing Program Foundation from Beijing Institute of Petrochemical Technology(BIPTAAl-2021007)the ZhiYuan Fund key Project from Beijing Institute of Petrochemical Technology(2024003).
文摘KanCell is a deep learning model based on Kolmogorov-Arnold networks(KAN)designed to enhance cellular heterogeneity analysis by integrating single-cell RNA sequencing and spatial transcriptomics(ST)data.ST technologies provide insights into gene expression within tissue context,revealing cellular interactions and microenvironments.To fully leverage this potential,effective computational models are crucial.We evaluate KanCell on both simulated and real datasets from technologies such as STARmap,Slide-seq,Visium,and Spatial Transcriptomics.Our results demonstrate that KanCell outperforms existing methods across metrics like PCC,SSIM,COSSIM,RMSE,JSD,ARS,and ROC,with robust performance under varying cell numbers and background noise.Real-world applications on human lymph nodes,hearts,melanoma,breast cancer,dorsolateral prefrontal cortex,and mouse embryo brains confirmed its reliability.Compared with traditional approaches,KanCell effectively captures non-linear relationships and optimizes computational efficiency through KAN,providing an accurate and efficient tool for ST.By improving data accuracy and resolving cell type composition,KanCell reveals cellular heterogeneity,clarifies disease microenvironments,and identifies therapeutic targets,addressing complex biological challenges.
基金supported by the National Natural Science Foundation of China(82002432 to J.W.,82302068 to M.Z.,and 32300568 to T.W.)the Natural Science Foundation of Shandong Province(ZR2024MH159 to Y.Z.,ZR2020QH179 to J.W.,ZR2022QH057 to M.Z.,and ZR2021QH005 to T.W.)the China Postdoctoral Science Foundation(2024M752006 to S.M.)。
文摘Although the spatial characteristics within the tumor microenvironment of lung adenocarcinoma(LUAD)have been identified,the mechanisms by which these factors promote LUAD progression and immune evasion remain unclear.Using spatial transcriptomics and single-cell RNA-sequencing data from multi-regional LUAD biopsies consisting of tumor core,tumor edge,and normal area,we sought to delineate the spatial heterogeneity and driving factors of cell colocalization.Two cancer cell sub-clusters(Cancer_c1 and Cancer_c2),associated with LUAD initiation and metastasis,respectively,exhibit distinct spatial distributions and immune cell colocalizations.In particular,Cancer_c1,enriched within the tumor core,could directly interact with B cells or indirectly recruit B cells through macrophages.Conversely,Cancer_c2 enriched within the tumor edge exhibits colocalization with CD8^(+)T cells.Collectively,our work elucidates the spatial distribution of cancer cell subtypes and their interaction with immune cells in the core and edge of LUAD,providing insights for developing therapeutic strategies for cancer intervention.
基金Supported by Science and Technology Research Program of Chongqing Municipal Education Commission,No.KJQN202100538Talent Innovation Project in Life Sciences of Chongqing Normal University,No.CSSK2023-04.
文摘Diabetic kidney disease(DKD),a primary cause of end-stage renal disease,results from progressive tissue remodeling and loss of kidney function.While single-cell RNA sequencing has significantly accelerated our understanding of cellular diversity and dynamics in DKD,its lack of spatial resolution limits insights into tissue-specific dysregulation and the microenvironment.Spatial transcriptomics(ST)is an innovative technology that combines gene expression with spatial localization,offering a powerful approach to dissect the molecular mechanisms of DKD.This mini-review introduces how ST has transformed DKD research by enabling spatially resolved analysis of cell interactions and identifying localized molecular alterations in glomeruli and tubules.ST has revealed dynamic intercellular communication within the renal microenvironment,lesion-specific gene expression patterns,and immune infiltration profiles.For example,SlideseqV2 has highlighted disease-specific cellular neighborhoods and associated signaling networks.Furthermore,ST has pinpointed key genes implicated in disease progression,such as fibrosis-related proteins and transcription factors in tubular damage.By integration of ST with computational tools such as machine learning and network-based analysis can help uncover gene regulatory mechanisms and potential therapeutic targets.However,challenges remain in limited spatial resolution,high data complexity,and computational demands.Addressing these limitations is essential for advancing precision medicine in DKD.
基金Supported by the Shandong Province Medical and Health Science and Technology Development Plan Project,No.202203030713Yantai Science and Technology Program,No.2024YD005,No.2024YD007 and No.2024YD010and Science and Technology Program of Yantai Affiliated Hospital of Binzhou Medical University,No.YTFY2022KYQD06。
文摘As a common malignant tumor,the heterogeneity of colorectal cancer plays an important role in tumor progression and treatment response.In recent years,the rapid development of single-cell transcriptomics and spatial transcriptomics technologies has provided new perspectives for resolving the heterogeneity of colorectal cancer.These techniques can reveal the complexity of cellular composition and their interactions in the tumor microenvironment,and thus facilitate a deeper understanding of tumor biology.However,in practical applications,researchers still face technical challenges such as data processing and result interpretation.The aim of this paper is to explore how to use artificial intelligence(AI)technology to enhance the research efficiency of single-cell and spatial transcriptomics,analyze the current research progress and its limitations,and explore how combining AI approaches can provide new ideas for decoding the heterogeneity of colorectal cancer,and ultimately provide theoretical basis and practical guidance for the clinical precision treatment.
基金supported by the National Natural Science Foundation of China(Grant Nos.12090052,U24A2014,and 12325405).
文摘Spatial transcriptomics technology provides novel insights into the spatial organization of gene expression during embryonic development.In this study,we propose a method that integrates analysis across both temporal and spatial dimensions to investigate spatial transcriptomics data from mouse embryos at different developmental stages.We quantified the spatial expression pattern of each gene at various stages by calculating its Moran’s I.Furthermore,by employing time-series clustering to identify dynamic co-expression modules,we identified several developmentally stage-specific regulatory gene modules.A key finding was the presence of distinct,stage-specific gene network modules across different developmental periods:Early modules focused on morphogenesis,mid-stage on organ development,and late-stage on neural and tissue maturation.Functional enrichment analysis further confirmed the core biological functions of each module.The dynamic,spatially-resolved gene expression model constructed in this study not only provides new biological insights into the programmed spatiotemporal reorganization of gene regulatory networks during embryonic development but also presents an effective approach for analyzing complex spatiotemporal omics data.This work provides a new perspective for understanding developmental biology,regenerative medicine,and related fields.
基金supported by the National Natural Science Foundation of China(No.81972012).
文摘Recent data suggest that vascular endothelial growth factor receptor inhibitor(VEGFRi)can enhance the anti-tumor activity of the anti-programmed cell death-1(anti-PD-1)antibody in colorectal cancer(CRC)with microsatellite stability(MSS).However,the comparison between this combination and standard third-line VEGFRi treatment is not performed,and reliable biomarkers are still lacking.We retrospectively enrolled MSS CRC patients receiving anti-PD-1 antibody plus VEGFRi(combination group,n=54)or VEGFRi alone(VEGFRi group,n=32),and their efficacy and safety were evaluated.We additionally examined the immune characteristics of the MSS CRC tumor microenvironment(TME)through single-cell and spatial transcriptomic data,and an MSS CRC immune cell-related signature(MCICRS)that can be used to predict the clinical outcomes of MSS CRC patients receiving immunotherapy was developed and validated in our in-house cohort.Compared with VEGFRi alone,the combination of anti-PD-1 antibody and VEGFRi exhibited a prolonged survival benefit(median progression-free survival:4.4 vs.2.0 months,P=0.0024;median overall survival:10.2 vs.5.2 months,P=0.0038)and a similar adverse event incidence.Through single-cell and spatial transcriptomic analysis,we determined ten MSS CRC-enriched immune cell types and their spatial distribution,including naive CD4+T,regulatory CD4+T,CD4+Th17,exhausted CD8+T,cytotoxic CD8+T,proliferated CD8+T,natural killer(NK)cells,plasma,and classical and intermediate monocytes.Based on a systemic meta-analysis and ten machine learning algorithms,we obtained MCICRS,an independent risk factor for the prognosis of MSS CRC patients.Further analyses demonstrated that the low-MCICRS group presented a higher immune cell infiltration and immune-related pathway activation,and hence a significant relation with the superior efficacy of pan-cancer immunotherapy.More importantly,the predictive value of MCICRS in MSS CRC patients receiving immunotherapy was also validated with an in-house cohort.Anti-PD-1 antibody combined with VEGFRi presented an improved clinical benefit in MSS CRC with manageable toxicity.MCICRS could serve as a robust and promising tool to predict clinical outcomes for individual MSS CRC patients receiving immunotherapy.
基金supported by the National Natural Science Foundation of China(Nos.62303271,U1806202,62103397)the Natural Science Foundation of Shandong Province(ZR2023QF081)Funding for open access charge:the National Natural Science Foundation of China(Nos.62303271,U1806202).
文摘Recent advances in spatially resolved transcriptomics(SRT)have provided new opportunities for characterizing spatial structures of various tissues.Graph-based geometric deep learning has gained widespread adoption for spatial domain identification tasks.Currently,most methods define adjacency relation between cells or spots by their spatial distance in SRT data,which overlooks key biological interactions like gene expression similarities,and leads to inaccuracies in spatial domain identification.To tackle this challenge,we propose a novel method,SpaGRA(https://github.com/sunxue-yy/SpaGRA),for automatic multi-relationship construction based on graph augmentation.SpaGRA uses spatial distance as prior knowledge and dynamically adjusts edge weights with multi-head graph attention networks(GATs).This helps SpaGRA to uncover diverse node relationships and enhance message passing in geometric contrastive learning.Additionally,SpaGRA uses these multi-view relationships to construct negative samples,addressing sampling bias posed by random selection.Experimental results show that SpaGRA presents superior domain identification performance on multiple datasets generated from different protocols.Using SpaGRA,we analyze the functional regions in the mouse hypothalamus,identify key genes related to heart development in mouse embryos,and observe cancer-associated fibroblasts enveloping cancer cells in the latest Visium HD data.Overall,SpaGRA can effectively characterize spatial structures across diverse SRT datasets.
