While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput...While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments.These technologies are emerging as transformative tools in molecular diagnostics and medical research.By integrating histopathological morphology with spatial multi-omics profiling(genome,transcriptome,epigenome,and proteome),spatial omics technologies open an avenue for understanding disease progression,therapeutic resistance mechanisms,and precise diagnosis.It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states,which may greatly facilitate tumor molecular subtyping,prognostic assessment,and prediction of the radiotherapy and chemotherapy efficacy.Despite the substantial advancements in spatial omics,the translation of spatial omics into clinical applications remains challenging due to robustness,efficacy,clinical validation,and cost constraints.In this review,we summarize the current progress and prospects of spatial omics technologies,particularly in medical research and diagnostic applications.展开更多
There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative...There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.展开更多
Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visuali...Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.展开更多
Cardiovascular diseases constitute a marked threat to global health,and the emergence of spatial omics technologies has revolutionized cardiovascular research.This review explores the application of spatial omics,incl...Cardiovascular diseases constitute a marked threat to global health,and the emergence of spatial omics technologies has revolutionized cardiovascular research.This review explores the application of spatial omics,including spatial transcriptomics,spatial proteomics,spatial metabolomics,spatial genomics,and spatial epigenomics,providing more insight into the molecular and cellular foundations of cardiovascular disease and highlighting the critical contributions of spatial omics to cardiovascular science,and discusses future prospects,including technological advancements,integration of multi-omics,and clinical applications.These developments should contribute to the understanding of cardiovascular diseases and guide the progress of precision medicine,targeted therapies,and personalized treatments.展开更多
Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(iCCA)represent the most prevalent primary malignancies of the liver(1,2).Both exhibit significant heterogeneity and complex tumor microenvironments,whic...Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(iCCA)represent the most prevalent primary malignancies of the liver(1,2).Both exhibit significant heterogeneity and complex tumor microenvironments,which contribute to their aggressive nature and poor prognosis.Conventional genomic and transcriptomic methodologies,including bulk sequencing and single-cell RNA sequencing,have identified critical driver mutations and cellular subpopulations.However,these approaches lack the ability to preserve the native spatial architecture of tissues,thereby limiting insights into cellular interactions and functional niches.The emergence of spatial omics technologies addresses this fundamental limitation.By enabling the simultaneous assessment of molecular expression and its precise histological context,these methods provide an unprecedented view of the tumor ecosystem,offering new avenues for understanding hepatobiliary cancer biology and developing targeted therapies.展开更多
Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of ...Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.展开更多
1文献来源CHEN H,DENG C,GAO J,et al.Integrative spatial analysis reveals tumor heterogeneity and immune colony niche related to clinical outcomes in small cell lung cancer[J].Cancer Cell,2025,43(3):519−536.e5.doi:10.10...1文献来源CHEN H,DENG C,GAO J,et al.Integrative spatial analysis reveals tumor heterogeneity and immune colony niche related to clinical outcomes in small cell lung cancer[J].Cancer Cell,2025,43(3):519−536.e5.doi:10.1016/j.ccell.2025.01.012.展开更多
Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context,significantly enhancing our understanding of the intricate and multifaceted biologic...Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context,significantly enhancing our understanding of the intricate and multifaceted biological system.With an increasing focus on spatial heterogeneity,there is a growing need for unbiased,spatially resolved omics technologies.Laser capture microdissection(LCM)is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest(ROIs)from heterogeneous tissues,with resolutions ranging from single cells to cell populations.Thus,LCM has been widely used for studying the cellular and molecular mechanisms of diseases.This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research.Key attributes of application cases are also highlighted,such as throughput and spatial resolution.In addition,we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research,disease diagnosis,and targeted therapy from the perspective of high-throughput,multi-omics,and single-cell resolution.展开更多
The idea of accurately modeling life within a computer is no longer science fiction;it is becoming a reality through the rise of the virtual cell.Over the past few years,fueled by advances in single-cell and spatial o...The idea of accurately modeling life within a computer is no longer science fiction;it is becoming a reality through the rise of the virtual cell.Over the past few years,fueled by advances in single-cell and spatial omics,artificial intelligence(AI),and high-performance computing,virtual cells have rapidly evolved from abstract concepts into practical tools with the power to reshape biomedical research.Building on earlier,more constrained attempts at integration,today’s virtual cells can merge diverse data streams with sophisticated computational models,enabling comprehensive simulations of cellular structure,function,and behavior.1,2 In doing so,they provide an unprecedented platform for reconstructing and manipulating life and open transformative opportunities for intelligent oncology.The core technical framework,data foundations,and key potential application areas of virtual cells in intelligent oncology are illustrated in Figure 1.展开更多
Recent advances in spatial and single-cell omics have significantly revolutionized biomarker discovery in tumor immunotherapy by addressing critical challenges such as tumor heterogeneity,immune evasion,and variabilit...Recent advances in spatial and single-cell omics have significantly revolutionized biomarker discovery in tumor immunotherapy by addressing critical challenges such as tumor heterogeneity,immune evasion,and variability within the tumor microenvironment(TME).Immunotherapeutic strategies,including immune checkpoint in-hibitors and adoptive T-cell transfer,have demonstrated promising clinical outcomes;however,their efficacy is limited by low response rates and the incidence of immune-related adverse events(irAEs).Therefore,the identification of reliable biomarkers is essential for predicting treatment efficacy,minimizing irAEs,and facili-tating patient stratification.Spatial omics integrates molecular profiling with spatial localization,thereby providing comprehensive insights into the cellular organization and functional states within the TME.By elucidating the spatial patterns of immune cell infiltration and tumor heterogeneity,this approach enhances the prediction of therapeutic responses.Similarly,single-cell omics enables high-resolution analysis of cellular heterogeneity by capturing transcriptomic,epigenomic,and metabolic signatures at the single-cell level.The integrated application of spatial and single-cell omics has enabled the identification of previously undetected biomarkers,including rare immune cell subsets implicated in resistance mechanisms.In addition to spatial transcriptomics(ST),this technological landscape also includes spatial proteomics(SP)and spatial metab-olomics,which further facilitate the study of dynamic tumor-immune interactions.Multi-omics integration provides a comprehensive overview of biomarker landscapes,while the rapid evolution of artificial intelligence(AI)-based approaches enhances the analysis of complex,multidimensional datasets to ultimately enhance pre-dictive potential and clinical utility.Despite substantial progress,several challenges remain in the context of standardization,data integration,and real-time monitoring.Nevertheless,the incorporation of spatial and single-cell omics into biomarker research holds transformative potential for advancing personalized cancer immuno-therapy.These emerging strategies pave the way for the development of innovative diagnostic and therapeutic interventions,thereby enabling precision oncology and improving treatment outcomes across a wide range of tumor profiles.This review aims to provide a comprehensive overview of the integration of spatial omics with single-cell omics in the discovery of biomarkers for tumor immunotherapy.Specifically,it examines the strategies by which these emerging technologies address the challenges related to tumor heterogeneity,immune evasion,and the dynamic nature of the TME.By elaborating on the principles,applications,and clinical potential of these technologies,this review also critically evaluates their limitations,challenges,and the current gaps in clinical translation.展开更多
基金supported by the National Natural Science Foundation of China(32171022,32221005,and 32401246).
文摘While conventional FISH and IHC methods struggle to decode complex tissue heterogeneity and comprehensive molecular diagnosis due to low-throughput spatial information,spatial omics technologies enable high-throughput molecular mapping across tissue microenvironments.These technologies are emerging as transformative tools in molecular diagnostics and medical research.By integrating histopathological morphology with spatial multi-omics profiling(genome,transcriptome,epigenome,and proteome),spatial omics technologies open an avenue for understanding disease progression,therapeutic resistance mechanisms,and precise diagnosis.It particularly enhances tumor microenvironment analysis by mapping immune cell distributions and functional states,which may greatly facilitate tumor molecular subtyping,prognostic assessment,and prediction of the radiotherapy and chemotherapy efficacy.Despite the substantial advancements in spatial omics,the translation of spatial omics into clinical applications remains challenging due to robustness,efficacy,clinical validation,and cost constraints.In this review,we summarize the current progress and prospects of spatial omics technologies,particularly in medical research and diagnostic applications.
基金supported by the China Science and Technology Innovation 2030-Major Project(Nos.2022ZD0211701,2021ZD0200700)the National Natural Science Foundation of China(Nos.82130042,81830040,22176195,82127801)+3 种基金Shenzhen Science and Technology Serial Funds(Nos.GJHZ20210705141400002,KCXFZ20211020164543006,JCYJ20220818101615033,ZDSYS20220606100606014,KQTD 20221101093608028)the National Key R&D Program of China(No.2022YFF0705003)Guangdong Province Zhu Jiang Talents Plan(No.2021QN02Y028)the Guangdong Science and Technology Department(No.2021B1212030004)。
文摘There is growing evidence that lipid metabolism instability in depressive disorder may be a core early pathological event associated with numerous pathogenesis hypotheses.However,spatial distributions and quantitative changes of lipids in specific brain regions associated with depressive disorder are far from elucidated.In the present study,lipid profiling characteristics of whole brain sections are systematically determined by using matrix-assisted laser desorption ionization-mass spectrometry imaging(MALDI-MSI)-combined with histomorphological analysis in rats with depressive-like behavior induced by multiple early life stress(mELS)and unstressed control.Lipid dyshomeostasis and different degrees of metabolic disturbance occur in the eight paired representative brain sections from micro-region and molecular level.More specifically,17 lipid molecules show the severe dyshomeostasis between intergroup(control and depressed rats)or intra-group(multiple emotion-regulation-related brain regions).Quite specially,phosphatidylcholine(PC)(39:6)expression in section 7 is significantly upregulated only in the amygdala of depressed rat relative to control rat,by contrast,up-regulated phosphatidylglycerol(PG)(34:2)in section 2 emerges in the medial prefrontal cortex,insular cortex,and nucleus accumbens simultaneously.Linking spatial distribution to quantitative variation of lipids from the whole brain sections contributes the uncovering of new insights in causal mechanism of lipid dyshomeostasis in depression investigation and related targeting interventions.
基金supported by Basic and Applied Basic Research Foundation of Guangdong Province(No.2022A1111220217)Medical Scientific Research Foundation of Guangdong Province(Nos.A2023216,A2022124)+3 种基金Science and Technology Program of Guangzhou(Nos.202201010840,202201010810,202102080132,202002030032,202002020023)Health Commission Program of Guangzhou(20212A010021,20201A010081,20211A011116)Science and Technology Project of Panyu,Guangzhou(2022-Z04-009,2022-Z04-090,2022-Z04-072,2021-Z04-013,2020-Z04-026,2019-Z04-02)Scientific Research Project of Guangzhou Panyu Central Hospital(Nos.2022Y002,2021Y004,2021Y002).
文摘Spatial omics technology integrates the concept of space into omics research and retains the spatial information of tissues or organs while obtaining molecular information.It is characterized by the ability to visualize changes in molecular information and yields intuitive and vivid visual results.Spatial omics technologies include spatial transcriptomics,spatial proteomics,spatial metabolomics,and other technologies,the most widely used of which are spatial transcriptomics and spatial proteomics.The tumor microenvironment refers to the surrounding microenvironment in which tumor cells exist,including the surrounding blood vessels,immune cells,fibroblasts,bone marrow-derived inflammatory cells,various signaling molecules,and extracellular matrix.A key issue in modern tumor biology is the application of spatial omics to the study of the tumor microenvironment,which can reveal problems that conventional research techniques cannot,potentially leading to the development of novel therapeutic agents for cancer.This paper summarizes the progress of research on spatial transcriptomics and spatial proteomics technologies for characterizing the tumor immune microenvironment.
基金supported by the National Natural Science Fund for Distinguished Young Scholars of China(82125004,to J.S.)the Beijing Natural Science Foundation(Z240015,to J.S.)the Frontier Biotechnology Key Project of National Key R&D Program of Ministry of Science and Technology of China(2023YFC3404300,to J.S.).
文摘Cardiovascular diseases constitute a marked threat to global health,and the emergence of spatial omics technologies has revolutionized cardiovascular research.This review explores the application of spatial omics,including spatial transcriptomics,spatial proteomics,spatial metabolomics,spatial genomics,and spatial epigenomics,providing more insight into the molecular and cellular foundations of cardiovascular disease and highlighting the critical contributions of spatial omics to cardiovascular science,and discusses future prospects,including technological advancements,integration of multi-omics,and clinical applications.These developments should contribute to the understanding of cardiovascular diseases and guide the progress of precision medicine,targeted therapies,and personalized treatments.
基金supported by the Beijing-Tianjin-Hebei Basic Research Cooperation Special Project(grant number 22JCZXJC00200)National High Level Hospital Clinical Research Funding(2025-PUMCH-C-030).
文摘Hepatocellular carcinoma(HCC)and intrahepatic cholangiocarcinoma(iCCA)represent the most prevalent primary malignancies of the liver(1,2).Both exhibit significant heterogeneity and complex tumor microenvironments,which contribute to their aggressive nature and poor prognosis.Conventional genomic and transcriptomic methodologies,including bulk sequencing and single-cell RNA sequencing,have identified critical driver mutations and cellular subpopulations.However,these approaches lack the ability to preserve the native spatial architecture of tissues,thereby limiting insights into cellular interactions and functional niches.The emergence of spatial omics technologies addresses this fundamental limitation.By enabling the simultaneous assessment of molecular expression and its precise histological context,these methods provide an unprecedented view of the tumor ecosystem,offering new avenues for understanding hepatobiliary cancer biology and developing targeted therapies.
基金supported by two DoD grants(HT94252310534 to R.J.T.and HT94252310519 to C.M.K.)the following NIH/NIAMS grants:R01 grants(AR078035 and AR076900 to C.L.+10 种基金AG069401 and AG067698 to L.Q.AI186118,HD112474,and HD107034 to R.J.T.AR076325 and AR071967 to C.M.K.AR080902 and AR072999 to F.G.AR074441 and AR077678 to S.Y.T.AR082667 and AR077527 to A.E.L.AR083900,AR075860 and AR077616 to J.S.),R21 grants(AR077226 to J.S.AR083217 to A.E.L.AR081517 to S.Y.T.)a T32 grant(HD007434 to D.R.K.)P30 center grants(AR074992 and AR073752).
文摘Musculoskeletal disorders,including osteoarthritis,rheumatoid arthritis,osteoporosis,bone fracture,intervertebral disc degeneration,tendinopathy,and myopathy,are prevalent conditions that profoundly impact quality of life and place substantial economic burdens on healthcare systems.Traditional bulk transcriptomics,genomics,proteomics,and metabolomics have played a pivotal role in uncovering disease-associated alterations at the population level.However,these approaches are inherently limited in their ability to resolve cellular heterogeneity or to capture the spatial organization of cells within tissues,thus hindering a comprehensive understanding of the complex cellular and molecular mechanisms underlying these diseases.To address these limitations,advanced single-cell and spatial omics techniques have emerged in recent years,offering unparalleled resolution for investigating cellular diversity,tissue microenvironments,and biomolecular interactions within musculoskeletal tissues.These cutting-edge techniques enable the detailed mapping of the molecular landscapes in diseased tissues,providing transformative insights into pathophysiological processes at both the single-cell and spatial levels.This review presents a comprehensive overview of the latest omics technologies as applied to musculoskeletal research,with a particular focus on their potential to revolutionize our understanding of disease mechanisms.Additionally,we explore the power of multi-omics integration in identifying novel therapeutic targets and highlight key challenges that must be overcome to successfully translate these advancements into clinical applications.
文摘1文献来源CHEN H,DENG C,GAO J,et al.Integrative spatial analysis reveals tumor heterogeneity and immune colony niche related to clinical outcomes in small cell lung cancer[J].Cancer Cell,2025,43(3):519−536.e5.doi:10.1016/j.ccell.2025.01.012.
基金supported by the National Natural Science Foundation of China(81973701 and 82204772)the Natural Science Foundation of Zhejiang Province(LZ20H290002)+2 种基金the Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine(ZYYCXTD-D-202002)the China Postdoctoral Science Foundation(2022M712811)Westlake Laboratory(Westlake Laboratory of Life Sciences and Biomedicine).
文摘Spatial omics technologies have become powerful methods to provide valuable insights into cells and tissues within a complex context,significantly enhancing our understanding of the intricate and multifaceted biological system.With an increasing focus on spatial heterogeneity,there is a growing need for unbiased,spatially resolved omics technologies.Laser capture microdissection(LCM)is a cutting-edge method for acquiring spatial information that can quickly collect regions of interest(ROIs)from heterogeneous tissues,with resolutions ranging from single cells to cell populations.Thus,LCM has been widely used for studying the cellular and molecular mechanisms of diseases.This review focuses on the differences among four types of commonly used LCM technologies and their applications in omics and disease research.Key attributes of application cases are also highlighted,such as throughput and spatial resolution.In addition,we comprehensively discuss the existing challenges and the great potential of LCM in biomedical research,disease diagnosis,and targeted therapy from the perspective of high-throughput,multi-omics,and single-cell resolution.
文摘The idea of accurately modeling life within a computer is no longer science fiction;it is becoming a reality through the rise of the virtual cell.Over the past few years,fueled by advances in single-cell and spatial omics,artificial intelligence(AI),and high-performance computing,virtual cells have rapidly evolved from abstract concepts into practical tools with the power to reshape biomedical research.Building on earlier,more constrained attempts at integration,today’s virtual cells can merge diverse data streams with sophisticated computational models,enabling comprehensive simulations of cellular structure,function,and behavior.1,2 In doing so,they provide an unprecedented platform for reconstructing and manipulating life and open transformative opportunities for intelligent oncology.The core technical framework,data foundations,and key potential application areas of virtual cells in intelligent oncology are illustrated in Figure 1.
基金support from Hangzhou Institute of Medicine,China(No.2024ZZBS11)Chinese Academy of Sciences,China Postdoctoral Science Foundation(No.2024M763331)+1 种基金National Oncology Clinical Key Specialty of China(No.2023-GJZK-001)Zhejiang Provincial Natural Science Foundation of China(No.LQN25H160009).
文摘Recent advances in spatial and single-cell omics have significantly revolutionized biomarker discovery in tumor immunotherapy by addressing critical challenges such as tumor heterogeneity,immune evasion,and variability within the tumor microenvironment(TME).Immunotherapeutic strategies,including immune checkpoint in-hibitors and adoptive T-cell transfer,have demonstrated promising clinical outcomes;however,their efficacy is limited by low response rates and the incidence of immune-related adverse events(irAEs).Therefore,the identification of reliable biomarkers is essential for predicting treatment efficacy,minimizing irAEs,and facili-tating patient stratification.Spatial omics integrates molecular profiling with spatial localization,thereby providing comprehensive insights into the cellular organization and functional states within the TME.By elucidating the spatial patterns of immune cell infiltration and tumor heterogeneity,this approach enhances the prediction of therapeutic responses.Similarly,single-cell omics enables high-resolution analysis of cellular heterogeneity by capturing transcriptomic,epigenomic,and metabolic signatures at the single-cell level.The integrated application of spatial and single-cell omics has enabled the identification of previously undetected biomarkers,including rare immune cell subsets implicated in resistance mechanisms.In addition to spatial transcriptomics(ST),this technological landscape also includes spatial proteomics(SP)and spatial metab-olomics,which further facilitate the study of dynamic tumor-immune interactions.Multi-omics integration provides a comprehensive overview of biomarker landscapes,while the rapid evolution of artificial intelligence(AI)-based approaches enhances the analysis of complex,multidimensional datasets to ultimately enhance pre-dictive potential and clinical utility.Despite substantial progress,several challenges remain in the context of standardization,data integration,and real-time monitoring.Nevertheless,the incorporation of spatial and single-cell omics into biomarker research holds transformative potential for advancing personalized cancer immuno-therapy.These emerging strategies pave the way for the development of innovative diagnostic and therapeutic interventions,thereby enabling precision oncology and improving treatment outcomes across a wide range of tumor profiles.This review aims to provide a comprehensive overview of the integration of spatial omics with single-cell omics in the discovery of biomarkers for tumor immunotherapy.Specifically,it examines the strategies by which these emerging technologies address the challenges related to tumor heterogeneity,immune evasion,and the dynamic nature of the TME.By elaborating on the principles,applications,and clinical potential of these technologies,this review also critically evaluates their limitations,challenges,and the current gaps in clinical translation.
