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Genetics and Genomics

Spatial omics technology potentially promotes the progress of tumor immunotherapy

Abstract

Immunotherapy has become an indispensable modality in the treatment of cancer, yet challenges such as resistance and substantial variability in therapeutic responses among patients remain significant obstacles. Key technologies, including spatial omics, have emerged as critical methods for exploring the complex tumor microenvironment. Increasing evidence suggests that, compared to single-cell sequencing, spatial omics technologies offer the advantage of preserving spatial context and integrating multimodal analyses, thereby advancing our understanding of complex interactions within biological tissues. In this perspective article, we present a comprehensive overview of the origins, classifications, and characteristics of various modalities of spatial omics analyses. Furthermore, we discuss the heterogeneity of the TME in the spatial context, such as the phenotypic differences between B cells and T cells near normal versus tumorous tissues—where they predominantly express immune-suppressive receptors in proximity to the tumor. Additionally, we summarize the applications of spatial omics in different cancer therapies, recent advancements in exploring cellular interactions and tertiary lymphoid structures, and the challenges faced in clinical translation. In light of these findings, we advocate for a broader application of spatial omics, combined with other technologies, as this will unveil overlooked therapeutic targets and could potentially realize precision immunotherapy for cancer.

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Fig. 1: Heterogeneity of tumour immune microenvironment.
Fig. 2: Characteristics of different immune cells.
Fig. 3: Immunosuppressive mechanisms of different tumours.

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References

  1. Zhang L, Shao J, Liu Z, Pan J, Li B, Yang Y, et al. Correction to: occurrence and prognostic value of perineural invasion in esophageal squamous cell cancer: a retrospective study. Ann Surg Oncol. 2021;28:897.

    Article  PubMed  Google Scholar 

  2. Attili I, Passaro A, de Marinis F. Anti-TIGIT to overcome resistance to immune checkpoint inhibitors in lung cancer: limits and potentials. Ann Oncol. 2022;33:119–22.

    Article  CAS  PubMed  Google Scholar 

  3. Hu Y, Zhang M, Yang T, Mo Z, Wei G, Jing R, et al. Sequential CD7 CAR T-cell therapy and allogeneic HSCT without GVHD prophylaxis. N Engl J Med. 2024;390:1467–80.

    Article  CAS  PubMed  Google Scholar 

  4. Mailankody S, Devlin SM, Landa J, Nath K, Diamonte C, Carstens EJ, et al. GPRC5D-targeted CAR T cells for myeloma. N Engl J Med. 2022;387:1196–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Awad MM, Govindan R, Balogh KN, Spigel DR, Garon EB, Bushway ME, et al. Personalized neoantigen vaccine NEO-PV-01 with chemotherapy and anti-PD-1 as first-line treatment for non-squamous non-small cell lung cancer. Cancer Cell. 2022;40:1010–26.e11.

    Article  CAS  PubMed  Google Scholar 

  6. Dooling LJ, Andrechak JC, Hayes BH, Kadu S, Zhang W, Pan R, et al. Cooperative phagocytosis of solid tumours by macrophages triggers durable anti-tumour responses. Nat Biomed Eng. 2023;7:1081–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Dacek MM, Kurtz KG, Wallisch P, Pierre SA, Khayat S, Bourne CM, et al. Potentiating antibody-dependent killing of cancers with CAR T cells secreting CD47-SIRPα checkpoint blocker. Blood. 2023;141:2003–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Reina-Campos M, Heeg M, Kennewick K, Mathews IT, Galletti G, Luna V, et al. Metabolic programs of T cell tissue residency empower tumour immunity. Nature. 2023;621:179–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Qi C, Gong J, Li J, Liu D, Qin Y, Ge S, et al. Claudin18.2-specific CAR T cells in gastrointestinal cancers: phase 1 trial interim results. Nat Med. 2022;28:1189–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Dimitri A, Herbst F, Fraietta JA. Engineering the next-generation of CAR T-cells with CRISPR-Cas9 gene editing. Mol Cancer. 2022;21:78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Vignali PDA, DePeaux K, Watson MJ, Ye C, Ford BR, Lontos K, et al. Hypoxia drives CD39-dependent suppressor function in exhausted T cells to limit antitumor immunity. Nat Immunol. 2023;24:267–79.

    Article  CAS  PubMed  Google Scholar 

  12. Zhu J, Naulaerts S, Boudhan L, Martin M, Gatto L, Van den Eynde BJ. Tumour immune rejection triggered by activation of α2-adrenergic receptors. Nature. 2023;618:607–15.

    Article  CAS  PubMed  Google Scholar 

  13. Sun D, Liu J, Zhou H, Shi M, Sun J, Zhao S, et al. Classification of tumor immune microenvironment according to Programmed Death-Ligand 1 expression and immune infiltration predicts response to immunotherapy plus chemotherapy in advanced patients with NSCLC. J Thorac Oncol. 2023;18:869–81.

    Article  CAS  PubMed  Google Scholar 

  14. Koti M, Robert Siemens D. A step closer to predicting progression after Bacillus Calmette-Guérin immunotherapy in high-risk non-muscle-invasive bladder cancer. Eur Urol. 2023;84:447–48.

    Article  CAS  PubMed  Google Scholar 

  15. Wang S, Zhang L, Jin Z, Wang Y, Zhang B, Zhao L. Visualizing temporal dynamics and research trends of macrophage-related diabetes studies between 2000 and 2022: a bibliometric analysis. Front Immunol. 2023;14:1194738.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Scheiner B, Pomej K, Kirstein MM, Hucke F, Finkelmeier F, Waidmann O, et al. Prognosis of patients with hepatocellular carcinoma treated with immunotherapy - development and validation of the CRAFITY score. J Hepatol. 2022;76:353–63.

    Article  CAS  PubMed  Google Scholar 

  17. Yang B, Li X, Zhang W, Fan J, Zhou Y, Li W, et al. Spatial heterogeneity of infiltrating T cells in high-grade serous ovarian cancer revealed by multi-omics analysis. Cell Rep Med. 2022;3:100856.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Xue R, Zhang Q, Cao Q, Kong R, Xiang X, Liu H, et al. Liver tumour immune microenvironment subtypes and neutrophil heterogeneity. Nature. 2022;612:141–47.

    Article  CAS  PubMed  Google Scholar 

  19. Wu VH, Yung BS, Faraji F, Saddawi-Konefka R, Wang Z, Wenzel AT, et al. The GPCR-Gα(s)-PKA signaling axis promotes T cell dysfunction and cancer immunotherapy failure. Nat Immunol. 2023;24:1318–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Liu Y, Xun Z, Ma K, Liang S, Li X, Zhou S, et al. Identification of a tumour immune barrier in the HCC microenvironment that determines the efficacy of immunotherapy. J Hepatol. 2023;78:770–82.

    Article  CAS  PubMed  Google Scholar 

  21. Zhao P, Zhu J, Ma Y, Zhou X. Modeling zero inflation is not necessary for spatial transcriptomics. Genome Biol. 2022;23:118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Park HE, Jo SH, Lee RH, Macks CP, Ku T, Park J, et al. Spatial transcriptomics: technical aspects of recent developments and their applications in neuroscience and cancer research. Adv Sci. 2023;10:e2206939.

    Article  Google Scholar 

  23. Robles-Remacho A, Sanchez-Martin RM, Diaz-Mochon JJ. Spatial transcriptomics: emerging technologies in tissue gene expression profiling. Anal Chem. 2023;95:15450–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Valihrach L, Zucha D, Abaffy P, Kubista M. A practical guide to spatial transcriptomics. Mol Asp Med. 2024;97:101276.

    Article  CAS  Google Scholar 

  25. Kim Y, Cheng W, Cho CS, Hwang Y, Si Y, Park A, et al. Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics. Nat Protoc. 2025;20:643–89.

    Article  CAS  PubMed  Google Scholar 

  26. Cross AR, Gartner L, Hester J, Issa F. Opportunities for high-plex spatial transcriptomics in solid organ transplantation. Transplantation. 2023;107:2464–72.

    Article  PubMed  Google Scholar 

  27. Yan Y, Luo X. BACT: nonparametric Bayesian cell typing for single-cell spatial transcriptomics data. Brief Bioinform. 2024;26:bbae689.

    Article  PubMed  Google Scholar 

  28. Dries R, Chen J, Del Rossi N, Khan MM, Sistig A, Yuan GC. Advances in spatial transcriptomic data analysis. Genome Res. 2021;31:1706–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Li J, Chen S, Pan X, Yuan Y, Shen HB. Cell clustering for spatial transcriptomics data with graph neural networks. Nat Comput Sci. 2022;2:399–408.

    Article  CAS  PubMed  Google Scholar 

  30. Zhou Z, Zhong Y, Zhang Z, Ren X. Spatial transcriptomics deconvolution at single-cell resolution using Redeconve. Nat Commun. 2023;14:7930.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Luo J, Fu J, Lu Z, Tu J. Deep learning in integrating spatial transcriptomics with other modalities. Brief Bioinform. 2024;26:bbae719.

    Article  PubMed  Google Scholar 

  32. Zhao Y, Long C, Shang W, Si Z, Liu Z, Feng Z, et al. A composite scaling network of EfficientNet for improving spatial ___domain identification performance. Commun Biol. 2024;7:1567.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zhong C, Ang KS, Chen J. Interpretable spatially aware dimension reduction of spatial transcriptomics with STAMP. Nat Methods. 2024;21:2072–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Liu W, Wang B, Bai Y, Liang X, Xue L, Luo J. SpaGIC: graph-informed clustering in spatial transcriptomics via self-supervised contrastive learning. Brief Bioinform. 2024;25:bbae578.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Wang Y, Liu Z, Ma X. MNMST: topology of cell networks leverages identification of spatial domains from spatial transcriptomics data. Genome Biol. 2024;25:133.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Sun D, Liu Z, Li T, Wu Q, Wang C. STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing. Nucleic Acids Res. 2022;50:e42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. McKellar DW, Mantri M, Hinchman MM, Parker JSL, Sethupathy P, Cosgrove BD, et al. Spatial mapping of the total transcriptome by in situ polyadenylation. Nat Biotechnol. 2023;41:513–20.

    Article  CAS  PubMed  Google Scholar 

  38. Wang Q, Zhu H, Deng L, Xu S, Xie W, Li M, et al. Spatial transcriptomics: biotechnologies, computational tools, and neuroscience applications. Small Methods. 2025;9:e2401107.

  39. Han S, Xu Q, Du Y, Tang C, Cui H, Xia X, et al. Single-cell spatial transcriptomics in cardiovascular development, disease, and medicine. Genes Dis. 2024;11:101163.

    Article  CAS  PubMed  Google Scholar 

  40. Baul S, Tanvir Ahmed K, Jiang Q, Wang G, Li Q, Yong J, et al. Integrating spatial transcriptomics and bulk RNA-seq: predicting gene expression with enhanced resolution through graph attention networks. Brief Bioinform. 2024;25:bbae316.

  41. An J, Lu Y, Chen Y, Chen Y, Zhou Z, Chen J, et al. Spatial transcriptomics in breast cancer: providing insight into tumor heterogeneity and promoting individualized therapy. Front Immunol. 2024;15:1499301.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Du J, Yang YC, An ZJ, Zhang MH, Fu XH, Huang ZF, et al. Advances in spatial transcriptomics and related data analysis strategies. J Transl Med. 2023;21:330.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Wu S, Qiu Y, Cheng X. ConSpaS: a contrastive learning framework for identifying spatial domains by integrating local and global similarities. Brief Bioinform. 2023;24:bbad395.

  44. Giacomello S. A new era for plant science: spatial single-cell transcriptomics. Curr Opin Plant Biol. 2021;60:102041.

    Article  CAS  PubMed  Google Scholar 

  45. Chen TY, You L, Hardillo JAU, Chien MP. Spatial transcriptomic technologies. Cells. 2023;12:2042.

  46. Chen H, Zhang Y, Zhou H, Chen W, Peng J, Feng Y, et al. Routine workflow of spatial proteomics on micro-formalin-fixed paraffin-embedded tissues. Anal Chem. 2023;95:16733–43.

    Article  CAS  PubMed  Google Scholar 

  47. Faktor J, Kote S, Bienkowski M, Hupp TR, Marek-Trzonkowska N. Novel FFPE proteomics method suggests prolactin induced protein as hormone induced cytoskeleton remodeling spatial biomarker. Commun Biol. 2024;7:708.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Griesser E, Wyatt H, Ten Have S, Stierstorfer B, Lenter M, Lamond AI. Quantitative Profiling of the Human Substantia Nigra Proteome from Laser-capture microdissected FFPE tissue. Mol Cell Proteom. 2020;19:839–51.

    Article  Google Scholar 

  49. Dong Z, Jiang W, Wu C, Chen T, Chen J, Ding X, et al. Spatial proteomics of single cells and organelles on tissue slides using filter-aided expansion proteomics. Nat Commun. 2024;15:9378.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Guo G, Papanicolaou M, Demarais NJ, Wang Z, Schey KL, Timpson P, et al. Automated annotation and visualisation of high-resolution spatial proteomic mass spectrometry imaging data using HIT-MAP. Nat Commun. 2021;12:3241.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Conroy LR, Chang JE, Sun Q, Clarke HA, Buoncristiani MD, Young LEA, et al. High-dimensionality reduction clustering of complex carbohydrates to study lung cancer metabolic heterogeneity. Adv Cancer Res. 2022;154:227–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kreutzer L, Weber P, Heider T, Heikenwälder M, Riedl T, Baumeister P, et al. Simultaneous metabolite MALDI-MSI, whole exome and transcriptome analysis from formalin-fixed paraffin-embedded tissue sections. Lab Invest. 2022;102:1400–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Chen R, Xu J, Wang B, Ding Y, Abdulla A, Li Y, et al. SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging. Nat Commun. 2024;15:2708.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Hosogane T, Casanova R, Bodenmiller B. DNA-barcoded signal amplification for imaging mass cytometry enables sensitive and highly multiplexed tissue imaging. Nat Methods. 2023;20:1304–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Li JR, Shaw V, Lin Y, Wang X, Aminu M, Li Y, et al. The prognostic effect of infiltrating immune cells is shaped by proximal M2 macrophages in lung adenocarcinoma. Mol Cancer. 2024;23:185.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Bao K, Chen X, Chen R, Gao Y, Dang J, He J, et al. Zr-NMOF tagged with heterobifunctionalized aptamers for highly sensitive, multiplexed and rapid imaging mass cytometry. Nanoscale. 2024;16:22283–96.

    Article  CAS  PubMed  Google Scholar 

  57. Mou M, Pan Z, Lu M, Sun H, Wang Y, Luo Y, et al. Application of machine learning in spatial proteomics. J Chem Inf Model. 2022;62:5875–95.

    Article  CAS  PubMed  Google Scholar 

  58. Du Y, Ding X, Ye Y. The spatial multi-omics revolution in cancer therapy: Precision redefined. Cell Rep Med. 2024;5:101740.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Zhang Y, Lee RY, Tan CW, Guo X, Yim WW, Lim JC, et al. Spatial omics techniques and data analysis for cancer immunotherapy applications. Curr Opin Biotechnol. 2024;87:103111.

    Article  CAS  PubMed  Google Scholar 

  60. Christopher JA, Geladaki A, Dawson CS, Vennard OL, Lilley KS. Subcellular transcriptomics and proteomics: a comparative methods review. Mol Cell Proteom. 2022;21:100186.

    Article  CAS  Google Scholar 

  61. Lewis SM, Asselin-Labat ML, Nguyen Q, Berthelet J, Tan X, Wimmer VC, et al. Spatial omics and multiplexed imaging to explore cancer biology. Nat Methods. 2021;18:997–1012.

    Article  CAS  PubMed  Google Scholar 

  62. Liu B, Meng X, Li K, Guo J, Cai Z. Visualization of lipids in cottonseeds by matrix-assisted laser desorption/ionization mass spectrometry imaging. Talanta. 2021;221:121614.

    Article  CAS  PubMed  Google Scholar 

  63. Liu P, Chen L, Zhang G, Hu Z, Zhang Y, Zhao Q, et al. Spatial lipidomic profiling reveals distinct lipid distribution patterns in poplar buds during growth and dormancy. Plant Cell Environ. 2025.

  64. Song X, Zang Q, Zare RN. Hydrogen-Deuterium exchange desorption electrospray ionization mass spectrometry visualizes an acidic tumor microenvironment. Anal Chem. 2021;93:10411–17.

    Article  CAS  PubMed  Google Scholar 

  65. Soudah T, Zoabi A, Margulis K. Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies. Mass Spectrom Rev. 2023;42:751–78.

    Article  CAS  PubMed  Google Scholar 

  66. Planque M, Igelmann S, Ferreira Campos AM, Fendt SM. Spatial metabolomics principles and application to cancer research. Curr Opin Chem Biol. 2023;76:102362.

    Article  CAS  PubMed  Google Scholar 

  67. Wang J, Sun N, Kunzke T, Shen J, Zens P, Prade VM, et al. Spatial metabolomics identifies distinct tumor-specific and stroma-specific subtypes in patients with lung squamous cell carcinoma. NPJ Precis Oncol. 2023;7:114.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zemaitis KJ, Lin VS, Ahkami AH, Winkler TE, Anderton CR, Veličković D. Expanded coverage of phytocompounds by mass spectrometry imaging using on-tissue chemical derivatization by 4-APEBA. Anal Chem. 2023;95:12701–09.

    Article  CAS  PubMed  Google Scholar 

  69. Dreisbach D, Heiles S, Bhandari DR, Petschenka G, Spengler B. Molecular networking and on-tissue chemical derivatization for enhanced identification and visualization of steroid Glycosides by MALDI Mass Spectrometry Imaging. Anal Chem. 2022;94:15971–79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Mavroudakis L, Golubova A, Lanekoff I. Spatial metabolomics platform combining mass spectrometry imaging and in-depth chemical characterization with capillary electrophoresis. Talanta. 2025;286:127460.

    Article  CAS  PubMed  Google Scholar 

  71. Min X, Zhao Y, Yu M, Zhang W, Jiang X, Guo K, et al. Spatially resolved metabolomics: From metabolite mapping to function visualising. Clin Transl Med. 2024;14:e70031.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Luo L, Ma W, Liang K, Wang Y, Su J, Liu R, et al. Spatial metabolomics reveals skeletal myofiber subtypes. Sci Adv. 2023;9:eadd0455.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Wang G, Heijs B, Kostidis S, Mahfouz A, Rietjens RGJ, Bijkerk R, et al. Analyzing cell-type-specific dynamics of metabolism in kidney repair. Nat Metab. 2022;4:1109–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Wang F, Ma S, Chen P, Han Y, Liu Z, Wang X, et al. Imaging the metabolic reprograming of fatty acid synthesis pathway enables new diagnostic and therapeutic opportunity for breast cancer. Cancer Cell Int. 2023;23:83.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Källback P, Vallianatou T, Nilsson A, Shariatgorji R, Schintu N, Pereira M, et al. Cross-validated Matrix-Assisted Laser Desorption/Ionization mass spectrometry imaging quantitation protocol for a pharmaceutical drug and its drug-target effects in the brain using time-of-flight and fourier transform ion cyclotron resonance analyzers. Anal Chem. 2020;92:14676–84.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Sun C, Wang F, Zhang Y, Yu J, Wang X. Mass spectrometry imaging-based metabolomics to visualize the spatially resolved reprogramming of carnitine metabolism in breast cancer. Theranostics. 2020;10:7070–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Vandenbosch M, Mutuku SM, Mantas MJQ, Patterson NH, Hallmark T, Claesen M, et al. Toward omics-scale quantitative mass spectrometry imaging of lipids in brain tissue using a multiclass internal standard mixture. Anal Chem. 2023;95:18719–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Qian Y, Ma X. Advances in Tandem Mass Spectrometry imaging for next-generation spatial metabolomics. Anal Chem. 2025;97:7589–99.

  79. Nguyen K, Carleton G, Lum JJ, Duncan KD. Expanding spatial metabolomics coverage with lithium-doped nanospray desorption electrospray ionization Mass Spectrometry Imaging. Anal Chem. 2024;96:18427–36.

    Article  CAS  PubMed  Google Scholar 

  80. Schwaiger-Haber M, Stancliffe E, Anbukumar DS, Sells B, Yi J, Cho K, et al. Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem. Nat Commun. 2023;14:2876.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. MacFawn IP, Magnon G, Gorecki G, Kunning S, Rashid R, Kaiza ME, et al. The activity of tertiary lymphoid structures in high grade serous ovarian cancer is governed by site, stroma, and cellular interactions. Cancer Cell. 2024;42:1864–81.e5.

    Article  CAS  PubMed  Google Scholar 

  82. Jerby-Arnon L, Regev A. DIALOGUE maps multicellular programs in tissue from single-cell or spatial transcriptomics data. Nat Biotechnol. 2022;40:1467–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Anderson AC, Yanai I, Yates LR, Wang L, Swarbrick A, Sorger P, et al. Spatial transcriptomics. Cancer Cell. 2022;40:895–900.

    Article  PubMed  Google Scholar 

  84. Liang L, Kuang X, He Y, Zhu L, Lau P, Li X, et al. Alterations in PD-L1 succinylation shape anti-tumor immune responses in melanoma. Nat Genet. 2025;57:680–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Qiu X, Zhou T, Li S, Wu J, Tang J, Ma G, et al. Spatial single-cell protein landscape reveals vimentin(high) macrophages as immune-suppressive in the microenvironment of hepatocellular carcinoma. Nat Cancer. 2024;5:1557–78.

    Article  CAS  PubMed  Google Scholar 

  86. Wang Y, Fan JL, Melms JC, Amin AD, Georgis Y, Barrera I, et al. Multimodal single-cell and whole-genome sequencing of small, frozen clinical specimens. Nat Genet. 2023;55:19–25.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Jackson C, Cherry C, Bom S, Dykema AG, Wang R, Thompson E, et al. Distinct myeloid-derived suppressor cell populations in human glioblastoma. Science. 2025;387:eabm5214.

    Article  CAS  PubMed  Google Scholar 

  88. Liu C, Nguyen RY, Pizzurro GA, Zhang X, Gong X, Martinez AR, et al. Self-assembly of mesoscale collagen architectures and applications in 3D cell migration. Acta Biomater. 2023;155:167–81.

    Article  CAS  PubMed  Google Scholar 

  89. Croizer H, Mhaidly R, Kieffer Y, Gentric G, Djerroudi L, Leclere R, et al. Deciphering the spatial landscape and plasticity of immunosuppressive fibroblasts in breast cancer. Nat Commun. 2024;15:2806.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Zhang R, Feng Y, Ma W, Guo Y, Luo M, Li Y, et al. Spatial transcriptome unveils a discontinuous inflammatory pattern in proficient mismatch repair colorectal adenocarcinoma. Fundam Res. 2023;3:640–46.

    Article  CAS  PubMed  Google Scholar 

  91. Ye QW, Liu YJ, Li JQ, Han M, Bian ZR, Chen TY, et al. GJA4 expressed on cancer associated fibroblasts (CAFs)-A ‘promoter’ of the mesenchymal phenotype. Transl Oncol. 2024;46:102009.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Wang X, Hu LP, Qin WT, Yang Q, Chen DY, Li Q, et al. Identification of a subset of immunosuppressive P2RX1-negative neutrophils in pancreatic cancer liver metastasis. Nat Commun. 2021;12:174.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Li Y, Chang RB, Stone ML, Delman D, Markowitz K, Xue Y, et al. Multimodal immune phenotyping reveals microbial-T cell interactions that shape pancreatic cancer. Cell Rep Med. 2024;5:101397.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Musiu C, Adamo A, Caligola S, Agostini A, Frusteri C, Lupo F, et al. Local ablation disrupts immune evasion in pancreatic cancer. Cancer Lett. 2025;609:217327.

    Article  CAS  PubMed  Google Scholar 

  95. Zhang H, Wang M, Xu Y. Understanding the mechanisms underlying obesity in remodeling the breast tumor immune microenvironment: from the perspective of inflammation. Cancer Biol Med. 2023;20:268–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Zhu Y, Banerjee A, Xie P, Ivanov AA, Uddin A, Jiao Q, et al. Pharmacological suppression of the OTUD4/CD73 proteolytic axis revives antitumor immunity against immune-suppressive breast cancers. J Clin Invest. 2024;134:e176390.

  97. Mirzaei R, D’Mello C, Liu M, Nikolic A, Kumar M, Visser F, et al. Single-cell spatial analysis identifies regulators of brain tumor-initiating cells. Cancer Res. 2023;83:1725–41.

    Article  CAS  PubMed  Google Scholar 

  98. Ravi VM, Neidert N, Will P, Joseph K, Maier JP, Kückelhaus J, et al. T-cell dysfunction in the glioblastoma microenvironment is mediated by myeloid cells releasing interleukin-10. Nat Commun. 2022;13:925.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Walsh LA, Quail DF. Decoding the tumor microenvironment with spatial technologies. Nat Immunol. 2023;24:1982–93.

    Article  CAS  PubMed  Google Scholar 

  100. Sloan L, Sen R, Liu C, Doucet M, Blosser L, Katulis L, et al. Radiation immunodynamics in patients with glioblastoma receiving chemoradiation. Front Immunol. 2024;15:1438044.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Liu X, Chen C, Li J, Li L, Ma M. Identification of tumor-specific T cell signature predicting cancer immunotherapy response in bladder cancer by multi-omics analysis and experimental verification. Cancer Cell Int. 2024;24:255.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Mohr AE, Hatem C, Sikand G, Rozga M, Moloney L, Sullivan J, et al. Effectiveness of medical nutrition therapy in the management of adult dyslipidemia: A systematic review and meta-analysis. J Clin Lipido. 2022;16:547–61.

    Article  Google Scholar 

  103. Zheng X, Mund A, Mann M. Deciphering functional tumor-immune crosstalk through highly multiplexed imaging and deep visual proteomics. Mol Cell. 2025;85:1008–23.e7.

    Article  CAS  PubMed  Google Scholar 

  104. Akiyama T, Yasuda T, Uchihara T, Yasuda-Yoshihara N, Tan BJY, Yonemura A, et al. Stromal reprogramming through dual PDGFRα/β blockade boosts the efficacy of anti-PD-1 immunotherapy in fibrotic tumors. Cancer Res. 2023;83:753–70.

    Article  CAS  PubMed  Google Scholar 

  105. Ma C, Yang C, Peng A, Sun T, Ji X, Mi J, et al. Pan-cancer spatially resolved single-cell analysis reveals the crosstalk between cancer-associated fibroblasts and tumor microenvironment. Mol Cancer. 2023;22:170.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Hsieh WC, Budiarto BR, Wang YF, Lin CY, Gwo MC, So DK, et al. Spatial multi-omics analyses of the tumor immune microenvironment. J Biomed Sci. 2022;29:96.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Walker CR, Angelo M. Insights and opportunity costs in applying spatial biology to study the tumor microenvironment. Cancer Discov. 2024;14:707–10.

    Article  PubMed  Google Scholar 

  108. Vadakekolathu J, Rutella S. Escape from T-cell-targeting immunotherapies in acute myeloid leukemia. Blood. 2024;143:2689–700.

    Article  CAS  PubMed  Google Scholar 

  109. Zhang Z, Bao S, Yan C, Hou P, Zhou M, Sun J. Computational principles and practice for decoding immune contexture in the tumor microenvironment. Brief Bioinform. 2021;22:bbaa075.

  110. Li S, Zhang N, Zhang H, Yang Z, Cheng Q, Wei K, et al. Deciphering the role of LGALS2: insights into tertiary lymphoid structure-associated dendritic cell activation and immunotherapeutic potential in breast cancer patients. Mol Cancer. 2024;23:216.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Xun Z, Zhou H, Shen M, Liu Y, Sun C, Du Y, et al. Identification of Hypoxia-ALCAM(high) macrophage- exhausted T cell axis in tumor microenvironment remodeling for immunotherapy resistance. Adv Sci. 2024;11:e2309885.

    Article  Google Scholar 

  112. Sun L, Kienzler JC, Reynoso JG, Lee A, Shiuan E, Li S, et al. Immune checkpoint blockade induces distinct alterations in the microenvironments of primary and metastatic brain tumors. J Clin Invest. 2023;133:e169314.

  113. Tian H, Sparvero LJ, Anthonymuthu TS, Sun WY, Amoscato AA, He RR, et al. successive high-resolution (H(2)O)(n)-GCIB and C(60)-SIMS imaging integrates multi-omics in different cell types in breast cancer tissue. Anal Chem. 2021;93:8143–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Surwase SS, Zhou XMM, Luly KM, Zhu Q, Anders RA, Green JJ, et al. Highly multiplexed immunofluorescence phenocycler panel for murine formalin-fixed paraffin-embedded tissues yields insight into tumor microenvironment immunoengineering. Lab Invest. 2025;105:102165.

    Article  CAS  PubMed  Google Scholar 

  115. Lapuente-Santana Ó, Sturm G, Kant J, Ausserhofer M, Zackl C, Zopoglou M, et al. Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion. iScience. 2024;27:110529.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Szalay AS, Taube JM. Data-rich spatial profiling of cancer tissue: astronomy informs pathology. Clin Cancer Res. 2022;28:3417–24.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Houel A, Foloppe J, Dieu-Nosjean MC. Harnessing the power of oncolytic virotherapy and tertiary lymphoid structures to amplify antitumor immune responses in cancer patients. Semin Immunol. 2023;69:101796.

    Article  CAS  PubMed  Google Scholar 

  118. Berthe J, Poudel P, Segerer FJ, Jennings EC, Ng F, Surace M, et al. Exploring the impact of tertiary lymphoid structures maturity in NSCLC: insights from TLS scoring. Front Immunol. 2024;15:1422206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Schumacher TN, Thommen DS. Tertiary lymphoid structures in cancer. Science. 2022;375:eabf9419.

    Article  CAS  PubMed  Google Scholar 

  120. Zhang Y, Xu M, Ren Y, Ba Y, Liu S, Zuo A, et al. Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application. Mol Cancer. 2024;23:75.

    Article  PubMed  PubMed Central  Google Scholar 

  121. Jiang L, Wang P, Hou Y, Chen J, Li H. Comprehensive single-cell pan-cancer atlas unveils IFI30+ macrophages as key modulators of intra-tumoral immune dynamics. Front Immunol. 2025;16:1523854.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Wu J, Koelzer VH. SST-editing: in silico spatial transcriptomic editing at single-cell resolution. Bioinformatics. 2024;40:btae077.

  123. Yao Y, Li B, Wang J, Chen C, Gao W, Li C. A novel HVEM-Fc recombinant protein for lung cancer immunotherapy. J Exp Clin Cancer Res. 2025;44:62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Cai F, Mao S, Peng S, Wang Z, Li W, Zhang R, et al. A comprehensive pan-cancer examination of transcription factor MAFF: Oncogenic potential, prognostic relevance, and immune landscape dynamics. Int Immunopharmacol. 2025;149:114105.

    Article  CAS  PubMed  Google Scholar 

  125. Zhang S, Deshpande A, Verma BK, Wang H, Mi H, Yuan L, et al. Integration of clinical trial spatial multiomics analysis and virtual clinical trials enables immunotherapy response prediction and biomarker discovery. Cancer Res. 2024;84:2734–48.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Wu Q, Liu Z, Gao Z, Luo Y, Li F, Yang C, et al. KLF5 inhibition potentiates anti-PD1 efficacy by enhancing CD8(+) T-cell-dependent antitumor immunity. Theranostics. 2023;13:1381–400.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Wang Y, Zhou SK, Wang Y, Lu ZD, Zhang Y, Xu CF, et al. Engineering tumor-specific gene nanomedicine to recruit and activate T cells for enhanced immunotherapy. Nat Commun. 2023;14:1993.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Chen W, He Y, Zhou G, Chen X, Ye Y, Zhang G, et al. Multiomics characterization of pyroptosis in the tumor microenvironment and therapeutic relevance in metastatic melanoma. BMC Med. 2024;22:24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Wang S, Kuai Y, Lin S, Li L, Gu Q, Zhang X, et al. NF-κB Activator 1 downregulation in macrophages activates STAT3 to promote adenoma-adenocarcinoma transition and immunosuppression in colorectal cancer. BMC Med. 2023;21:115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Hu Y, Jia H, Cui H, Song J. Application of spatial omics in the cardiovascular system. Research. 2025;8:0628.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Wan J, Sun Z, Feng X, Zhou P, Macho MTN, Jiao Z, et al. Spatial omics strategies for investigating human carotid atherosclerotic disease. Clin Transl Med. 2025;15:e70277.

    Article  PubMed  PubMed Central  Google Scholar 

  132. Liu J, Peng X, Yang S, Li X, Huang M, Wei S, et al. Extracellular vesicle PD-L1 in reshaping tumor immune microenvironment: biological function and potential therapy strategies. Cell Commun Signal. 2022;20:14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  133. Wang R, Hastings WJ, Saliba JG, Bao D, Huang Y, Maity S, et al. Applications of nanotechnology for spatial omics: biological structures and functions at nanoscale resolution. ACS Nano. 2025;19:73–100.

    Article  CAS  PubMed  Google Scholar 

  134. Marconato L, Palla G, Yamauchi KA, Virshup I, Heidari E, Treis T, et al. SpatialData: an open and universal data framework for spatial omics. Nat Methods. 2025;22:58–62.

    Article  CAS  PubMed  Google Scholar 

  135. Tran M, Yoon S, Teoh M, Andersen S, Lam PY, Purdue BW, et al. A robust experimental and computational analysis framework at multiple resolutions, modalities and coverages. Front Immunol. 2022;13:911873.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Jiang H, Gao B, Meng Z, Wang Y, Jiao T, Li J, et al. Integrative multi-omics analysis reveals the role of tumor-associated endothelial cells and their signature in prognosis of intrahepatic cholangiocarcinoma. J Transl Med. 2024;22:948.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  137. Haddad TS, Friedl P, Farahani N, Treanor D, Zlobec I, Nagtegaal I. Tutorial: methods for three-dimensional visualization of archival tissue material. Nat Protoc. 2021;16:4945–62.

    Article  CAS  PubMed  Google Scholar 

  138. Li W, Sun J, Sun R, Wei Y, Zheng J, Zhu Y, et al. Integral-omics: serial extraction and profiling of metabolome, lipidome, genome, transcriptome, whole proteome and phosphoproteome using biopsy tissue. Anal Chem. 2025;97:1190–98.

    Article  CAS  PubMed  Google Scholar 

  139. Decruyenaere P, Verniers K, Poma-Soto F, Van Dorpe J, Offner F, Vandesompele J. RNA extraction method impacts quality metrics and sequencing results in formalin-fixed, paraffin-embedded tissue samples. Lab Invest. 2023;103:100027.

    Article  CAS  PubMed  Google Scholar 

  140. Youssef O, Loukola A, Zidi-Mouaffak YHS, Tamlander M, Ruotsalainen S, Kilpeläinen E, et al. High-resolution genotyping of formalin-fixed tissue accurately estimates polygenic risk scores in human diseases. Lab Invest. 2024;104:100325.

    Article  CAS  PubMed  Google Scholar 

  141. Dube S, Al-Mannai S, Liu L, Tomei S, Hubrack S, Sherif S, et al. Systematic comparison of quantity and quality of RNA recovered with commercial FFPE tissue extraction kits. J Transl Med. 2025;23:11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  142. Kohale IN, Burgenske DM, Mladek AC, Bakken KK, Kuang J, Boughey JC, et al. Quantitative analysis of Tyrosine Phosphorylation from FFPE tissues reveals patient-specific signaling networks. Cancer Res. 2021;81:3930–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  143. Barnabas GD, Goebeler V, Tsui J, Bush JW, Lange PF. ASAP─automated sonication-free acid-assisted proteomes─from cells and FFPE tissues. Anal Chem. 2023;95:3291–99.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Wang FA, Zhuang Z, Gao F, He R, Zhang S, Wang L, et al. TMO-Net: an explainable pretrained multi-omics model for multi-task learning in oncology. Genome Biol. 2024;25:149.

    Article  PubMed  PubMed Central  Google Scholar 

  145. Verheijen M, Sarkans U, Wolski W, Jennen D, Caiment F, Kleinjans J. Multi-omics HeCaToS dataset of repeated dose toxicity for cardiotoxic & hepatotoxic compounds. Sci Data. 2022;9:699.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  146. Lita A, Sjöberg J, Păcioianu D, Siminea N, Celiku O, Dowdy T, et al. Raman-based machine-learning platform reveals unique metabolic differences between IDHmut and IDHwt glioma. Neuro Oncol. 2024;26:1994–2009.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Wang H, Li J, Jing S, Lin P, Qiu Y, Yan X, et al. SOAPy: a Python package to dissect spatial architecture, dynamics, and communication. Genome Biol. 2025;26:80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Zhao Z, Jiang M, He C, Yin W, Feng Y, Wang P, et al. Enhancing specific fluorescence in situ hybridization with quantum dots for single-molecule RNA imaging in formalin-fixed paraffin-embedded tumor tissues. ACS Nano. 2024;18:9958–68.

    Article  CAS  PubMed  Google Scholar 

  149. Jiang W, Zhang X, Xu Z, Cheng Q, Li X, Zhu Y, et al. High-throughput single-nucleus RNA profiling of minimal puncture FFPE samples reveals spatiotemporal heterogeneity of cancer. Adv Sci. 2025;12:e2410713.

    Article  Google Scholar 

  150. Good CJ, Neumann EK, Butrico CE, Cassat JE, Caprioli RM, Spraggins JM. High spatial resolution MALDI Imaging Mass Spectrometry of fresh-frozen bone. Anal Chem. 2022;94:3165–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Wu X, Xu W, Deng L, Li Y, Wang Z, Sun L, et al. Spatial multi-omics at subcellular resolution via high-throughput in situ pairwise sequencing. Nat Biomed Eng. 2024;8:872–89.

    Article  CAS  PubMed  Google Scholar 

  152. Fu Y, Tao J, Gu Y, Liu Y, Qiu J, Su D, et al. Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer. NPJ Precis Oncol. 2024;8:109.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Yu L, Wang X, Mu Q, Tam SST, Loi DSC, Chan AKY, et al. scONE-seq: A single-cell multi-omics method enables simultaneous dissection of phenotype and genotype heterogeneity from frozen tumors. Sci Adv. 2023;9:eabp8901.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Xie B, Gao D, Zhou B, Chen S, Wang L. New discoveries in the field of metabolism by applying single-cell and spatial omics. J Pharm Anal. 2023;13:711–25.

    Article  PubMed  PubMed Central  Google Scholar 

  155. Huo Y, Liu K, Lou X. Strong additive and synergistic effects of polyoxyethylene nonionic surfactant-assisted protein MALDI imaging mass spectrometry. Talanta. 2021;222:121524.

    Article  CAS  PubMed  Google Scholar 

  156. Lin J, Lin H, Li C, Liao N, Zheng Y, Yu X, et al. Unveiling characteristic metabolic accumulation over enzymatic-catalyzed process of Tieguanyin oolong tea manufacturing by DESI-MSI and multiple-omics. Food Res Int. 2024;181:114136.

    Article  CAS  PubMed  Google Scholar 

  157. Kataoka K, Mori K, Nakamura Y, Watanabe J, Akazawa N, Hirata K, et al. Survival benefit of adjuvant chemotherapy based on molecular residual disease detection in resected colorectal liver metastases: subgroup analysis from CIRCULATE-Japan GALAXY. Ann Oncol. 2024;35:1015–25.

    Article  CAS  PubMed  Google Scholar 

  158. Fu L, Zhou X, Zhang X, Li X, Zhang F, Gu H, et al. Circulating tumor DNA in lymphoma: technologies and applications. J Hematol Oncol. 2025;18:29.

    Article  PubMed  PubMed Central  Google Scholar 

  159. Coakley M, Villacampa G, Sritharan P, Swift C, Dunne K, Kilburn L, et al. Comparison of circulating tumor DNA assays for molecular residual disease detection in early-stage triple-negative breast cancer. Clin Cancer Res. 2024;30:895–903.

    Article  CAS  PubMed  Google Scholar 

  160. Tanaka I, Furukawa T, Morise M. The current issues and future perspective of artificial intelligence for developing new treatment strategy in non-small cell lung cancer: harmonization of molecular cancer biology and artificial intelligence. Cancer Cell Int. 2021;21:454.

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

This study was supported by Henan Youth and Middle-aged Health Science and Technology Innovation Leaders Training Project (NO. YXKC2022004). Henan Health Young and Middle-aged discipline Leader Project (NO. HNSWJW-2022011). Henan Medical Science and Technology Tackling Programme of Provincial-Ministry Joint Major Project (No. SBGJ202401004). Key Research and Development Projects of Henan Province (NO. 251111310100).

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Z.l. finished the manuscript and figures.Y.Y., L.L., C.W. collected the related paper. Y.L., Q.W. and Z.S. gave constructive guidance and made critical revisions.

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Lan, Z., Yang, Y., Li, L. et al. Spatial omics technology potentially promotes the progress of tumor immunotherapy. Br J Cancer (2025). https://doi.org/10.1038/s41416-025-03075-5

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