Search
Search
Close this search box.

Application of spatial-omics to the classification of kidney biopsy samples in transplantation – Nature Reviews Nephrology

  • Poggio, E. D., Augustine, J. J., Arrigain, S., Brennan, D. C. & Schold, J. D. Long-term kidney transplant graft survival-making progress when most needed. Am. J. Transpl. 21, 2824–2832 (2021).

    Article 

    Google Scholar
     

  • Van Loon, E. et al. Assessing the complex causes of kidney allograft loss. Transplantation 104, 2557–2566 (2020).

    Article 
    PubMed 

    Google Scholar
     

  • Mayrdorfer, M. et al. Exploring the complexity of death-censored kidney allograft failure. J. Am. Soc. Nephrol. 32, 1513–1526 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • D’Agati, V. D. et al. Obesity-related glomerulopathy: clinical and pathologic characteristics and pathogenesis. Nat. Rev. Nephrol. 12, 453–471 (2016).

    Article 
    PubMed 

    Google Scholar
     

  • D’Costa, M. R. et al. Chronic histologic changes are present regardless of HLA mismatches: evidence from HLA-identical living donor kidney transplants. Transplantation 105, e244–e256 (2021).

    Article 
    PubMed 

    Google Scholar
     

  • de Vries, A. P. J. et al. Insulin resistance as putative cause of chronic renal transplant dysfunction. Am. J. Kidney Dis. 41, 859–867 (2003).

    Article 
    PubMed 

    Google Scholar
     

  • Halloran, P. F., Madill-Thomsen, K. S. & Reeve, J. The molecular phenotype of kidney transplants: insights from the MMDx project. Transplantation 108, 45–71 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Madill-Thomsen, K. et al. Discrepancy analysis comparing molecular and histology diagnoses in kidney transplant biopsies. Am. J. Transplant. 20, 1341–1350 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Loupy, A., Mengel, M. & Haas, M. Thirty years of the International Banff Classification for Allograft Pathology: the past, present, and future of kidney transplant diagnostics. Kidney Int. 101, 678–691 (2022).

    Article 
    PubMed 

    Google Scholar
     

  • Callemeyn, J. et al. Allorecognition and the spectrum of kidney transplant rejection. Kidney Int. 101, 692–710 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Harden, P. N. et al. Feasibility, long-term safety, and immune monitoring of regulatory T cell therapy in living donor kidney transplant recipients. Am. J. Transpl. 21, 1603–1611 (2021).

    Article 
    CAS 

    Google Scholar
     

  • Williams, C. G., Lee, H. J., Asatsuma, T., Vento-Tormo, R. & Haque, A. An introduction to spatial transcriptomics for biomedical research. Genome Med. 14, 68 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lamarthée, B. et al. Transcriptional and spatial profiling of the kidney allograft unravels a central role for FcyRIII+ innate immune cells in rejection. Nat. Commun. 14, 4359 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Loupy, A. et al. Prediction system for risk of allograft loss in patients receiving kidney transplants: international derivation and validation study. BMJ 366, 4923 (2019).

    Article 

    Google Scholar
     

  • Raynaud, M. et al. Dynamic prediction of renal survival among deeply phenotyped kidney transplant recipients using artificial intelligence: an observational, international, multicohort study. Lancet Digital Health 3, e795–e805 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Zwart, T. C. et al. Volumetric microsampling for simultaneous remote immunosuppressant and kidney function monitoring in outpatient kidney transplant recipients. Br. J. Clin. Pharmacol. 88, 4854–4869 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Davis, S. et al. Adequate tacrolimus exposure modulates the impact of HLA class II molecular mismatch: a validation study in an American cohort. Am. J. Transpl. 21, 322–328 (2021).

    Article 
    CAS 

    Google Scholar
     

  • Meziyerh, S. et al. Tacrolimus and mycophenolic acid exposure are associated with biopsy-proven acute rejection: a study to provide evidence for longer-term target ranges. Clin. Pharmacol. Ther. 114, 192–200 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Gold, A., Tönshoff, B., Döhler, B. & Süsal, C. Association of graft survival with tacrolimus exposure and late intra-patient tacrolimus variability in pediatric and young adult renal transplant recipients — an international CTS registry analysis. Transpl. Int. 33, 1681–1692 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • van den Broek, D. A. J. et al. The clinical utility of post-transplant monitoring of donor-specific antibodies in stable renal transplant recipients: a consensus report with guideline statements for clinical practice. Transpl. Int. 36, 11321 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Doberer, K. et al. Torque teno virus load is associated with subclinical alloreactivity in kidney transplant recipients: a prospective observational trial. Transplantation 105, 2112–2118 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Park, S. et al. European Society of Organ Transplantation consensus statement on testing for non-invasive diagnosis of kidney allograft rejection. Transpl. Int. 36, 12115 (2024).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Van Loon, E. et al. Automated urinary chemokine assays for noninvasive detection of kidney transplant rejection: a prospective cohort study. Am. J. Kidney Dis. 83, 467–476 (2023).

    Article 
    PubMed 

    Google Scholar
     

  • Nankivell, B. J. et al. The natural history of chronic allograft nephropathy. N. Engl. J. Med. 349, 2326–2333 (2003).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Kataria, A., Kumar, D. & Gupta, G. Donor-derived cell-free DNA in solid-organ transplant diagnostics: indications, limitations, and future directions. Transplantation 105, 1203–1211 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Eckardt, K.-U., Kasiske, B. L. & Zeier, M. G. Special issue: KDIGO clinical practice guideline for the care of kidney transplant recipients. Am. J. Transpl. 9, s1–s155 (2009).

    Article 

    Google Scholar
     

  • Bloom, R. D. & Augustine, J. J. Beyond the biopsy: monitoring immune status in kidney recipients. Clin. J. Am. Soc. Nephrol. 16, 1413–1422 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Naesens, M. et al. The Banff 2022 Kidney Meeting report: reappraisal of microvascular inflammation and the role of biopsy-based transcript diagnostics. Am. J. Transpl. 24, 338–349 (2023).

    Article 

    Google Scholar
     

  • Louis, D. N. et al. The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol. 23, 1231–1251 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Roufosse, C. et al. The Banff 2022 Kidney Meeting work plan: data-driven refinement of the Banff Classification for renal allografts. Am. J. Transplant. 24, 350–361 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Haas, M. et al. The Banff 2017 Kidney Meeting report: revised diagnostic criteria for chronic active T cell-mediated rejection, antibody-mediated rejection, and prospects for integrative endpoints for next-generation clinical trials. Am. J. Transplant. 18, 293–307 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yoo, D. et al. An automated histological classification system for precision diagnostics of kidney allografts. Nat. Med. 29, 1211–1220 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Hermsen, M. et al. Deep learning-based histopathologic assessment of kidney tissue. J. Am. Soc. Nephrol. 30, 1968–1979 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Farris, A. B. et al. Banff Digital Pathology working group: image bank, artificial intelligence algorithm, and challenge trial developments. Transpl. Int. 36, 11783 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kers, J. et al. Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study. Lancet Digital Health 4, e18–e26 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Cristoferi, I. et al. Multiomic profiling of transplant glomerulopathy reveals a novel T-cell dominant subclass. Kidney Int. 105, 812–823 (2024).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Sellarés, J. et al. Molecular diagnosis of antibody-mediated rejection in human kidney transplants. Am. J. Transpl. 13, 971–983 (2013).

    Article 

    Google Scholar
     

  • Halloran, P. F. et al. Microarray diagnosis of antibody-mediated rejection in kidney transplant biopsies: an international prospective study (INTERCOM). Am. J. Transpl. 13, 2865–2874 (2013).

    Article 
    CAS 

    Google Scholar
     

  • Reeve, J. et al. Molecular diagnosis of T cell-mediated rejection in human kidney transplant biopsies. Am. J. Transpl. 13, 645–655 (2013).

    Article 
    CAS 

    Google Scholar
     

  • Reeve, J. et al. Generating automated kidney transplant biopsy reports combining molecular measurements with ensembles of machine learning classifiers. Am. J. Transpl. 19, 2719–2731 (2019).

    Article 
    CAS 

    Google Scholar
     

  • Jaksik, R., Iwanaszko, M., Rzeszowska-Wolny, J. & Kimmel, M. Microarray experiments and factors which affect their reliability. Biol. Direct 10, 46 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Loupy, A. et al. The Banff 2019 Kidney Meeting Report (I): updates on and clarification of criteria for T cell- and antibody-mediated rejection. Am. J. Transpl. 20, 2318–2331 (2020).

    Article 
    CAS 

    Google Scholar
     

  • Hidalgo, L. G. et al. NK cell transcripts and NK cells in kidney biopsies from patients with donor-specific antibodies: evidence for NK cell involvement in antibody-mediated rejection. Am. J. Transpl. 10, 1812–1822 (2010).

    Article 
    CAS 

    Google Scholar
     

  • Yazdani, S. et al. Natural killer cell infiltration is discriminative for antibody-mediated rejection and predicts outcome after kidney transplantation. Kidney Int. 95, 188–198 (2019).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Xinmin, L. & Cun-Yu, W. From bulk, single-cell to spatial RNA sequencing. Int. J. Oral. Sci. 13, 36 (2021).

    Article 

    Google Scholar
     

  • Zhang, Y. et al. Single‐cell RNA sequencing in cancer research. J. Exp. Clin. Cancer Res. 40, 81 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kuppe, C., Perales-Patón, J., Saez-Rodriguez, J. & Kramann, R. Experimental and computational technologies to dissect the kidney at the single-cell level. Nephrol. Dial. Transpl. 37, 628–637 (2022).

    Article 
    CAS 

    Google Scholar
     

  • Wu, H. et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J. Am. Soc. Nephrol. 29, 2069–2080 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wilson, P. C. et al. The single-cell transcriptomic landscape of early human diabetic nephropathy. Proc. Natl Acad. Sci. USA 116, 19619–19625 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • do Valle Duraes, F. et al. Immune cell landscaping reveals a protective role for regulatory T cells during kidney injury and fibrosis. JCI Insight 5, e130651 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Subramanian, A. et al. Single cell census of human kidney organoids shows reproducibility and diminished off-target cells after transplantation. Nat. Commun. 10, 5462 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Stewart, B. J., Ferdinand, J. R. & Clatworthy, M. R. Using single-cell technologies to map the human immune system — implications for nephrology. Nat. Rev. Nephrol. 16, 112–128 (2020).

    Article 
    PubMed 

    Google Scholar
     

  • Liao, J. et al. Single-cell RNA sequencing of human kidney. Sci. Data 7, 4 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Malone, A. F. & Humphreys, B. D. Single-cell transcriptomics and solid organ transplantation. Transplantation 103, 1776–1782 (2019).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zheng, G. X. Y. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dimitrov, D. et al. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat. Commun. 13, 3224 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yang, W. et al. DeepCCI: a deep learning framework for identifying cell–cell interactions from single-cell RNA sequencing data. Bioinformatics 39, btad596 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Leckie-Harre, A., Silverman, I., Wu, H., Humphreys, B. D. & Malone, A. F. Sequencing of physically interacting cells in human kidney allograft rejection to infer contact-dependent immune cell transcription. Transplantation 108, 421–429 (2024).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Shakoori, A. R. in Chromosome Structure and Aberrations (eds Bhat, T., Wani, A.) 343–367 https://doi.org/10.1007/978-81-322-3673-3_16 (Springer, 2017).

  • Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. & Zhuang, X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090 (2015).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • He, S. et al. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. Nat. Biotechnol. 40, 1794–1806 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Janesick, A. et al. High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis. Nat. Commun. 14, 8353 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wang, Y. et al. Spatial transcriptomics: technologies, applications and experimental considerations. Genomics 115, 110671 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Zhang, L. et al. Clinical and translational values of spatial transcriptomics. Signal. Transduct. Target. Ther. 7, 111 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777–1792.e21 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Liu, X. et al. Clinical challenges of tissue preparation for spatial transcriptome. Clin. Transl. Med. 12, e669 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Asp, M., Bergenstråhle, J. & Lundeberg, J. Spatially resolved transcriptomes — next generation tools for tissue exploration. BioEssays 42, e1900221 (2020).

    Article 
    PubMed 

    Google Scholar
     

  • Pour, M. & Yanai, I. New adventures in spatial transcriptomics. Dev. Cell 57, 1209–1210 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Slavov, N. Learning from natural variation across the proteomes of single cells. PLoS Biol. 20, e3001512 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Verma, S. K. & Molitoris, B. A. Renal endothelial injury and microvascular dysfunction in acute kidney injury. Semin. Nephrol. 35, 96–107 (2015).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Colombo, S. et al. Phospholipidome of endothelial cells shows a different adaptation response upon oxidative, glycative and lipoxidative stress. Sci. Rep. 8, 12365 (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dumas, S. J. et al. Phenotypic diversity and metabolic specialization of renal endothelial cells. Nat. Rev. Nephrol. 17, 441–464 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Marcu, R. et al. Human organ-specific endothelial cell heterogeneity. iScience 4, 20–35 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nolan, D. J. et al. Molecular signatures of tissue-specific microvascular endothelial cell heterogeneity in organ maintenance and regeneration. Dev. Cell 26, 204–219 (2013).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Dumas, S. J. et al. Single-cell RNA sequencing reveals renal endothelium heterogeneity and metabolic adaptation to water deprivation. J. Am. Soc. Nephrol. 31, 118–138 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Bancroft J., S. A. e., The Theory and Practice of Histological Techniques. 2nd ed. (Longman Group Limited, 1982).

  • Sheng, W. et al. Multiplex immunofluorescence: a powerful tool. cancer immunotherapy. Int. J. Mol. Sci. 24, 3086 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tan, W. C. C. et al. Overview of multiplex immunohistochemistry/immunofluorescence techniques in the era of cancer immunotherapy. Cancer Commun. 40, 135–153 (2020).

    Article 

    Google Scholar
     

  • Bosisio, F. M. et al. Next-generation pathology using multiplexed immunohistochemistry: mapping tissue architecture at single-cell level. Front. Oncol. 12, 918900 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Giesen, C. et al. Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nat. Methods 11, 417–422 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Schapiro, D. et al. HistoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. Nat. Methods 14, 873–876 (2017).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Le Rochais, M., Hemon, P., Pers, J.-O. & Uguen, A. Application of high-throughput imaging mass cytometry hyperion in cancer research. Front. Immunol. 13, 859414 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Hickey, J. W., Tan, Y., Nolan, G. P. & Goltsev, Y. Strategies for accurate cell type identification in CODEX multiplexed imaging data. Front. Immunol. 12, 727626 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lin, J.-R., Fallahi-Sichani, M., Chen, J.-Y. & Sorger, P. K. Cyclic immunofluorescence (CycIF), a highly multiplexed method for single-cell imaging. Curr. Protoc. Chem. Biol. 8, 251–264 (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kennedy-Darling, J. et al. Highly multiplexed tissue imaging using repeated oligonucleotide exchange reaction. Eur. J. Immunol. 51, 1262–1277 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Goltsev, Y. et al. Deep profiling of mouse splenic architecture with CODEX multiplexed imaging. Cell 174, 968–981.e15 (2018).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Calvani, J. et al. In situ multiplex immunofluorescence analysis of the inflammatory burden in kidney allograft rejection: a new tool to characterize the alloimmune response. Am. J. Transpl. 20, 942–953 (2020).

    Article 
    CAS 

    Google Scholar
     

  • Kim, M.-S. et al. Multiplex immunofluorescence assay of infiltrating mononuclear cell subsets in acute T-cell-mediated rejection and BK virus-associated nephropathy in the allograft kidney. Diagnostics 12, 268 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Neumann, E. K. et al. Highly multiplexed immunofluorescence of the human kidney using co-detection by indexing. Kidney Int. 101, 137–143 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Alexander, M. P. et al. Exploring the single-cell immune landscape of kidney allograft inflammation using imaging mass cytometry. Am. J. Transpl. 24, 549–563 (2023).

    Article 

    Google Scholar
     

  • Zhu, X., Xu, T., Peng, C. & We, S. Advances in MALDI mass spectrometry imaging single cell and tissues. Front. Chem. 9, 782432 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Unsihuay, D., Mesa Sanchez, D. & Laskin, J. Quantitative mass spectrometry imaging of biological systems. Annu. Rev. Phys. Chem. 72, 307–329 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Baquer, G. et al. What are we imaging? Software tools and experimental strategies for annotation and identification of small molecules in mass spectrometry imaging. Mass. Spectrom. Rev. 42, 1927–1964 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Denti, V. et al. Antigen retrieval and its effect on the MALDI-MSI of lipids in formalin-fixed paraffin-embedded tissue. J. Am. Soc. Mass. Spectrom. 31, 1619–1624 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Argelaguet, R., Cuomo, A. S. E., Stegle, O. & Marioni, J. C. Computational principles and challenges in single-cell data integration. Nat. Biotechnol. 39, 1202–1215 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Ma, A., McDermaid, A., Xu, J., Chang, Y. & Ma, Q. Integrative methods and practical challenges for single-cell multi-omics. Trends Biotechnol. 38, 1007–1022 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vandereyken, K., Sifrim, A., Thienpont, B. & Voet, T. Methods and applications for single-cell and spatial multi-omics. Nat. Rev. Genet. 24, 494–515 (2023).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Bergenstråhle, L. et al. Super-resolved spatial transcriptomics by deep data fusion. Nat. Biotechnol. 40, 476–479 (2022).

    Article 
    PubMed 

    Google Scholar
     

  • Efremova, M. & Teichmann, S. A. Computational methods for single-cell omics across modalities. Nat. Methods 17, 14–17 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Kleino, I., Frolovaitė, P., Suomi, T. & Elo, L. L. Computational solutions for spatial transcriptomics. Comput. Struct. Biotechnol. J. 20, 4870–4884 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lipkova, J. et al. Artificial intelligence for multimodal data integration in oncology. Cancer Cell 40, 1095–1110 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chen, R. J. et al. Pathomic fusion: an integrated framework for fusing histopathology and genomic features for cancer diagnosis and prognosis. IEEE Trans. Med. Imaging 41, 757–770 (2022).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhang, D. et al. Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology. Nat. Biotechnol. 25, bbae052 (2024).


    Google Scholar
     

  • Suo, L., Murillo, M. C., Gallay, B. & Hod-Dvorai, R. Discrepancy analysis between histology and molecular diagnoses in kidney allograft biopsies: a single-center experience. Int. J. Mol. Sci. 24, 13817 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kaya, I. et al. Histology-compatible MALDI mass spectrometry based imaging of neuronal lipids for subsequent immunofluorescent staining. Anal. Chem. 89, 4685–4694 (2017).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Wang, G. et al. Analyzing cell-type-specific dynamics of metabolism in kidney repair. Nat. Metab. 4, 1109–1118 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Vicari, M. et al., Spatial multimodal analysis of transcriptomes and metabolomes in tissues. Nat. Biotechnol. https://doi.org/10.1038/s41587-023-01937-y (2023).

  • Dunne, J. et al. Evaluation of antibody-based single cell type imaging techniques coupled to multiplexed imaging of N-glycans and collagen peptides by matrix-assisted laser desorption/ionization mass spectrometry imaging. Anal. Bioanal. Chem. 415, 7011–7024 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • El-Achkar, T. M. et al. A multimodal and integrated approach to interrogate human kidney biopsies with rigor and reproducibility: guidelines from the Kidney Precision Medicine Project. Physiol. Genomics 53, 1–11 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Salem, F. et al. The spatially resolved transcriptional profile of acute T cell-mediated rejection in a kidney allograft. Kidney Int. 101, 131–136 (2022).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Rietjens, R. et al. FC 120: lipid changes as early indicator for diabetes induced renal pathology. Nephrol. Dial. Transpl. 37, gfac125.002 (2022).

    Article 

    Google Scholar
     

  • Moore, J. L., Patterson, N. H., Norris, J. L. & Caprioli, R. M. Prospective on imaging mass spectrometry in clinical diagnostics. Mol. Cell. Proteom. 22, 100576 (2023).

    Article 
    CAS 

    Google Scholar
     

  • Stella, M. et al. Histology-guided proteomic analysis to investigate the molecular profiles of clear cell renal cell carcinoma grades. J. Proteom. 191, 38–47 (2019).

    Article 
    CAS 

    Google Scholar
     

  • Kriegsmann, M. et al. Mass spectrometry imaging differentiates chromophobe renal cell carcinoma and renal oncocytoma with high accuracy. J. Cancer 11, 6081–6089 (2020).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Möginger, U., Marcussen, N. & Jensen, O. N. Histo-molecular differentiation of renal cancer subtypes by mass spectrometry imaging and rapid proteome profiling of formalin-fixed paraffin-embedded tumor tissue sections. Oncotarget 11, 3998–4015 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nizioł, J. et al. Localization of metabolites of human kidney tissue with infrared laser-based selected reaction monitoring mass spectrometry imaging and silver-109 nanoparticle-based surface assisted laser desorption/ionization mass spectrometry imaging. Anal. Chem. 92, 4251–4258 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhang, J., Li, S. Q., Lin, J. Q., Yu, W. & Eberlin, L. S. Mass spectrometry imaging enables discrimination of renal oncocytoma from renal cell cancer subtypes and normal kidney tissues. Cancer Res. 80, 689–698 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Erlmeier, F. et al. MALDI mass spectrometry imaging — prognostic pathways and metabolites for renal cell carcinomas. Cancers 14, 1763 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Oppenheimer, S. R., Mi, D., Sanders, M. E. & Caprioli, R. M. Molecular analysis of tumor margins by MALDI mass spectrometry in renal carcinoma. J. Proteome Res. 9, 2182–2190 (2010).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Grove, K. J. et al. Diabetic nephropathy induces alterations in the glomerular and tubule lipid profiles. J. Lipid Res. 55, 1375–1385 (2014).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Smith, A. et al. Detecting proteomic indicators to distinguish diabetic nephropathy from hypertensive nephrosclerosis by integrating matrix-assisted laser desorption/ionization mass spectrometry imaging with high-mass accuracy mass spectrometry. Kidney Blood Press. Res. 45, 233–248 (2020).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Wang, Z. et al. Spatial-resolved metabolomics reveals tissue-specific metabolic reprogramming in diabetic nephropathy by using mass spectrometry imaging. Acta Pharm. Sin. B 11, 3665–3677 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rietjens, R. G. J. et al. Phosphatidylinositol metabolism of the renal proximal tubule S3 segment is disturbed in response to diabetes. Sci. Rep. 13, 6261 (2023).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • van Smaalen, T. C. et al. Rapid identification of ischemic injury in renal tissue by mass-spectrometry imaging. Anal. Chem. 91, 3575–3581 (2019).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Rao, S. et al. Early lipid changes in acute kidney injury using SWATH lipidomics coupled with MALDI tissue imaging. Am. J. Physiol. Renal Physiol. 310, F1136–F1147 (2016).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Abdelmoula, W. M. et al. massNet: integrated processing and classification of spatially resolved mass spectrometry data using deep learning for rapid tumor delineation. Bioinformatics 38, 2015–2021 (2022).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ly, A. et al. Site‐to‐site reproducibility and spatial resolution in MALDI–MSI of peptides from formalin‐fixed paraffin‐embedded samples. Proteom. Clin. Appl. 13, e1800029 (2019).

    Article 

    Google Scholar
     

  • Boskamp, T. et al. Cross-normalization of MALDI mass spectrometry imaging data improves site-to-site reproducibility. Anal. Chem. 93, 10584–10592 (2021).

    Article 
    CAS 
    PubMed 

    Google Scholar
     

  • Denti, V. et al. Reproducible lipid alterations in patient-derived breast cancer xenograft FFPE tissue identified with MALDI MSI for pre-clinical and clinical application. Metabolites 11, 577 (2021).

    Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Alexandrov, T. Spatial metabolomics and imaging mass spectrometry in the age of artificial intelligence. Annu. Rev. Biomed. Data Sci. 3, 61–87 (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar