IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-59005-9.html
   My bibliography  Save this article

Transcriptome analysis of archived tumors by Visium, GeoMx DSP, and Chromium reveals patient heterogeneity

Author

Listed:
  • Yixing Dong

    (Lausanne University Hospital; University of Lausanne)

  • Chiara Saglietti

    (Lausanne University Hospital and University of Lausanne)

  • Quentin Bayard

    (Owkin)

  • Almudena Espin Perez

    (Owkin)

  • Sabrina Carpentier

    (Owkin)

  • Daria Buszta

    (Lausanne University Hospital; Swiss Cancer Center Leman)

  • Stephanie Tissot

    (Lausanne University Hospital; Swiss Cancer Center Leman
    Ludwig Insitute for Cancer Research)

  • Rémy Dubois

    (Owkin)

  • Atanas Kamburov

    (Owkin)

  • Senbai Kang

    (Lausanne University Hospital; University of Lausanne)

  • Carla Haignere

    (Owkin)

  • Rita Sarkis

    (Lausanne University Hospital and University of Lausanne)

  • Sylvie Andre

    (Lausanne University Hospital; Swiss Cancer Center Leman
    Ludwig Insitute for Cancer Research
    Agora Translational Research Center)

  • Marina Alexandre Gaveta

    (Lausanne University Hospital; Swiss Cancer Center Leman
    Ludwig Insitute for Cancer Research
    Agora Translational Research Center)

  • Silvia Lopez Lastra

    (Owkin)

  • Nathalie Piazzon

    (Lausanne University Hospital and University of Lausanne)

  • Rita Santos

    (Owkin)

  • Katharina Loga

    (Owkin)

  • Caroline Hoffmann

    (Owkin)

  • George Coukos

    (Lausanne University Hospital; Swiss Cancer Center Leman
    Ludwig Insitute for Cancer Research
    Agora Translational Research Center)

  • Solange Peters

    (Lausanne University Hospital; Swiss Cancer Center Leman)

  • Vassili Soumelis

    (Owkin)

  • Eric Yves Durand

    (Owkin)

  • Laurence Leval

    (Lausanne University Hospital and University of Lausanne)

  • Raphael Gottardo

    (Lausanne University Hospital; University of Lausanne
    Agora Translational Research Center
    Swiss Institute of Bioinformatics
    Ecole Polytechnique Fédérale de)

  • Krisztian Homicsko

    (Lausanne University Hospital; Swiss Cancer Center Leman
    Ludwig Insitute for Cancer Research
    Agora Translational Research Center)

  • Elo Madissoon

    (Owkin)

Abstract

Recent advancements in probe-based, full-transcriptome technologies for FFPE tissues, such as Visium CytAssist, Chromium Flex, and GeoMx DSP, enable analysis of archival samples, facilitating the generation of data from extensive cohorts. However, these methods can be labor-intensive and costly, requiring informed selection based on research objectives. We compare these methods on FFPE tumor samples in Breast, NSCLC and DLBCL showing 1) good-quality, highly reproducible data from all methods; 2) GeoMx data containing cell mixtures despite marker-based preselection; 3) Visium and Chromium outperform GeoMx in discovering tumor heterogeneity and potential drug targets. We recommend the use of Visium and Chromium for high-throughput and discovery projects, while the manually more challenging GeoMx platform with targeted regions remains valuable for specialized questions.

Suggested Citation

  • Yixing Dong & Chiara Saglietti & Quentin Bayard & Almudena Espin Perez & Sabrina Carpentier & Daria Buszta & Stephanie Tissot & Rémy Dubois & Atanas Kamburov & Senbai Kang & Carla Haignere & Rita Sark, 2025. "Transcriptome analysis of archived tumors by Visium, GeoMx DSP, and Chromium reveals patient heterogeneity," Nature Communications, Nature, vol. 16(1), pages 1-18, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59005-9
    DOI: 10.1038/s41467-025-59005-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-59005-9
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-025-59005-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Patrick Danaher & Youngmi Kim & Brenn Nelson & Maddy Griswold & Zhi Yang & Erin Piazza & Joseph M. Beechem, 2022. "Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Amanda Janesick & Robert Shelansky & Andrew D. Gottscho & Florian Wagner & Stephen R. Williams & Morgane Rouault & Ghezal Beliakoff & Carolyn A. Morrison & Michelli F. Oliveira & Jordan T. Sicherman &, 2023. "High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    3. Zijian Ni & Aman Prasad & Shuyang Chen & Richard B. Halberg & Lisa M. Arkin & Beth A. Drolet & Michael A. Newton & Christina Kendziorski, 2022. "SpotClean adjusts for spot swapping in spatial transcriptomics data," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuma Takano & Jun Suzuki & Kotaro Nomura & Gento Fujii & Junko Zenkoh & Hitomi Kawai & Yuta Kuze & Yukie Kashima & Satoi Nagasawa & Yuka Nakamura & Motohiro Kojima & Katsuya Tsuchihara & Masahide Seki, 2024. "Spatially resolved gene expression profiling of tumor microenvironment reveals key steps of lung adenocarcinoma development," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Arezou Rahimi & Luis A. Vale-Silva & Maria Fälth Savitski & Jovan Tanevski & Julio Saez-Rodriguez, 2024. "DOT: a flexible multi-objective optimization framework for transferring features across single-cell and spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    3. Shuangsang Fang & Mengyang Xu & Lei Cao & Xiaobin Liu & Marija Bezulj & Liwei Tan & Zhiyuan Yuan & Yao Li & Tianyi Xia & Longyu Guo & Vladimir Kovacevic & Junhou Hui & Lidong Guo & Chao Liu & Mengnan , 2025. "Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics," Nature Communications, Nature, vol. 16(1), pages 1-19, December.
    4. Haoyang Li & Yingxin Lin & Wenjia He & Wenkai Han & Xiaopeng Xu & Chencheng Xu & Elva Gao & Hongyu Zhao & Xin Gao, 2024. "SANTO: a coarse-to-fine alignment and stitching method for spatial omics," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Peng Zhang & Chaofei Gao & Zhuoyu Zhang & Zhiyuan Yuan & Qian Zhang & Ping Zhang & Shiyu Du & Weixun Zhou & Yan Li & Shao Li, 2025. "Systematic inference of super-resolution cell spatial profiles from histology images," Nature Communications, Nature, vol. 16(1), pages 1-21, December.
    6. Xiaohang Fu & Yingxin Lin & David M. Lin & Daniel Mechtersheimer & Chuhan Wang & Farhan Ameen & Shila Ghazanfar & Ellis Patrick & Jinman Kim & Jean Y. H. Yang, 2024. "BIDCell: Biologically-informed self-supervised learning for segmentation of subcellular spatial transcriptomics data," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    7. Bohan Li & Feng Bao & Yimin Hou & Fengji Li & Hongjue Li & Yue Deng & Qionghai Dai, 2024. "Tissue characterization at an enhanced resolution across spatial omics platforms with deep generative model," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    8. Leonardo D. Garma & Lisbeth Harder & Juan M. Barba-Reyes & Sergio Marco Salas & Mónica Díez-Salguero & Mats Nilsson & Alberto Serrano-Pozo & Bradley T. Hyman & Ana B. Muñoz-Manchado, 2024. "Interneuron diversity in the human dorsal striatum," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    9. Rafael dos Santos Peixoto & Brendan F. Miller & Maigan A. Brusko & Gohta Aihara & Lyla Atta & Manjari Anant & Mark A. Atkinson & Todd M. Brusko & Clive H. Wasserfall & Jean Fan, 2025. "Characterizing cell-type spatial relationships across length scales in spatially resolved omics data," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    10. A. S. Eisele & M. Tarbier & A. A. Dormann & V. Pelechano & D. M. Suter, 2024. "Gene-expression memory-based prediction of cell lineages from scRNA-seq datasets," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    11. Yuqiao Gong & Xin Yuan & Qiong Jiao & Zhangsheng Yu, 2025. "Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    12. Haoyang Li & Juexiao Zhou & Zhongxiao Li & Siyuan Chen & Xingyu Liao & Bin Zhang & Ruochi Zhang & Yu Wang & Shiwei Sun & Xin Gao, 2023. "A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    13. Yanming Ren & Zongyao Huang & Lingling Zhou & Peng Xiao & Junwei Song & Ping He & Chuanxing Xie & Ran Zhou & Menghan Li & Xiangqun Dong & Qing Mao & Chao You & Jianguo Xu & Yanhui Liu & Zhigang Lan & , 2023. "Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    14. Chunman Zuo & Yijian Zhang & Chen Cao & Jinwang Feng & Mingqi Jiao & Luonan Chen, 2022. "Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    15. Thomas M. Goralski & Lindsay Meyerdirk & Libby Breton & Laura Brasseur & Kevin Kurgat & Daniella DeWeerd & Lisa Turner & Katelyn Becker & Marie Adams & Daniel J. Newhouse & Michael X. Henderson, 2024. "Spatial transcriptomics reveals molecular dysfunction associated with cortical Lewy pathology," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    16. Eduard Chelebian & Christophe Avenel & Carolina Wählby, 2025. "Combining spatial transcriptomics with tissue morphology," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    17. Xuejiao Liu & Simin Zhao & Keke Wang & Liting Zhou & Ming Jiang & Yunfeng Gao & Ran Yang & Shiwen Yan & Wen Zhang & Bingbing Lu & Feifei Liu & Ran Zhao & Wenting Liu & Zihan Zhang & Kangdong Liu & Xia, 2023. "Spatial transcriptomics analysis of esophageal squamous precancerous lesions and their progression to esophageal cancer," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    18. Qi Zhang & Rober Abdo & Cristiana Iosef & Tomonori Kaneko & Matthew Cecchini & Victor K. Han & Shawn Shun-Cheng Li, 2022. "The spatial transcriptomic landscape of non-small cell lung cancer brain metastasis," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    19. Jingyang Qian & Hudong Bao & Xin Shao & Yin Fang & Jie Liao & Zhuo Chen & Chengyu Li & Wenbo Guo & Yining Hu & Anyao Li & Yue Yao & Xiaohui Fan & Yiyu Cheng, 2024. "Simulating multiple variability in spatially resolved transcriptomics with scCube," Nature Communications, Nature, vol. 15(1), pages 1-21, December.
    20. Dominik Schienstock & Jyh Liang Hor & Sapna Devi & Scott N. Mueller, 2025. "Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour," Nature Communications, Nature, vol. 16(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-59005-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.