IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v9y2018i1d10.1038_s41467-018-04724-5.html
   My bibliography  Save this article

Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity

Author

Listed:
  • Emelie Berglund

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Jonas Maaskola

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Niklas Schultz

    (Karolinska Institutet (KI), Science for Life Laboratory)

  • Stefanie Friedrich

    (Stockholm University, Science for Life Laboratory)

  • Maja Marklund

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Joseph Bergenstråhle

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Firas Tarish

    (Karolinska Institutet (KI), Science for Life Laboratory)

  • Anna Tanoglidi

    (University Uppsala Hospital)

  • Sanja Vickovic

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Ludvig Larsson

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Fredrik Salmén

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Christoph Ogris

    (Stockholm University, Science for Life Laboratory)

  • Karolina Wallenborg

    (Karolinska Institutet (KI), Science for Life Laboratory)

  • Jens Lagergren

    (School of Computer Science and Communication, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Patrik Ståhl

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

  • Erik Sonnhammer

    (Stockholm University, Science for Life Laboratory)

  • Thomas Helleday

    (Karolinska Institutet (KI), Science for Life Laboratory)

  • Joakim Lundeberg

    (School of Engineering Sciences in Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), Science for Life Laboratory)

Abstract

Intra-tumor heterogeneity is one of the biggest challenges in cancer treatment today. Here we investigate tissue-wide gene expression heterogeneity throughout a multifocal prostate cancer using the spatial transcriptomics (ST) technology. Utilizing a novel approach for deconvolution, we analyze the transcriptomes of nearly 6750 tissue regions and extract distinct expression profiles for the different tissue components, such as stroma, normal and PIN glands, immune cells and cancer. We distinguish healthy and diseased areas and thereby provide insight into gene expression changes during the progression of prostate cancer. Compared to pathologist annotations, we delineate the extent of cancer foci more accurately, interestingly without link to histological changes. We identify gene expression gradients in stroma adjacent to tumor regions that allow for re-stratification of the tumor microenvironment. The establishment of these profiles is the first step towards an unbiased view of prostate cancer and can serve as a dictionary for future studies.

Suggested Citation

  • Emelie Berglund & Jonas Maaskola & Niklas Schultz & Stefanie Friedrich & Maja Marklund & Joseph Bergenstråhle & Firas Tarish & Anna Tanoglidi & Sanja Vickovic & Ludvig Larsson & Fredrik Salmén & Chri, 2018. "Spatial maps of prostate cancer transcriptomes reveal an unexplored landscape of heterogeneity," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-04724-5
    DOI: 10.1038/s41467-018-04724-5
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-018-04724-5
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-018-04724-5?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. S. Vickovic & B. Lötstedt & J. Klughammer & S. Mages & Å Segerstolpe & O. Rozenblatt-Rosen & A. Regev, 2022. "SM-Omics is an automated platform for high-throughput spatial multi-omics," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    2. Guidantonio Malagoli Tagliazucchi & Anna J. Wiecek & Eloise Withnell & Maria Secrier, 2023. "Genomic and microenvironmental heterogeneity shaping epithelial-to-mesenchymal trajectories in cancer," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
    3. Jie Liao & Jingyang Qian & Yin Fang & Zhuo Chen & Xiang Zhuang & Ningyu Zhang & Xin Shao & Yining Hu & Penghui Yang & Junyun Cheng & Yang Hu & Lingqi Yu & Haihong Yang & Jinlu Zhang & Xiaoyan Lu & Li , 2022. "De novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    4. Zhixing Zhong & Junchen Hou & Zhixian Yao & Lei Dong & Feng Liu & Junqiu Yue & Tiantian Wu & Junhua Zheng & Gaoliang Ouyang & Chaoyong Yang & Jia Song, 2024. "Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    5. Ziyang Tang & Zuotian Li & Tieying Hou & Tonglin Zhang & Baijian Yang & Jing Su & Qianqian Song, 2023. "SiGra: single-cell spatial elucidation through an image-augmented graph transformer," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    6. Simon Davis & Connor Scott & Janina Oetjen & Philip D. Charles & Benedikt M. Kessler & Olaf Ansorge & Roman Fischer, 2023. "Deep topographic proteomics of a human brain tumour," Nature Communications, Nature, vol. 14(1), pages 1-15, 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. Linhua Wang & Mirjana Maletic-Savatic & Zhandong Liu, 2022. "Region-specific denoising identifies spatial co-expression patterns and intra-tissue heterogeneity in spatially resolved transcriptomics data," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    9. Yang Yang & Chenyu Chu & Li Liu & Chenbing Wang & Chen Hu & Shengan Rung & Yi Man & Yili Qu, 2023. "Tracing immune cells around biomaterials with spatial anchors during large-scale wound regeneration," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    10. 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.
    11. Caravagna Giulio, 2020. "Measuring evolutionary cancer dynamics from genome sequencing, one patient at a time," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 19(4-6), pages 1-12, December.
    12. Maja Marklund & Niklas Schultz & Stefanie Friedrich & Emelie Berglund & Firas Tarish & Anna Tanoglidi & Yao Liu & Ludvig Bergenstråhle & Andrew Erickson & Thomas Helleday & Alastair D. Lamb & Erik Son, 2022. "Spatio-temporal analysis of prostate tumors in situ suggests pre-existence of treatment-resistant clones," Nature Communications, Nature, vol. 13(1), pages 1-18, 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:9:y:2018:i:1:d:10.1038_s41467-018-04724-5. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.