IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-48010-z.html
   My bibliography  Save this article

A vascularized breast cancer spheroid platform for the ranked evaluation of tumor microenvironment-targeted drugs by light sheet fluorescence microscopy

Author

Listed:
  • David Ascheid

    (Julius-Maximilians-Universität Würzburg)

  • Magdalena Baumann

    (Julius-Maximilians-Universität Würzburg)

  • Jürgen Pinnecker

    (Julius-Maximilians-Universität Würzburg)

  • Mike Friedrich

    (Julius-Maximilians-Universität Würzburg)

  • Daniel Szi-Marton

    (Julius-Maximilians-Universität Würzburg)

  • Cornelia Medved

    (Julius-Maximilians-Universität Würzburg)

  • Maja Bundalo

    (Universitätsklinikum Würzburg)

  • Vanessa Ortmann

    (Julius-Maximilians-Universität Würzburg)

  • Asli Öztürk

    (Julius-Maximilians-Universität Würzburg)

  • Rajender Nandigama

    (Julius-Maximilians-Universität Würzburg
    Max Planck Institute of Heart and Lung Research)

  • Katherina Hemmen

    (Julius-Maximilians-Universität Würzburg)

  • Süleymann Ergün

    (Julius-Maximilians-Universität Würzburg)

  • Alma Zernecke

    (Universitätsklinikum Würzburg)

  • Matthias Hirth

    (Technische Universität Illmenau)

  • Katrin G. Heinze

    (Julius-Maximilians-Universität Würzburg)

  • Erik Henke

    (Julius-Maximilians-Universität Würzburg
    Julius-Maximilians-Universität Würzburg)

Abstract

Targeting the supportive tumor microenvironment (TME) is an approach of high interest in cancer drug development. However, assessing TME-targeted drug candidates presents a unique set of challenges. We develop a comprehensive screening platform that allows monitoring, quantifying, and ranking drug-induced effects in self-organizing, vascularized tumor spheroids (VTSs). The confrontation of four human-derived cell populations makes it possible to recreate and study complex changes in TME composition and cell-cell interaction. The platform is modular and adaptable for tumor entity or genetic manipulation. Treatment effects are recorded by light sheet fluorescence microscopy and translated by an advanced image analysis routine in processable multi-parametric datasets. The system proved to be robust, with strong interassay reliability. We demonstrate the platform’s utility for evaluating TME-targeted antifibrotic and antiangiogenic drugs side-by-side. The platform’s output enabled the differential evaluation of even closely related drug candidates according to projected therapeutic needs.

Suggested Citation

  • David Ascheid & Magdalena Baumann & Jürgen Pinnecker & Mike Friedrich & Daniel Szi-Marton & Cornelia Medved & Maja Bundalo & Vanessa Ortmann & Asli Öztürk & Rajender Nandigama & Katherina Hemmen & Sül, 2024. "A vascularized breast cancer spheroid platform for the ranked evaluation of tumor microenvironment-targeted drugs by light sheet fluorescence microscopy," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-48010-z
    DOI: 10.1038/s41467-024-48010-z
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-48010-z
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-024-48010-z?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. Henry Gerdes & Pedro Casado & Arran Dokal & Maruan Hijazi & Nosheen Akhtar & Ruth Osuntola & Vinothini Rajeeve & Jude Fitzgibbon & Jon Travers & David Britton & Shirin Khorsandi & Pedro R. Cutillas, 2021. "Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    2. Zhao-Qiu Wu & R. Grant Rowe & Kim-Chew Lim & Yongshun Lin & Amanda Willis & Yi Tang & Xiao-Yan Li & Jacques E. Nor & Ivan Maillard & Stephen J. Weiss, 2014. "A Snail1/Notch1 signalling axis controls embryonic vascular development," Nature Communications, Nature, vol. 5(1), pages 1-15, September.
    3. Charles M. Perou & Therese Sørlie & Michael B. Eisen & Matt van de Rijn & Stefanie S. Jeffrey & Christian A. Rees & Jonathan R. Pollack & Douglas T. Ross & Hilde Johnsen & Lars A. Akslen & Øystein Flu, 2000. "Molecular portraits of human breast tumours," Nature, Nature, vol. 406(6797), pages 747-752, August.
    4. Magdalena Paolino & Axel Choidas & Stephanie Wallner & Blanka Pranjic & Iris Uribesalgo & Stefanie Loeser & Amanda M. Jamieson & Wallace Y. Langdon & Fumiyo Ikeda & Juan Pablo Fededa & Shane J. Cronin, 2014. "The E3 ligase Cbl-b and TAM receptors regulate cancer metastasis via natural killer cells," Nature, Nature, vol. 507(7493), pages 508-512, March.
    5. Irene Noguera-Troise & Christopher Daly & Nicholas J. Papadopoulos & Sandra Coetzee & Pat Boland & Nicholas W. Gale & Hsin Chieh Lin & George D. Yancopoulos & Gavin Thurston, 2006. "Blockade of Dll4 inhibits tumour growth by promoting non-productive angiogenesis," Nature, Nature, vol. 444(7122), pages 1032-1037, 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. Yang, Xi & Hoadley, Katherine A. & Hannig, Jan & Marron, J.S., 2023. "Jackstraw inference for AJIVE data integration," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    2. Egashira, Kento & Yata, Kazuyoshi & Aoshima, Makoto, 2024. "Asymptotic properties of hierarchical clustering in high-dimensional settings," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    3. María Elena Martínez & Jonathan T Unkart & Li Tao & Candyce H Kroenke & Richard Schwab & Ian Komenaka & Scarlett Lin Gomez, 2017. "Prognostic significance of marital status in breast cancer survival: A population-based study," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
    4. Yishai Shimoni, 2018. "Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-15, February.
    5. Yoo-Ah Kim & Stefan Wuchty & Teresa M Przytycka, 2011. "Identifying Causal Genes and Dysregulated Pathways in Complex Diseases," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-13, March.
    6. Radhakrishnan Nagarajan & Marco Scutari, 2013. "Impact of Noise on Molecular Network Inference," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    7. R Joseph Bender & Feilim Mac Gabhann, 2013. "Expression of VEGF and Semaphorin Genes Define Subgroups of Triple Negative Breast Cancer," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
    8. Deepak Poduval & Zuzana Sichmanova & Anne Hege Straume & Per Eystein Lønning & Stian Knappskog, 2020. "The novel microRNAs hsa-miR-nov7 and hsa-miR-nov3 are over-expressed in locally advanced breast cancer," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-23, April.
    9. Zhiguang Huo & Li Zhu & Tianzhou Ma & Hongcheng Liu & Song Han & Daiqing Liao & Jinying Zhao & George Tseng, 2020. "Two-Way Horizontal and Vertical Omics Integration for Disease Subtype Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(1), pages 1-22, April.
    10. Markus Ringnér & Erik Fredlund & Jari Häkkinen & Åke Borg & Johan Staaf, 2011. "GOBO: Gene Expression-Based Outcome for Breast Cancer Online," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-11, March.
    11. Casey S Greene & Olga G Troyanskaya, 2012. "Chapter 2: Data-Driven View of Disease Biology," PLOS Computational Biology, Public Library of Science, vol. 8(12), pages 1-8, December.
    12. Mark Reimers, 2010. "Making Informed Choices about Microarray Data Analysis," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-7, May.
    13. Alan A. Arslan & Yian Zhang & Nedim Durmus & Sultan Pehlivan & Adrienne Addessi & Freya Schnabel & Yongzhao Shao & Joan Reibman, 2021. "Breast Cancer Characteristics in the Population of Survivors Participating in the World Trade Center Environmental Health Center Program 2002–2019," IJERPH, MDPI, vol. 18(14), pages 1-11, July.
    14. Sandra M. Rocha & Sílvia Socorro & Luís A. Passarinha & Cláudio J. Maia, 2022. "Comprehensive Landscape of STEAP Family Members Expression in Human Cancers: Unraveling the Potential Usefulness in Clinical Practice Using Integrated Bioinformatics Analysis," Data, MDPI, vol. 7(5), pages 1-48, May.
    15. Martin H van Vliet & Christiaan N Klijn & Lodewyk F A Wessels & Marcel J T Reinders, 2007. "Module-Based Outcome Prediction Using Breast Cancer Compendia," PLOS ONE, Public Library of Science, vol. 2(10), pages 1-10, October.
    16. Sung Gwe Ahn & Minkyung Lee & Tae Joo Jeon & Kyunghwa Han & Hak Min Lee & Seung Ah Lee & Young Hoon Ryu & Eun Ju Son & Joon Jeong, 2014. "[18F]-Fluorodeoxyglucose Positron Emission Tomography Can Contribute to Discriminate Patients with Poor Prognosis in Hormone Receptor-Positive Breast Cancer," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-7, August.
    17. Erhan Bilal & Janusz Dutkowski & Justin Guinney & In Sock Jang & Benjamin A Logsdon & Gaurav Pandey & Benjamin A Sauerwine & Yishai Shimoni & Hans Kristian Moen Vollan & Brigham H Mecham & Oscar M Rue, 2013. "Improving Breast Cancer Survival Analysis through Competition-Based Multidimensional Modeling," PLOS Computational Biology, Public Library of Science, vol. 9(5), pages 1-16, May.
    18. Maurizio Callari & Antonio Lembo & Giampaolo Bianchini & Valeria Musella & Vera Cappelletti & Luca Gianni & Maria Grazia Daidone & Paolo Provero, 2014. "Accurate Data Processing Improves the Reliability of Affymetrix Gene Expression Profiles from FFPE Samples," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    19. Silje Kjølle & Kenneth Finne & Even Birkeland & Vandana Ardawatia & Ingeborg Winge & Sura Aziz & Gøril Knutsvik & Elisabeth Wik & Joao A. Paulo & Heidrun Vethe & Dimitrios Kleftogiannis & Lars A. Aksl, 2023. "Hypoxia induced responses are reflected in the stromal proteome of breast cancer," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    20. Zheqi Li & Olivia McGinn & Yang Wu & Amir Bahreini & Nolan M. Priedigkeit & Kai Ding & Sayali Onkar & Caleb Lampenfeld & Carol A. Sartorius & Lori Miller & Margaret Rosenzweig & Ofir Cohen & Nikhil Wa, 2022. "ESR1 mutant breast cancers show elevated basal cytokeratins and immune activation," 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:15:y:2024:i:1:d:10.1038_s41467-024-48010-z. 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.