IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0112143.html
   My bibliography  Save this article

Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics

Author

Listed:
  • Li Chen
  • Peter L Choyke
  • Niya Wang
  • Robert Clarke
  • Zaver M Bhujwalla
  • Elizabeth M C Hillman
  • Ge Wang
  • Yue Wang

Abstract

With the existence of biologically distinctive malignant cells originated within the same tumor, intratumor functional heterogeneity is present in many cancers and is often manifested by the intermingled vascular compartments with distinct pharmacokinetics. However, intratumor vascular heterogeneity cannot be resolved directly by most in vivo dynamic imaging. We developed multi-tissue compartment modeling (MTCM), a completely unsupervised method of deconvoluting dynamic imaging series from heterogeneous tumors that can improve vascular characterization in many biological contexts. Applying MTCM to dynamic contrast-enhanced magnetic resonance imaging of breast cancers revealed characteristic intratumor vascular heterogeneity and therapeutic responses that were otherwise undetectable. MTCM is readily applicable to other dynamic imaging modalities for studying intratumor functional and phenotypic heterogeneity, together with a variety of foreseeable applications in the clinic.

Suggested Citation

  • Li Chen & Peter L Choyke & Niya Wang & Robert Clarke & Zaver M Bhujwalla & Elizabeth M C Hillman & Ge Wang & Yue Wang, 2014. "Unsupervised Deconvolution of Dynamic Imaging Reveals Intratumor Vascular Heterogeneity and Repopulation Dynamics," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    • Handle: RePEc:plo:pone00:0112143
    DOI: 10.1371/journal.pone.0112143
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0112143
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0112143&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0112143?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. Rebecca A. Burrell & Nicholas McGranahan & Jiri Bartek & Charles Swanton, 2013. "The causes and consequences of genetic heterogeneity in cancer evolution," Nature, Nature, vol. 501(7467), pages 338-345, September.
    2. Melissa R. Junttila & Frederic J. de Sauvage, 2013. "Influence of tumour micro-environment heterogeneity on therapeutic response," Nature, Nature, vol. 501(7467), pages 346-354, September.
    3. Philippe L. Bedard & Aaron R. Hansen & Mark J. Ratain & Lillian L. Siu, 2013. "Tumour heterogeneity in the clinic," Nature, Nature, vol. 501(7467), pages 355-364, September.
    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. Shiqian Ma & Daniel Johnson & Cody Ashby & Donghai Xiong & Carole L Cramer & Jason H Moore & Shuzhong Zhang & Xiuzhen Huang, 2015. "SPARCoC: A New Framework for Molecular Pattern Discovery and Cancer Gene Identification," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-19, March.
    2. Humberto Contreras-Trujillo & Jiya Eerdeng & Samir Akre & Du Jiang & Jorge Contreras & Basia Gala & Mary C. Vergel-Rodriguez & Yeachan Lee & Aparna Jorapur & Areen Andreasian & Lisa Harton & Charles S, 2021. "Deciphering intratumoral heterogeneity using integrated clonal tracking and single-cell transcriptome analyses," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    3. Albert H Gough & Ning Chen & Tong Ying Shun & Timothy R Lezon & Robert C Boltz & Celeste E Reese & Jacob Wagner & Lawrence A Vernetti & Jennifer R Grandis & Adrian V Lee & Andrew M Stern & Mark E Schu, 2014. "Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-16, July.
    4. Lida Qiu & Deyong Kang & Chuan Wang & Wenhui Guo & Fangmeng Fu & Qingxiang Wu & Gangqin Xi & Jiajia He & Liqin Zheng & Qingyuan Zhang & Xiaoxia Liao & Lianhuang Li & Jianxin Chen & Haohua Tu, 2022. "Intratumor graph neural network recovers hidden prognostic value of multi-biomarker spatial heterogeneity," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    5. Lianfeng Shan & Ming Li & Jianzhong Ma & Huidan Zhang, 2014. "PCR-Based Assays versus Direct Sequencing for Evaluating the Effect of KRAS Status on Anti-EGFR Treatment Response in Colorectal Cancer Patients: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 9(9), pages 1-7, September.
    6. Benjamin Wölfl & Hedy te Rietmole & Monica Salvioli & Artem Kaznatcheev & Frank Thuijsman & Joel S. Brown & Boudewijn Burgering & Kateřina Staňková, 2022. "The Contribution of Evolutionary Game Theory to Understanding and Treating Cancer," Dynamic Games and Applications, Springer, vol. 12(2), pages 313-342, June.
    7. Christopher R S Banerji & Simone Severini & Carlos Caldas & Andrew E Teschendorff, 2015. "Intra-Tumour Signalling Entropy Determines Clinical Outcome in Breast and Lung Cancer," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-23, March.
    8. Jose M. Ayuso & María Virumbrales-Muñoz & Joshua M. Lang & David J. Beebe, 2022. "A role for microfluidic systems in precision medicine," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    9. Marion Porcherie & Nyan Linn & Anne Roué Le Gall & Marie-Florence Thomas & Emmanuelle Faure & Stéphane Rican & Jean Simos & Nicola Cantoreggi & Zoé Vaillant & Linda Cambon & Jean-Philippe Regnaux, 2021. "Relationship between Urban Green Spaces and Cancer: A Scoping Review," IJERPH, MDPI, vol. 18(4), pages 1-19, February.
    10. Shen Zhao & De-Pin Chen & Tong Fu & Jing-Cheng Yang & Ding Ma & Xiu-Zhi Zhu & Xiang-Xue Wang & Yi-Ping Jiao & Xi Jin & Yi Xiao & Wen-Xuan Xiao & Hu-Yunlong Zhang & Hong Lv & Anant Madabhushi & Wen-Tao, 2023. "Single-cell morphological and topological atlas reveals the ecosystem diversity of human breast cancer," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    11. Jae-Woong Min & Woo Jin Kim & Jeong A Han & Yu-Jin Jung & Kyu-Tae Kim & Woong-Yang Park & Hae-Ock Lee & Sun Shim Choi, 2015. "Identification of Distinct Tumor Subpopulations in Lung Adenocarcinoma via Single-Cell RNA-seq," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-17, August.
    12. Duncan Ingram & Guy-Bart Stan, 2023. "Modelling genetic stability in engineered cell populations," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    13. Gunnarsson, Einar Bjarki & Leder, Kevin & Foo, Jasmine, 2021. "Exact site frequency spectra of neutrally evolving tumors: A transition between power laws reveals a signature of cell viability," Theoretical Population Biology, Elsevier, vol. 142(C), pages 67-90.
    14. Jacob C Kimmel & Amy Y Chang & Andrew S Brack & Wallace F Marshall, 2018. "Inferring cell state by quantitative motility analysis reveals a dynamic state system and broken detailed balance," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-29, January.
    15. Nick Henscheid & Eric Clarkson & Kyle J Myers & Harrison H Barrett, 2018. "Physiological random processes in precision cancer therapy," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-25, June.
    16. Richard Newton & Lorenz Wernisch, 2019. "A meta-analysis of multiple matched aCGH/expression cancer datasets reveals regulatory relationships and pathway enrichment of potential oncogenes," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-28, July.

    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:plo:pone00:0112143. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.