Label-free visualization and characterization of extracellular vesicles in breast cancer.


Journal

Proceedings of the National Academy of Sciences of the United States of America
ISSN: 1091-6490
Titre abrégé: Proc Natl Acad Sci U S A
Pays: United States
ID NLM: 7505876

Informations de publication

Date de publication:
26 11 2019
Historique:
pubmed: 17 11 2019
medline: 23 4 2020
entrez: 17 11 2019
Statut: ppublish

Résumé

Despite extensive interest, extracellular vesicle (EV) research remains technically challenging. One of the unexplored gaps in EV research has been the inability to characterize the spatially and functionally heterogeneous populations of EVs based on their metabolic profile. In this paper, we utilize the intrinsic optical metabolic and structural contrast of EVs and demonstrate in vivo/in situ characterization of EVs in a variety of unprocessed (pre)clinical samples. With a pixel-level segmentation mask provided by the deep neural network, individual EVs can be analyzed in terms of their optical signature in the context of their spatial distribution. Quantitative analysis of living tumor-bearing animals and fresh excised human breast tissue revealed abundance of NAD(P)H-rich EVs within the tumor, near the tumor boundary, and around vessel structures. Furthermore, the percentage of NAD(P)H-rich EVs is highly correlated with human breast cancer diagnosis, which emphasizes the important role of metabolic imaging for EV characterization as well as its potential for clinical applications. In addition to the characterization of EV properties, we also demonstrate label-free monitoring of EV dynamics (uptake, release, and movement) in live cells and animals. The in situ metabolic profiling capacity of the proposed method together with the finding of increasing NAD(P)H-rich EV subpopulations in breast cancer have the potential for empowering applications in basic science and enhancing our understanding of the active metabolic roles that EVs play in cancer progression.

Identifiants

pubmed: 31732668
pii: 1909243116
doi: 10.1073/pnas.1909243116
pmc: PMC6883786
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

24012-24018

Subventions

Organisme : NCI NIH HHS
ID : R01 CA166309
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA213149
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB023232
Pays : United States

Déclaration de conflit d'intérêts

Competing interest statement: S.A.B., H.T., and S.Y. are named inventors on patents filed by the University of Illinois at Urbana–Champaign related to the laser source technology and the imaging and quantification of extracellular vesicles. S.A.B. and H.T. are co-founders and hold equity interest in LiveBx, LLC, Champaign, IL, which is commercializing the laser source technology used in this study. Requests for materials should be addressed to S.A.B. All other authors declare that they have no competing financial interests.

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Auteurs

Sixian You (S)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Ronit Barkalifa (R)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Eric J Chaney (EJ)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Haohua Tu (H)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Jaena Park (J)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Janet Elise Sorrells (JE)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Yi Sun (Y)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Yuan-Zhi Liu (YZ)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Lin Yang (L)

Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556.

Danny Z Chen (DZ)

Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556.

Marina Marjanovic (M)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Saurabh Sinha (S)

Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

Stephen A Boppart (SA)

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; boppart@illinois.edu.
Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801.
Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL 61801.

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