Evidence map›Paper›PMID 33093167›Full record

ArticleCancer research2020

Autofluorescence Imaging of 3D Tumor-Macrophage Microscale Cultures Resolves Spatial and Temporal Dynamics of Macrophage Metabolism.

Tiffany M Heaster, Mouhita Humayun, Jiaquan Yu, David J Beebe, Melissa C Skala

Open access · bronzeAbstract read
In one paragraph

Article in Cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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  11. Imaging immunometabolismImmunometabolism (Cobham, Surrey) · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Tiffany M HeasterDepartment of Biomedical Engineering, University of Wisconsin- Madison, Madison, Wisconsin.
Mouhita HumayunDepartment of Biomedical Engineering, University of Wisconsin- Madison, Madison, Wisconsin.
Jiaquan YuDepartment of Biomedical Engineering, University of Wisconsin- Madison, Madison, Wisconsin.
David J BeebeDepartment of Biomedical Engineering, University of Wisconsin- Madison, Madison, Wisconsin.
Melissa C SkalaDepartment of Biomedical Engineering, University of Wisconsin- Madison, Madison, Wisconsin. mcskala@wisc.edu.ORCID 0000-0002-6320-7637
University of Wisconsin–Madison · US

Funding

Optical imaging of pancreas cancer organoids for drug development and personalized treatmentR01CA211082 · NCI · MORGRIDGE INSTITUTE FOR RESEARCH, INC. · PI SKALA, MELISSA CAROLINE · 2017 to 2021
$3.5M
(PQ7) Quantitative in vivo optical imaging of tumor heterogeneityR01CA205101 · NCI · MORGRIDGE INSTITUTE FOR RESEARCH, INC. · PI SKALA, MELISSA CAROLINE · 2016 to 2020
$1.9M
Cellular-level Optical Metabolic Imaging to Predict Drug Response in CancerR01CA185747 · NCI · VANDERBILT UNIVERSITY · PI SKALA, MELISSA CAROLINE · 2014 to 2019
$1.6M
Targeting cancer-stroma interactions in breast cancer metastasis using organotypic modelingF31CA247248 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI HUMAYUN, MOUHITA · 2019 to 2021
$67k
NCI NIH HHS F31 CA247248NCI NIH HHS R01 CA185747NCI NIH HHS R01 CA205101NCI NIH HHS R01 CA211082
6 · The paper itself

Abstract

Macrophages within the tumor microenvironment (TME) exhibit a spectrum of protumor and antitumor functions, yet it is unclear how the TME regulates this macrophage heterogeneity. Standard methods to measure macrophage heterogeneity require destructive processing, limiting spatiotemporal studies of function within the live, intact 3D TME. Here, we demonstrate two-photon autofluorescence imaging of NAD(P)H and FAD to nondestructively resolve spatiotemporal metabolic heterogeneity of individual macrophages within 3D microscale TME models. Fluorescence lifetimes and intensities of NAD(P)H and FAD were acquired at 24, 48, and 72 hours poststimulation for mouse macrophages (RAW264.7) stimulated with IFNγ or IL4 plus IL13 in 2D culture, confirming that autofluorescence measurements capture known metabolic phenotypes. To quantify metabolic dynamics of macrophages within the TME, mouse macrophages or human monocytes (RAW264.7 or THP-1) were cultured alone or with breast cancer cells (mouse polyoma-middle T virus or primary human IDC) in 3D microfluidic platforms. Human monocytes and mouse macrophages in tumor cocultures exhibited significantly different FAD mean lifetimes and greater migration than monocultures at 24, 48, and 72 hours postseeding. In cocultures with primary human cancer cells, actively migrating monocyte-derived macrophages had greater redox ratios [NAD(P)H/FAD intensity] compared with passively migrating monocytes at 24 and 48 hours postseeding, reflecting metabolic heterogeneity in this subpopulation of monocytes. Genetic analyses further confirmed this metabolic heterogeneity. These results establish label-free autofluorescence imaging to quantify dynamic metabolism, polarization, and migration of macrophages at single-cell resolution within 3D microscale models. This combined culture and imaging system provides unique insights into spatiotemporal tumor-immune cross-talk within the 3D TME. SIGNIFICANCE: Label-free metabolic imaging and microscale culture technologies enable monitoring of single-cell macrophage metabolism, migration, and function in the 3D tumor microenvironment.

Indexed as

AnimalsBreast NeoplasmsCell Culture TechniquesCell MovementCoculture TechniquesFemaleFlavin-Adenine DinucleotideHumansImaging, Three-DimensionalLab-On-A-Chip DevicesMacrophagesMiceNADPOptical ImagingRAW 264.7 CellsTumor MicroenvironmentFlavin-Adenine DinucleotideNADP

Identifiers

PMID33093167
PMCPMC7718391
OpenAlexW3093718969

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.