Evidence map›Paper›PMID 37020875›Full record

ArticleFrontiers in oncology2023

Single cell metabolic imaging of tumor and immune cells

Alexa R Heaton, Peter R Rehani, Anna Hoefges, Angelica F Lopez, Amy K Erbe, Paul M Sondel, Melissa C Skala

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Imaging immunometabolismImmunometabolism (Cobham, Surrey) · 2024
    Article
  9. Article
  10. Review
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

7 authors at 2 institutions in 1 country.

Alexa R HeatonMorgridge Institute for Research, Madison, WI, United States.
Peter R RehaniMorgridge Institute for Research, Madison, WI, United States.
Anna HoefgesDepartment of Human Oncology, University of Wisconsin, Madison, WI, United States.
Angelica F LopezDepartment of Biomedical Engineering, University of Wisconsin, Madison, WI, United States.
Amy K ErbeDepartment of Human Oncology, University of Wisconsin, Madison, WI, United States.
Paul M SondelDepartment of Human Oncology, University of Wisconsin, Madison, WI, United States.
Melissa C SkalaMorgridge Institute for Research, Madison, WI, United States.
University of Wisconsin–Madison · USMorgridge Institute for Research · US

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Christian Capitini · 1985 to 2026
$142.6M
University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Understanding and Overcoming Resistance to Immunotherapies in Childhood CancersU54CA232568 · NCI · CHILDREN'S HOSP OF PHILADELPHIA · PI MACKALL, CRYSTAL, MARIS, JOHN M · 2018 to 2022
$13.1M
Radionuclide Production and Radiochemistry Core Description CoreP01CA250972 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI BEDNARZ, BRYAN PATRICK · 2020 to 2024
$12.5M
Enhancing Antibody-directed Innate Immunity to Improve Cancer OutcomeR35CA197078 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI SONDEL, PAUL M · 2015 to 2021
$6.4M
(PQ7) Quantitative in vivo optical imaging of tumor heterogeneityR01CA205101 · NCI · MORGRIDGE INSTITUTE FOR RESEARCH, INC. · PI SKALA, MELISSA CAROLINE · 2016 to 2020
$1.9M
Automated Tissue MicroarrayerS10OD023526 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI MATKOWSKYJ, KRISTINA A. · 2018 to 2018
$184k
NCATS NIH HHS UL1 TR002373NCI NIH HHS P01 CA250972NCI NIH HHS P30 CA014520NCI NIH HHS R01 CA205101NCI NIH HHS R35 CA197078NCI NIH HHS U54 CA232568NIH HHS S10 OD023526
6 · The paper itself

Abstract

Introduction: Metabolic reprogramming of cancer and immune cells occurs during tumorigenesis and has a significant impact on cancer progression. Unfortunately, current techniques to measure tumor and immune cell metabolism require sample destruction and/or cell isolations that remove the spatial context. Two-photon fluorescence lifetime imaging microscopy (FLIM) of the autofluorescent metabolic coenzymes nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) provides Methods: Here, we report an immunocompetent mCherry reporter mouse model for immune cells that express CD4 either during differentiation or CD4 and/or CD8 in their mature state and perform Results: We found that immune cells within B78 tumors exhibited decreased FAD mean lifetime and an increased proportion of bound FAD compared to immune cells within spleens. Tumor infiltrating immune cell size also increased compared to immune cells from spleens. These changes are consistent with a shift towards increased activation and proliferation in tumor infiltrating immune cells compared to immune cells from spleens. Tumor infiltrating immune cells exhibited increased FAD mean lifetime and increased protein-bound FAD lifetime compared to B78 tumor cells within the same tumor. Single cell metabolic heterogeneity was observed in both immune and tumor cells Discussion: This approach can be used to monitor single cell metabolic heterogeneity in tumor cells and immune cells to study promising treatments for cancer in the native

Indexed as

autofluorescenceimmune cellsintravital imagingmelanomametabolismmultiphoton/two-photon imagingmurine models

Identifiers

PMID37020875
PMCPMC10067577
OpenAlexW4327979147

What OpenQuestion holds

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LicenceCC BY
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.