Evidence map›Paper›PMID 37343066›Full record

ArticleMolecular cancer research : MCR2023

Metabolic Imaging as a Tool to Characterize Chemoresistance and Guide Therapy in Triple-Negative Breast Cancer (TNBC).

Enakshi D Sunassee, Bruna Victorasso Jardim-Perassi, Megan C Madonna, Bryce Ordway, Nirmala Ramanujam

Abstract read
In one paragraph

Article in Molecular cancer research : MCR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
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. Article
  2. Article
  3. Article
  4. Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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.

Enakshi D SunasseeDepartment of Biomedical Engineering, Duke University, Durham, North Carolina.ORCID 0000-0002-8346-442X
Bruna Victorasso Jardim-PerassiDepartment of Cancer Physiology, Moffitt Cancer Center, Tampa, Florida.ORCID 0000-0001-5908-4470
Megan C MadonnaDepartment of Biomedical Engineering, Duke University, Durham, North Carolina.ORCID 0000-0001-8297-7672
Bryce OrdwayDepartment of Cancer Physiology, Moffitt Cancer Center, Tampa, Florida.ORCID 0000-0002-1492-9473
Nirmala RamanujamDepartment of Biomedical Engineering, Duke University, Durham, North Carolina.ORCID 0000-0001-7319-8415

Funding

Development of CapCell Scope for Metabolic Imaging of Tissue Heterogeneity and Therapy ResponseR01EB028148 · NIBIB · DUKE UNIVERSITY · PI ANDREI GOGA, Nirmala Ramanujam · 2019 to 2026
$4.0M
NIBIB NIH HHS R01 EB028148
6 · The paper itself

Abstract

After an initial response to chemotherapy, tumor relapse is frequent. This event is reflective of both the spatiotemporal heterogeneities of the tumor microenvironment as well as the evolutionary propensity of cancer cell populations to adapt to variable conditions. Because the cause of this adaptation could be genetic or epigenetic, studying phenotypic properties such as tumor metabolism is useful as it reflects molecular, cellular, and tissue-level dynamics. In triple-negative breast cancer (TNBC), the characteristic metabolic phenotype is a highly fermentative state. However, during treatment, the spatial and temporal dynamics of the metabolic landscape are highly unstable, with surviving populations taking on a variety of metabolic states. Thus, longitudinally imaging tumor metabolism provides a promising approach to inform therapeutic strategies, and to monitor treatment responses to understand and mitigate recurrence. Here we summarize some examples of the metabolic plasticity reported in TNBC following chemotherapy and review the current metabolic imaging techniques available in monitoring chemotherapy responses clinically and preclinically. The ensemble of imaging technologies we describe has distinct attributes that make them uniquely suited for a particular length scale, biological model, and/or features that can be captured. We focus on TNBC to highlight the potential of each of these technological advances in understanding evolution-based therapeutic resistance.

Indexed as

Triple Negative Breast NeoplasmsDrug Resistance, NeoplasmHumansNeoplasm Recurrence, LocalTumor Microenvironment

Identifiers

PMID37343066
PMCPMC10592445

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Registered trials

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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.