Data from: In vivo imaging of metabolic heterogeneity across three endpoints relevant to aggressive breast cancer

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  • Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with poor prognosis and a high likelihood of recurrence. Residual disease after therapy is a key predictor of recurrence, often driven by intra-tumoral metabolic heterogeneity. Accumulating evidence indicates that tumors shift between glycolysis and oxidative pathways, relying on alternative substrates such as fatty acid oxidation (FAO) to sustain growth and resist therapy. To investigate spatially distinct metabolic profiles within tumors, we developed a novel in vivo imaging method that leverages exogenous fluorophores to concurrently quantify oxidative phosphorylation and two key substrates that drive it: glucose and fat. We first developed an unmixing method to differentiate spectrally overlapping fluorophores. Next, we validated a concurrent imaging scheme where each fluorophore is injected into a living animal and imaged through a window chamber. Finally, we investigated heterogeneity and spatial relationships between metabolic endpoints. We validated our unmixing method in scattering phantoms. We validated our imaging system in vivo; we saw no significant difference in fluorophore measurements when all three were present versus the gold standard. Normal tissues displayed predominantly oxidative phosphorylation. Tumor tissues relied on both glucose (low mitochondrial metabolism, suggesting glycolysis) and fatty acids (high mitochondrial metabolism suggesting FAO). A single metabolic phenotype was uniformly distributed across normal tissues; tumors were more heterogeneous. These findings underscore the presence of simultaneous yet compartmentalized metabolic pathways within a single tumor. This study establishes a validated imaging strategy for quantifying metabolic heterogeneity in living tumors, enabling deeper insights into the metabolic underpinnings of TNBC.

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Total Size
6 files (11.9 GB)
Data Citation
  • D'Agostino, V. W. & Ramanujam, N. (2025). Data from: In vivo imaging of metabolic heterogeneity across three endpoints relevant to aggressive breast cancer. Duke Research Data Repository. https://doi.org/10.7924/r4z32354z
DOI
  • 10.7924/r4z32354z
Publication Date
ARK
  • ark:/87924/r4z32354z
Collection Dates
  • 2024 to 2025
Language
Type
Format
Funding Agency
  • National Institutes of Health
Grant Number
  • 1R01EB02818-01
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Title
  • Data from: In vivo imaging of metabolic heterogeneity across three endpoints relevant to aggressive breast cancer
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file details README.txt 2025-06-11 Public Download
file details Figure 1 Raw Data and Scripts.zip 2025-06-11 Public
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file details Figure 2 Scripts.zip 2025-06-11 Public Download
file details Figure 2, 3, 4, and SI Raw Data.zip 2025-06-11 Public
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file details Figure 4 Script.zip 2025-06-11 Public Download
file details Figure SI3 Script.zip 2025-06-11 Public Download

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