ArticleNPJ breast cancer2022
In vivo metabolic imaging identifies lipid vulnerability in a preclinical model of Her2+/Neu breast cancer residual disease and recurrence.
Article in NPJ breast cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 14 citations in OpenAlex.
- Bridging In Vitro and Murine Breast Cancer Models: Advanced Imaging Across Multiscale Experimental Platforms.Cancers · 2026Review
- Fatty acid metabolic reprogramming in the tumor microenvironment: Unraveling mechanisms and therapeutic prospects.Genes & diseases · 2026Review
- In vivo imaging of metabolic heterogeneity across three endpoints relevant to aggressive breast cancer.PNAS nexus · 2026Article
- Cancer Cell Dormancy and Chemotherapy Resistance.Journal of Cancer · 2026Review
- Catabolic rewiring in cancer impacts dietary interventions.Communications biology · 2025Review
- Lipid metabolic reprograming: the unsung hero in breast cancer progression and tumor microenvironment.Molecular cancer · 2025Review
- Metabolic Reprogramming and Adaption in Breast Cancer Progression and Metastasis.Advances in experimental medicine and biology · 2025Review
- Quantifying Spatiotemporal Heterogeneity of Tumor Metabolism and Vasculature with a Multiparametric Point-of-Investigation Microscope.BME frontiers · 2025Article
- Article
- Optical imaging reveals chemotherapy-induced metabolic reprogramming of residual disease and recurrence.Science advances · 2024Article
- Decoding the tumor microenvironment with spatial technologies.Nature immunology · 2023Review
- Non-Mass Spectrometric Targeted Single-Cell Metabolomics.Trends in analytical chemistry : TRAC · 2023Article
- Metabolic Imaging as a Tool to Characterize Chemoresistance and Guide Therapy in Triple-Negative Breast Cancer (TNBC).Molecular cancer research : MCR · 2023Article
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
Recurrent cancer cells that evade therapy is a leading cause of death in breast cancer patients. This risk is high for women showing an overexpression of human epidermal growth factor receptor 2 (Her2). Cells that persist can rely on different substrates for energy production relative to their primary tumor counterpart. Here, we characterize metabolic reprogramming related to tumor dormancy and recurrence in a doxycycline-induced Her2+/Neu model of breast cancer with varying times to recurrence using longitudinal fluorescence microscopy. Glucose uptake (2-NBDG) and mitochondrial membrane potential (TMRE) imaging metabolically phenotype mammary tumors as they transition to regression, dormancy, and recurrence. "Fast-recurrence" tumors (time to recurrence ~55 days), transition from glycolysis to mitochondrial metabolism during regression and this persists upon recurrence. "Slow-recurrence" tumors (time to recurrence ~100 days) rely on both glycolysis and mitochondrial metabolism during recurrence. The increase in mitochondrial activity in fast-recurrence tumors is attributed to a switch from glucose to fatty acids as the primary energy source for mitochondrial metabolism. Consequently, when fast-recurrence tumors receive treatment with a fatty acid inhibitor, Etomoxir, tumors report an increase in glucose uptake and lipid synthesis during regression. Treatment with Etomoxir ultimately prolongs survival. We show that metabolic reprogramming reports on tumor recurrence characteristics, particularly at time points that are essential for actionable targets. The temporal characteristics of metabolic reprogramming will be critical in determining the use of an appropriate timing for potential therapies; namely, the notion that metabolic-targeted inhibition during regression reports long-term therapeutic benefit.
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Registered trials
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.