Targeting the Metabolic Dependencies of Metastatic Tumor Cells
This project aims to identify and target unique amino acid dependencies in metastatic melanoma cells to develop novel therapies that prevent metastasis and improve cancer treatment outcomes.
Projectdetails
Introduction
Metastasis is responsible for over 90% of deaths that occur in patients with cancer. So far, there are no therapies that precisely target metastatic disease due to the limited number of efficient druggable targets.
Recent Discoveries
Recently, I discovered in melanoma that circulating tumor cells depend on arginine for their survival. In addition, I revealed that liver metastases specifically upregulate their alanine metabolism during metastasis. Thus, metastatic cells at different stages have dependencies on unique amino acids (AA).
Research Focus
While most research focuses on the primary stage, my proposal will address the missing gap aiming to prevent metastasis formation. Based on these new paradigm-changing discoveries, I hypothesize that metastatic cells modulate their AA metabolism during metastatic progression, and targeting the unique AA dependencies will decrease their survival and metastatic potential.
Methodology
Using sophisticated in vivo metastasis assays both in mice and in patients, cutting-edge mass spectrometry, and in vivo isotope tracing technologies, I will identify metastasis-specific inhibitors by investigating the following questions:
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How does arginine support melanoma cell survival in circulation?
By using metabolomics, stable isotope tracer analysis, and transplantation assays both in mice and humans, I will uncover how we can use this unique AA dependency of circulating tumor cells (CTCs) as a novel target. -
How does metabolic heterogeneity in the circulating tumor cells support organotropism?
To mechanically dissect metastatic organotropism, I will map metabolic differences in melanoma metastases and also examine how we can target alanine metabolism to block metastases.
Conclusion
The understanding of AA adaptation of cancer cells is essential for the prevention of metastasis. My results will reveal new metabolic pathways that are required by metastasizing cells in vivo and therefore will fundamentally advance the ability to develop new targeted therapies for preventing early and late-stage metastatic cancer.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.493.750 |
Totale projectbegroting | € 1.493.750 |
Tijdlijn
Startdatum | 1-6-2024 |
Einddatum | 31-5-2029 |
Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- UNIVERSITAETSKLINIKUM ESSENpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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Intercellular trading in nucleotide metabolism: an emerging target
This project aims to identify nucleotide sources and metabolic interactions in cancer and stromal cells using single-cell multi-omics to develop targeted therapies against nucleotide-dependent tumors.
Targeting Palmitic Acid Signaling Machinery to Inhibit Metastatic Cancer
PalmitoMET seeks to discover inhibitors of specific protein lipidation to combat cancer metastasis, aiming to develop first-in-class drugs for preclinical and clinical applications.
Treating Liver Metastasis
This project aims to enhance immunotherapy for colorectal liver metastases by targeting innate immune responses, utilizing advanced models to identify key cellular interactions and functions.
Targeting Mfrn2 to Inhibit Metastatic Cancers
This project aims to evaluate a solute carrier transporter as a drug target to inhibit metastatic growth in breast cancer, utilizing patient samples and mouse models for comprehensive analysis.
Formate-dependent Regulation of Cancer Metastasis
This project aims to elucidate the role of formate overflow in cancer metastasis and develop targeted therapies by investigating mitochondrial one-carbon metabolism and its signaling mechanisms.
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The project aims to develop TAX2, a novel peptide therapy targeting the tumor microenvironment to inhibit solid tumor progression and enhance immunotherapy efficacy, with a focus on ovarian cancer.
3D spheroids derived from single cells for discovering stochastic patterns behind metastasis
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