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'UNMET' - Uncovering Mechanisms and Establishing Strategies to Target Vessel Co-Opted Colorectal Cancer Liver Metastases

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An estimated 25-50% of colorectal cancer patients will encounter liver metastasis during their illness. Tumor vessel co-option is a non-angiogenic mechanism whereby tumors, rather than forming new blood vessels (a process known as angiogenic growth), hijack pre-existing blood vessels in the affected organ. Standard anti-angiogenic therapy (AAT) is ineffective against vessel co-optioned tumors. This process has been linked to unfavorable patient outcomes. The exact mechanisms distinguishing vessel co-option remain elusive. Preliminary data suggest that metastatic cancer displaying the vessel co-option phenotype increased in gene expression, regulated by Lymphoid enhancer binding factor 1 or LEF1 protein, which is a key mediator of the Wnt/-catenin signaling. The dysregulation of the Wnt pathway can activate target genes that promote cell proliferation and survival. In this proposal, I hypothesize, that inhibition of the Wnt signaling (e.g. by blocking LEF1), will change the properties of vessel co-optioned tumors and improve the effectiveness of conventional treatment for liver metastases. Patient-derived organoids, obtained from hospitals, will be used to validate whether the inhibition of LEF1 will impact the vessel co-option phenotype, making it more susceptible to AAT. Advanced microscopy techniques, like Atomic force microscopy and Scanning ion-conductance microscopy, will facilitate monitoring the decreased stiffness of vessel co-opted tumor cells, leading to improved AAT delivery. By using humanized patient-derived organoid xenografts with inhibited Wnt signaling, I will monitor tumor growth, its phenotype, and the response to AAT in vivo. Furthermore, I aim to pinpoint diagnostic markers for vessel co-option tumors using blood tests and computed tomography (CT) scans. Utilizing artificial intelligence tools, I plan to analyze CT scans of liver patients to better predict metastatic tumor subtypes and treatment responses in the future.

Wissenschaftliches Gebiet (EuroSciVoc)

CORDIS klassifiziert Projekte mit EuroSciVoc, einer mehrsprachigen Taxonomie der Wissenschaftsbereiche, durch einen halbautomatischen Prozess, der auf Verfahren der Verarbeitung natürlicher Sprache beruht.

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AARHUS UNIVERSITET
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Dänemark

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