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Imaging-derived biomarkers in metastatic breast cancer: towards optimizing personalized treatment strategies

PhD ceremony:drs. B. van Essen-EissesWhen:June 15, 2026 Start:12:45Supervisors:dr. C.P. (Carolien) Schröder, prof. dr. E.G.E. (Elisabeth) de VriesWhere:Academy building UGFaculty:Medical Sciences / UMCG
Imaging-derived biomarkers in metastatic breast cancer: towards
optimizing personalized treatment strategies

Imaging-derived biomarkers in metastatic breast cancer: towards optimizing personalized treatment strategies

This thesis of Bertha van Essen-Eisses investigated how tumor biopsies, advanced PET imaging, and the analysis of tumor cells circulating in the blood may help identify the most effective treatment for patients with metastatic breast cancer. The results show that PET imaging can provide important additional whole-body information beyond a biopsy of a single metastasis. By visualizing HER2, a protein involved in the regulation of cell growth and division (HER2-PET imaging), it became apparent that metastases within the same patient can differ substantially in HER2 expression. This may potentially support treatment selection for HER2-targeted therapies.

The thesis also investigated whether FDG-PET imaging, which visualizes glucose consumption by cancer cells, could provide information about treatment effectiveness early during therapy. Improvement on FDG-PET as early as two weeks after treatment initiation was able to identify patients with a better prognosis. In the future, this may contribute to earlier treatment adjustments. Furthermore, the study showed that circulating tumor cells (CTCs) in the blood provide additional prognostic information alongside FES-PET imaging, which visualizes hormone-sensitive cancer cells throughout the body, and tissue biopsies.

This thesis demonstrates that combining molecular imaging with PET scans, tissue analysis, and circulating tumor cells may contribute to more personalized care for patients with metastatic breast cancer. In the future, this approach may help physicians select the most appropriate treatment more quickly while avoiding unnecessary treatments and side effects.

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