One out of 8 women develops breast cancer (BC) in her lifetime and 1 out of 2 is overweight or obese in industrialized countries. While heavier women have an increased risk of developing BC and heavier BC patients present with worse disease characteristics, BC is so far still treated regardless of patient adiposity because of the limited knowledge accumulated so far.
I hypothesize that increased adiposity provides a different ‘soil’ for the tumor cells (the 'seeds') to grow, potentially leading to biological peculiarities of the tumor cells and the cells from the tumor microenvironment. To investigate this hypothesis, I will firstly study the associations between patient adiposity and the genomic and transcriptomic features of the bulk tumor in >2.700 BC patients (FATomics). Secondly, I will complement these findings at the single cell level by creating a comprehensive atlas of BC according to various patient and mammary adiposity measures for the two most common BC histological subtypes (FATlas). Special attention will be given to the mammary fat cells, the adipocytes, and how these help tumor cells to grow and affect treatment efficacy. State-of-the-art technologies such as single-nuclei RNA sequencing, spatial protein visualization and digital pathology will be applied. Thirdly, the FATlas data will be shared with the scientific community through a web-based dataportal (FATshare). Finally, using samples from a prospective in-house clinical trial, I will investigate whether adiposity-associated features are associated with anti-proliferative and/or immune response to immunotherapy and endocrine therapy (FATrial).
FAT-BC integrates complementary and multidisciplinary approaches with state-of-the-art technologies and will build upon my expertise in BC biology. The results should lead to the identification of potential strategies to tailor BC treatment according to adiposity, a still unmet clinical need in the context of personalized medicine.
Fields of science
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