A novel breast cancer therapy based on secreted protein ligands from CD36+ fibroblasts
Cancer cells recruit and alter fibroblasts' biochemical and physical properties (FBs) to benefit their growth.
Cancer-associated fibroblasts (CAFs) have emerged as potential targets for reprogramming the tumor
microenvironment and for optimizing therapeutic strategies. However, there is a critical gap in research targeting
tumors and CAFs simultaneously. Breast cancer tumors have distinct subtypes. And there is a lack of a
biochemical marker exclusive to CAFs because of their heterogeneity. In fact, the currently available CAF-
targeted therapies succumb to off-target effects, so their applications are limited. We aim to address this
conundrum by testing our central hypothesis that factors secreted from non-cancer-associated FBs that express
CD36—a cell surface receptor downregulated in CAFs—could be utilized as an alternative strategy to induce
growth suppression in subtypes of breast cancer while upregulating CD36 in CAFs. This hypothesis is based on
our pilot study showing that co-transplantation of breast cancer cells with CD36+ FBs dramatically suppressed
tumor growth in animals. Furthermore, for the first time, we identified three active protein ligands in the secretome
of CD36+ FBs and determined the effective concentration of their corresponding recombinant proteins that induce
growth suppression in breast cancer cell lines while overexpressing CD36 in at least one CAF model. This study
is significant because it will have a positive translational impact on breast cancer therapy with reduced toxicity.
We will continue to test our hypothesis through two specific aims and the integration of a novel technological
platform: Aim 1a will identify breast cancer subtypes that are sensitive to the three recombinant proteins (RPs).
To this end, we will employ 3D cultures of the established cell lines and patient-derived organoids. We will also
investigate the overexpression of CD36, by the active ligands, on a panel of CAFs. To facilitate a large number
of experimental variables and intrinsic heterogeneity of organoids, we will develop a novel high-throughput
imaging and high-content screening by coupling printed 3D cultures or organoids with 3D microscopy and deep
learning methods for quantitative profiling of 3D organization and molecular features. Aim 1b will determine the
mechanisms by which the three recombinant proteins induce (a) growth suppression in sensitive breast cancer
subtypes or (b) upregulate CD36 in CAFs. Mechanistic studies will be anchored by apoptotic pathways, the cis-
regulatory networks' prediction, and the application of bioinformatics techniques. It will also include the
mechanisms of mitochondrial dysfunction induced by RPs. Aim 2 will use mouse models to investigate tumor
suppression in sensitive cell lines, mouse tumors, and PDX models. Resected tumors will also be profiled for
tumor morphology and molecular endpoints using advanced computational methods. In addition, in select cases,
tumor sections will be complemented with spatial proteomics/transcriptomic for additional mechanistic studies.
The study is innovative because it applies, for the first time, factors secreted from CD36+ FBs that confer tumor
suppression and could be utilized to treat subtypes of breast cancer with few side effects.