Approximately 40% ERα-positive breast cancer patients suffer from therapeutic resistance to tamoxifen. Although reduced ERα level is the major cause of tamoxifen resistance, the underlying mechanisms remain elusive. Here, we report that FRMD8 raises the level of ERα at both transcriptional and post-translational layers. FRMD8 deficiency in MMTV-Cre⁺; Frmd8^fl/fl; PyMT mice accelerates mammary tumor growth and loss of luminal phenotype, and confers tamoxifen resistance. Single-cell RNA profiling reveals that Frmd8 loss decreases the proportion of hormone-sensing differentiated epithelial cells and downregulates the levels of ERα. Mechanically, on one hand, loss of FRMD8 inhibits ESR1 transcription via suppressing the expression of FOXO3A, a transcription factor of ESR1. On the other hand, FRMD8 interacts both with ERα and UBE3A, and disrupts the interaction of UBE3A with ERα, thereby blocking UBE3A-mediated ERα degradation. In breast cancer patients, FRMD8 gene promoter is found hypermethylated and low level of FRMD8 predicts poor prognosis. Therefore, FRMD8 is an important regulator of ERα and may control therapeutic sensitivity to tamoxifen in ERα-positive breast cancer patients.

The tumor stroma consists mainly of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions are altered during malignancy: tumor cells transform fibroblasts into cancer-associated fibroblasts, which exhibit immunosuppressive activities on which growth and metastasis depend. These include exclusion of immune cells from the tumor nest, cancer progression, and inhibition of T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data into a minimal dynamical system, explore the variety of outcomes, and finally establish a spatio-temporal model that explains the cell distribution. We reproduce that cancer-associated fibroblasts act as a barrier to tumor expansion, but also reduce the efficiency of the immune response. Our conclusion is that the final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxicity, and fibroblast activity. However, despite the existence of a wide range of scenarios, distinct trajectories, and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols.