Changes in epithelial proportions and transcriptional state underlie major premenopausal breast cancer risks

The human breast undergoes lifelong remodeling in response to estrogen and progesterone, but hormone exposure also increases breast cancer risk. Here, we use single-cell analysis to identify distinct mechanisms through which breast composition and cell state affect hormone signaling. We show that prior pregnancy reduces the transcriptional response of hormone-responsive (HR+) epithelial cells, whereas high body mass index (BMI) reduces overall HR+ cell proportions. These distinct changes both impact neighboring cells by effectively reducing the magnitude of paracrine signals originating from HR+ cells. Because pregnancy and high BMI are known to protect against hormone-dependent breast cancer in premenopausal women, our findings directly link breast cancer risk with person-to-person heterogeneity in hormone responsiveness. More broadly, our findings illustrate how cell proportions and cell state can collectively impact cell communities through the action of cell-to-cell signaling networks

MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices.

Sample multiplexing facilitates scRNA-seq by reducing costs and identifying artifacts such as cell doublets. However, universal and scalable sample barcoding strategies have not been described. We therefore developed MULTI-seq: multiplexing using lipid-tagged indices for single-cell and single-nucleus RNA sequencing. MULTI-seq reagents can barcode any cell type or nucleus from any species with an accessible plasma membrane. The method involves minimal sample processing, thereby preserving cell viability and endogenous gene expression patterns. When cells are classified into sample groups using MULTI-seq barcode abundances, data quality is improved through doublet identification and recovery of cells with low RNA content that would otherwise be discarded by standard quality-control workflows. We use MULTI-seq to track the dynamics of T-cell activation, perform a 96-plex perturbation experiment with primary human mammary epithelial cells and multiplex cryopreserved tumors and metastatic sites isolated from a patient-derived xenograft mouse model of triple-negative breast cancer

Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution.

The rise and fall of estrogen and progesterone across menstrual cycles and during pregnancy regulates breast development and modifies cancer risk. How these hormones impact each cell type in the breast remains poorly understood because they act indirectly through paracrine networks. Using single-cell analysis of premenopausal breast tissue, we reveal a network of coordinated transcriptional programs representing the tissue-level response to changing hormone levels. Our computational approach, DECIPHER-seq, leverages person-to-person variability in breast composition and cell state to uncover programs that co-vary across individuals. We use differences in cell-type proportions to infer a subset of programs that arise from direct cell-cell interactions regulated by hormones. Further, we demonstrate that prior pregnancy and obesity modify hormone responsiveness through distinct mechanisms: obesity reduces the proportion of hormone-responsive cells, whereas pregnancy dampens the direct response of these cells to hormones. Together, these results provide a comprehensive map of the cycling human breast

ATG12–ATG3 interacts with Alix to promote basal autophagic flux and late endosome function

The ubiquitin-like molecule ATG12 is required for the early steps of autophagy. Recently, we identified ATG3, the E2-like enzyme required for LC3 lipidation during autophagy, as an ATG12 conjugation target. Here, we demonstrate that cells lacking ATG12-ATG3 have impaired basal autophagic flux, accumulation of perinuclear late endosomes, and impaired endolysosomal trafficking. Furthermore, we identify an interaction between ATG12-ATG3 and the ESCRT-associated protein Alix (also known as PDCD6IP) and demonstrate that ATG12-ATG3 controls multiple Alix-dependent processes including late endosome distribution, exosome biogenesis, and viral budding. Lastly, similar to ATG12-ATG3, Alix is functionally required for efficient basal, but not starvation-induced, autophagy. Overall, these results identify a link between the core autophagy and ESCRT machineries and uncover a role for ATG12-ATG3 in late endosome function that is distinct from the canonical role of either ATG in autophagosome formation