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Macrophages are pivotal in driving breast tumor development, progression, and resistance to treatment, particularly in estrogen receptor-positive (ER+) tumors, where they infiltrate the tumor microenvironment (TME) influenced by cancer cell-secreted factors. By analyzing single-cell RNA sequencing data from 25 ER+ tumors, we elucidated interactions between cancer cells and macrophages, correlating macrophage density with epithelial cancer cell density. We identified that S100A11, a previously unexplored factor in macrophage-cancer crosstalk, predicts high macrophage density and poor outcomes in ER+ tumors. We found that recombinant S100A11 enhances macrophage infiltration and migration in a dose-dependent manner. Additionally, in a 3D matrix using a panel of three ER+ breast cancer cell lines, we showed that secreted S100A11 levels from cancer cells were associated with increased monocyte infiltration that subsequently differentiation toward macrophages. Genetic silencing of S100A11 in the S100A11-high T47D cancer cells reduced monocyte infiltration, consistent with results using a S100A11 blocking antibody in T47D cancer cells and in a clinically relevant patient-derived organoid model. Phenotypic analysis of macrophages cocultured with T47D cancer cells following S100A11 knockdown revealed lower expression of the immunosuppressive marker CD206, further underscoring the role of S100A11 as a paracrine regulator of pro-tumorigenic cancer-macrophage crosstalk. This study offers novel insights into the interplay between macrophages and cancer cells in ER+ breast tumors, highlighting S100A11 as a potential therapeutic target to modulate the macrophage-rich tumor microenvironment. [ABSTRACT FROM AUTHOR]

Transcription factors (TFs) drive significant cellular changes in response to environmental cues and intercellular signaling. Neighboring cells influence TF activity and, consequently, cellular fate and function. Spatial transcriptomics (ST) captures mRNA expression patterns across tissue samples, enabling characterization of the local microenvironment. However, these datasets have not been fully leveraged to systematically estimate TF activity governing cell identity. Here, we present STAN ( S patially informed T ranscription factor A ctivity N etwork), a linear mixed-effects computational method that predicts spot-specific, spatially informed TF activities by integrating curated TF-target gene priors, mRNA expression, spatial coordinates, and morphological features from corresponding imaging data. We tested STAN using lymph node, breast cancer, and glioblastoma ST datasets to demonstrate its applicability by identifying TFs associated with specific cell types, spatial domains, pathological regions, and ligand‒receptor pairs. STAN augments the utility of STs to reveal the intricate interplay between TFs and spatial organization across a spectrum of cellular contexts.

Macrophages are pivotal in driving breast tumor development, progression, and resistance to treatment, particularly in estrogen receptor-positive (ER+) tumors, where they infiltrate the tumor microenvironment (TME) influenced by cancer cell-secreted factors. By analyzing single-cell RNA-sequencing data from 25 ER+ tumors, we elucidated interactions between cancer cells and macrophages, correlating macrophage density with epithelial cancer cell density. We identified that S100A11, a previously unexplored factor in macrophage-cancer crosstalk, predicts high macrophage density and poor outcomes in ER+ tumors. We found that recombinant S100A11 enhances macrophage infiltration and migration in a dose-dependent manner. Additionally, in 3D models, we showed that S100A11 expression levels in ER+ cancer cells predict macrophage infiltration patterns. Neutralizing S100A11 decreased macrophage recruitment, both in cancer cell lines and in a clinically relevant patient-derived organoid model, underscoring its role as a paracrine regulator of cancer-macrophage interactions in the protumorigenic TME. This study offers novel insights into the interplay between macrophages and cancer cells in ER+ breast tumors, highlighting S100A11 as a potential therapeutic target to modulate the macrophage-rich tumor microenvironment., Competing Interests: Competing interests The authors declare that they have no competing interests.

High-grade serous ovarian carcinoma (HGSOC) is a heterogeneous disease, and a high stromal/desmoplastic tumor microenvironment (TME) is associated with a poor outcome. Stromal cell subtypes, including fibroblasts, myofibroblasts, and cancer-associated mesenchymal stem cells, establish a complex network of paracrine signaling pathways with tumor-infiltrating immune cells that drive effector cell tumor immune exclusion and inhibit the antitumor immune response. Single-cell transcriptomics of the HGSOC TME from public and in-house datasets revealed a distinct transcriptomic landscape for immune and non-immune cells in high-stromal vs. low-stromal tumors. High-stromal tumors had a lower fraction of certain T cells, natural killer (NK) cells, and macrophages and increased expression of CXCL12 in epithelial cancer cells and cancer-associated mesenchymal stem cells (CA-MSCs). Analysis of cell-cell communication indicated that epithelial cancer cells and CA-MSCs secreted CXCL12 that interacted with the CXCR4 receptor, which was overexpressed on NK and CD8 + T cells. CXCL12 and/or CXCR4 antibodies confirmed the immunosuppressive role of CXCL12-CXCR4 in high-stromal tumors.

Point-of-care documentation has been identified as a patient safety measure for improving accuracy and timeliness of data. To evaluate the barriers that nurses and nurse aide/clinical technicians encounter for electronic point-of-care documentation, we conducted surveys on a telemetry unit at a southwestern Pennsylvania community hospital. Our first survey revealed that the location of the in-room computers, perceived lack of in-room computer reliability, Health Insurance Portability and Accountability Act/privacy concerns, and perceptions of the patients' response to charting on computers in patient rooms were all barriers to point-of-care documentation. Our second survey revealed that workflow priority issues were also a barrier to point-of-care documentation, as staff members did not rate documentation as a high priority in terms of delivering timely medical care. Changes in both nursing practices and hospital infrastructure may be needed if these barriers to point-of-care documentation are to be overcome.