Tumor associated macrophages (TAMs), which differentiate from circulating monocytes, are pervasive across human cancers and comprise heterogeneous populations. The contribution of tumor-derived signals to TAM heterogeneity is not well understood. In particular, tumors release both soluble factors and extracellular vesicles (EVs), whose respective impact on TAM precursors may be different. Here, we show that triple negative breast cancer cells (TNBCs) release EVs and soluble molecules promoting monocyte differentiation toward distinct macrophage fates. EVs specifically promoted proinflammatory macrophages bearing an interferon response signature. The combination in TNBC EVs of surface CSF-1 promoting survival and cargoes promoting cGAS/STING or other activation pathways led to differentiation of this particular macrophage subset. Notably, macrophages expressing the EV-induced signature were found among patients’ TAMs. Furthermore, higher expression of this signature was associated with T cell infiltration and extended patient survival. Together, this data indicates that TNBC-released CSF-1-bearing EVs promote a tumor immune microenvironment associated with a better prognosis in TNBC patients.
Pubmed ID: 35439048 RIS Download
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A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.
View all literature mentionsRepository for all research outputs from across all fields of science in any file format as well as both positive and negative results. They assign all publicly available uploads a Digital Object Identifier (DOI) to make the upload easily and uniquely citeable. They further support harvesting of all content via the OAI-PMH protocol. They promote peer-reviewed openly accessible research, and curate uploads. ZENODO allows users to create their own collection and accept or reject all uploads to it. They allow for uploading under a multitude of different licenses and access levels.
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