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Biology subjects

Charville, G. W.

Publications and source records attributed to Charville, G. W..

5 recordsLinked to original sources

A spatial map of human macrophage niches links tissue location with function

Macrophages are the most abundant immune cell type in the tumor microenvironment (TME). Yet the spatial distribution and cell interactions that shape macrophage function are incompletely understood. Here we use single-cell RNA sequencing data and multiplex imaging to discriminate and spatially resolve macrophage niches within benign and malignant breast and colon tissue. We discover four distinct tissue-resident macrophage (TRM) layers within benign bowel, two TRM niches within benign breast, and three tumor-associated macrophage (TAM) populations within breast and colon cancer. We demonstrate that IL4I1 marks phagocytosing macrophages, SPP1 TAMs are enriched in hypoxic and necrotic tumor regions, and a novel subset of FOLR2 TRMs localizes within the plasma cell niche. Furthermore, NLRP3 TAMs that colocalize with neutrophils activate an inflammasome in the TME and in Crohns disease and are associated with poor outcomes in breast cancer patients. This work suggests novel macrophage therapy targets and provides a framework to study human macrophage function in clinical samples.

cancer biology↗

Single-cell analysis of non-alcoholic fatty livers identifies a role for the constitutive androstane receptor

Non-alcoholic fatty liver disease is a heterogeneous disease with unclear underlying molecular mechanisms. While several genetic risk factors have been identified, the cellular and molecular heterogeneity associated with the development of hepatic steatosis are still not fully understood. Here, we perform single-cell RNA sequencing of hepatocytes and hepatic nonparenchymal cells to map the lipid signatures in mice with non-alcoholic fatty liver disease (NAFLD). We uncover previously unidentified clusters of hepatocytes characterized by either high or low srebp1 expression with unique molecular signatures of lipid synthesis. We find that NAFLD livers have elevated expression of the constitutive androstane receptor (CAR), a gene previously associated with lipid synthesis. Furthermore, nuclear expression of CAR positively correlates with steatohepatitis in humans. These findings demonstrate significant cellular differences in lipid signatures and identify a gene with a high likelihood of being linked to hepatic steatosis in humans.

cell biology↗

7-UP: generating in silico CODEX from a small set of immunofluorescence markers

Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex imaging can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework, 7-UP, that can computationally generate in silico 40-plex CODEX at single-cell resolution from a standard 7-plex mIF panel by leveraging cellular morphology. We demonstrate the usefulness of the imputed biomarkers in accurately classifying cell types and predicting patient survival outcomes. Furthermore, 7-UPs imputations generalize well across samples from different clinical sites and cancer types. 7-UP opens the possibility of in silico CODEX, making insights from high-plex mIF more widely available.

bioinformatics↗

Interactions in CSF1-driven Tenosynovial Giant Cell Tumors

The majority of cells in Tenosynovial Giant Cell Tumor (TGCT) are macrophages responding to CSF1 that is overproduced by a small number of neoplastic cells with a chromosomal translocation involving the CSF1 gene. Treatment with inhibitors of the CSF1 pathway has been clinically effective. An autocrine loop was postulated where the neoplastic cells are stimulated through the CSF1 receptor (CSF1R) expressed on their surface. Here we show that the neoplastic cells themselves do not express CSF1R and therefore may be unaffected by current therapies. We identified a new marker for synoviocytes, GFPT2, that highlights the tumor cells in TCGT and is associated with activation of the YAP1/TAZ pathway. The neoplastic cells in TGCT are highly similar non-neoplastic synoviocytes. Finally, we provide molecular support for the osteoclast-like features of the giant cells in TGCT that correlate with the destructive effects of TGCT on bone.

cancer biology↗

SPACE-GM: geometric deep learning of disease-associated microenvironments from multiplex spatial protein profiles.

Multiplexed immunofluorescence imaging enables high-dimensional molecular profiling at subcellular resolution. However, learning disease-relevant cellular environments from these rich imaging data is an open challenge. We developed SPAtial CEllular Graphical Modeling (SPACE-GM), a geometric deep learning framework that flexibly models tumor microenvironments (TMEs) as cellular graphs. We applied SPACE-GM to 658 head-and-neck and colorectal human cancer samples assayed with 40-plex immunofluorescence imaging to identify spatial motifs associated with cancer recurrence and patient survival after immunotherapy. SPACE-GM is substantially more accurate in predicting patient outcomes than previous approaches for modeling spatial data using neighborhood cell-type compositions. Computational interpretation of the disease-relevant microenvironments identified by SPACE-GM generates insights into the effect of spatial dispersion of tumor cells and granulocytes on patient prognosis.

bioinformatics↗