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Arnold, J. N.

Publications and source records attributed to Arnold, J. N..

2 recordsLinked to original sources

Lyve-1 expressing perivascular macrophages orchestrate pericyte expansion to sustain angiogenesis in cancer

Tumor associated macrophages (TAMs) are a highly plastic stromal cell type which support cancer progression. Using single-cell RNA-sequencing of TAMs from a spontaneous murine model of mammary adenocarcinoma (MMTV-PyMT) we characterize a subset of these cells expressing lymphatic vessel endothelial hyaluronic acid receptor 1 (Lyve-1) which spatially reside proximal to blood vasculature. We demonstrate that Lyve-1+ TAMs support tumor growth and identify a pivotal role for these cells in maintaining a population of perivascular mesenchymal cells which express alpha-smooth muscle actin and phenotypically resemble pericytes. Using photolabeling techniques show that mesenchymal cells maintain their prevalence in the growing tumor through proliferation and uncover a role for Lyve-1+ TAMs in orchestrating a selective platelet-derived growth factor-CC-dependent expansion of the perivascular mesenchymal population, creating a pro-angiogenic niche. This study highlights the inter-reliance of the immune and non-immune stromal network which support cancer progression and provides therapeutic opportunities for tackling the disease.

cancer biology

ImmunoCluster: A computational framework for the non-specialist to immune profile cellular heterogeneity using liquid and imaging mass, and flow cytometry datasets

High dimensional cytometry is an innovative tool for immune monitoring in health and disease, it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of multiparametric "big data" usually requires specialist computational knowledge. Here we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster) an R package for immune profiling cellular heterogeneity in high dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a non-specialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users needs. The protocol consists of three core computational stages: 1, data import and quality control, 2, dimensionality reduction and unsupervised clustering; and 3, annotation and differential testing, all contained within an R-based open-source framework.

systems biology