real-time-detection-vitro-tumor-cell-apoptosis-induced-cd8-t-cells-to

Real Time Detection of In Vitro Tumor Cell Apoptosis Induced by CD8<sup>+</sup> T Cells to Study Immune Suppressive Functions of Tumor-infiltrating Myeloid Cells

Potentiation of the tumor-killing ability of CD8+ T cells in tumors, along with their efficient tumor infiltration, is a key element of successful ...

University of Edinburgh

Angiogenesis is important in cancer progression and can be influenced by tumor-associated myofibroblasts. We addressed the hypothesis that glucocorticoids indirectly affect angiogenesis by altering the release of pro-angiogenic factors from colon cancer-derived myofibroblasts. Our study shows that glucocorticoids reduced prostanoids, urokinase-type plasminogen activator (uPA) and angiopoietin-like protein-2 (ANGPTL2) levels, but increased angiogenin (ANG) in supernatant from human CT5.3hTERT colon cancer-derived myofibroblasts. Conditioned medium from solvent- (CMS) and dexamethasone (Dex)-treated (CMD) myofibroblasts increased human umbilical vein endothelial cell (HUVEC) proliferation, but did not affect expression of pro-angiogenic factors or tube-like structure formation (by HUVECs or human aortic ECs). In a HUVEC scratch assay CMS-induced acceleration of wound healing was blunted by CMD treatment. Moreover, CMS-induced neovessel growth in mouse aortic rings ex vivo was also blunted using CMD. The latter effect could be ascribed to both Dex-driven reduction of secreted factors and potential residual Dex present in CMD (indicated using a dexamethasone-spiked CMS control). A similar control in the scratch assay, however, revealed that altered levels of factors in the CMD, and not potential residual Dex, were responsible for decreased wound closure. In conclusion, our results suggest that glucocorticoids indirectly alter endothelial cell function during tumor development in vivo.

Colon cancer-derived myofibroblasts increase endothelial cell migration by glucocorticoid-sensitive secretion of a pro-migratory factor.

There is a large amount of information in brightfield images that was previously inaccessible by using traditional microscopy techniques. This information can now be exploited by using machine-learning approaches for both image segmentation and the classification of objects. We have combined these approaches with a label-free assay for growth and differentiation of leukemic colonies, to generate a novel platform for phenotypic drug discovery. Initially, a supervised machine-learning algorithm was used to identify in-focus colonies growing in a three-dimensional (3D) methylcellulose gel. Once identified, unsupervised clustering and principle component analysis of texture-based phenotypic profiles were applied to group similar phenotypes. In a proof-of-concept study, we successfully identified a novel phenotype induced by a compound that is currently in clinical trials for the treatment of leukemia. We believe that our platform will be of great benefit for the utilization of patient-derived 3D cell culture systems for both drug discovery and diagnostic applications.

Machine Learning Enables Live Label-Free Phenotypic Screening in Three Dimensions.

Metastasis-associated macrophages (MAMs) play pivotal roles in breast cancer metastasis by promoting extravasation and survival of metastasizing cancer cells. In a metastatic breast cancer mouse model, we previously reported that circulating classical monocytes (C-MOs) preferentially migrated into the tumor-challenged lung where they differentiated into MAMs. However, the fate and characteristics of C-MOs in the metastatic site has not been defined. In this study, we identified that adoptively transferred C-MOs (F4/80CD11bLy6C) differentiated into a distinct myeloid cell population that is characterized as F4/80CD11bLy6C and gives rise to MAMs (F4/80CD11bLy6C) within 18 h after migration into the metastatic lung. In mouse models of breast cancer, the CD11bLy6C MAM precursor cells (MAMPCs) were commonly found in the metastatic lung, and their accumulation was increased during metastatic tumor growth. The morphology and gene expression profile of MAMPCs were distinct from C-MOs and had greater similarity to MAMs. For example MAMPCs expressed mature macrophage markers such as CD14, CD36, CD64, and CD206 at comparable levels with MAMs, suggesting that MAMPCs have committed to a macrophage lineage in the tumor microenvironment. MAMPCs also expressed higher levels of , and  than C-MOs to a comparable level to MAMs. Expression of these MAM-associated genes in MAMPCs was reduced by genetic deletion of colony-stimulating factor 1 receptor (CSF1R). On the other hand, transient CSF1R blockade did not reduce the number of MAMPCs in the metastatic site, suggesting that CSF1 signaling is active in MAMPCs but is not required for their accumulation. Functionally MAMPCs suppressed the cytotoxicity of activated CD8 T cells  in part through superoxide production. Overall, our results indicate that immediately following migration into the metastatic tumors C-MOs differentiate into immunosuppressive cells that have characteristics of monocytic myeloid-derived suppressor cell phenotype and might be targeted to enhance efficacy of immunotherapy for metastatic breast cancer.

Article	Year
Colon cancer-derived myofibroblasts increase endothelial cell migration by glucocorticoid-sensitive secretion of a pro-migratory factor. Vascular pharmacology\| PubMed ID: 27717848	2017
Machine Learning Enables Live Label-Free Phenotypic Screening in Three Dimensions. Assay and drug development technologies\| PubMed ID: 29345979	2018
Monocytes Differentiate to Immune Suppressive Precursors of Metastasis-Associated Macrophages in Mouse Models of Metastatic Breast Cancer. Frontiers in immunology\| PubMed ID: 29387063	2017

Dahlia Doughty-Shenton

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