Biology subjects

Gruosso, T.

Publications and source records attributed to Gruosso, T..

3 recordsLinked to original sources

bioRxiv2020

Inflammation promotes tumor aggression by stimulating stromal cell-dependent collagen crosslinking and stromal stiffening

Collagen deposition and stromal stiffening accompany malignancy, compromise treatment, and promote tumor aggression. Clarifying the molecular nature of and the factors that regulate extracellular matrix stiffening in tumors should identify biomarkers to stratify patients for therapy and therapeutic interventions to improve outcome. We profiled lysyl hydroxylase- and lysyl oxidase-mediated collagen crosslinks and quantified the greatest abundance of total and complex collagen crosslinks in more aggressive human breast cancer subtypes with the stiffest stroma. These tissues also harbored the highest number of tumor-associated macrophages (TAM), whose therapeutic ablation not only reduced metastasis, but also concomitantly decreased accumulation of collagen crosslinks and stromal stiffening. Epithelial-targeted expression of the crosslinking enzyme lysyl oxidase had no impact on collagen crosslinking in PyMT mammary tumors, whereas stromal cell targeting did. Consistently, stromal cells in microdissected human tumors expressed the highest level of collagen crosslinking enzymes. Immunohistochemical analysis of a cohort of breast cancer patient biopsies revealed that stromal expression of lysyl hydroxylase two, an enzyme that induces hydroxylysine aldehyde-derived collagen crosslinks and stromal stiffening correlated significantly disease specific mortality. The findings link tissue inflammation, stromal cell-mediated collagen crosslinking and stiffening to tumor aggression and identify lysyl hydroxylase two as a novel stromal biomarker. SignificanceWe show infiltrating macrophages induce stromal fibroblast, and not epithelial, expression of collagen crosslinking enzymes that drive tumor stiffening. Stromal enzyme LH2 is significantly upregulated in breast cancer patients with the stiffest stroma, the most trivalent HLCCs and the worst prognosis, underscoring its potential as a biomarker and therapeutic target.

cancer biology↗

bioRxiv2018

Infiltration of CD8+ T cells into tumor-cell clusters in Triple Negative Breast Cancer

Infiltration of CD8+ T lymphocytes into solid tumors is associated with good prognosis in various types of cancer, including Triple Negative Breast Cancers (TNBC). However, the mechanisms underlying different infiltration-levels are largely unknown. Here, we have characterized the spatial profile of CD8+ T cells around tumorcell clusters in the core and margin regions in TNBC. Combining mathematical modeling and data analysis, we propose that there exists a possible chemo-repellent inside tumor-cell clusters, which prevents CD8+ T cells from infiltrating into tumor-cell clusters. Furthermore, investigation into the properties of collagen fibers suggests that variations in desmoplastic elements does not limit infiltration of CD8+ T lymphocytes into tumor-cell clusters. This is consistent with the prediction of our mathematical modeling analysis whereby CD8+ T cells are predicted to infiltrate the fibrotic barrier and their infiltration into tumor clusters is governed by other mechanisms involving a local repellent.

cancer biology↗

bioRxiv2017

CrosstalkNet: mining large-scale bipartite co-expression networks to characterize epi-stroma crosstalk

BackgroundOver the last several years, we have witnessed the metamorphosis of network biology from being a mere representation of molecular interactions to models enabling inference of complex biological processes. Networks provide promising tools to elucidate intercellular interactions that contribute to the functioning of key biological pathways in a cell. However, the exploration of these large-scale networks remains a challenge due to their high-dimensionality.\n\nResultsCrosstalkNet is a user friendly, web-based network visualization tool to retrieve and mine interactions in large-scale bipartite co-expression networks. In this study, we discuss the use of gene co-expression networks to explore the rewiring of interactions between tumor epithelial and stromal cells. We show how CrosstalkNet can be used to efficiently visualize, mine, and interpret large co-expression networks representing the crosstalk occurring between the tumour and its microenvironment.\n\nConclusionCrosstalkNet serves as a tool to assist biologists and clinicians in exploring complex, large interaction graphs to obtain insights into the biological processes that govern the tumor epithelial-stromal crosstalk. A comprehensive tutorial along with case studies are provided with the application.\n\nAvailabilityThe web-based application is available at the following location: http://epistroma.pmgenomics.ca/app/. The code is open-source and freely available from http://github.com/bhklab/EpiStroma-webapp.\n\nContactbhaibeka@uhnresearch.ca

systems biology↗