Versican Associates with Tumor Immune Phenotype and Limits T-cell Trafficking via Chondroitin Sulfate.

Immunotherapies for cancers of epithelial origin have limited efficacy, and a growing body of evidence links the composition of extracellular matrix (ECM) with the likelihood of a favorable response to treatment. The ECM may be considered an immunologic barrier, restricting the localization of cytotoxic immune cells to stromal areas and inhibiting their contact with tumor cells. Identifying ECM components of this immunologic barrier could provide targets that whether degraded in situ may support antitumor immunity and improve immunotherapy response. Using a library of primary triple-negative breast cancer tissues, we correlated CD8+ T-cell tumor contact with ECM composition and identified a proteoglycan, versican (VCAN), as a putative member of the immunologic barrier. Our analysis reveals that CD8+ T-cell contact with tumor associates with the location of VCAN expression, the specific glycovariant of VCAN [defined through the pattern of posttranslational attachments of glycosaminoglycans (GAG)], and the cell types that produce the variant. In functional studies, the isomers of chondroitin sulfate presented on VCAN have opposing roles being either supportive or inhibiting of T-cell trafficking, and removal of the GAGs ameliorates these effects on T-cell trafficking. Overall, we conclude that VCAN can either support or inhibit T-cell trafficking within the tumor microenvironment depending on the pattern of GAGs present, and that VCAN is a major component of the ECM immunologic barrier that defines the type of response to immunotherapy. SIGNIFICANCE: The response to immunotherapy has been poor toward solid tumors despite immune cells infiltrating into the tumor. The ECM has been associated with impacting T-cell infiltration toward the tumor and in this article we have identified VCAN and its structural modification, chondroitin sulfate as having a key role in T-cell invasion.

Targeting Versican as a Potential Immunotherapeutic Strategy in the Treatment of Cancer.

A growing body of literature links events associated with the progression and severity of immunity and inflammatory disease with the composition of the tissue extracellular matrix as defined by the matrisome. One protein in the matrisome that is common to many inflammatory diseases is the large proteoglycan versican, whose varied function is achieved through multiple isoforms and post-translational modifications of glycosaminoglycan structures. In cancer, increased levels of versican are associated with immune cell phenotype, disease prognosis and failure to respond to treatment. Whether these associations between versican expression and tumour immunity are the result of a direct role in the pathogenesis of tumours is not clear. In this review, we have focused on the role of versican in the immune response as it relates to tumour progression, with the aim of determining whether our current understanding of the immunobiology of versican warrants further study as a cancer immunotherapy target.

Mouse Ovarian Cancer Models Recapitulate the Human Tumor Microenvironment and Patient Response to Treatment.

Although there are many prospective targets in the tumor microenvironment (TME) of high-grade serous ovarian cancer (HGSOC), pre-clinical testing is challenging, especially as there is limited information on the murine TME. Here, we characterize the TME of six orthotopic, transplantable syngeneic murine HGSOC lines established from genetic models and compare these to patient biopsies. We identify significant correlations between the transcriptome, host cell infiltrates, matrisome, vasculature, and tissue modulus of mouse and human TMEs, with several stromal and malignant targets in common. However, each model shows distinct differences and potential vulnerabilities that enabled us to test predictions about response to chemotherapy and an anti-IL-6 antibody. Using machine learning, the transcriptional profiles of the mouse tumors that differed in chemotherapy response are able to classify chemotherapy-sensitive and -refractory patient tumors. These models provide useful pre-clinical tools and may help identify subgroups of HGSOC patients who are most likely to respond to specific therapies.