Bladder cancer, as one of the most common cancer types and with high recurrence risk, is considered a candidate for novel immunotherapy strategies. An important aspect of the research for immunotherapy drug development for bladder cancer is to study the tumor microenvironment (TME) and it’s immune contexture. Besides tumor-infiltrating lymphocytes (TILs) as the main drivers of anti-tumor response, recent studies revealed the importance of tumor-associated tertiary lymphoid structures (TLSs) and high endothelial venules (HEVs) in the TME. Structures similar to these were found to spontaneously form in the orthotopic MB49 model used for bladder cancer research in our group. The aim of this study was to perform a deeper characterization of the TME in this model, by using immunofluorescent staining and microscopy. Specifically, the co-localization of tumor infiltrating lymphocytes (CD8+ and CD4+ T cells, CD19+ B cells), CD11c+ dendritic cells and HEVs along with CCL21 signaling were analyzed within orthotopic MB49 tumors, with and without immune stimulation. The quantification of cells expressing CD8, CD19 and CD11c immune markers, CCL21 levels, vascular density and numbers of HEVs, showed higher densities within the immune-stimulated tumors, indicating a rapid effect of immune stimulation on increasing immune cell infiltration and vascular density after only 24 hours post CpG therapy. Also, the highest frequency of TILs, CCL21 chemokine and vascular density was located in regions of the tumor border indicating that these regions should be studied further in depth as a potential target for entry of cells to the tumor with immunotherapy or as a model of the tumor microenvironment since tumor cell density is maintained high in these locations.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-366582 |
Date | January 2018 |
Creators | Kurtinović, Andrea |
Publisher | Uppsala universitet, Institutionen för medicinsk biokemi och mikrobiologi |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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