BackgroundIntravital multiphoton microscopy (IMM) provides single-cell imaging within intact living systems. IMM of the autofluorescent metabolic co-enzymes NAD(P)H and FAD, or optical metabolic imaging (OMI), provides in vivo label-free imaging of metabolic changes. The metabolism of tumor cells and immune cells is closely associated with cancer progression,1–3 so we aim to study metabolic trends before and after administration of an established, effective, triple-combination immunotherapy within murine melanoma tumors.4 This therapy includes 12 Gy external beam radiation, intratumoral administration of a hu14.18-IL2 immunocytokine (anti-GD2 mAb fused to IL2), and intraperitoneal administration of anti-CTLA-4 leading to in situ vaccination and cure of GD2+ murine tumors.4 Previous work has shown that a T cell response is critical to the efficacy of this therapy,4 5 so we created mCherry-labeled T cell mouse models to study T cell response. Here, IMM was used to image concurrent tumor cell and T cell metabolic trends, T cell infiltration, and tumor microenvironment composition.MethodsWe created mCherry-labeled T cell mouse models through CRISPR/Cas9 knock-in and Cre- lox genetic modifications. We then implanted syngeneic B78 (GD2+) melanoma cells intradermally into the flanks of C57BL/6 mice to induce measurable tumors. Mice were anesthetized, skin flap surgery performed, and tumors imaged at varying time points. IMM was performed using 750–1040 nm to excite NAD(P)H, FAD, and mCherry through a 40X (1.15 NA) objective. Fluorescence lifetime data was collected using time correlated single photon counting electronics. Murine tissues were later harvested and analyzed via flow cytometry and immunohistochemistry to confirm mCherry expression in mouse models and IMM findings.ResultsHere we demonstrate the feasibility of our IMM platform to perform single-cell resolution imaging in vivo. We establish that our genetically engineered mouse models enable clear identification and tracking of mCherry T cell populations. In addition, we show that label-free OMI provides metabolic trends and structural information in vivo (figure 1). Overall, we demonstrate concurrent imaging of intravital tumor cell and T cell populations within the tumor microenvironment.ConclusionsOur preliminary results suggest that the combination of IMM and our mCherry mouse models with OMI allows for concurrent imaging of T cell infiltration and metabolic trends. With continued work, this imaging platform has the potential to provide dynamic, metabolic information on tumor cell and immune cell populations to inform further immunotherapy development.AcknowledgementsThis work is supported by the Morgridge Institute for Research (Interdisciplinary Fellowship awarded to A.R.H.) and the NIH (R01 CA205101 and R35 CA197078). The authors thank the University of Wisconsin Carbone Cancer Center (UWCCC) Support Grant P30 CA014520, the UWCCC Translational Research Initiatives in Pathology laboratory - supported by the UW Department of Pathology and Laboratory Medicine and the Office of The Director NIH (S10OD023526), the UWCCC Flow Cytometry Laboratory, and the Genome Editing and Animal Models Laboratory for core services.Abstract 42 Figure 1Representative intravital multiphoton microscopy images of a B78 syngeneic melanoma growing in a mouse with mCherry-labeled T cells. (A) Fluorescence intensity image of all fluorophores shows mCherry-labeled T cells (red) infiltrating untreated tumor tissue and vasculature as well as metabolic coenzymes NAD(P)H (blue) and FAD (green) expressed by the tumor. (B) Fluorescence intensity image of NAD(P)H alone shows NAD(P)H landscape as well as tumor boundaries and winding vasculature filled with red blood cells. (C) Fluorescence lifetime image shows mCherry-labeled T cell populations and their corresponding mean lifetime (tau m ) values. Fluorescence lifetime values help distinguish mCherry-labeled T cells (typical tau m = 1,400 ps) from nonspecific red autofluorescence in vivo. (D) Fluorescence lifetime image shows NAD(P)H expression and corresponding mean lifetime values which give insight into tumor metabolism and microenvironment.Ethics ApprovalAll animal work was approved by the University of Wisconsin Institutional Animal Care and Use Committees.ReferencesRenner K, Singer K, Koehl GE, Geissler EK, Peter K, Siska PJ, Kreutz M. Metabolic hallmarks of tumor and immune cells in the tumor microenvironment. Front Immunol. 2017, 8 (MAR), 1–11.Mockler MB, Conroy MJ, Lysaght J, Targeting T. Cell Immunometabolism for cancer immunotherapy; understanding the impact of the tumor microenvironment. Front Oncol. 2014, 4 (May), 1–11.Ghesquière B, Wong BW, Kuchnio A, Carmeliet P. Metabolism of stromal and immune cells in health and disease. Nature 2014, 511 (7508), 167–176.Morris ZS, Guy EI, Francis DM, Gressett MM, Werner LR, Carmichael LL, Yang RK, Armstrong EA, Huang S, Navid F, Gillies SD, Korman A, Hank JA, Rakhmilevich AL, Harari PM, Sondel PM. In situ tumor vaccination by combining local radiation and tumor-specific antibody or immunocytokine treatments. Cancer Res 2016;76 (13):3929–3941.Morris ZS, Guy EI, Werner LR, Carlson PM, Heinze CM, Kler JS, Busche SM, Jaquish A, A, Sriramaneni RN, Carmichael LL, Loibner H, Gillies SD, Korman AJ, Erbe AK, Hank J, A, Rakhmilevich AL, Harari PM, Sondel PM. Tumor-specific inhibition of in situ vaccination by distant untreated tumor sites. Cancer Immunol Res 2018;6 (7):825–834.
Reciprocal Dysregulation of MiR-146b and MiR-451 Contributes in Malignant Phenotype of Follicular Thyroid Tumor