Above, we provide our workflows for open-source analysis of PhenoCycler imaging data. analysis pipeline. Using these protocols, we used PhenoCycler to spatially resolve the TME of 8 routinely employed pre-clinical models of lymphoma, breast cancer, and melanoma preserved as FFPE. Results Our data reveal distinct IDO/TDO-IN-1 TMEs in the different cancer models that were imaged and show that cell-cell contacts differ depending on the tumour type examined. For instance, we found that the immune infiltration in a murine model of melanoma is altered in cellular organization in melanomas that become resistant to PD-1 therapy, with depletions in a number of cell-cell interactions. Conclusions This work presents a valuable resource study seamlessly adaptable to any field of research involving murine models. The methodology described allows researchers to address newly formed hypotheses using archival materials, bypassing the new to perform new mouse studies. Supplementary Information The online version contains supplementary material available at 10.1186/s13578-024-01199-4. Keywords: PhenoCycler, Murine FFPE, Tumour microenvironment, Spatial analysis, Immunofluorescence Background Over the past two decades, there has been growing appreciation for the role of the tumour microenvironment (TME) in cancer biology [1, 2]. As such, the central dogma of tumour progression has evolved to assert that oncogenic mutations underlie the transformation of normal cells to malignant cells, and subsequently, non-transformed cells are recruited via secretion of soluble factors, such as cytokines, chemokines, and extracellular vesicles, to support further cancer cell survival and propagation [3C6]. Rabbit polyclonal to PLSCR1 The non-transformed cellular elements of the TME, including immune cells, fibroblasts, and endothelial cells, interact with tumour IDO/TDO-IN-1 cells, and both cellular composition and intercellular interactions within the TME are critical influencers of cancer cell growth, metastasis, and response to therapy. Many emerging therapeutics, most notably immune checkpoint inhibitors (ICIs), specifically target components of the TME to elicit tumour control. Phenotyping of IDO/TDO-IN-1 the murine TME has helped to understand the response to novel combinatorial therapies and to track changes in tumour progression from initiation to metastatic disease [7, 8], with multi-parameter flow cytometry being the most widely used technique to study the composition of the TME [9]. In this method, malignant tissues are dissociated into single cell suspensions, stained with a panel of antibodies, and run through a flow cytometer, allowing for the identification of cells within the TME. However, a recent body of work has highlighted that TME composition alone is only part of a much bigger picture, and spatial information (e.g. cell-cell interactions) is crucial to further understand tumour progression and response to treatment. Immunofluorescence (IF) imaging of tumour sections, on the other hand, can preserve tissue architecture but is usually restricted to detection of 1 1 or 2 2 markers. To overcome these limitations, a surge of highly multiplexed tissue imaging technologies has emerged in the last 10 years [10C13], aimed at providing single cell spatial phenotyping of the TME and other complex tissue types. PhenoCycler, formerly known as CODEX (CO-Detection by indEXing [13]), has shown immense promise in the highly multiplexed imaging space. In brief, antibodies targeting desired proteins are conjugated to unique oligonucleotide barcodes and are then used to stain fresh frozen or formalin-fixed paraffin-embedded (FFPE) tissues. The PhenoCycler instrument is then used to automate IDO/TDO-IN-1 the cyclic process of tissue washing, hybridizing up to three fluorescent reporters to primary antibodies oligonucleotide barcodes, imaging the tissue, then removing the fluorescent reporters before starting a new cycle process. This iterative process is repeated until all antibodies in a staining panel have been visualized [14]. Reporters are complementary oligonucleotides to the unique barcodes, and are tagged with either fluorophores ATTO550 AF647, or AF750. As of this writing, PhenoCycler has been used to image up to 101 different markers in single tissue [15, 16], and has been used to spatially IDO/TDO-IN-1 profile human cancers such as cutaneous T cell lymphoma [17], follicular lymphoma [18], diffuse large B cell lymphoma [19], Hodgkins lymphoma [20], bladder cancer [21], colorectal cancer [22], basal cell carcinoma [23], glioblastoma [24], breast cancer [25], and.
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