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Biology subjects

Rivest, F.

Publications and source records attributed to Rivest, F..

2 recordsLinked to original sources

Fully Automated Sequential Immunofluorescence (seqIF) for Hyperplex Spatial Proteomics

Tissues are complex environments where different cell types are in constant interaction with each other and with non-cellular components. Preserving the spatial context during proteomics analyses of tissue samples has become an important objective for different applications, one of the most important being the investigation of the tumor microenvironment. Here, we describe a multiplexed protein biomarker detection method on the COMET instrument, coined sequential ImmunoFluorescence (seqIF). The fully automated method uses successive applications of antibody incubation and elution, and in-situ imaging enabled by an integrated microscope and a microfluidic chip that provides optimized optical access to the sample. We show seqIF data on different sample types such as tumor and healthy tissue, including 40-plex on a single tissue section that is obtained in less than 24 hours, using off-the-shelf antibodies. We also present extensive characterization of the developed method, including elution efficiency, epitope stability, repeatability and reproducibility, signal uniformity, and dynamic range, in addition to marker and panel optimization strategies. The streamlined workflow using off-the-shelf antibodies, data quality enabling quantitative downstream analysis, and ease of reaching hyperplex levels make seqIF suitable for immune-oncology research and other disciplines requiring spatial analysis, paving the way for its adoption in clinical settings.

cancer biology↗

Probing the killing potency of tumor-infiltrating lymphocytes on microarrayed autologous tumoroids

Immunotherapy has shown promise as an approach to fight cancer by harnessing the immune system. However, due to the lack of biomarkers to guide treatment regimens and predict response rates, there is an unmet need for more robust ex vivo and in vitro systems that recapitulate patient-specific tumor biology and enable response prediction for immune therapies in an autologous setting. To address this issue, we developed a high-content screening-compatible assay based on microcavity arrays to study tumor-infiltrating lymphocyte (TIL) functionality on 3D tumoroid models. We validated our system using the pmel-1 activated T cell mouse model to assess both cancer immunogenicity and T cell functionality. To demonstrate the translational potential of the platform, we used it to evaluate the response of patient-derived TILs to autologous human colorectal cancer (CRC) tumoroids. Using a combination of imaging and flow cytometry, we determined several features of the antitumor activity of TILs, including the extent of tumoroid killing and secretion of cytokines. We then used the approach to identify responders to immunotherapy, such as the immune checkpoint blockade (ICB) agent Nivolumab (PD-1 inhibitor) and Ipilimumab (CTLA-4 inhibitor). Our system allows not only the identification of immunogenic tumors, but also the testing of patients for response to immunomodulators, enabling personalized immuno-oncology.

cancer biology↗