P01.04 A spatially resolved, highly multiplexed biomarker analysis pipeline that bridges the divide between discovery and clinical research

Background Multiplexed immunofluorescence (mIF) allows the visualization of multiple biomarkers in a single tumor tissue section, while at the same time preserving the spatial biology of the tumor microenvironment (TMI). CO-Detection by indEXing (CODEX®) and Phenoptics™ platforms are complementary mIF technologies that span the full spectrum of cancer research, from discovery to translational and clinical research. CODEX® is ultra-high plex and allows imaging of up to 40 antigens on a single tissue section with single-cell resolution. Phenoptics™ is an established mIF platform that enables high-throughput whole slide multispectral image acquisition and tissue interrogation with up to 8 markers plus DAPI. Here we present a study that compares shared sets of immune and tumor markers between the CODEX® and Phenoptics™ platforms. This cross-platform comparison provides a conceptual framework for researchers to translate biomarker signatures from discovery to high-throughput translational studies. Materials and Methods Serial sections of human formalin-fixed paraffin embedded non-small cell lung cancer (NSCLC) and tonsils were analyzed. An initial screen with a 28-plex CODEX® antibody panel revealed multiple biomarkers of interest, including CK, CD8, Ki67, PD-L1 and PD-1; all of these biomarkers showed abundant expression in the TMI. Building on this result, we next developed a 6-plex Opal™ Phenotpics™ panel. This panel was screened and analyzed via high-throughput whole slide scanning of sample tissues. Image processing and data analysis were conducted similarly for both datasets so that repeatability and consistency of measurements could be established. Results Both CODEX® and Phenoptics™ detected the same cell phenotypes and displayed similar frequencies of cells expressing CK, CD8, Ki67, PD-L1 and PD-1 in serial sections of tonsil and NSCLC tissues. These observations were consistent and cross-validated in data from CODEX® and Phenoptics™ platforms. Crucially, this means that the two approaches can be made analytically equivalent, and hence, that they can be used in conjunction with each other as research progresses along the continuum from discovery to translational and clinical research. Conclusions Our cross-platform comparison provides a conceptual framework for biomarkers discovered on the CODEX® platform to be translated to the Phenoptics™ platform for high-throughput translational studies. The resulting comprehensive phenotyping and quantification data retain spatial context and provide unprecedented insight into tumor biology. Disclosure Information O. Braubach: A. Employment (full or part-time); Significant; Akoya Biosciences. M. Gallina: A. Employment (full or part-time); Significant; Akoya Biosciences. B. Remeniuk: A. Employment (full or part-time); Significant; Akoya Biosciences. C. Wang: A. Employment (full or part-time); Significant; Akoya Biosciences. N. Nikulina: A. Employment (full or part-time); Significant; Akoya Biosciences. R. Bashier: A. Employment (full or part-time); Significant; Akoya Biosciences. J. Kennedy-Darling: A. Employment (full or part-time); Significant; Akoya Biosciences. C. Hoyt: A. Employment (full or part-time); Significant; Akoya Biosciences.