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

2020 ◽  
Vol 8 (Suppl 2) ◽  
pp. A9.2-A10
Author(s):  
O Braubach ◽  
M Gallina ◽  
B Remeniuk ◽  
C Wang ◽  
N Nikulina ◽  
...  

BackgroundMultiplexed 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 MethodsSerial 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.ResultsBoth 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.ConclusionsOur 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.Abstract P01.04 Figure 1Disclosure InformationO. 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.

2021 ◽  
Vol 26 (6) ◽  
pp. 579-590
Author(s):  
Sam Elder ◽  
Carleen Klumpp-Thomas ◽  
Adam Yasgar ◽  
Jameson Travers ◽  
Shayne Frebert ◽  
...  

Current high-throughput screening assay optimization is often a manual and time-consuming process, even when utilizing design-of-experiment approaches. A cross-platform, Cloud-based Bayesian optimization-based algorithm was developed as part of the National Center for Advancing Translational Sciences (NCATS) ASPIRE (A Specialized Platform for Innovative Research Exploration) Initiative to accelerate preclinical drug discovery. A cell-free assay for papain enzymatic activity was used as proof of concept for biological assay development and system operationalization. Compared with a brute-force approach that sequentially tested all 294 assay conditions to find the global optimum, the Bayesian optimization algorithm could find suitable conditions for optimal assay performance by testing 21 assay conditions on average, with up to 20 conditions being tested simultaneously, as confirmed by repeated simulation. The algorithm could achieve a sevenfold reduction in costs for lab supplies and high-throughput experimentation runtime, all while being controlled from a remote site through a secure connection. Based on this proof of concept, this technology is expected to be applied to more complex biological assays and automated chemistry reaction screening at NCATS, and should be transferable to other institutions. Graphical Abstract


Sensors ◽  
2012 ◽  
Vol 12 (9) ◽  
pp. 12710-12728 ◽  
Author(s):  
Katja Köhler ◽  
Harald Seitz

Vaccine ◽  
2011 ◽  
Vol 29 (44) ◽  
pp. 7794-7800 ◽  
Author(s):  
Chuen-Yen Lau ◽  
Edith M. Swann ◽  
Sagri Singh ◽  
Zuhayr Kafaar ◽  
Helen I. Meissner ◽  
...  

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