1. Establishing standardized immune phenotyping of metastatic melanoma by digital pathology
- Author
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Bettina Sobottka, Marta Nowak, Anja Laura Frei, Martina Haberecker, Samuel Merki, Mitchell P. Levesque, Reinhard Dummer, Holger Moch, Viktor Hendrik Koelzer, Rudolf Aebersold, Melike Ak, Faisal S. Al-Quaddoomi, Jonas Albinus, Ilaria Alborelli, Sonali Andani, Per-Olof Attinger, Marina Bacac, Daniel Baumhoer, Beatrice Beck-Schimmer, Niko Beerenwinkel, Christian Beisel, Lara Bernasconi, Anne Bertolini, Bernd Bodenmiller, Ximena Bonilla, Ruben Casanova, Stéphane Chevrier, Natalia Chicherova, Maya D'Costa, Esther Danenberg, Natalie Davidson, Monica-Andreea Drăganmoch, Stefanie Engler, Martin Erkens, Katja Eschbach, Cinzia Esposito, André Fedier, Pedro Ferreira, Joanna Ficek, Bruno Frey, Sandra Goetze, Linda Grob, Gabriele Gut, Detlef Günther, Pirmin Haeuptle, Viola Heinzelmann-Schwarz, Sylvia Herter, Rene Holtackers, Tamara Huesser, Anja Irmisch, Francis Jacob, Andrea Jacobs, Tim M. Jaeger, Katharina Jahn, Alva R. James, Philip M. Jermann, André Kahles, Abdullah Kahraman, Werner Kuebler, Jack Kuipers, Christian P. Kunze, Christian Kurzeder, Kjong-Van Lehmann, Sebastian Lugert, Gerd Maass, Markus G. Manz, Philipp Markolin, Julien Mena, Ulrike Menzel, Julian M. Metzler, Nicola Miglino, Emanuela S. Milani, Simone Muenst, Riccardo Murri, Charlotte K.Y. Ng, Stefan Nicolet, Patrick G.A. Pedrioli, Lucas Pelkmans, Salvatore Piscuoglio, Michael Prummer, Mathilde Ritter, Christian Rommel, María L. Rosano-González, Gunnar Rätsch, Natascha Santacroce, Jacobo Sarabia del Castillo, Ramona Schlenker, Petra C. Schwalie, Severin Schwan, Tobias Schär, Gabriela Senti, Franziska Singer, Sujana Sivapatham, Berend Snijder, Vipin T. Sreedharan, Stefan Stark, Daniel J. Stekhoven, Alexandre P.A. Theocharides, Tinu M. Thomas, Markus Tolnay, Vinko Tosevski, Nora C. Toussaint, Mustafa A. Tuncel, Marina Tusup, Audrey Van Drogen, Marcus Vetter, Tatjana Vlajnic, Sandra Weber, Walter P. Weber, Rebekka Wegmann, Michael Weller, Fabian Wendt, Norbert Wey, Andreas Wicki, Mattheus HE Wildschut, Bernd Wollscheid, Shuqing Yu, Johanna Ziegler, Marc Zimmermann, Martin Zoche, Gregor Zuend, University of Zurich, Sobottka-Brillout, Bettina, and Koelzer, Viktor Hendrik
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Pathology ,medicine.medical_specialty ,Stromal cell ,610 Medicine & health ,Disease ,Predictive markers ,Article ,Pathology and Forensic Medicine ,1307 Cell Biology ,Immune system ,10049 Institute of Pathology and Molecular Pathology ,1312 Molecular Biology ,Medicine ,Compartment (pharmacokinetics) ,Molecular Biology ,Melanoma ,business.industry ,10177 Dermatology Clinic ,Digital pathology ,10060 Epidemiology, Biostatistics and Prevention Institute (EBPI) ,Cell Biology ,Biomarker (cell) ,2734 Pathology and Forensic Medicine ,10032 Clinic for Oncology and Hematology ,Cohort ,Imaging the immune system ,business ,CD8 - Abstract
CD8+ tumor-infiltrating T cells can be regarded as one of the most relevant predictive biomarkers in immune-oncology. Highly infiltrated tumors, referred to as inflamed (clinically “hot”), show the most favorable response to immune checkpoint inhibitors in contrast to tumors with a scarce immune infiltrate called immune desert or excluded (clinically “cold”). Nevertheless, quantitative and reproducible methods examining their prevalence within tumors are lacking. We therefore established a computational diagnostic algorithm to quantitatively measure spatial densities of tumor-infiltrating CD8+ T cells by digital pathology within the three known tumor compartments as recommended by the International Immuno-Oncology Biomarker Working Group in 116 prospective metastatic melanomas of the Swiss Tumor Profiler cohort. Workflow robustness was confirmed in 33 samples of an independent retrospective validation cohort. The introduction of the intratumoral tumor center compartment proved to be most relevant for establishing an immune diagnosis in metastatic disease, independent of metastatic site. Cut-off values for reproducible classification were defined and successfully assigned densities into the respective immune diagnostic category in the validation cohort with high sensitivity, specificity, and precision. We provide a robust diagnostic algorithm based on intratumoral and stromal CD8+ T-cell densities in the tumor center compartment that translates spatial densities of tumor-infiltrating CD8+ T cells into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”. The consideration of the intratumoral tumor center compartment allows immune phenotyping in the clinically highly relevant setting of metastatic lesions, even if the invasive margin compartment is not captured in biopsy material., The authors present a robust diagnostic algorithm based on digital pathology and image analysis that quantifies intratumoral and stromal CD8+ T-cell densities in the tumor center and invasive margin compartment in metastatic melanoma. Spatial CD8+ T-cell densities are translated into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”. Their approach also allows efficient immune phenotyping of metastatic lesions, on biopsy material or even in the absence of material from the invasive margin.
- Published
- 2021
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