| Literature DB >> 34112666 |
Sneha Berry1,2,3, Nicolas A Giraldo4, Benjamin F Green1,2,5, Alexander S Szalay1,6,7, Janis M Taube8,2,4,5, Tricia R Cottrell4, Julie E Stein4, Elizabeth L Engle1,2,5, Haiying Xu1,2,5, Aleksandra Ogurtsova1,2,5, Charles Roberts2,5, Daphne Wang5, Peter Nguyen5, Qingfeng Zhu4, Sigfredo Soto-Diaz2,5, Jose Loyola2,5, Inbal B Sander5, Pok Fai Wong9, Shlomit Jessel9, Joshua Doyle6,7, Danielle Signer5, Richard Wilton6,7, Jeffrey S Roskes6,7, Margaret Eminizer6,7, Seyoun Park1,10, Joel C Sunshine5, Elizabeth M Jaffee1,2,3, Alexander Baras4, Angelo M De Marzo3,4, Suzanne L Topalian2,11, Harriet Kluger12, Leslie Cope1,2,13, Evan J Lipson1,2,3, Ludmila Danilova1,2,13, Robert A Anders1,2,4, David L Rimm9, Drew M Pardoll1,2,3.
Abstract
Next-generation tissue-based biomarkers for immunotherapy will likely include the simultaneous analysis of multiple cell types and their spatial interactions, as well as distinct expression patterns of immunoregulatory molecules. Here, we introduce a comprehensive platform for multispectral imaging and mapping of multiple parameters in tumor tissue sections with high-fidelity single-cell resolution. Image analysis and data handling components were drawn from the field of astronomy. Using this "AstroPath" whole-slide platform and only six markers, we identified key features in pretreatment melanoma specimens that predicted response to anti-programmed cell death-1 (PD-1)-based therapy, including CD163+PD-L1- myeloid cells and CD8+FoxP3+PD-1low/mid T cells. These features were combined to stratify long-term survival after anti-PD-1 blockade. This signature was validated in an independent cohort of patients with melanoma from a different institution.Entities:
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Year: 2021 PMID： 34112666 PMCID： PMC8709533 DOI： 10.1126/science.aba2609
Source DB: PubMed Journal: Science ISSN： 0036-8075 Impact factor: 47.728