作者
Daniiar Dyikanov,A. V. Zaitsev,Т.В. Васильева,Iris Wang,Arseniy A. Sokolov,Evgenii S. Bolshakov,Alena Frank,Polina Turova,Olga Golubeva,Anna Gantseva,Anna Kamysheva,Polina Shpudeiko,Ilya Krauz,Mary Abdou,Madison Chasse,Tori Conroy,Nicholas R. Merriam,Julia E. Alesse,Noel English,Boris Shpak,Anna Shchetsova,Evgenii Tikhonov,I. V. Filatov,Anastasia Radko,Anastasiia A. Bolshakova,Anastasia I Kachalova,Nika Lugovykh,Andrey Bulahov,Anastasiia Kilina,Syimyk Asanbekov,Irina Zheleznyak,Pavel Skoptsov,E. A. Alekseeva,Jennifer M. Johnson,Joseph Curry,Alban Linnenbach,Andrew P. South,EnJun Yang,Konstantin R. Morozov,А. А. Терентьева,Lira Nigmatullina,Dmitry Fastovetz,Anatoly Bobe,Linda Balabanian,Krystle Nomie,Sheila T. Yong,Christopher Davitt,Alexander A. Ryabykh,Olga Kudryashova,Cagdas Tazearslan,Alexander Bagaev,Nathan Fowler,Adam Luginbuhl,Ravshan Ataullakhanov,Michael Goldberg
摘要
The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient's immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types and gene expression profiles. An independent analysis of 17,800 open-source transcriptomes with the same approach corroborated these findings. Continuous immunotype-based signature scores were developed to correlate systemic immunity with patient responses to different cancer treatments, including immunotherapy, prognostically and predictively. Our approach and findings illustrate the potential utility of a simple blood test as a flexible tool for stratifying cancer patients into therapy response groups based on systemic immunoprofiling.