Details

Autor(en) / Beteiligte

• Dyikanov, Daniiar
• Zaitsev, Aleksandr
• Vasileva, Tatiana
• Wang, Iris
• Sokolov, Arseniy A.
• Bolshakov, Evgenii S.
• Frank, Alena
• Turova, Polina
• Golubeva, Olga
• Gantseva, Anna
• Kamysheva, Anna
• Shpudeiko, Polina
• Krauz, Ilya
• Abdou, Mary
• Chasse, Madison
• Conroy, Tori
• Merriam, Nicholas R.
• Alesse, Julia E.
• English, Noel
• Shpak, Boris
• Shchetsova, Anna
• Tikhonov, Evgenii
• Filatov, Ivan
• Radko, Anastasia
• Bolshakova, Anastasiia
• Kachalova, Anastasia
• Lugovykh, Nika
• Bulahov, Andrey
• Kilina, Anastasiia
• Asanbekov, Syimyk
• Zheleznyak, Irina
• Skoptsov, Pavel
• Alekseeva, Evgenia
• Johnson, Jennifer M.
• Curry, Joseph M.
• Linnenbach, Alban J.
• South, Andrew P.
• Yang, EnJun
• Morozov, Kirill
• Terenteva, Anastasiya
• Nigmatullina, Lira
• Fastovetz, Dmitry
• Bobe, Anatoly
• Balabanian, Linda
• Nomie, Krystle
• Yong, Sheila T.
• Davitt, Christopher J.H.
• Ryabykh, Alexander
• Kudryashova, Olga
• Tazearslan, Cagdas
• Bagaev, Alexander
• Fowler, Nathan
• Luginbuhl, Adam J.
• Ataullakhanov, Ravshan I.
• Goldberg, Michael F.

Titel

Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in patients with cancer

Ist Teil von

• Cancer cell, 2024-05, Vol.42 (5), p.759-779.e12

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2024

Quelle

MEDLINE

Beschreibungen/Notizen

• 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. [Display omitted] •Development of a machine learning-based clinical immunoprofiling platform•Depiction of immune states by multiparameter flow cytometry and bulk RNA-seq using peripheral blood•Identification and validation of five immunotypes conserved across diverse diagnoses•Potential clinical utility in stratifying treatment responses via a simple blood test Dyikanov et al. developed a machine learning platform that uses a simple blood test to reveal cellular compositions reflective of a person’s immune system. These compositions, delineated into five conserved immunotypes, can reflect a person’s disease status or how someone responds to specific treatments, thus underscoring their potential clinical utility for cancer patients.