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  3. Immune signatures predict development of autoimmune toxicity in patients with cancer treated with immune checkpoint inhibitors.
 

Immune signatures predict development of autoimmune toxicity in patients with cancer treated with immune checkpoint inhibitors.

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BORIS DOI
10.48350/177872
Date of Publication
February 10, 2023
Publication Type
Article
Division/Institute

Universitätsklinik fü...

Contributor
Nuñez, Nicolas Gonzalo
Berner, Fiamma
Friebel, Ekaterina
Unger, Susanne
Wyss, Nina
Gomez, Julia Martinez
Purde, Mette-Triin
Niederer, Rebekka
Porsch, Maximilian
Lichtensteiger, Christa
Kramer, Rafaela
Erdmann, Michael
Schmitt, Christina
Heinzerling, Lucie
Abdou, Marie-Therese
Karbach, Julia
Schadendorf, Dirk
Zimmer, Lisa
Ugurel, Selma
Klümper, Niklas
Hölzel, Michael
Power, Laura
Kreutmair, Stefanie
Capone, Mariaelena
Madonna, Gabriele
Cevhertas, Lacin
Heider, Anja
Amaral, Teresa
Hasan Ali, Omar
Bomze, David
Dimitriou, Florentia
Diem, Stefan
Ascierto, Paolo Antonio
Dummer, Reinhard
Jäger, Elke
Driessen, Christoph
Levesque, Mitchell Paul
van de Veen, Willem
Joerger, Markus
Früh, Martin
Universitätsklinik für Medizinische Onkologie
Becher, Burkhard
Flatz, Lukas
Subject(s)

600 - Technology::610...

Series
Med (N Y)
ISSN or ISBN (if monograph)
2666-6340
Publisher
Cell Press
Language
English
Publisher DOI
10.1016/j.medj.2022.12.007
PubMed ID
36693381
Uncontrolled Keywords

Translation to patien...

Description
BACKGROUND

Immune checkpoint inhibitors (ICIs) are among the most promising treatment options for melanoma and non-small cell lung cancer (NSCLC). While ICIs can induce effective anti-tumor responses, they may also drive serious immune-related adverse events (irAEs). Identifying biomarkers to predict which patients will suffer from irAEs would enable more accurate clinical risk-benefit analysis for ICI treatment and may also shed light on common or distinct mechanisms underpinning treatment success and irAEs.

METHODS

In this prospective multi-center study, we combined a multi-omics approach including unbiased single-cell profiling of over 300 peripheral blood mononuclear cell (PBMC) samples and high-throughput proteomics analysis of over 500 serum samples to characterize the systemic immune compartment of patients with melanoma or NSCLC before and during treatment with ICIs.

FINDINGS

When we combined the parameters obtained from the multi-omics profiling of patient blood and serum, we identified potential predictive biomarkers for ICI-induced irAEs. Specifically, an early increase in CXCL9/CXCL10/CXCL11 and interferon-γ (IFN-γ) 1 to 2 weeks after the start of therapy are likely indicators of heightened risk of developing irAEs. In addition, an early expansion of Ki-67+ regulatory T cells (Tregs) and Ki-67+ CD8+ T cells is also likely to be associated with increased risk of irAEs.

CONCLUSIONS

We suggest that the combination of these cellular and proteomic biomarkers may help to predict which patients are likely to benefit most from ICI therapy and those requiring intensive monitoring for irAEs.

FUNDING

This work was primarily funded by the European Research Council, the Swiss National Science Foundation, the Swiss Cancer League, and the Forschungsförderung of the Kantonsspital St. Gallen.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/120902
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1-s2.0-S2666634022005232-main.pdftextAdobe PDF5.75 MBpublishedOpen
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