Details

Autor(en) / Beteiligte

• Stein-Thoeringer, Christoph K
• Saini, Neeraj Y
• Zamir, Eli
• Blumenberg, Viktoria
• Schubert, Maria-Luisa
• Mor, Uria
• Fante, Matthias A
• Schmidt, Sabine
• Hayase, Eiko
• Hayase, Tomo
• Rohrbach, Roman
• Chang, Chia-Chi
• McDaniel, Lauren
• Flores, Ivonne
• Gaiser, Rogier
• Edinger, Matthias
• Wolff, Daniel
• Heidenreich, Martin
• Strati, Paolo
• Nair, Ranjit
• Chihara, Dai
• Fayad, Luis E
• Ahmed, Sairah
• Iyer, Swaminathan P
• Steiner, Raphael E
• Jain, Preetesh
• Nastoupil, Loretta J
• Westin, Jason
• Arora, Reetakshi
• Wang, Michael L
• Turner, Joel
• Menges, Meghan
• Hidalgo-Vargas, Melanie
• Reid, Kayla
• Dreger, Peter
• Schmitt, Anita
• Müller-Tidow, Carsten
• Locke, Frederick L
• Davila, Marco L
• Champlin, Richard E
• Flowers, Christopher R
• Shpall, Elizabeth J
• Poeck, Hendrik
• Neelapu, Sattva S
• Schmitt, Michael
• Subklewe, Marion
• Jain, Michael D
• Jenq, Robert R
• Elinav, Eran

Titel

A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy

Ist Teil von

• Nature medicine, 2023-04, Vol.29 (4), p.906-916

Ort / Verlag

United States: Nature Publishing Group

Erscheinungsjahr

2023

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Increasing evidence suggests that the gut microbiome may modulate the efficacy of cancer immunotherapy. In a B cell lymphoma patient cohort from five centers in Germany and the United States (Germany, n = 66; United States, n = 106; total, n = 172), we demonstrate that wide-spectrum antibiotics treatment ('high-risk antibiotics') prior to CD19-targeted chimeric antigen receptor (CAR)-T cell therapy is associated with adverse outcomes, but this effect is likely to be confounded by an increased pretreatment tumor burden and systemic inflammation in patients pretreated with high-risk antibiotics. To resolve this confounding effect and gain insights into antibiotics-masked microbiome signals impacting CAR-T efficacy, we focused on the high-risk antibiotics non-exposed patient population. Indeed, in these patients, significant correlations were noted between pre-CAR-T infusion Bifidobacterium longum and microbiome-encoded peptidoglycan biosynthesis, and CAR-T treatment-associated 6-month survival or lymphoma progression. Furthermore, predictive pre-CAR-T treatment microbiome-based machine learning algorithms trained on the high-risk antibiotics non-exposed German cohort and validated by the respective US cohort robustly segregated long-term responders from non-responders. Bacteroides, Ruminococcus, Eubacterium and Akkermansia were most important in determining CAR-T responsiveness, with Akkermansia also being associated with pre-infusion peripheral T cell levels in these patients. Collectively, we identify conserved microbiome features across clinical and geographical variations, which may enable cross-cohort microbiome-based predictions of outcomes in CAR-T cell immunotherapy.