TY - JOUR
T1 - A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy
AU - Stein-Thoeringer, Christoph K.
AU - Saini, Neeraj Y.
AU - Zamir, Eli
AU - Blumenberg, Viktoria
AU - Schubert, Maria Luisa
AU - Mor, Uria
AU - Fante, Matthias A.
AU - Schmidt, Sabine
AU - Hayase, Eiko
AU - Hayase, Tomo
AU - Rohrbach, Roman
AU - Chang, Chia Chi
AU - McDaniel, Lauren
AU - Flores, Ivonne
AU - Gaiser, Rogier
AU - Edinger, Matthias
AU - Wolff, Daniel
AU - Heidenreich, Martin
AU - Strati, Paolo
AU - Nair, Ranjit
AU - Chihara, Dai
AU - Fayad, Luis E.
AU - Ahmed, Sairah
AU - Iyer, Swaminathan P.
AU - Steiner, Raphael E.
AU - Jain, Preetesh
AU - Nastoupil, Loretta J.
AU - Westin, Jason
AU - Arora, Reetakshi
AU - Wang, Michael L.
AU - Turner, Joel
AU - Menges, Meghan
AU - Hidalgo-Vargas, Melanie
AU - Reid, Kayla
AU - Dreger, Peter
AU - Schmitt, Anita
AU - Müller-Tidow, Carsten
AU - Locke, Frederick L.
AU - Davila, Marco L.
AU - Champlin, Richard E.
AU - Flowers, Christopher R.
AU - Shpall, Elizabeth J.
AU - Poeck, Hendrik
AU - Neelapu, Sattva S.
AU - Schmitt, Michael
AU - Subklewe, Marion
AU - Jain, Michael D.
AU - Jenq, Robert R.
AU - Elinav, Eran
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2023/4
Y1 - 2023/4
N2 - 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.
AB - 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.
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U2 - 10.1038/s41591-023-02234-6
DO - 10.1038/s41591-023-02234-6
M3 - Article
C2 - 36914893
AN - SCOPUS:85149849549
SN - 1078-8956
VL - 29
SP - 906
EP - 916
JO - Nature medicine
JF - Nature medicine
IS - 4
ER -