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

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

Research output: Contribution to journalArticlepeer-review

42 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)906-916
Number of pages11
JournalNature medicine
Volume29
Issue number4
DOIs
StatePublished - Apr 2023

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology

MD Anderson CCSG core facilities

  • Advanced Technology Genomics Core
  • Microbiome Facility

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