Interaction of bacterial genera associated with therapeutic response to immune checkpoint PD-1 blockade in a United States cohort
Open accessAbstract
BACKGROUND: Recent studies show that human gut microbial composition can determine whether a patient is a responder or non-responder to immunotherapy but have not identified a common microbial signal shared by responding patients. The functional relationship between immunity, intestinal microbiota, and NSCLC response to immune checkpoint inhibitor/inhibition (ICI) in an American cohort remains unexplored. METHODS: RNAlater-preserved fecal samples were collected from 65 pre-treatment (baseline) and post-treatment stage III/IV NSCLC patients undergoing ICI therapy, categorized as responders or non-responders according to RECIST criteria. Pooled and individual responder and non-responder microbiota were transplanted into a gnotobiotic mouse model of lung cancer and treated with ICIs. 16S rDNA and RNA sequencing was performed on patient fecal samples, 16S rDNA sequencing on mouse fecal samples, and flow cytometric analysis on mouse tumor tissue. RESULTS: Responder patients have both a different microbial community structure than non-responders (P = 0.004) and a different bacterial transcriptome (PC2 = 0.03) at baseline. Taxa significantly enriched in responders include amplicon sequence variants (ASVs) belonging to the genera Ruminococcus, Akkermansia, and Faecalibacterium. Pooled and individual responder microbiota transplantation into gnotobiotic mice decreased tumor growth compared to non-responder colonized mice following ICI (P = 0.023, P = 0.019, P = 0.008, respectively). Responder tumors showed an increased anti-tumor cellular phenotype following ICI treatment. Responder mice are enriched with ASVs belonging to the genera Bacteroides, Blautia, Akkermansia, and Faecalibacterium. Overlapping taxa mapping between human and mouse cohorts correlated with tumor size and weight revealed a network highlighting responder-associated ASVs belonging to the genera Colidextribacter, Frisingicoccus, Marvinbryantia, and Blautia which have not yet been reported. CONCLUSIONS: The role of isolate-specific function and bacterial gene expression in gut microbial-driven responsiveness to ICI has been underappreciated. This work supports further investigation using isolate-driven models to characterize the mechanisms underlying this phenomenon.
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Cites
Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548 · see citing works
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400 · see citing works
Cytoscape: A software Environment for integrated models of biomolecular interaction networks
Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., & Ideker, T. (2003) · Genome Research · doi:10.1101/gr.1239303 · Cited by 51,888 · see citing works
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364 · see citing works
DADA2: High–resolution sample inference from Illumina amplicon data
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., & Holmes, S. P. (2016) · Nature Methods · doi:10.1038/nmeth.3869 · Cited by 35,698 · see citing works
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989 · see citing works
featureCounts: an efficient general purpose program for assigning sequence reads to genomic features
Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219 · see citing works
Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2
Bolyen, E., Rideout, J. R., Dillon, M. R., Bokulich, N. A., Abnet, C. C., Al-Ghalith, G. A., Alexander, H., Alm, E. J., Arumugam, M., Asnicar, F., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0209-9 · Cited by 23,742 · see citing works
phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data
McMurdie, P. J., & Holmes, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061217 · Cited by 21,013 · see citing works
Prokka: rapid prokaryotic genome annotation
Seemann, T. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu153 · Cited by 18,512 · see citing works
Fast and sensitive protein alignment using DIAMOND
Buchfink, B., Xie, C., & Huson, D. H. (2015) · Nature Methods · doi:10.1038/nmeth.3176 · Cited by 14,201 · see citing works
Safety, activity, and immune correlates of anti–PD-1 antibody in cancer
Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., Atkins, M. B., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200690 · Cited by 12,628 · see citing works
Self-citationLi, D., Liu, C.-M., Luo, R., Sadakane, K., & Lam, T. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv033 · Cited by 9,781 · see citing works
UniFrac: a New Phylogenetic Method for Comparing Microbial Communities
Lozupone, C., & Knight, R. (2005) · Applied and Environmental Microbiology · doi:10.1128/aem.71.12.8228-8235.2005 · Cited by 8,227 · see citing works
Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors
Routy, B., Le Chatelier, E., Derosa, L., Duong, C. P. M., Alou, M. T., Daillère, R., Fluckiger, A., Messaoudene, M., Rauber, C., Roberti, M. P., et al. (2018) · Science · doi:10.1126/science.aan3706 · Cited by 5,671 · cited 4× · see citing works
“was the first to examine the gut microbial composition of NSCLC responders and non-responders to ICI, using a cohort of 140 patients [4].”
BackgroundMethodInfluentialGAGE: generally applicable gene set enrichment for pathway analysis
Luo, W., Friedman, M. S., Shedden, K., Hankenson, K. D., & Woolf, P. J. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-161 · Cited by 1,333 · see citing works
Human Intestinal Lumen and Mucosa-Associated Microbiota in Patients with Colorectal Cancer
Chen, W., Liu, F., Ling, Z., Tong, X., & Xiang, C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039743 · Cited by 1,029 · see citing works
Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response
Spencer, C. N., McQuade, J. L., Gopalakrishnan, V., McCulloch, J. A., Vetizou, M., Cogdill, A. P., Khan, M. A. W., Zhang, X., White, M. G., Peterson, C. B., et al. (2021) · Science · doi:10.1126/science.aaz7015 · Cited by 966 · see citing works
Revisiting the role of CD4+ T cells in cancer immunotherapy—new insights into old paradigms
Tay, R. E., Richardson, E. K., & Toh, H. C. (2020) · Cancer Gene Therapy · doi:10.1038/s41417-020-0183-x · Cited by 801 · see citing works
Intestinal Blautia Is Associated with Reduced Death from Graft-versus-Host Disease
Jenq, R. R., Taur, Y., Devlin, S. M., Ponce, D. M., Goldberg, J. D., Ahr, K. F., Littmann, E. R., Ling, L., Gobourne, A. C., Miller, L. C., et al. (2015) · Biology of Blood and Marrow Transplantation · doi:10.1016/j.bbmt.2015.04.016 · Cited by 748 · see citing works
Gut microbiota signatures are associated with toxicity to combined CTLA-4 and PD-1 blockade
Andrews, M. C., Duong, C. P. M., Gopalakrishnan, V., Iebba, V., Chen, W.-S., Derosa, L., Khan, M. A. W., Cogdill, A. P., White, M. G., Wong, M. C., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01406-6 · Cited by 437 · see citing works
Arthur, J. C., Gharaibeh, R. Z., Mühlbauer, M., Perez-Chanona, E., Uronis, J. M., McCafferty, J., Fodor, A. A., & Jobin, C. (2014) · Nature Communications · doi:10.1038/ncomms5724 · Cited by 392 · see citing works
Self-citationLee, S.-H., Cho, S.-Y., Yoon, Y., Park, C., Sohn, J., Jeong, J.-J., Jeon, B.-N., Jang, M., An, C., Lee, S., et al. (2021) · Nature Microbiology · doi:10.1038/s41564-020-00831-6 · Cited by 325 · see citing works
McCafferty, J., Mühlbauer, M., Gharaibeh, R. Z., Arthur, J. C., Perez-Chanona, E., Sha, W., Jobin, C., & Fodor, A. A. (2013) · The ISME Journal · doi:10.1038/ismej.2013.106 · Cited by 259 · see citing works
Self-citationLocoregional Effects of Microbiota in a Preclinical Model of Colon Carcinogenesis
Tomkovich, S., Yang, Y., Winglee, K., Gauthier, J., Mühlbauer, M., Sun, X., Mohamadzadeh, M., Liu, X., Martin, P., Wang, G. P., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-16-3472 · Cited by 252 · see citing works
Self-citationNivolumab in NSCLC: latest evidence and clinical potential
Sundar, R., Cho, B. C., Brahmer, J. R., & Soo, R. A. (2015) · Therapeutic Advances in Medical Oncology · doi:10.1177/1758834014567470 · Cited by 228 · see citing works
Li, H. Y., McSharry, M. V., Bullock, B., Nguyen, T. T., Kwak, J., Poczobutt, J. M., Sippel, T. R., Heasley, L. E., Weiser-Evans, M. C. M., Clambey, E. T., et al. (2017) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-16-0365 · Cited by 186 · see citing works
Microbiota and cancer immunotherapy: in search of microbial signals
Gharaibeh, R. Z., & Jobin, C. (2019) · Gut · doi:10.1136/gutjnl-2018-317220 · Cited by 144 · see citing works
Self-citationShima, T., Shimoda, M., Shigenobu, T., Ohtsuka, T., Nishimura, T., Emoto, K., Hayashi, Y., Iwasaki, T., Abe, T., Asamura, H., et al. (2019) · Cancer Science · doi:10.1111/cas.14272 · Cited by 56 · see citing works
Hecht, G., Bar-Nathan, C., Milite, G. P., Alon, I., Moshe, Y., Greenfeld, L., Dotsenko, N., Suez, J., Levy, M., Thaiss, C. A., et al. (2014) · Laboratory Animals · doi:10.1177/0023677214544728 · Cited by 55 · see citing works
Paik, J., Pershutkina, O. V., Meeker, S. M., Yi, J., Dowling, S. C., Hsu, C. C., Hajjar, A. M., Maggio‐Price, L., & Beck, D. A. C. (2015) · Gut Microbes · doi:10.1080/19490976.2015.1064576 · Cited by 46 · see citing works
Immune Checkpoint Inhibitors in Lung Cancer: Past, Present and Future
Seetharamu, N., Budman, D. R., & Sullivan, K. M. (2016) · Future Oncology · doi:10.2217/fon.16.20 · Cited by 34 · see citing works
Hogue, S., Gomez, M. F., da Silva, W. V., & Pierce, C. M. (2019) · Microbial Ecology · doi:10.1007/s00248-019-01346-2 · Cited by 28 · see citing works
Self-citationFarhadfar, N., Gharaibeh, R. Z., Dahl, W. J., Mead, L., Alabasi, K. M., Newsome, R. C., Irizarry-Gatell, V., Weaver, M. T., Al‐Mansour, Z., Jobin, C., et al. (2021) · Transplantation and Cellular Therapy · doi:10.1016/j.jtct.2021.02.017 · Cited by 25 · see citing works
Self-citation
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- [34]Newsome RC, Gharaibeh RZ, Pierce CM, da Silva WV, Paul S, Hogue SR, et al. RNAseq a network of bacterial genera associated with therapeutic response to immune checkpoint PD-1 blockade in a United States cohort. Sequence Read Arch. 2021. https://www.ncbi.nlm.nih.gov/bioproject/PRJNA767368/. PMC8961902 35346337
- [35]Newsome RC, Gharaibeh RZ, Pierce CM, da Silva WV, Paul S, Hogue SR, et al. 16S human for a network of bacterial genera associated with therapeutic response to immune checkpoint PD-1 blockade in a United States cohort. Sequence Read Arch. 2021. https://www.ncbi.nlm.nih.gov/bioproject/PRJNA768678/. PMC8961902 35346337
- [36]Newsome RC, Gharaibeh RZ, Pierce CM, da Silva WV, Paul S, Hogue SR, et al. 16S mouse study for a network of bacterial genera associated with therapeutic response to immune checkpoint PD-1 blockade in a United States cohort. Sequence Read Arch. 2021. https://www.ncbi.nlm.nih.gov/bioproject/PRJNA768820/. PMC8961902 35346337
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Derosa, L., Iebba, V., Silva, C. A. C., Piccinno, G., Wu, G., Lordello, L., Routy, B., Zhao, N., Thelemaque, C., Birebent, R., et al. (2024) · Cell · doi:10.1016/j.cell.2024.05.029 · Cited by 198 · see citing works
Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy
Thomas, A. M., Fidelle, M., Routy, B., Kroemer, G., Wargo, J. A., Segata, N., & Zitvogel, L. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00785-8 · Cited by 141 · see citing works
<i>Faecalibacterium prausnitzii</i> strain EXL01 boosts efficacy of immune checkpoint inhibitors
Bredon, M., Danne, C., Pham, H. P., Ruffié, P., Bessede, A., Rolhion, N., Creusot, L., Brot, L., Alonso, I., Langella, P., et al. (2024) · OncoImmunology · doi:10.1080/2162402x.2024.2374954 · Cited by 74 · see citing works
Computational methods and challenges in analyzing intratumoral microbiome data
Wang, Q., Liu, Z., Ma, A., Li, Z., Liu, B., & Ma, Q. (2023) · Trends in Microbiology · doi:10.1016/j.tim.2023.01.011 · Cited by 37 · see citing works
Gamrath, L., Pedersen, T. B., Møller, M. V., Volmer, L. M., Holst-Christensen, L., Vestermark, L. W., & Donskov, F. (2025) · Current Oncology Reports · doi:10.1007/s11912-024-01622-6 · Cited by 30 · see citing works
“Several studies found Akkermansia significantly increased in responders to immunotherapy (Table 1) [15, 18, 20–26].”
- Authors
- Newsome, R. C., Gharaibeh, R. Z., Pierce, C. M., da Silva, W. V., Paul, S., Hogue, S. R., Yu, Q., Antonia, S., Conejo-Garcia, J. R., Robinson, L. A., & Jobin, C.
- Affiliations
- University of Florida Health (US)
- Merck & Co., Inc., Rahway, NJ, USA (United States) (US)
- Moffitt Cancer Center (US)
- Corresponding author
- Jobin, Christian
- ORCID
- Venue
- Genome Medicine
- Published
- 2022-03-29
- Volume
- 14
- Issue
- 1
- Pages
- 35-35
- ISSN
- 1756-994X (ISSN-L)
- PMC
- PMC8961902
- OpenAlex
- W4221050169
- Cited by
- 104
- References
- 34
- Citations by year
- 2026: 21 · 2025: 34 · 2024: 23 · 2023: 19 · 2022: 7
- FWCI
- 8.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- University of Florida (TL1TR001428, UL1 TR001427)
- Moffitt Cancer Center (P30CA076292, CA076292)
- National Institutes of Health (UL1TR001427, TL1TR001428)
- University of Florida Health (UL1TR001427)
- International Centre for Bamboo and Rattan
- National Cancer Institute (P30CA076292, T32CA257923)
- National Center for Advancing Translational Sciences
- State of Florida
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- gut microbiota, immune checkpoint inhibitors, anti-PD-1 therapy, non-small cell lung cancer, immunotherapy response, bacterial gene expression, Akkermansia, Faecalibacterium, Blautia, Ruminococcus, microbiota transplantation, gnotobiotic mouse model, antitumor immunity, bacterial genera
- MeSH terms
- Gastrointestinal Microbiome, Immune Checkpoint Inhibitors, Animals, Carcinoma, Non-Small-Cell Lung, Humans, Lung Neoplasms, United States, Mice, Programmed Cell Death 1 Receptor
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