Diet-driven microbial ecology underpins associations between cancer immunotherapy outcomes and the gut microbiome.


Journal

Nature medicine
ISSN: 1546-170X
Titre abrégé: Nat Med
Pays: United States
ID NLM: 9502015

Informations de publication

Date de publication:
11 2022
Historique:
received: 03 05 2022
accepted: 22 07 2022
pubmed: 23 9 2022
medline: 22 11 2022
entrez: 22 9 2022
Statut: ppublish

Résumé

The gut microbiota shapes the response to immune checkpoint inhibitors (ICIs) in cancer, however dietary and geographic influences have not been well-studied in prospective trials. To address this, we prospectively profiled baseline gut (fecal) microbiota signatures and dietary patterns of 103 trial patients from Australia and the Netherlands treated with neoadjuvant ICIs for high risk resectable metastatic melanoma and performed an integrated analysis with data from 115 patients with melanoma treated with ICIs in the United States. We observed geographically distinct microbial signatures of response and immune-related adverse events (irAEs). Overall, response rates were higher in Ruminococcaceae-dominated microbiomes than in Bacteroidaceae-dominated microbiomes. Poor response was associated with lower fiber and omega 3 fatty acid consumption and elevated levels of C-reactive protein in the peripheral circulation at baseline. Together, these data provide insight into the relevance of native gut microbiota signatures, dietary intake and systemic inflammation in shaping the response to and toxicity from ICIs, prompting the need for further studies in this area.

Identifiants

pubmed: 36138151
doi: 10.1038/s41591-022-01965-2
pii: 10.1038/s41591-022-01965-2
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2344-2352

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

Références

Seidel, J. A., Otsuka, A. & Kabashima, K. Anti-PD-1 and anti-CTLA-4 therapies in cancer: mechanisms of action, efficacy, and limitations. Front Oncol. 8, 86 (2018).
pubmed: 29644214 pmcid: 5883082 doi: 10.3389/fonc.2018.00086
Larkin, J. et al. Five-year survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 381, 1535–1546 (2019).
pubmed: 31562797 doi: 10.1056/NEJMoa1910836
Larkin, J. et al. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N. Engl. J. Med. 373, 23–34 (2015).
pubmed: 26027431 pmcid: 5698905 doi: 10.1056/NEJMoa1504030
Wolchok, J. D. et al. Overall survival with combined nivolumab and ipilimumab in advanced melanoma. N. Engl. J. Med. 377, 1345–1356 (2017).
pubmed: 28889792 pmcid: 5706778 doi: 10.1056/NEJMoa1709684
Long, G. V. et al. Standard-dose pembrolizumab in combination with reduced-dose ipilimumab for patients with advanced melanoma (KEYNOTE-029): an open-label, phase 1b trial. Lancet Oncol. 18, 1202–1210 (2017).
pubmed: 28729151 doi: 10.1016/S1470-2045(17)30428-X
Long, G. V. et al. Combination nivolumab and ipilimumab or nivolumab alone in melanoma brain metastases: a multicentre randomised phase 2 study. Lancet Oncol. 19, 672–681 (2018).
pubmed: 29602646 doi: 10.1016/S1470-2045(18)30139-6
Rozeman, E. A. et al. Identification of the optimal combination dosing schedule of neoadjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma (OpACIN-neo): a multicentre, phase 2, randomised, controlled trial. Lancet Oncol. 20, 948–960 (2019).
pubmed: 31160251 doi: 10.1016/S1470-2045(19)30151-2
Menzies, A. M. et al. Pathological response and survival with neoadjuvant therapy in melanoma: a pooled analysis from the International Neoadjuvant Melanoma Consortium (INMC). Nat. Med. 27, 301–309 (2021).
pubmed: 33558722 doi: 10.1038/s41591-020-01188-3
Rozeman, E. A. et al. Survival and biomarker analyses from the OpACIN-neo and OpACIN neoadjuvant immunotherapy trials in stage III melanoma. Nat. Med. 27, 256–263 (2021).
pubmed: 33558721 doi: 10.1038/s41591-020-01211-7
Luke, J. J., Flaherty, K. T., Ribas, A. & Long, G. V. Targeted agents and immunotherapies: optimizing outcomes in melanoma. Nat. Rev. Clin. Oncol. 14, 463–482 (2017).
pubmed: 28374786 doi: 10.1038/nrclinonc.2017.43
Grainger, J., Daw, R. & Wemyss, K. Systemic instruction of cell-mediated immunity by the intestinal microbiome. F1000Res 7, (2018).
Harkiolaki, M. et al. T cell-mediated autoimmune disease due to low-affinity crossreactivity to common microbial peptides. Immunity 30, 348–357 (2009).
pubmed: 19303388 doi: 10.1016/j.immuni.2009.01.009
Horai, R. et al. Microbiota-dependent activation of an autoreactive t cell receptor provokes autoimmunity in an immunologically privileged site.Immunity 43, 343–353 (2015).
pubmed: 26287682 pmcid: 4544742 doi: 10.1016/j.immuni.2015.07.014
Parada Venegas, D. et al. Short chain fatty acids (scfas)-mediated gut epithelial and immune regulation and its relevance for inflammatory bowel diseases. Front Immunol. 10, 277 (2019).
pubmed: 30915065 pmcid: 6421268 doi: 10.3389/fimmu.2019.00277
Steed, A. L. et al. The microbial metabolite desaminotyrosine protects from influenza through type I interferon. Science 357, 498–502 (2017).
pubmed: 28774928 pmcid: 5753406 doi: 10.1126/science.aam5336
Bachem, A. et al. Microbiota-derived short-chain fatty acids promote the memory potential of antigen-activated CD8(+) T cells. Immunity 51(2), 285–297.e5, https://doi.org/10.1016/j.immuni.2019.06.002 (2019).
doi: 10.1016/j.immuni.2019.06.002 pubmed: 31272808
Marchesi, J. R. et al. The gut microbiota and host health: a new clinical frontier. Gut 65, 330–339 (2016).
pubmed: 26338727 doi: 10.1136/gutjnl-2015-309990
Matson, V. et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 359, 104–108 (2018).
pubmed: 29302014 pmcid: 6707353 doi: 10.1126/science.aao3290
Gopalakrishnan, V. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 359, 97–103 (2018).
pubmed: 29097493 doi: 10.1126/science.aan4236
Routy, B. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 359, 91–97 (2018).
pubmed: 29097494 doi: 10.1126/science.aan3706
Vetizou, M. et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science 350, 1079–1084 (2015).
pubmed: 26541610 pmcid: 4721659 doi: 10.1126/science.aad1329
Chaput, N. et al. Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab. Ann. Oncol. 28, 1368–1379 (2017).
pubmed: 28368458 doi: 10.1093/annonc/mdx108
Coutzac, C. et al. Systemic short chain fatty acids limit antitumor effect of CTLA-4 blockade in hosts with cancer. Nat. Commun. 11, 2168 (2020).
pubmed: 32358520 pmcid: 7195489 doi: 10.1038/s41467-020-16079-x
Smith, M. et al. Gut microbiome correlates of response and toxicity following anti-CD19 CAR T cell therapy. Nat. Med. 28, 713–723 (2022).
pubmed: 35288695 pmcid: 9434490 doi: 10.1038/s41591-022-01702-9
Andrews, M. C. et al. Gut microbiota signatures are associated with toxicity to combined CTLA-4 and PD-1 blockade. Nat. Med. 27, 1432–1441 (2021).
pubmed: 34239137 doi: 10.1038/s41591-021-01406-6
McCulloch, J. A. et al. Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1. Nat. Med. 28, 545–556, https://doi.org/10.1038/s41591-022-01698-2 (2022).
doi: 10.1038/s41591-022-01698-2 pubmed: 35228752
Lee, K. A. et al. Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma. Nat. Med. 28, 535–544, https://doi.org/10.1038/s41591-022-01695-5 (2022).
doi: 10.1038/s41591-022-01695-5 pubmed: 35228751 pmcid: 8938272
Gharaibeh, R. Z. & Jobin, C. Microbiota and cancer immunotherapy: in search of microbial signals. Gut 68, 385–388, https://doi.org/10.1136/gutjnl-2018-317220 (2018).
doi: 10.1136/gutjnl-2018-317220 pubmed: 30530851
Tetzlaff, M. T. et al. Pathological assessment of resection specimens after neoadjuvant therapy for metastatic melanoma. Ann. Oncol. 29, 1861–1868 (2018).
pubmed: 29945191 pmcid: 6096739 doi: 10.1093/annonc/mdy226
Amaria, R. N. et al. Neoadjuvant systemic therapy in melanoma: recommendations of the International Neoadjuvant Melanoma Consortium. Lancet Oncol. 20, e378–e389 (2019).
pubmed: 31267972 doi: 10.1016/S1470-2045(19)30332-8
Frankel, A. E. et al. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 19, 848–855 (2017).
pubmed: 28923537 pmcid: 5602478 doi: 10.1016/j.neo.2017.08.004
Peters, B. A. et al. Relating the gut metagenome and metatranscriptome to immunotherapy responses in melanoma patients. Genome Med 11, 61 (2019).
pubmed: 31597568 pmcid: 6785875 doi: 10.1186/s13073-019-0672-4
Yu, L. C. Microbiota dysbiosis and barrier dysfunction in inflammatory bowel disease and colorectal cancers: exploring a common ground hypothesis. J. Biomed. Sci. 25, 79 (2018).
pubmed: 30413188 pmcid: 6234774 doi: 10.1186/s12929-018-0483-8
Rajca, S. et al. Alterations in the intestinal microbiome (dysbiosis) as a predictor of relapse after infliximab withdrawal in Crohn’s disease. Inflamm. Bowel Dis. 20, 978–986 (2014).
pubmed: 24788220
Bang, C. & Schmitz, R. A. Archaea associated with human surfaces: not to be underestimated. FEMS Microbiol. Rev. 39, 631–648 (2015).
pubmed: 25907112 doi: 10.1093/femsre/fuv010
Smith, N. W., Shorten, P. R., Altermann, E. H., Roy, N. C. & McNabb, W. C. Hydrogen cross-feeders of the human gastrointestinal tract. Gut Microbes 10, 270–288 (2019).
pubmed: 30563420 doi: 10.1080/19490976.2018.1546522
Belkaid, Y. & Hand, T. W. Role of the microbiota in immunity and inflammation. Cell 157, 121–141 (2014).
pubmed: 24679531 pmcid: 4056765 doi: 10.1016/j.cell.2014.03.011
Llewellyn, S. R. et al. Interactions between diet and the intestinal microbiota alter intestinal permeability and colitis severity in mice. Gastroenterology 154, e1032 (2018).
doi: 10.1053/j.gastro.2017.11.030
Nestel, P. et al. Indications for omega-3 long chain polyunsaturated fatty acid in the prevention and treatment of cardiovascular disease. Heart Lung Circ. 24, 769–779 (2015).
pubmed: 25936871 doi: 10.1016/j.hlc.2015.03.020
Macia, L. et al. Metabolite-sensing receptors GPR43 and GPR109A facilitate dietary fibre-induced gut homeostasis through regulation of the inflammasome. Nat. Commun. 6, 6734 (2015).
pubmed: 25828455 doi: 10.1038/ncomms7734
Chiba, M., Nakane, K. & Komatsu, M. Westernized diet is the most ubiquitous environmental factor in inflammatory bowel disease. Perm. J. 23, 18–107 (2019).
pubmed: 30624192 pmcid: 6499111 doi: 10.7812/TPP/18-107
Watson, H. et al. A randomised trial of the effect of omega-3 polyunsaturated fatty acid supplements on the human intestinal microbiota. Gut 67, 1974–1983 (2018).
pubmed: 28951525 doi: 10.1136/gutjnl-2017-314968
Lam, Y. Y. et al. Effects of dietary fat profile on gut permeability and microbiota and their relationships with metabolic changes in mice. Obes. (Silver Spring) 23, 1429–1439 (2015).
doi: 10.1002/oby.21122
Mager, L. F. et al. Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy. Science 369, 1481–1489 (2020).
pubmed: 32792462 doi: 10.1126/science.abc3421
Dubin, K. et al. Intestinal microbiome analyses identify melanoma patients at risk for checkpoint-blockade-induced colitis. Nat. Commun. 7, 10391 (2016).
pubmed: 26837003 pmcid: 4740747 doi: 10.1038/ncomms10391
Chen, J., Zhao, K.N. & Vitetta, L. Effects of intestinal microbial(-)elaborated butyrate on oncogenic signaling pathways. Nutrients 11(5), 1026 (2019).
pmcid: 6566851 doi: 10.3390/nu11051026
He, Y. et al. Regional variation limits applications of healthy gut microbiome reference ranges and disease models. Nat. Med. 24, 1532–1535 (2018).
pubmed: 30150716 doi: 10.1038/s41591-018-0164-x
Arumugam, M. et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011).
pubmed: 21508958 pmcid: 3728647 doi: 10.1038/nature09944
Holmes, I., Harris, K. & Quince, C. Dirichlet multinomial mixtures: generative models for microbial metagenomics. PLoS One 7, e30126 (2012).
pubmed: 22319561 pmcid: 3272020 doi: 10.1371/journal.pone.0030126
Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011).
pubmed: 21885731 pmcid: 3368382 doi: 10.1126/science.1208344
Costea, P. I. et al. Enterotypes in the landscape of gut microbial community composition. Nat. Microbiol 3, 8–16 (2018).
pubmed: 29255284 doi: 10.1038/s41564-017-0072-8
Singh, R. K. et al. Influence of diet on the gut microbiome and implications for human health. J. Transl. Med 15, 73 (2017).
pubmed: 28388917 pmcid: 5385025 doi: 10.1186/s12967-017-1175-y
Chung, D. & Keles, S. Sparse partial least squares classification for high dimensional data. Stat Appl Genet Mol Biol 9(1), (2010).
Spencer, C. N. et al. Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response. Science 374, 1632–1640 (2021).
pubmed: 34941392 pmcid: 8970537 doi: 10.1126/science.aaz7015
Kovatcheva-Datchary, P. et al. Dietary fiber-induced improvement in glucose metabolism is associated with increased abundance of prevotella. Cell Metab. 22, 971–982 (2015).
pubmed: 26552345 doi: 10.1016/j.cmet.2015.10.001
Zeevi, D. et al. Personalized nutrition by prediction of glycemic responses. Cell 163, 1079–1094 (2015).
pubmed: 26590418 doi: 10.1016/j.cell.2015.11.001
Zmora, N. et al. Personalized gut mucosal colonization resistance to empiric probiotics is associated with unique host and microbiome features. Cell 174, 1388–1405 e1321 (2018).
pubmed: 30193112 doi: 10.1016/j.cell.2018.08.041
Lam, K. C. et al. Microbiota triggers STING-type I IFN-dependent monocyte reprogramming of the tumor microenvironment. Cell https://doi.org/10.1016/j.cell.2021.09.019 (2021).
doi: 10.1016/j.cell.2021.09.019 pubmed: 34624222 pmcid: 8650838
Baruch, E. N. et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 371(6529), 602–609, https://doi.org/10.1126/science.abb5920 (2020).
doi: 10.1126/science.abb5920 pubmed: 33303685
Davar, D. et al. Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients. Science 371, 595–602 (2021).
pubmed: 33542131 pmcid: 8097968 doi: 10.1126/science.abf3363
Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).
pubmed: 27214047 pmcid: 4927377 doi: 10.1038/nmeth.3869
McMurdie, J. & Holmes, S. Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8, e61217 (2013).
pubmed: 23630581 pmcid: 3632530 doi: 10.1371/journal.pone.0061217
Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol. 12, R60 (2011).
pubmed: 21702898 pmcid: 3218848 doi: 10.1186/gb-2011-12-6-r60
Sidhu, P. et al. Radiological manifestations of immune-related adverse effects observed in patients with melanoma undergoing immunotherapy. J. Med Imaging Radiat. Oncol. 61, 759–766 (2017).
pubmed: 29024572 doi: 10.1111/1754-9485.12653
Franzosa, E. A. et al. Species-level functional profiling of metagenomes and metatranscriptomes. Nat. Methods 15, 962–968 (2018).
pubmed: 30377376 pmcid: 6235447 doi: 10.1038/s41592-018-0176-y
Suzek, B. E. et al. UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics 31, 926–932 (2015).
pubmed: 25398609 doi: 10.1093/bioinformatics/btu739
Caspi, R. et al. The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res. 46, D633–D639 (2018).
pubmed: 29059334 doi: 10.1093/nar/gkx935
Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V. & Egozcue, J. J. Microbiome Datasets Are Compositional: And This Is Not Optional. Front Microbiol 8, 2224 (2017).
pubmed: 29187837 pmcid: 5695134 doi: 10.3389/fmicb.2017.02224
Rohart, F., Gautier, B., Singh, A. & Le Cao, K. A. mixOmics: An R package for ‘omics feature selection and multiple data integration. PLoS Comput. Biol. 13, e1005752 (2017).
pubmed: 29099853 pmcid: 5687754 doi: 10.1371/journal.pcbi.1005752
Zoll, J. et al. Fecal microbiota transplantation from high caloric-fed donors alters glucose metabolism in recipient mice, independently of adiposity or exercise status. Am. J. Physiol. Endocrinol. Metab. 319, E203–E216 (2020).
pubmed: 32516027 doi: 10.1152/ajpendo.00037.2020
Siebelink, E., Geelen, A. & de Vries, J. H. Self-reported energy intake by FFQ compared with actual energy intake to maintain body weight in 516 adults. Br. J. Nutr. 106, 274–281 (2011).
pubmed: 21338536 doi: 10.1017/S0007114511000067
Metsalu, T. & Vilo, J. ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap. Nucleic Acids Res. 43, W566–W570 (2015).
pubmed: 25969447 pmcid: 4489295 doi: 10.1093/nar/gkv468
Shanahan, E. R. et al. Influence of cigarette smoking on the human duodenal mucosa-associated microbiota. Microbiome 6, 150 (2018).
pubmed: 30157953 pmcid: 6116507 doi: 10.1186/s40168-018-0531-3
Ramirez-Farias, C. et al. Effect of inulin on the human gut microbiota: stimulation of Bifidobacterium adolescentis and Faecalibacterium prausnitzii. Br. J. Nutr. 101, 541–550 (2009).
pubmed: 18590586 doi: 10.1017/S0007114508019880
Mackie, R. I. et al. Ecology of uncultivated Oscillospira species in the rumen of cattle, sheep, and reindeer as assessed by microscopy and molecular approaches. Appl. Environ. Microbiol. 69, 6808–6815 (2003).
pubmed: 14602644 pmcid: 262257 doi: 10.1128/AEM.69.11.6808-6815.2003
Yanagita, K. et al. Flow cytometric sorting, phylogenetic analysis and in situ detection of Oscillospira guillermondii, a large, morphologically conspicuous but uncultured ruminal bacterium. Int J. Syst. Evol. Microbiol 53, 1609–1614 (2003).
pubmed: 13130057 doi: 10.1099/ijs.0.02541-0
Hook, S. E., Northwood, K. S., Wright, A. D. & McBride, B. W. Long-term monensin supplementation does not significantly affect the quantity or diversity of methanogens in the rumen of the lactating dairy cow. Appl. Environ. Microbiol. 75, 374–380 (2009).
pubmed: 19028912 doi: 10.1128/AEM.01672-08
Ohnishi, A. et al. Development of a 16S rRNA gene primer and PCR-restriction fragment length polymorphism method for rapid detection of members of the genus Megasphaera and species-level identification. Appl. Environ. Microbiol. 77, 5533–5535 (2011).
pubmed: 21705538 pmcid: 3147432 doi: 10.1128/AEM.00359-11
Layton, A. et al. Development of Bacteroides 16S rRNA gene TaqMan-based real-time PCR assays for estimation of total, human, and bovine fecal pollution in water. Appl. Environ. Microbiol. 72, 4214–4224 (2006).
pubmed: 16751534 pmcid: 1489674 doi: 10.1128/AEM.01036-05
Schneeberger, M. et al. Akkermansia muciniphila inversely correlates with the onset of inflammation, altered adipose tissue metabolism and metabolic disorders during obesity in mice. Sci. Rep. 5, 16643 (2015).
pubmed: 26563823 pmcid: 4643218 doi: 10.1038/srep16643
& Geirnaert, A. et al. Interindividual differences in response to treatment with butyrate-producing Butyricicoccus pullicaecorum 25-3 T studied in an in vitro gut model. FEMS Microbiol Ecol 91, (2015).
Hermann-Bank, M. L., Skovgaard, K., Stockmarr, A., Larsen, N. & Molbak, L. The Gut Microbiotassay: a high-throughput qPCR approach combinable with next generation sequencing to study gut microbial diversity. BMC Genomics 14, 788 (2013).
pubmed: 24225361 pmcid: 3879714 doi: 10.1186/1471-2164-14-788

Auteurs

Rebecca C Simpson (RC)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Charles Perkins Centre, The University of Sydney, Sydney, Australia.

Erin R Shanahan (ER)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Life and Environmental Science, Faculty of Science, The University of Sydney, Sydney, Australia.

Marcel Batten (M)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.

Irene L M Reijers (ILM)

Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.

Mark Read (M)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Computer Science, The University of Sydney, Sydney, Australia.
The Westmead Initiative, The University of Sydney, Sydney, Australia.

Ines P Silva (IP)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Westmead and Blacktown Hospitals, Sydney, Australia.

Judith M Versluis (JM)

Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.

Rosilene Ribeiro (R)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Life and Environmental Science, Faculty of Science, The University of Sydney, Sydney, Australia.

Alexandra S Angelatos (AS)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.

Jian Tan (J)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.

Chandra Adhikari (C)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.

Alexander M Menzies (AM)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Department of Medical Oncology, Royal North Shore and Mater Hospitals, Sydney, Australia.

Robyn P M Saw (RPM)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, Australia.

Maria Gonzalez (M)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.

Kerwin F Shannon (KF)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Department of Melanoma and Surgical Oncology, Royal Prince Alfred Hospital, Sydney, Australia.

Andrew J Spillane (AJ)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
School of Life and Environmental Science, Faculty of Science, The University of Sydney, Sydney, Australia.
Breast and Melanoma Surgery Department, Royal North Shore Hospital, St Leonards, Australia.

Rebecca Velickovic (R)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.

Alexander J Lazar (AJ)

Department of Pathology and Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Ashish V Damania (AV)

Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Aditya K Mishra (AK)

Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Manoj Chelvanambi (M)

Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Anik Banerjee (A)

The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA.

Nadim J Ajami (NJ)

Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Jennifer A Wargo (JA)

Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Laurence Macia (L)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.

Andrew J Holmes (AJ)

Charles Perkins Centre, The University of Sydney, Sydney, Australia.
School of Life and Environmental Science, Faculty of Science, The University of Sydney, Sydney, Australia.

James S Wilmott (JS)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Charles Perkins Centre, The University of Sydney, Sydney, Australia.

Christian U Blank (CU)

Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, The Netherlands.

Richard A Scolyer (RA)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Charles Perkins Centre, The University of Sydney, Sydney, Australia.
Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, Australia.

Georgina V Long (GV)

Melanoma Institute Australia, The University of Sydney, Sydney, Australia. georgina.long@sydney.edu.au.
Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia. georgina.long@sydney.edu.au.
Charles Perkins Centre, The University of Sydney, Sydney, Australia. georgina.long@sydney.edu.au.
Department of Medical Oncology, Royal North Shore and Mater Hospitals, Sydney, Australia. georgina.long@sydney.edu.au.

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Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
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Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
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Humans Yoga Low Back Pain Female Male

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