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<article xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" article-type="research-article" xml:lang="en"><processing-meta tagset-family="jats" base-tagset="archiving" mathml-version="3.0" table-model="xhtml"><custom-meta-group><custom-meta assigning-authority="highwire" xlink:type="simple"><meta-name>recast-jats-build</meta-name><meta-value>d8e1462159</meta-value></custom-meta></custom-meta-group></processing-meta><front><journal-meta><journal-id journal-id-type="hwp">jitc</journal-id><journal-id journal-id-type="nlm-ta">J Immunother Cancer</journal-id><journal-id journal-id-type="publisher-id">40425</journal-id><journal-title-group><journal-title>Journal for ImmunoTherapy of Cancer</journal-title><abbrev-journal-title abbrev-type="publisher">J Immunother Cancer</abbrev-journal-title></journal-title-group><issn pub-type="epub">2051-1426</issn><publisher><publisher-name>BMJ Publishing Group Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">s40425-019-0775-x</article-id><article-id pub-id-type="manuscript">775</article-id><article-id pub-id-type="doi">10.1186/s40425-019-0775-x</article-id><article-id pub-id-type="pmid">31694714</article-id><article-id pub-id-type="apath" assigning-authority="highwire">/jitc/7/1/287.atom</article-id><article-categories><subj-group subj-group-type="heading"><subject>Commentary</subject></subj-group><subj-group subj-group-type="article-collection" specific-use="SubjectSection"><subject>Commentary/Editorials</subject></subj-group><subj-group subj-group-type="collection" assigning-authority="publisher"><subject>Commentary/Editorials</subject></subj-group><subj-group subj-group-type="collection" assigning-authority="highwire"><subject>Special collections</subject><subj-group><subject>JITC</subject><subj-group><subject>Commentary/Editorials</subject></subj-group></subj-group></subj-group></article-categories><title-group><article-title xml:lang="en">Antibiotic therapy and outcome from immune-checkpoint inhibitors</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" xlink:type="simple"><contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0002-3529-0103</contrib-id><name name-style="western"><surname>Pinato</surname><given-names>David J.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref><xref ref-type="aff" rid="Aff2">2</xref><xref ref-type="corresp" rid="IDs404250190775x_cor1">a</xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gramenitskaya</surname><given-names>Daria</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Altmann</surname><given-names>Daniel M.</given-names></name><xref ref-type="aff" rid="Aff3">3</xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Boyton</surname><given-names>Rosemary J.</given-names></name><xref ref-type="aff" rid="Aff4">4</xref><xref ref-type="aff" rid="Aff5">5</xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mullish</surname><given-names>Benjamin H.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Marchesi</surname><given-names>Julian R.</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Bower</surname><given-names>Mark</given-names></name><xref ref-type="aff" rid="Aff6">6</xref></contrib><aff id="Aff1">
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</corresp><fn fn-type="other"><label>Publisher’s Note</label><p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p></fn></author-notes><pub-date date-type="pub" iso-8601-date="2019-12" pub-type="ppub" publication-format="print"><month>12</month><year>2019</year></pub-date><pub-date date-type="pub" iso-8601-date="2019-11-06" pub-type="epub-original" publication-format="electronic"><day>6</day><month>11</month><year>2019</year></pub-date><pub-date iso-8601-date="2019-11-18T10:22:57-08:00" pub-type="hwp-received"><day>18</day><month>11</month><year>2019</year></pub-date><pub-date iso-8601-date="2019-11-18T10:22:57-08:00" pub-type="hwp-created"><day>18</day><month>11</month><year>2019</year></pub-date><pub-date iso-8601-date="2019-11-06T00:00:00-08:00" pub-type="epub"><day>6</day><month>11</month><year>2019</year></pub-date><volume>7</volume><issue>1</issue><elocation-id>287</elocation-id><history><date date-type="received" iso-8601-date="2019-07-12"><day>12</day><month>7</month><year>2019</year></date><date date-type="accepted" iso-8601-date="2019-10-09"><day>9</day><month>10</month><year>2019</year></date></history><permissions><copyright-statement>© The Author(s).</copyright-statement><copyright-year>2019</copyright-year><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/" xlink:type="simple"><license-p>
<bold>Open Access</bold>This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/" xlink:type="simple">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="40425_2019_Article_775_nlm.pdf" xlink:type="simple"/><abstract id="Abs1" xml:lang="en"><p id="Par1">Sensitivity to immune checkpoint inhibitor (ICPI) therapy is governed by a complex interplay of tumor and host-related determinants. Epidemiological studies have highlighted that exposure to antibiotic therapy influences the probability of response to ICPI and predict for shorter patient survival across malignancies. Whilst a number of studies have reproducibly documented the detrimental effect of broad-spectrum antibiotics, the immune-biologic mechanisms underlying the association with outcome are poorly understood. Perturbation of the gut microbiota, an increasingly well-characterized factor capable of influencing ICPI-mediated immune reconstitution, has been indicated as a putative mechanism to explain the adverse effects attributed to antibiotic exposure in the context of ICPI therapy. Prospective studies are required to validate antibiotic-mediated gut perturbations as a mechanism of ICPI refractoriness and guide the development of strategies to overcome this barrier to an effective delivery of anti-cancer immunotherapy.</p></abstract><kwd-group xml:lang="en"><kwd>Antibiotics</kwd><kwd>Immune checkpoint inhibitors</kwd><kwd>Survival</kwd></kwd-group><custom-meta-group><custom-meta xlink:type="simple"><meta-name>publisher-imprint-name</meta-name><meta-value>BioMed Central</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>volume-issue-count</meta-name><meta-value>2</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>issue-article-count</meta-name><meta-value>0</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>issue-toc-levels</meta-name><meta-value>0</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>issue-pricelist-year</meta-name><meta-value>2019</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>issue-copyright-holder</meta-name><meta-value>The Author(s)</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>issue-copyright-year</meta-name><meta-value>2019</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-contains-esm</meta-name><meta-value>No</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-numbering-style</meta-name><meta-value>Unnumbered</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-registration-date-year</meta-name><meta-value>2019</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-registration-date-month</meta-name><meta-value>10</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-registration-date-day</meta-name><meta-value>9</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-toc-levels</meta-name><meta-value>0</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>toc-levels</meta-name><meta-value>0</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>volume-type</meta-name><meta-value>Regular</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>journal-product</meta-name><meta-value>ArchiveJournal</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>numbering-style</meta-name><meta-value>Unnumbered</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-grants-type</meta-name><meta-value>OpenChoice</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>metadata-grant</meta-name><meta-value>OpenAccess</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>abstract-grant</meta-name><meta-value>OpenAccess</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>bodypdf-grant</meta-name><meta-value>OpenAccess</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>bodyhtml-grant</meta-name><meta-value>OpenAccess</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>bibliography-grant</meta-name><meta-value>OpenAccess</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>esm-grant</meta-name><meta-value>OpenAccess</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>online-first</meta-name><meta-value>false</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>pdf-file-reference</meta-name><meta-value>BodyRef/PDF/40425_2019_Article_775.pdf</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>pdf-type</meta-name><meta-value>Typeset</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>target-type</meta-name><meta-value>OnlinePDF</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>issue-type</meta-name><meta-value>Regular</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>article-type</meta-name><meta-value>Letter</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>journal-subject-primary</meta-name><meta-value>Medicine &amp; Public Health</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>journal-subject-secondary</meta-name><meta-value>Oncology</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>journal-subject-secondary</meta-name><meta-value>Immunology</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>journal-subject-collection</meta-name><meta-value>Medicine</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>open-access</meta-name><meta-value>true</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="Sec1"><title>Introduction</title><p id="Par27">Antibiotic therapy has produced unquestionable advances in the management of patients with cancer, a population with intrinsically higher risk of bacterial infection as a result of malignancy or treatment-related immune suppression.</p><p id="Par28">While antimicrobial therapy has markedly reduced morbidity and mortality stemming from infection, the effects of broad-spectrum antibiotics on commensal, non-pathogenic bacterial species have remained for a long time an under-appreciated effect of this therapeutic class of drugs.</p><p id="Par29">The gut microbiota, source of over 100 trillion bacteria, exists in a condition of mutually beneficial relationship with the host. Commensal bacteria are provided with a niche to colonise the host in return for their participation in the digestion of nutrients and xenobiotics, protection from pathogens and shaping of the host’s immune system subsets. Derangement of this delicate relationship has been increasingly well-characterised in the context of tumour-specific immune tolerogenesis [<xref ref-type="bibr" rid="CR1">1</xref>].</p><p id="Par30">Multiple levels of evidence now support the link between sensitivity to immunotherapy, taxonomic diversity and enrichment in specific gut bacterial taxa, suggesting that some species or species consortia provide intrinsic immune-modulating properties. The landmark study by Gopalakrishnan [<xref ref-type="bibr" rid="CR2">2</xref>] demonstrated how broader stool bacterial diversity and higher representation of <italic toggle="yes">Ruminococcaceae</italic> communities including <italic toggle="yes">Faecalibacterium</italic> positively influences patients’ survival following ICPI by promoting a strongly immune-reactive microenvironment and lower systemic release of pro-inflammatory cytokines [<xref ref-type="bibr" rid="CR3">3</xref>]. Many other commensal bacteria have subsequently been recognised to play a similar role including <italic toggle="yes">Bifidobacteria</italic> spp., a saccarolytic Gram-positive genus highly represented within the gut that facilitates dendritic cell maturation and increased accumulation of antigen-specific T-cells within the tumour microenvironment [<xref ref-type="bibr" rid="CR4">4</xref>]. Similarly, the presence of the anaerobic commensal <italic toggle="yes">Akkermansia Muciniphila</italic> is more common in responders to ICPI, who display higher peripheral CD4 and CD8 memory T-cell responses to this bacterium [<xref ref-type="bibr" rid="CR5">5</xref>].</p><p id="Par31">Antibiotic (ATB) therapy imposes profound and protracted changes to the taxonomic diversity of the host microbial ecosystem, affecting the composition of up to 30% of the bacterial species in the gut microbiome [<xref ref-type="bibr" rid="CR6">6</xref>], consequently leading to loss of microbial functions that are protective for the host. Such changes in gut microbial communities are rapid and pervasive, occurring within days from the first antibiotic dose [<xref ref-type="bibr" rid="CR7">7</xref>] and persisting for up to several months after completion of therapy [<xref ref-type="bibr" rid="CR8">8</xref>].</p><p id="Par32">Mounting evidence from epidemiological studies has underscored the detrimental role of antibiotics in ICPI outcome, with exposure to antibiotics having been linked to shortened progression-free, overall survival and reduced response rates in patients receiving ICPI as part of clinical trials and in routine practice (Table <xref rid="Tab1" ref-type="table">1</xref>). In a previous study, we demonstrated time-dependence of antibiotics exposure as a strong, tumour-agnostic determinant of outcome in ICPI recipients, confirming prior, but not concurrent antibiotic therapy as doubling the risk of primary progression to immunotherapy and leading to a &gt; 20-months shortening in patients’ survival independent of established prognostic factors and corticosteroid use [<xref ref-type="bibr" rid="CR10">10</xref>]. Whilst mirroring pre-clinical evidence, where antibiotic pre-conditioning ahead of tumour implantation leads to impaired responses to ICPI in mice [<xref ref-type="bibr" rid="CR26">26</xref>, <xref ref-type="bibr" rid="CR27">27</xref>], the expanding body of clinical studies has so far painted an incomplete picture as to the mechanistic foundations underlying the relationship between ATB and immunotherapy, a point of greater consequence given the potential practice-influencing implications of ATB prescribing in the clinic.<table-wrap id="Tab1" position="float" orientation="portrait"><object-id pub-id-type="publisher-id">Tab1</object-id><caption xml:lang="en"><p>The relationship between antibiotic exposure and outcomes from immune checkpoint inhibitor therapy</p></caption><table frame="hsides" rules="groups"><thead><tr><th rowspan="1" colspan="1">Study</th><th rowspan="1" colspan="1">Tumour Sites</th><th rowspan="1" colspan="1">ICPI(n, %)</th><th rowspan="1" colspan="1">ATB exposure</th><th rowspan="1" colspan="1">ATB Duration</th><th rowspan="1" colspan="1">ATB Type</th><th rowspan="1" colspan="1">Administration route</th><th rowspan="1" colspan="1">Response</th><th rowspan="1" colspan="1">Survival</th><th rowspan="1" colspan="1">Notes</th></tr></thead><tbody><tr><td rowspan="2" colspan="1">Derosa L et al. [9]</td><td rowspan="1" colspan="1">NSCLC (239)</td><td rowspan="1" colspan="1">PD-L1 (205, 86%)PD-L1/ CTLA-4 (34, 14%)</td><td rowspan="1" colspan="1">pATB (within 30 days)(48, 20%)No ATB (191, 80%)</td><td rowspan="1" colspan="1">≤ 7 days(35, 73%)&gt;  7 days(13, 27%)</td><td rowspan="1" colspan="1">Beta-lactam(15, 32%)Quinolones(14, 29%)Macrolides(4, 8%)Sulfonamides (12, 25%)Tetracyclines(1, 2%)Nitromidazole (1, 2%)Others(1, 2%)</td><td rowspan="1" colspan="1">Oral(42, 87%)IM/ IV(5, 11%)Unreported(1, 2%)</td><td rowspan="1" colspan="1">PD in 52% exposed vs in 43% unexposed, P = 0.26</td><td rowspan="1" colspan="1">ATB vs no ATBmedian OS:7.9 months vs 24.6 months,HR 4.4, 95% CI 2.6–7.7, P &lt; 0.01median PFS:1.9 months vs 3.8 months, HR 1.5, 95%CI 1.0–2.2, P = 0.03</td><td rowspan="2" colspan="1">Significant impact supported by multivariate analysis</td></tr><tr><td rowspan="1" colspan="1">RCC (121)</td><td rowspan="1" colspan="1">PD-L1 (106, 88%)PD-L1/CTLA-4(10, 8%)PD-L1/Bevacizumab (5, 4%)</td><td rowspan="1" colspan="1">pATB (within 30 days) (16, 13%)No ATB (105, 87%)</td><td rowspan="1" colspan="1">≤ 7 days(8, 50%)&gt;  7 days(8, 50%)</td><td rowspan="1" colspan="1">Beta-lactam(13, 82%)Quinolones(1, 6%)Tetracyclines(1, 6%)Aminoglycosides (1, 6%)</td><td rowspan="1" colspan="1">Oral(15, 94%)IV/ IM(1, 6%)</td><td rowspan="1" colspan="1">PD in 75% exposed vsin 22% unexposed, P &lt; 0.01</td><td rowspan="1" colspan="1">ATB vs no ATBmedian OS:17.3 months vs 30.6 months, HR 3.5, 95% CI 1.1–10.8, P = 0.03median PFS:1.9 months vs 7.4 months, HR 3.1, 95% CI 1.4–6.9, P &lt; 0.01</td></tr><tr><td rowspan="1" colspan="1">Pinato DJ et al. [10]</td><td rowspan="1" colspan="1">NSCLC(119, 60%)Melanoma (38, 20%)Renal(27, 14%)Head &amp; neck(10, 5%)Total n = 196</td><td rowspan="1" colspan="1">PD-1/PD-L1(189, 96%)</td><td rowspan="1" colspan="1">pATB (29, 15%)(within 30 days)cATB (during ICPI therapy until cessation) (68, 35%)no ATB(99, 50%)</td><td rowspan="1" colspan="1">pATB≤7 days(26, 90%)&gt;  7 days(3, 10%)cATB≤7 days(39, 88%)</td><td rowspan="1" colspan="1">pATBBeta-lactamin 22, 75%cATBBeta-lactamin 49, 72%</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">pATB:PD in 80% exposed vs 44% unexposed, p &lt; 0.001cATB:PD in 50% exposed vs 49% unexposed, p = 0.87</td><td rowspan="1" colspan="1">pATB (p &lt; 0.001) but not cATB (p = 0.76) predicted worse OS (26 vs 2 months, HR 7.4, 95% CI 4.2–12.9) Multivariate analysis confirmed pATB as a predictor of OS (HR 3.4, 95%CI 1.9–6.1 p &lt; 0.001)</td><td rowspan="1" colspan="1">ICPI-refractory in 81% pATB vs 44% no pATB, p &lt; 0.001</td></tr><tr><td rowspan="1" colspan="1">Hakozaki T et al. [11]</td><td rowspan="1" colspan="1">NSCLC (90)</td><td rowspan="1" colspan="1">PD-1 (90)</td><td rowspan="1" colspan="1">pATB(13, 14%)(30 days before ICPI initiation)no pATB (77, 86%)</td><td rowspan="1" colspan="1">≤7 days (1, 8%)&gt;  7 days (12, 92%)</td><td rowspan="1" colspan="1">Beta-lactam (8, 61%) Sulfonamides (4, 31%)Quinolones (1, 8%)</td><td rowspan="1" colspan="1">Oral(10, 77%)IV(3, 23%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">pATB vs no ATBmedian PFS:1.2 [95% CI, 0.5–5.8] vs 4.4 months [95% CI, 2.5–7.4], P = 0.04median OS:8.8 months vs not reached, P = 0.037</td><td rowspan="1" colspan="1">Unsupported by multivariate analysis of pATB and OS:HR 2.02, (95% CI, 0.7–5.83, P = 0.19)</td></tr><tr><td rowspan="1" colspan="1">Galli G et al. [12]</td><td rowspan="1" colspan="1">NSCLC (157)</td><td rowspan="1" colspan="1">PD-1 (98, 62.4%)PD-L1 (52, 33%)CTLA4 (1, 0.6%)PD-L1/CTLA4 (6, 4%)</td><td rowspan="1" colspan="1">ATB:in EIOP (27, 17%)in WIOP (46, 29%)No ATB (111, 71%)High AIER23 (15%)Low AIER(134, 85%)</td><td rowspan="1" colspan="1">Median duration7.0 days (5.0–33.0)</td><td rowspan="1" colspan="1">Quinolone (33, 72%)Macrolide (8, 17%)Beta-lactam (14, 30%)Rifaximin (4, 8.7%)</td><td rowspan="1" colspan="1">Oral(44, 98%) IM(3, 6.5%), IV(2, 4.4%).</td><td rowspan="1" colspan="1">Exposed in EIOPRR: 11.1% vs 24.6%, p = 0.20; DCR: 51.9% vs 56.2%, p = 0.8319.AIER (high vs low)RR: 8.7%, vs 26.6%. p = 0.11DCR: 47.8% vs 56.0%, p = 0.50,</td><td rowspan="1" colspan="1">High vs low AIERmedian PFS:1.9 [95% CI, 1.3–3.0] vs3.5 months [95% CI, 2.6–5.0] p &lt; 0.0001median OS:5.1 [95% CI, 3.8–5.9] vs 13.2 months [95% CI, 9.9–5.9] p = 0.0004</td><td rowspan="1" colspan="1">Exposed vs unexposed in EIOPmedian PFS:2.2 [95% CI, 1.8–3.2] vs 3.3 months [95% CI, 2.6–4.8]P = 0.1772median OS:11.9 [95% CI, 9.2–15.6] vs 5.9 months [95% CI, 4.5–22.5]P = 0.2492Significant impact supported by multivariate analysis</td></tr><tr><td rowspan="1" colspan="1">Ahmed J et al. [13]</td><td rowspan="1" colspan="1">NSCLC (34, 57%)Renal (4, 7%)HCC (5, 8%)Urothelial (5, 8%)Other (12 20%)Total n = 60</td><td rowspan="1" colspan="1">ICPI with chemotherapy (8, 13%)PD-1 (49, 82%)PD-L1 (3, 5%)</td><td rowspan="1" colspan="1">pATB or cATB (2 weeks before or after ICPI initiation)(17, 28%)No ATB (43, 72%)</td><td rowspan="1" colspan="1">8–14 days</td><td rowspan="1" colspan="1">Beta-lactam (14, 82%)Quinolone (5, 29%)Vancomycin (7, 41%)Daptomycin (1, 6%)Linezolid (2, 12%)Meropenem (3, 18%)Tetracyclines (2, 12%)Bactrim (1, 6%)Azithromycin (1, 6%)Nitrofurantoin (1, 6%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">RR: 29.4% in exposed vs 62.8% in unexposed,p = 0.024</td><td rowspan="1" colspan="1">Decreased PFS with ATBHR 1.6; 95% CI: 0.84–3.03, p = 0.048Median OS:24 in exposed vs 89 months in unexposed p = 0.003</td><td rowspan="1" colspan="1">Narrow-spectrum ATB alone did not affect the RR, but broad-spectrum ATB decreased RR (p = 0.02) and PFS (p = 0.012).Multivariate analysis found that only ATB decreased RR (p = 0.0038) and PFS (p = 0.01)</td></tr><tr><td rowspan="1" colspan="1">Tinsley N et al. [14]</td><td rowspan="1" colspan="1">Melanoma (206, 66%)NSCLC (56, 18%)Renal (46, 15%)Total n = 303</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">pATB or cATB (2 weeks before or 6 weeks after ICPI initiation) (94,31%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">The commonest ATBs: beta-lactam and macrolides</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ATB vs no ATBPFS97 (95% CI 84–122) vs 178 days (95% CI 155–304) p = 0.049OS317 days (95% CI 221–584) vs 651 days (95% CI 477–998) p = 0.001.</td><td rowspan="1" colspan="1">Cumulative ATB (&gt;  10 days, multiple concurrent/successive courses) further shortened PFS to 87 days (95% CI 83–122) p = 0.0093 and OS to 193 days (95% CI 96–355) p = 0.00021pATB exposed had shorter PFS and OS than cATB exposed (HR 1.37, p = 0.29 and HR 1.72, p = 0.08)</td></tr><tr><td rowspan="1" colspan="1">Khan U et al. [15]</td><td rowspan="1" colspan="1">Lung (111, 46%)Bladder (36, 15%)Renal (35, 14%)GI (16, 7%)Other (44, 18%)Total n = 242</td><td rowspan="1" colspan="1">PD-1 (189, 78%)PD-L1 (52, 21%)</td><td rowspan="1" colspan="1">75, 46 and 32% received ATBs within 6 months, 60 days and 30 days of starting ICPIs</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">cATB use in the first 30- or 60-days of ICPI therapy associated with inferior ORR(OR 0.40, p = 0.01 and OR 0.42, p = 0.005, respectively)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">pATB or cATB use in the first 6 months of ICPI use had no impact</td></tr><tr><td rowspan="1" colspan="1">Routy B et al. [5]</td><td rowspan="1" colspan="1">NSCLC (140, 56%), RCC (67, 27%)urothelial carcinoma (42, 17%)Total n = 249</td><td rowspan="1" colspan="1">PD-1/PD-L1 (249, 100%)</td><td rowspan="1" colspan="1">pATB or cATB(2 months before or 1 month after ICPI initiation)(69, 28%)no ATB (180, 72%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">β-lactam+/− inhibitors, fluoroquinolonesor macrolides</td><td rowspan="1" colspan="1">Mostly oral</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ATB vs no ATBFor all groups combinedmedian PFS:3.5 vs 4.1 monthsp = 0.017median OS:11.5 vs 20.6 monthsp &lt; 0.001For individual cancer groups,PFS and/or OS were also shorter in ATB group</td><td rowspan="1" colspan="1">Univariate and multivariate Cox regression analyses confirmed the negative impact of ATB, independent from other factors</td></tr><tr><td rowspan="1" colspan="1">Mielgo-Rubio X et al. [16]</td><td rowspan="1" colspan="1">NSCLC (168)</td><td rowspan="1" colspan="1">PD-1 (168,100%)</td><td rowspan="1" colspan="1">pATB or cATB(2 months before or 1 month after ICPI initiation)(47.9%)No ATB(52.1%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">Oral (70%) IV (30%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ATB vs no ATBOS:8.1 (95%CI 3.6–12.5) vs 11.9 months (95%CI 9.1–14.7) p = 0.026PFS:5 (95%CI 3.1–6.9) vs 7.3 months (95%CI 2–12) p = 0.028</td><td rowspan="1" colspan="1">IV ATB had a more negative impact than oral ATBOS:2.9 (95%CI, 1.6–4.1) vs 14.2 months (95%CI, 7.9–20.6) p = 0.0001PFS:2.2 (95%CI 0.6–3.7) vs 5.9 months (95%CI 3.9–8) p = 0.001</td></tr><tr><td rowspan="1" colspan="1">Ouaknine J et al. [17]</td><td rowspan="1" colspan="1">NSCLC (72)</td><td rowspan="1" colspan="1">PD-1 (72,100%)</td><td rowspan="1" colspan="1">pATB or cATB (2 months before or 1 month after ICPI initiation)(30, 42%)No ATB (42, 58%)</td><td rowspan="1" colspan="1">Median duration 9.5 days (IQR 7–14)</td><td rowspan="1" colspan="1">The commonest ATBs:β-lactam and vancomycin</td><td rowspan="1" colspan="1">Mostly oral (65%)</td><td rowspan="1" colspan="1">ATB vs no pATBORR37% vs 24% p = 0.276 Clinical benefit rate 27% vs 29% p = 0.859</td><td rowspan="1" colspan="1">ATB vs no ATBmedian OS: 5.1  (IQR 3.4-not reached) vs 13.4 months (IQR 10.6-not reached) p = 0.03median PFS:2.8(IQR 1.4–5.1) vs 3.3 months (IQR 1.8–7.3) p = 0.249</td><td rowspan="1" colspan="1">–</td></tr><tr><td rowspan="1" colspan="1">Kaderbhai C et al. [18]</td><td rowspan="1" colspan="1">NSCLC (74)</td><td rowspan="1" colspan="1">PD-1 (74, 100%)</td><td rowspan="1" colspan="1">pATB(within 3 months) (15, 20%)No ATB(59, 80%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">No difference in ORRp = 0.75</td><td rowspan="1" colspan="1">No difference in PFS and p = 0.72,</td><td rowspan="1" colspan="1">–</td></tr><tr><td rowspan="1" colspan="1">Zhao S et al. [19]</td><td rowspan="1" colspan="1">NSCLC (109)</td><td rowspan="1" colspan="1">PD-1 (57, 52%)PD-1/ chemotherapy (33, 30%)PD-1/apatinib or bevacizumab (19, 18%)</td><td rowspan="1" colspan="1">pATB or cATB (1 month before or after ICPI initiation) (20, 18%)No ATB (89, 82%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">The commonest ATBs:β-lactam inhibitors and fluoroquinolones</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">Higher PD rates in ATB-treated group (p = 0.092)</td><td rowspan="1" colspan="1">ATB decreased PFS, p &lt; 0.0001and OS, p = 0.0021</td><td rowspan="1" colspan="1">In multivariable analysis, ATB was associated with shorter PFS (HR = 0.29, 95%CI 0.15–0.56, p &lt; 0.0001) and OS (HR = 0.35, 95%CI 0.16–0.77, p = 0.009)</td></tr><tr><td rowspan="1" colspan="1">Thompson et al. [20]</td><td rowspan="1" colspan="1">NSCLC (74)</td><td rowspan="1" colspan="1">PD-1 (74, 100%)</td><td rowspan="1" colspan="1">pATB (within 6 weeks) (18, 24%)No ATB (56, 76%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">Mostly fluoroquinolones (50%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ORR in ATB vs no ATB groups25% vs 23% (adjusted OR 1.2, p = 0.20).</td><td rowspan="1" colspan="1">ATB vs no ATBPFS2.0 vs 3.8 monthsp &lt; 0.001)OS4.0 vs 12.6 months, p = 0.005</td><td rowspan="1" colspan="1">The impact of ATB on PFS and OS was independent of other factors (HR 2.5, p = 0.02), (HR 3.5, p = 0.004), respectively</td></tr><tr><td rowspan="1" colspan="1">Derosa L et al. [21]</td><td rowspan="1" colspan="1">RCC (80)</td><td rowspan="1" colspan="1">PD1/PD-L1 (67, 84%),PD-1/CTLA-4 (10, 12%)PD-L1/ bevacizumab (3, 4%)</td><td rowspan="1" colspan="1">pATB(within 1 month)(16, 20%)No ATB (64, 80%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">Mostly β-lactam and fluoroquinolones</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">Lower ORR in ATB group vs no ATB p &lt; 0.002</td><td rowspan="1" colspan="1">ATB vs no ATBPFS2.3 vs. 8.1 months, p &lt; 0.001</td><td rowspan="1" colspan="1">Confirmed by multivariate analysis</td></tr><tr><td rowspan="1" colspan="1">Do TP et al. [22]</td><td rowspan="1" colspan="1">Lung (109)</td><td rowspan="1" colspan="1">PD-1 (109, 100%)</td><td rowspan="1" colspan="1">pATB or cATB(1 month before ICPI or concurrently)(87, 80%)No ATB (22, 20%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">β-lactam(12, 13.8%) quinolones(11,12.6%)other(7, 8.1%) multiple antibiotics(57, 65.5%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ATB vs no ATBOS5.4 vs 17.2 months(HR 0.29, 95% CI 0.15–0.58 p = 0.0004)</td><td rowspan="1" colspan="1"/></tr><tr><td rowspan="1" colspan="1">Elkrief A et al. [23]</td><td rowspan="1" colspan="1">Melanoma (74)</td><td rowspan="1" colspan="1">PD-1 (54, 73%)CTLA-4 (5, 6.8%)CTLA-4/ carboplatin/paclitaxel (15, 20%)</td><td rowspan="1" colspan="1">pATB(within 1 month)(10, 13.5%)No ATB(64, 86.5%)</td><td rowspan="1" colspan="1">&gt; 7 days (7, 70%)&lt; 7 days (3, 30%)</td><td rowspan="1" colspan="1">Mostly β-lactams± inhibitors</td><td rowspan="1" colspan="1">Oral (40%)IV (60%)</td><td rowspan="1" colspan="1">ORRATB vs no ATB0% vs 34%</td><td rowspan="1" colspan="1">ATB vs no ATBmedian PFS2.4 vs 7.3 months(HR 0.28, 95% CI 0.10–0.76p = 0.01)median OS10.7 vs 18.3 months(HR: 0.52, 95% CI 0.21–1.32p = 0.17).</td><td rowspan="1" colspan="1">The multivariate analysis supported the impact of ATB on PFS(HR 0.32 (0.13–0.83) 95% CI, p = 0.02).</td></tr><tr><td rowspan="1" colspan="1">Huemer F et al. [24]</td><td rowspan="1" colspan="1">NSCLC (30)</td><td rowspan="1" colspan="1">PD-1 (30, 100%)</td><td rowspan="1" colspan="1">pATB or cATB(1 month before or 1 month after ICPI initiation)(11, 37%)No ATB(19, 63%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">β-lactam (7, 64%), fluoroquinolones (4, 36%) and carbapenems (2, 18%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ATB vs no ATBmedian PFS3.1 vs 2.9 months, (HR = 0.46 95%CI: 0.12–0.90 p = 0.031). median OS 15.1 vs 7.5 months (HR = 0.31 95%CI: 0.02–0.78 p = 0.026).</td><td rowspan="1" colspan="1">The multivariate analysis supported the impact of ATB on PFS (p = 0.028) and OS (p = 0.026).</td></tr><tr><td rowspan="1" colspan="1">Lalani A et al. [25]</td><td rowspan="1" colspan="1">RCC (146)</td><td rowspan="1" colspan="1">PD-1/PD-L1 (146, 100%)</td><td rowspan="1" colspan="1">pATB or cATB(2 months before or 1 month after ICPI initiation) (31, 21%)No ATB(115, 79%)</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">–</td><td rowspan="1" colspan="1">ATB vs no ATBORR12.9 vs 34.8%p = 0.026</td><td rowspan="1" colspan="1">ATB vs no ATB2.6 (1.7–5.3) vs8.1 (5.6–10.9) monthsp = 0.008</td><td rowspan="1" colspan="1">–</td></tr></tbody></table><table-wrap-foot><p>Abbreviations: <italic toggle="yes">EIOP</italic> (Early Immunotherapy Period): antibiotics given between 1 month before and 3 months after starting immunotherapy, <italic toggle="yes">WIOP</italic> (Whole immunotherapy Period): antibiotics given throughout immunotherapy, cumulative exposure to antibiotics; AIER defined as “days of antibiotic therapy/days of immunotherapy’: AIER stratified over the median (4.2%) into high and low AIER groups, <italic toggle="yes">RR</italic> Response rate, <italic toggle="yes">DCR</italic> Disease control rate, <italic toggle="yes">GI</italic> Gastrointestinal, <italic toggle="yes">ORR</italic> Overall response rate, <italic toggle="yes">IV</italic> Intravenous, <italic toggle="yes">IM</italic> Intramuscular</p></table-wrap-foot></table-wrap>
</p><p id="Par33">Most of the studies highlighting the importance of a healthy gut microbial environment as a pre-requisite for ICPI response were unfortunately characterised by insufficient data on preceding or concomitant antibiotic exposure, making it impossible to disentangle the role of antibiotic-induced perturbation of the gut ecosystem in influencing clinically meaningful outcomes in these patients [<xref ref-type="bibr" rid="CR3">3</xref>].</p><p id="Par34">Mechanistically, the breadth and depth of downstream effects produced by antibiotics within the cancer-immune synapse are an important challenge in studying this prognostically adverse relationship. On one hand, the direct bacteriostatic/bactericidal effect of antibiotics can cause selective pressure within the host microbial ecosystem and instigate an alternative microbiota state characterised, amongst other traits, by downregulation of major histocompatibility complex (MHC) class I/II genes and impaired effector T-cell responses, immunologic traits implicated in reduced responsiveness to ICPI [<xref ref-type="bibr" rid="CR28">28</xref>].</p><p id="Par35">ATB-induced depletion of gut bacteria can also shift the repertoire of microbial-associated molecular patterns (MAMPS). These molecules signal through mucosal innate immune cells primarily via toll-like receptors (TLRs) and NOD1 [<xref ref-type="bibr" rid="CR29">29</xref>] to influence neutrophil priming, reduce local cytokine release and prime adaptive immunity by influencing the expression of MHC genes within the intestinal mucosa and reduce immunoglobulin secretion [<xref ref-type="bibr" rid="CR30">30</xref>]. Antibiotic treatment impairs TH<sub>1</sub>/TH<sub>17</sub> responses in tumour-bearing mice through direct pre-conditioning of the gut microbiota, reducing the efficacy of cyclophosphamide-mediate immune-rejection of the tumour [<xref ref-type="bibr" rid="CR31">31</xref>]. In addition, antibiotics can also reduce the capacity of adoptively transferred CD8+ T-cells to mediate a tumour-specific response through altered LPS/TLR4 signaling in lymphodepleted mice [<xref ref-type="bibr" rid="CR32">32</xref>].</p><p id="Par36">By disrupting the gut ecosystem, antibiotics instigate downstream metabolic alterations within the microenvironment with complex repercussions to the tumour-host-microbe interface. Amongst them, changes in the availability of short-chain fatty acids produced by <italic toggle="yes">Akkermansia, Faecalibacteria</italic> and <italic toggle="yes">Enterococcus</italic> from the catabolism of non-digestible carbohydrates and the conversion of primary bile acids to secondary bile acids (including deoxycholate) mediated by <italic toggle="yes">Clostridiales</italic> can significantly alter gut homeostasis and lead to profound and clinically meaningful immune-modulatory consequences [<xref ref-type="bibr" rid="CR33">33</xref>]. The immune-metabolic repercussions secondary to gut dysbiosis, potentially reversible by oral <italic toggle="yes">Akkermansia</italic> supplementation [<xref ref-type="bibr" rid="CR34">34</xref>], might explain the influence of body mass index in determining response to ICPI [<xref ref-type="bibr" rid="CR35">35</xref>, <xref ref-type="bibr" rid="CR36">36</xref>].</p><p id="Par37">With improved characterization of immune-microbiologic underpinning of the relationship between antibiotics and ICPI outcome, a key question now is whether disruption of a well-equilibrated gut bacterial ecosystem is truly causal in this relationship, and thus whether reversal of antibiotic-mediated gut dysbiosis might prove beneficial in restoring full sensitivity to ICPI. Whether a favourable gut microbiota is a reflection of an otherwise healthy host rather than the <italic toggle="yes">primum movens</italic> of clinically meaningful anti-cancer immune responses is still the subject of intense debate [<xref ref-type="bibr" rid="CR13">13</xref>]. To this end, appreciating how antibiotics might dynamically affect such a strong immune-microbiologic correlate of response to checkpoint inhibition is of key importance to pave the way for strategies that could restore or protect the integrity of this important phenotypic correlate of response. To address the multiplicity of mechanisms that are likely to underscore this complex and bi-directional relationship, the coordinated study of a number of fundamental pathophysiologic processes including bacterial translocation, immune-modulation, an altered metabolome, enzymatic degradation and reduced diversity of the gut microbiome has been proposed as an overarching framework [<xref ref-type="bibr" rid="CR37">37</xref>].</p><p id="Par38">Gaining sufficient insight as to the mode of action by which bacteria might work as biotherapeutic agents is not just important for patient prognostication, but is in fact key to a successful, rational development of microbiome-modulating therapies which improve patient’s outcome with ICPI. With antibiotic use now having been validated as an important and dynamic factor influencing outcome from immunotherapy, concerted efforts should be aimed at characterizing the candidate taxonomic features in the gut microbiota that are associated with worse outcome from ICPI in the context of preceding and concomitant antibiotic exposure and evaluate them in conjunction with the concomitant prescription of proton pump inhibitors, corticosteroids and vaccines, all of which have been postulated to influence ICPI response [<xref ref-type="bibr" rid="CR38">38</xref>].</p><p id="Par39">Recognising these changes is expected to facilitate the clinical development of diverse biotherapeutic approaches to induce microbiome reprogramming including dietary interventions with pre-biotics, therapeutic administration of single or multiple types of bacterial species or their metabolites, selective antibiotic therapy or faecal microbial transplantation, all of which are currently at the focus of intense clinical research efforts [<xref ref-type="bibr" rid="CR26">26</xref>].</p></sec></body><back><sec><title>Funding</title><p>DJP, RJB, BHM, JRM, DMA have received direct project funding by the NIHR Imperial Biomedical Research Centre (BRC), ITMAT Push for Impact Grant Scheme 2019. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.</p></sec><ack><p>The authors would like to acknowledge the Imperial College National Institute for Health Research Biomedical Research Centre and Imperial Cancer Research UK centre for infrastructural and grant funding support. DJP is supported by grant funding from the Wellcome Trust Strategic Fund (PS3416). BHM is the recipient of a Medical Research Council (MRC) Clinical Research Training Fellowship (grant MR/R000875/1).</p></ack><notes notes-type="author-contribution"><title>Authors’ contributions</title><p>DJP, DG, DMA, RJB, BHM, JRM and MB contributed to the writing and editing of this manuscript. All authors read and approved the final version of the manuscript.</p></notes><notes notes-type="data-availability"><title>Availability of data and materials</title><p>n/a.</p></notes><notes notes-type="ethics"><sec id="FPar1"><title>Ethics approval and consent to participate</title><p id="Par40">n/a.</p></sec><sec id="FPar2"><title>Consent for publication</title><p id="Par41">n/a.</p></sec><sec id="FPar3"><title>Competing interests</title><p id="Par42">Dr. Pinato reports receiving grant funding in support of clinical trials from Merck Sharpe and Dohme and Bristol Myers Squibb and having received speaker/consultancy fees from ViiV Healthcare, Bayer and MiNa therapeutics outside the submitted work. There are no other conflicts of interest to report.</p></sec></notes><ref-list id="Bib1"><title>References</title><ref id="CR1"><label>1.</label><mixed-citation publication-type="journal" xlink:type="simple">
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