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The aging microbiome and response to immunotherapy: Considerations for the treatment of older adults with cancer

  • Daniel Spakowicz
    Correspondence
    Corresponding author at: Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA.
    Affiliations
    Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA

    Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA
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  • Amna Bibi
    Affiliations
    Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA
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  • Mitchell Muniak
    Affiliations
    Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA
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  • Nyelia F. Williams
    Affiliations
    Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA
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  • Rebecca Hoyd
    Affiliations
    Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA
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  • Carolyn J. Presley
    Affiliations
    Division of Medical Oncology, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center-James, Columbus, OH, USA
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Open AccessPublished:February 18, 2021DOI:https://doi.org/10.1016/j.jgo.2021.02.001

      Keywords

      Abbreviations:

      ICI (Immune Checkpoint Inhibitor), R (responder to immune checkpoint inhibitor), NR (non-responder to immune checkpoint inhibitor), FMT (Fecal microbiota transplantation)

      1. Introduction

      The gut microbiome affects many aspects of human health including aging and cancer. Recent evidence has demonstrated a causal relationship between the microbes in the gut and response to cancer treatment with immune checkpoint inhibitors (ICIs) [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ,
      • Baruch E.N.
      • et al.
      Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients.
      ,
      • Tanoue T.
      • et al.
      A defined commensal consortium elicits CD8 T cells and anti-cancer immunity.
      ,
      • Mager L.F.
      • et al.
      Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy.
      ]. Individuals whose cancers respond to ICIs can be distinguished from those who do not solely by the composition of their gut microbes at the start of treatment [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ,
      • Gopalakrishnan V.
      • et al.
      Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients.
      ,
      • Matson V.
      • et al.
      The commensal microbiome is associated with anti–PD-1 efficacy in metastatic melanoma patients.
      ]. Provocatively, preclinical models supplemented with a single microbial strain or microbially-derived metabolite can modify response to treatment [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ,
      • Tanoue T.
      • et al.
      A defined commensal consortium elicits CD8 T cells and anti-cancer immunity.
      ,
      • Mager L.F.
      • et al.
      Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy.
      ]. The microbiome therefore represents both a biomarker and therapeutic target for modifying and improving cancer care. As is often the case with emerging treatments, older adults are not strongly represented in the clinical trials leading to treatment approval [
      • Singh H.
      • Beaver J.A.
      • Kim G.
      • Pazdur R.
      Enrollment of older adults on oncology trials: an FDA perspective.
      ]. Meanwhile, there are well-documented shifts in the microbiome as one ages [
      • Claesson M.J.
      • et al.
      Composition, variability, and temporal stability of the intestinal microbiota of the elderly.
      ]. Age is important to consider as we seek to modify the microbiome to promote treatment response. In this perspective, we summarize findings across aging and immunotherapy studies to relate the microbes found in each. We demonstrate that age-related changes tend to shift the microbiome toward a non-responder-like composition, lacking microbes demonstrated to support treatment response, which may contribute to the decreased efficacy for older adults [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ]. We review the potential mechanisms by which these effects occur and posit a model to interpret the broad-level changes observed. Finally, we discuss trials currently underway to target this novel treatment modality in the understudied and growing older adult population.

      1.1 The Microbiome Changes with Age

      In 2007, The elderly gut metagenomics (ELDERMET) study in Ireland was the first major trial to focus on the microbiome of older adults and recruited 400 participants aged 65 years old and older. Since then, similar studies have been performed in older adult populations from other European countries as well as China and Japan [
      • Claesson M.J.
      • et al.
      Composition, variability, and temporal stability of the intestinal microbiota of the elderly.
      ,
      • Mueller S.
      • et al.
      Differences in fecal microbiota in different European study populations in relation to age, gender, and country: a cross-sectional study.
      ]. Each study found differences between younger and older adults, but a universal older adult microbiome was not observed across the geographically-distinct populations. For example, the ELDERMET study found increased relative abundance of Alistipes and Oscillibacter and decreased Prevotella and Ruminococcus [
      • Claesson M.J.
      • et al.
      Gut microbiota composition correlates with diet and health in the elderly.
      ]. In Japan Firmicutes, Bacteroidetes and Proteobacteria were enriched [
      • Claesson M.J.
      • et al.
      Composition, variability, and temporal stability of the intestinal microbiota of the elderly.
      ]. Most consistently, the genus Bifidobacterium is decreased, which is notable as being the microbe most enriched in infants via the pre-biotic effects of breast milk. Bifidobacterium has been associated with health in a variety of settings, including response to immunotherapy [
      • Lawson M.A.E.
      • et al.
      Breast milk-derived human milk oligosaccharides promote Bifidobacterium interactions within a single ecosystem.
      ,
      • Schell M.A.
      • et al.
      The genome sequence of Bifidobacterium longum reflects its adaptation to the human gastrointestinal tract.
      ,
      • Favier C.F.
      • Vaughan E.E.
      • De Vos W.M.
      • Akkermans A.D.L.
      Molecular monitoring of succession of bacterial communities in human neonates.
      ,
      • Harmsen H.J.M.
      • et al.
      Analysis of intestinal Flora development in breast-fed and formula-fed infants by using molecular identification and detection methods.
      ].
      While Bifidobacterium is most consistently depleted in older adults, the diverse phylum Proteobacteria are consistently enriched. The Proteobacteria are more abundant in the environment than in the healthy gut, and a relatively high abundance (e.g. > ~ 10%) is associated with diverse diseases [
      • Shin N.-R.
      • Whon T.W.
      • Bae J.-W.
      Proteobacteria: microbial signature of dysbiosis in gut microbiota.
      ]. This has led to the speculation that a healthy gut is characterized by its ability to defend against constant incursions by Proteobacteria coming in from the environment.
      Increased Proteobacteria in older adults could be driven by several age-related changes including (1) reduced efficacy of the immune system, (2) a lower fiber diet, and (3) decreased gut barrier function. This results in a more aerobic gut, more frequent blooms of organisms encountered in the environment (i.e. decreased microbiome stability), increased bacterial translocation across the gut barrier, and, chronic inflammation (Fig. 1). These may be causally connected via a feedback loop, whereby each aspect can exacerbate chronic inflammation.
      Fig. 1
      Fig. 1Summary of age-related effects on response to immunotherapy via the microbiome. Lifestyle factors (e.g. diet, exercise, medications) affect the gut microbiota and particularly the fraction of Proteobacteria. This enters a cycle by which the microbes affect gut leakiness and systemic inflammation and thereby a variety of age-related illnesses, which then also affect the microbiome. Related diseases include cancer and particularly treatments that involve the immune system. Created with BioRender.com
      A consistent feature across longitudinal studies of the microbiomes of older adults is higher intra-individual variability in older adults relative to younger. That is, the strains of microbes shift rapidly over time; in the context of common clustering approaches (e.g. principle components analysis) which demonstrates larger distances between points. The ELDERMET Study proposed diet to be the causal driver; individuals living in the community tended to have microbiomes more like healthy young controls, whereas individuals living in long-term care facilities showed reduced diversity and higher variability. Long term care was associated with lower-fiber diets, and the change in diet preceded a shift in the microbiome by roughly one year.
      Regardless of the cause, the shift in microbiomes with age is a pressing concern when considering that age is a dominant risk factor for cancer and the microbiome plays a role in whether individuals will respond to ICIs. In many cancers ICIs are, or are predicted to soon be, the first-line treatment, making the link between the aging microbiome and ICI response a more pressing issue for more patients.

      2. The Microbiome and Response to Immune Checkpoint Inhibitors

      Several recent papers have suggested a critical role for the microbiome in response to ICIs. The first indications included retrospective analyses of patients who received microbiome-disrupting medications before the start of ICI treatment or shortly after [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ,
      • Spakowicz D.
      • et al.
      Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications.
      ,
      • Wilson B.E.
      • Routy B.
      • Nagrial A.
      • Chin V.T.
      The effect of antibiotics on clinical outcomes in immune-checkpoint blockade: a systematic review and meta-analysis of observational studies.
      ]. Patients who received antibiotics showed shorter overall survival across many cancers when controlling for covariates that might represent differences between the retrospective cohorts, including the Charlson Comorbidity Index [
      • Spakowicz D.
      • et al.
      Inferring the role of the microbiome on survival in patients treated with immune checkpoint inhibitors: causal modeling, timing, and classes of concomitant medications.
      ,
      • Hoyd Rebecca
      • Muniak Mitchell
      • Spakowicz Dan
      spakowiczlab/co-med-io.
      ]. Prospective studies and systematic reviews have confirmed these findings [
      • Pinato D.J.
      • et al.
      association of prior antibiotic treatment with survival and response to immune checkpoint inhibitor therapy in patients with cancer.
      ].
      Direct measurements of the microbiome in patients receiving ICIs confirmed this epidemiological observation. Several groups demonstrated that the microbiomes of patients at the start of ICI treatment are distinct between patients who respond (R) and do not respond (NR) [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ,
      • Gopalakrishnan V.
      • et al.
      Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients.
      ,
      • Matson V.
      • et al.
      The commensal microbiome is associated with anti–PD-1 efficacy in metastatic melanoma patients.
      ]. Moreover, the R phenotype could be transferred to mouse models using the patients' stool [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ]. Mice inoculated with a sarcoma cell line and treated with ICIs showed reduced tumor size when given a fecal transplant with human R stool relative to NR stool. This suggests that the microbiome may be a biomarker for predicting response to ICIs.
      In addition to a biomarker, the microbiome may be a therapeutic target. In preclinical studies, NR mice could be switched to an R state by supplementation with a single microbe that was enriched in the R microbiome: A. muciniphila. Similar findings have been reported when another microbe, an unnamed strain in the genus Ruminococcus, is enriched by feeding mice a pre-biotic [
      • Messaoudene M.
      • et al.
      Abstract 5730: a new polyphenol prebiotic isolated from Myrciaria dubia improves gut microbiota composition and increases anti-PD-1 efficacy in murine cancer models.
      ]. Later work showed a similar increase in response to ICIs by giving a community of 11 microbes, lacking A. muciniphila but containing an unnamed strain in the Ruminococcus family [
      • Tanoue T.
      • et al.
      A defined commensal consortium elicits CD8 T cells and anti-cancer immunity.
      ]. Finally, response to ICIs was increased by mono-colonization with a strain of Bifidobacterium, and by a molecule produced by the microbe, inosine. This demonstrates that response to ICIs could be modified by enrichment of one or a few microbes, and possibly by supplementation with small molecules such as inosine.
      A consensus set of organisms that are most important, and for whom, has not been defined. A. muciniphila associated with R-patients in only one study [
      • Routy B.
      • et al.
      Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors.
      ]. Matson et al found enrichment of Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium [
      • Matson V.
      • et al.
      The commensal microbiome is associated with anti–PD-1 efficacy in metastatic melanoma patients.
      ]. Gopalakrishnan et al found that response correlated with higher alpha diversity and bacteria in the Ruminococcaceae family (which does not contain A. muciniphlia, nor any of the microbes found by Matson et al) [
      • Gopalakrishnan V.
      • et al.
      Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients.
      ]. Chaput et al found enrichment of Faecalibacterium prausnitzii and Gemmiger formicilis [
      • Chaput N.
      • et al.
      Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab.
      ]. Potential sources of this variation could include geographic differences in the microbiomes of patients, and convergent evolution in terms of ecological roles of the microbes or the molecules they produce, or age differences in the cohorts of each study.
      There is a clear role for the microbiome in ICI response, leading to great hope for using it as a therapeutic target. However, more work is needed to define the microbes associated with the R and NR states and especially how best to modify them. It is prudent to use knowledge about healthy microbiomes to estimate which populations are likely to require microbiome modification.

      3. Relating the Microbes Associated with Response to ICIs and Age

      Many of the microbes that have been shown to change with age have been implicated in response to ICIs. Three of the microbes that have been shown to improve response to ICIs in preclinical models (Akkermansia [
      • Messaoudene M.
      • et al.
      Abstract 5730: a new polyphenol prebiotic isolated from Myrciaria dubia improves gut microbiota composition and increases anti-PD-1 efficacy in murine cancer models.
      ], Bifidobacterium [
      • Mager L.F.
      • et al.
      Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy.
      ], Ruminococcus [
      • Messaoudene M.
      • et al.
      Abstract 5730: a new polyphenol prebiotic isolated from Myrciaria dubia improves gut microbiota composition and increases anti-PD-1 efficacy in murine cancer models.
      ]), are depleted in older adults (Fig. 2). In addition, several microbes enriched in non-responders to ICIs are also enriched in older adults. This includes the Proteobacteria like Escherichia, but also several members of the Bacteroidetes phylum. A single genus enriched in NR have been associated with younger adults (Fig. 2).
      Fig. 2
      Fig. 2The gut microbes associated with aging and response to immune checkpoint inhibitors. NR = non-responders, R = responders, U/M = unknown/mixed results, Y = young, O = old.
      However, the current picture is somewhat mixed. Several genera associated with response have been shown to be enriched older adults (Faecalibacterium, Enterococcus, Alistipes) (Fig. 2). Faecalibacterium, in particular, has been broadly associated with gut health and is marketed as a probiotic. While these microbes have not shown a causal relationship with response, such as for A. muciniphila described above, the possiblity remains that they will do so, perhaps in a way that is specific to older-adults Finally, the largest fraction of the genera associated with treatment response have either unknown or mixed associations with age, further highlighting the need for more study.

      4. Underrepresentation of Older Adults in Cancer and Microbiome Studies

      The median age of a patient diagnosed with lung cancer is 70 years, and that statistic continues to rise [
      • Siegel R.L.
      • Miller K.D.
      • Jemal A.
      Cancer statistics, 2019.
      ,
      • Smith B.D.
      • Smith G.L.
      • Hurria A.
      • Hortobagyi G.N.
      • Buchholz T.A.
      Future of cancer incidence in the United States: burdens upon an aging, changing nation.
      ]. As overall tolerance for ICIs is generally better than for chemotherapy [
      • Schell M.A.
      • et al.
      The genome sequence of Bifidobacterium longum reflects its adaptation to the human gastrointestinal tract.
      ], the risk-benefit balance of ICIs may be especially profitable in older patients. However, patients enrolled in clinical trials generally tend to be younger than those treated in clinical practice [
      • Favier C.F.
      • Vaughan E.E.
      • De Vos W.M.
      • Akkermans A.D.L.
      Molecular monitoring of succession of bacterial communities in human neonates.
      ], possibly due to selection criteria that excludes based on performance status or the presence of comorbidities. Over the past two decades, <10% of older adults age 75+ years are included in cancer clinical trials and this value has remained static [
      • Singh H.
      • Beaver J.A.
      • Kim G.
      • Pazdur R.
      Enrollment of older adults on oncology trials: an FDA perspective.
      ,
      • Liu J.
      • et al.
      Strategies to improve participation of older adults in cancer research.
      ]. The median age of a cancer diagnosis is higher than the median age of studies reporting on the association between the microbiome and response to ICIs and of trials that seek to modify the microbiome to improve cancer outcomes. As of August 2020, we found 31 trials that expressly intended to modify the microbiome to affect cancer outcomes. Four of these (13%) chose an age range to focus on older adults (Table 1).
      Table 1Clinical trials to modify cancer outcomes via the microbiome.
      NCT#AgeDescriptionLocationInvestigatorStatusLength
      NCT0426787455–77

      Black raspberry diet intervention for MB modification & LC preventionOSUCCCD. SpakowiczR10/19-

      12/22
      NCT0422938160+

      Physical therapy & stress intervention to improve resiliency in LC patientsOSUCCCC. PresleyR1/20-

      12/21
      NCT0279173760+

      Exercise intervention to improve physical activity in cancer patientsOSUCCCA. RoskoN7/16-

      12/20
      NCT0368620218+

      Assess efficacy of microbial ecosystem therapeutics in altering IO responsePrincess Margaret CCL. Siu

      A. Spreafico
      N11/18-

      12/23
      NCT038919791.5-100

      Assess change in immune activation following antibiotics & IONYU LangoneD. CohenS6/19-

      5/21
      NCT0377289919+

      Assess if combination FMT & IO can enhance antitumor effects in melanomaLRCPJ. LenehanR3/19-

      12/23
      NCT0381712518+

      Assess efficacy of oral MB intervention paired with IO in melanomaParker Institute (& others)R. Ibrahim (& others)R1/19-

      2/22
      NCT0416328918+

      Assess efficacy of FMT combination treatment in reducing immune-toxicitiesLRCPR. Fernandes

      S. Maleki
      R1/20-

      11/28
      NCT04056026AllEnhance the MB via FMT to improve the efficacy IOProgenaBiomeProgena

      Biome
      C9/18-

      12/18
      NCT0413076318-70

      Assess if FMT capsules improve IO responseBeijing Cancer HospitalL. ShenR12/19-

      10/20
      NCT0411677518+

      Assess FMT from responders to IO into non-responder PCA patientsVA Portland Health Care SystemJ. N GraffR10/19-

      10/23
      NCT0381929618+

      FMT for medication-induced GI complications in melanoma, GUMD Anderson CCY. WangX2/20-

      7/22
      NCT0335340218+

      Assess FMT from IO responders to non-responder melanoma patientsSheba MCG. MarkelR11/17-

      12/21
      NCT0334114318+

      Assess if FMT improves the body's ability to fight melanomaUPMC Hillman CCD. DavarS1/18-

      10/20
      NCT0284342530+

      Assess if beans can increase MB health & reduce obesity-related cancer risksMD Anderson CCC. Daniel-MacDougallN7/16-

      7/25
      NCT0192912218+

      Assess effects of bean powder or rice bran on the MB of CRC survivorsColorado State UniversityE. P RyanC8/10-

      12/14
      NCT0407927018+

      Assess effect of diet intervention on breast cancer outcomes & biomarkersSheba MCE. Gal-YamR7/19-

      12/25
      NCT0378242818+

      Assess the role of probiotics in reducing CRC related inflammatory markersNational University of MalaysiaR. Affendi

      R. Ali
      C8/16-

      11/18
      NCT0366104718+

      Assess effects of omega-3 oil on tumor immune microenvironment in CCRMassachusetts General HospitalM. SongR11/19-

      9/23
      NCT0378177818+

      Assess effect of resistant starch on inflammation & MB in CCR survivorsFred Hutch/UW Cancer ConsortiumM. NeuhouserS5/19-

      9/20
      NCT0344800318 +

      Assess if comprehensive lifestyle changes can prevent breast cancerMD Anderson CCL. CohenR4/19-

      9/22
      NCT0335851118 +

      Assess effect of probiotics on breast cancer immune responseMayo ClinicS. ChumsriC10/17-

      5/20
      NCT0302883140-65

      Fiber intervention of native Alaskan diet for MB modification & CRC reductionAK Native Tribal Health ConsortiumG. RiscutaR12/17-

      1/22
      NCT03290651AllProbiotic intervention for displacement of cancer related inflammatory bacteriaSt. Joseph's Health CareG. Reid

      M. Brackstone
      R7/19-

      12/21
      NCT0385392818 +

      Assess if MB intervention in patients with cirrhosis alters incidence of HCCAustral University (sponsor)F. PiñeroX5/19-

      5/23
      NCT0326865550-75

      Assess if ginger can create an anti-inflammatory, CRC-protective MBMayo Clinic CC

      (& others)
      A. PrizmentC11/18-

      6/20
      NCT0393482718+

      Assess efficacy of BT MRx0518 as an immunomodulating agent in tumorsImperial College London NHS TrustJ. KrellR4/19-

      2/22
      NCT0363780318+

      Assess efficacy of BT MRx0518 paired with IO in tumor patientsM.D. Anderson CCS. PantR1/19– 3/24
      NCT0335340218+

      Assess FMT from IO responders to non-responder cancer patientsSheba MCG. MarkelR11/17– 4/19
      NCT0377585018+

      A Study of EDP1503 in Patients With Colorectal Cancer, Breast Cancer, and Checkpoint Inhibitor Relapsed TumorsHighlands Oncology Group (& others)J. BendellR12/18– 12/20
      NCT0359568318+

      Pembrolizumab and EDP1503 in Advanced MelanomaUniversity of Chicago MCJ. LukeN10/18– 11/23
      Abbreviations: OSUCCC = Ohio State University Comprehensive Cancer Center; CC = Cancer center; MC = Medical center; LRCP = London Regional Cancer Program; R = Recruiting; S = Suspended; N = Active not recruiting; C = Completed; X = Not yet recruiting; FMT = Fecal microbiota transplantation; IO = Immuno-oncology or immunotherapy; CRC = Colorectal cancer; HCC = Hepatocellular carcinoma; PCA = Prostate cancer; MB = Microbiome; LC = Lung cancer; BT = Biotherapeutic.
      There are several methods proposed to modify the microbiome including probiotic supplementation (35%), fecal microbiota transplantation (FMT) (25%) and interventions for the diet (26%) and lifestyle (10%). Each has potential benefits and pitfalls with regards to their safety, suspected efficacy, and speed of modification. FMTs have the strongest track record through successful clinical trials in the context of treatment for recurrent Clostridiodes difficile infections. However, they are challenged by demonstrating donor material is safe; on June 15, 2019, the FDA issued a safety alert requiring additional testing for clinical trials using FMT following a patient death [
      • Commissioner, O. of the. FDA
      In Brief: FDA warns about potential risk of serious infections caused by multi-drug resistant organisms related to the investigational use of Fecal Microbiota for Transplantation.
      ]. Probiotics hold promise as most closely mirroring the experiments in which murine models were made to start responding to ICIs. However, probiotic supplementation has recently been shown to decrease gut diversity which has had negative effects on health such as increasing recovery time after antibiotic treatment [
      • Suez J.
      • et al.
      Post-antibiotic gut mucosal microbiome reconstitution is impaired by probiotics and improved by autologous FMT.
      ,
      • Zmora N.
      • et al.
      Personalized gut mucosal colonization resistance to empiric probiotics is associated with unique host and microbiome features.
      ]. Studies on response to ICIs found that the diversity of the gut microbiome, in addition to particular microbes such as A. muciniphila, was important for response [
      • Gopalakrishnan V.
      • et al.
      Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients.
      ], though more recently a small consortium or even mono-colonization with Bifidobacterium was shown to modify response in murine models [
      • Tanoue T.
      • et al.
      A defined commensal consortium elicits CD8 T cells and anti-cancer immunity.
      ,
      • Mager L.F.
      • et al.
      Microbiome-derived inosine modulates response to checkpoint inhibitor immunotherapy.
      ]. Further study is needed to determine if probiotic supplementation can improve response or decreases diversity in a way that is detrimental to cancer outcomes. Diet-based interventions may also modify response through enriching for certain microbes, though this has not yet been demonstrated in humans [
      • Messaoudene M.
      • et al.
      Abstract 5730: a new polyphenol prebiotic isolated from Myrciaria dubia improves gut microbiota composition and increases anti-PD-1 efficacy in murine cancer models.
      ]. Rational manipulation of the microbiome with diet has been complicated, with the same foods eliciting different responses in the microbiome, presumably based on the starting condition of the microbiome. Other longitudinal studies with dietary interventions have shown relatively minor changes, where individuals' microbiomes clustered more closely with themselves at other time points than other individuals. Which method, or combination of methods, will effectively change a person's microbiome to promote response to ICIs at a clinically relevant timescale may be highly individualized.

      5. Conclusion

      The microbiome is a promising way to monitor and modify the state of the immune system. Applying this to older adults is complicated by many factors, including age-related changes to the microbiome. Studies focused on older adults are needed to tailor interventions to this large and rapidly growing demographic with cancer.
      The following are the supplementary data related to this article.

      Reproducibility Statement

      Code to generate Fig. 2 from Supplementary Table 1 and the fraction of trials in each clinical trial type from Table 1 are available at github.io/spakowiczlab/mageio.

      Declaration of Competing Interest

      The authors declare no conflicts of interest.

      Acknowledgements

      This work was supported by a Ohio State University Comprehensive Cancer Center Pelotonia Young Investigator Award (D.S.), a Lung Cancer Foundation of America & Bristol-Meyers Squibb Foundation & International Lung Cancer Foundation Award in Immuno-Oncology (D.S.), the National Institute of Aging (C.J.P., R03AG064374 ), and the National Cancer Institute K12 Training Grant for Clinical Faculty Investigators (C.J.P., K12CA133250 ).
      DS + CP conceived of the study, MM + AB+NW + DS collected the data, RH + AB+MM generated the figures and tables, RH created the code repository, DS drafted the manuscript, all authors reviewed and approved the manuscript.

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