The Relationship Between Checkpoint Inhibitors and the Gut Microbiome and Its Application in Prostate Cancer

OncologyONCOLOGY Vol 34 Issue 3
Volume 34
Issue 3

This review article discusses the concepts of a tumor microenvironment and a gut microbiome and their effects on responses to checkpoint inhibitors (CPIs). It also reviews recent research investigating these 3 topics, and how it can be applied to using CPIs in prostate cancer.

Dr. Maniar is an internal medicine resident at Oregon Health Sciences University, he will be completing his fellowship in hematology-oncology at Columbia University next year. During residency his research focused on identifying pathways to enhance response to immunotherapy and on palliative care.

Dr. Moran is an assistant professor of Cell, Developmental and Cancer Biology at the Department of Medicine, Division of Hematology and Oncology at Oregon Health Sciences University.

Dr. Graff is the section chief of hematology/oncology at the VA Portland Health Care System. Together with Drs. Moran and Karen Sfanos, she is conducting a trial of fecal transplant in patients with metastatic castration resistant prostate cancer to enhance responses to immunotherapy.

Figure 1Outcomes of fecal transplant, PD-L1 monoclonal antibody therapy, Bifidoceterium species incoulation in mice. (A) Mice with TAC microbiome treated with PD-L1 monoclonal antibody had increased t-cell activity, intratumoral CD8+ cell population, reduced tumor growth. (B) Mice with TAC microbiome received fecalmicrobiobe transplant from JAX mice and had increased t-cell activity, intratumoral CD8+ cell population, reduced tumor growth. (C) Mice with TAC microbiome received fecalmicrobiobe transplant from JAX mice and treated with PD-L1 monoclonal antibody showed greater increase in T-cell activity, intratumoral CD8+ population and greater reduction in tumor growth compared to mice in A,B,D and E. (D) Mice with TAC microbiome inoculated with Bifidobacterium inoculation had increased T-cell activity, intratumoral CD8+ cell population, reduced tumor growth. (E) Mice with TAC microbiome depleted of CD8 cells did not have response when inoculated with Bifidobacterium

Figure 2Outcome of mice with sarcoma that were reared as germ-free or pre-treated with broad spectrum antibiotics receiving CTLA4 antibody treatment. (A) Select mice pre-treated with broad spectrum antibiotic were inoculated with Bacteroides fragiis (Bf). Mice receiving Bf and subsequent treated with a CTLA4 antibody showed therapeutic effect with tumor suppression and increase in Th1 cell population in draining LN whereas mice that did not receive Bf did not show a therapeutic effect when treated with a CTLA4 Antibody. Next, mice pre-treated with broad spectrum antibiotics were injected with Th1 cells that were induced by Bf or Bacteroides distasonis (Bd). Mice receiving Bf induced Th1 cells responded to CTLA4 antibody with suppression of the sarcoma tumor whereas mice receiving Bd induced Th1 cells did not respond when treated with a CTLA4 antibody. (B) similar outcome in germ-free mice with sarcoma.

Indications for checkpoint inhibitors (CPIs) are growing rapidly within the field of oncology; however, they continue to have heterogeneous outcomes in different cancers. Other than mismatch repair deficiency, there are no consistent tests to determine a tumor’s susceptibility. By exploring factors beyond the cancer cell, researchers have learned that the efficacy of CPIs may be governed by a myriad of variable host factors, including the tumor microenvironment (TME) and gut microbiome (GMB). The GMB serves as one of the primary organs of immune defense and has well-established local and systemic effects on the host immune system. Recent investigations suggest that the GMB also affects the TME. This review article discusses the concepts of a TME and a GMB and their effects on responses to CPIs. It also reviews recent research investigating these 3 topics, and how it can be applied to using CPIs in prostate cancer. By highlighting this important pathophysiologic process, we hope to provide insight into a possible explanation for differences in interindividual response to CPIs, discuss a potential method for transferring treatment efficacy between patients, and propose a method for expanding the use of CPIs to prostate cancer.


As a disease, cancer remains one of the most complex pathologic processes in the body. Although unregulated cell division is a hallmark of the disease, it is well understood that there are a vast number of factors that contribute to the pathophysiology of cancer. These factors include, but are not limited to, sex, genetics, nutrition, macroenvironment, microenvironment, comorbidities, and immune-mediated host processes. Investigating these factors is paramount to creating a thorough understanding of cancer, and it also provides a potential opportunity for new therapeutic interventions. The relationship between systemic immunity, the tumor microenvironment (TME), and the gut microbiome (GMB) is an emerging topic of research in oncology-especially as it applies to outcomes with immunotherapy.1-4 Within the last decade, checkpoint inhibitors (CPIs) gained approval for use in over 10 different solid tumor cancers and classical Hodgkin lymphoma.5 Despite the increased utilization of this class of medications, there remains a large spectrum of response between individual patients.6 The GMB contributes to systemic immunity and recent investigations point toward a significant interaction between CPIs and the GMB.7 A greater understanding of this interaction may allow for an explanation of the interindividual variability in response to CPIs and novel targets to improve immunotherapy outcomes. This review aims to outline current understandings of the TME, GMB, and CPIs, and review recent research investigating the relationship between these entities. Of particular interest is applying this relationship to the field of prostate cancer, as the efficacy of CPIs has largely evaded this field-suggesting the need for a novel approach.  


Although tumors may initially arise from abnormal cellular division, as the tumor progresses, a TME develops that drives its interactions with the host.8 This TME is composed of cancerous cells, vasculature, stroma, inflammatory cells, and a myriad of signaling factors.9 The microenvironment serves as the growth scaffold for the tumor, allowing it to manipulate its surroundings in a way that promotes tumor proliferation. Host immune cells, including tumor-infiltrating lymphocytes (TILs), may recognize antigens from cancerous cells as foreign and invade the TME in an attempt to provide defense through activation of cytotoxic T-cell lymphocytes (CTLs); however, tumors can evade host immunity through a myriad of pathways.10 This process is known as tumor escape and it is centered on suppressing or manipulating invading immune cells in a way that prevents immune-mediated tumor regression.11 Escape mechanisms include alterations of malignant cells to reduce immunogenicity, alteration of immune-mediated signaling to promote the release of inhibitory cytokines or reactive oxygen species,12 upregulation of host anti-inflammatory pathways, and the formation of a physical barrier of macrophages that prevent CTL-associated tumor infiltration.13 Additionally, this chronic inflammatory state can lead to T-cell exhaustion, further dampening the immune system response to tumors.14 On the contrary, tumors that have more immune activity, both within the core and at the periphery, seem to have a higher degree of immune-mediated tumor regression and response to CPIs.15 Essentially, the TME is a dynamic, elegant system that mandates a nuanced understanding to identify potential treatment options. 


T cells can receive a co-inhibitory signal from the tumor cell, interfering with T-cell activation and tumor cell death. These co-inhibitory signals are collectively termed checkpoints.16 Checkpoints are found on T cells, antigen-presenting cells (APCs), macrophages, and cancerous cells and provide a physiologic role in regulating T-cell activity-preventing auto-immunity and excessive tissue damage during pathologic states.17 Cytotoxic T-lymphocyte antigen 4 (CTLA4) and programmed cell death protein 1 (PD-1) are 2 particular checkpoints that play a pivotal role in immune evasion and have demonstrated clinical efficacy.18

During T-cell activation, APCs process foreign antigens and present them on major histocompatibility complexes that interact with T-cell receptors.19 T-cell activation is enhanced by the costimulatory receptor CD28, expressed on T cells, interacting with CD80/86 on APCs. CTLA4 is found on T-cells and attenuates T-cell activation by competing with CD28 for CD80/86 ligands, reducing the costimulatory signal and inducing multiple intracellular signaling pathways that decrease T-cell activity.20 This process occurs, primarily, within secondary lymphoid organs.21 During inflammatory states, such as cancer, CTLA4 expression increases in an attempt to avoid excessive inflammation, thereby reducing antitumor immunity.22

While CTLA4 acts at the APC and T-cell interface, PD-1 on T cells interacts with programmed cell death ligand-1 (PD-L1) on cancer cells in peripheral tissue. Therefore, PD-1/PD-L1 activity is primarily within the TME, where malignant cells express PD-L1 binding ligands and TILs have high PD-1 expression.23 Once bound, PD-1 ligands are thought to influence multiple signaling pathways that ultimately lead to reduced T-cell activity.24   

There are 2 identified mechanisms for increased PD-L1 expression within TMEs-innate and adaptive immune resistance. Innate immune resistance refers to genetic alterations within malignant cells that leads to increased PD-L1 expression, whereas adaptive immune resistance refers to increased PD-L1 expression in response to inflammatory factors.25 By manipulating overexpression of these checkpoints, tumors are able to avoid immune-mediated attacks, promoting cellular immortality. 

CPIs are monoclonal antibodies that bind checkpoint receptors or ligands, and inhibit interaction with the endogenous protein allowing for a more effective, host-mediated immune response to cancer.26 Examples of CPIs used in clinical practice include ipilimumab (a CTLA4 antibody); nivolumab, pembrolizumab, and cemiplimab (PD-1 inhibitors); and avelumab, atezolizumab, and durvalumab (PD-L1 inhibitors).  Initially approved for use in melanoma, CPIs are now approved for use in more than 10 solid tumors and classical Hodgkin lymphoma. As with other treatments, there is significant variability in efficacy among patients. This variability is attributed to multiple causes including poor antigenicity of a tumor, tumor-specific immunosuppression, and aberrant or exhausted host immune system function. Recently, an understanding of the GMB as a factor in host immunity led to investigations on its role in immunotherapy. 


The human GMB is a complex, living entity that starts developing at birth and continues to develop throughout adulthood.27 Through a longitudinal process that is influenced by environment, diet, genetics, sex, and multiple other factors, the microbiome matures to contain over 100 trillion microorganisms with a high degree of variability between individuals, and it continues to evolve as one ages.28 Initially, the purported contributions of the GMB were limited to the metabolism and absorption of nutrients and defense against pathogenic bacteria.29 Understanding of the GMB is now expanding, with studies showing that it plays a key role in the development of gut-associated lymphoid tissue (GALT), regulation of inflammation, and overall host immunity.30 This first came to light when mice raised in germ-free environments displayed incomplete GALT-with follow-up studies showing that gut microbes provided necessary stimulatory signals for GALT maturation.31 Furthermore, studies showing that mice from germ-free environments had reduced regulatory T cells (involved in reducing immune activity) and T helper cells (pro-inflammatory cells), provide a basis for the role of the GMB in immune system homeostasis.32,33 In addition to local gut immunomodulation, there is evidence to suggest that the GMB affects systemic immune function, with immune regulatory proteins derived from gut microbes found in distant organs.34,35 The effect this immune regulation process has on autoimmune conditions such as inflammatory bowel disease is well studied; however, recent studies suggest that the GMB also plays a role in cancer.36 

Gut Microbiome in Cancer

Studies thus far indicate that the GMB has both oncogenic and tumor suppressive actions. The International Agency for Research on Cancer identifies several carcinogenic microbes that are associated with oncogenesis-typically through signaling pathways that promote direct double-stranded DNA damage, increased reactive oxygen species, β-catenin pathway modulation, and amplification of nuclear factor kappa-light-chain-enhancer of activated B cells signaling.37 This interaction may be driven by interplay between an oncogenic microbe and commensal gut bacteria. In a study of mice infected with H. pylori only, they had delayed development of gastric cancer compared with mice harboring both gut bacteria and H. pylori.38

In contrast, there is substantial work showing that the microbiome may promote anti-tumor effects as well. One general protective measure that the GMB provides is competition that selects against carcinogenic pathogens, reducing the ability for these pathogens to populate a host.39 Much of this selection is determined by the predominant species within the GMB. Additionally, metabolism of certain host nutrients by microbes may protect against tumorigenesis. In particular, the byproducts of fiber, which are processed by distal gut bacteria, may protect against cancer.27 Donohoe et al reared mice in gnotobiotic (ie, specific known microbials) conditions that varied in the presence of a butyrate-producing gut microbe.40 The 3 conditions were: wild type, attenuated producers, and non-butyrate-producing microbes. These mice were fed a high-fiber or low-fiber diet. The mice were injected with carcinogenic azoxymethane and dextran sodium sulfate to induce the formation of colorectal carcinoma. Among the high-fiber diet population, mice reared with wild-type, butyrate-producing microbes had less tumor burden, while those reared with attenuated and nonproducing bacteria had the highest tumor burden. Additionally, providing exogenous butyrate to mice reared with non-butyrate-producing bacteria led to a lower tumor burden than similar mice that were not given exogenous butyrate.40 Butyrate is thought to protect against cancer by altering gene expression and reducing inflammation. Colonocytes typically utilize butyrate as their primary metabolic source, however neoplastic colonocytes utilize glucose, allowing butyrate to accumulate within the nucleus of these neoplastic cells, where it can act as a histone deacetylase inhibitor, promoting cell apoptosis and halting cell cycle progression.41 Butyrate also appears to have protein-coupled signaling effects, promoting immunosuppressive regulatory T-cell recruitment and reducing inflammatory states that can led to cellular dysplasia.42 In addition to these locally protective mechanisms, the promotion of regulatory T cells by microbes may reduce the formation of extraintestinal tumors, suggesting a more systemic effect of gut microbes.43 Further studies showed that commensal bacteria affected the composition of the TME and, consequently, the response to chemotherapeutic drugs.2

Given the substantial evidence suggesting a relationship between host microbiome and immune system function, it is logical to posit a connection between the microbiome and immunotherapy response. This connection is supported by several murine models showing reduced tumor control in mice pretreated with broad-spectrum antibiotics prior to CPI initiation.1,4 To better understand this relationship, Sivan et al studied the response to CPI therapy in mice with melanoma from 2 different populations-Jackson Laboratory (JAX) and Taconic Farms (TAC)-with known different commensal bacteria.44 The mice from JAX had higher tumor-mediated T-cell responses, a higher volume of intratumoral CD8 T cells, and subsequently, less aggressive melanoma growth rate. Prophylactic transfer of JAX fecal material to TAC recipients resulted in delayed tumor growth, increased T-cell activity, and an increased intratumoral CD8 population compared with TAC recipients receiving a saline transplant or TAC fecal material. This observation suggests that variance among the 2 microbial populations conferred innate differences to tumor susceptibility. Next, TAC mice with melanoma received JAX fecal material alone, a monoclonal antibody to PD-L1 (mAb PD-L1), or a combination of the 2. Mice receiving a fecal transplant or antibody therapy alone had comparable increases in T-cell activity and intratumoral CD8 populations and decreases in tumor growth. However, combination recipients had a greater reduction in tumor growth and a higher increase in T-cell activity. Additionally, JAX mice receiving the mAb PD-L1 showed improved tumor control compared with TAC mice receiving the mAB PD-L1. When combined, these findings suggest a complex interplay between the GMB and CPIs that can lead to an aggregated response to therapy. 

Analysis of the JAX fecal transplant TAC recipients showed a significant increase in the Bifidobacterium population that corresponded with antitumor T-cell activity. TAC mice with melanoma were fed a mixed species Bifidobacterium preparation or a non-Bifidobacterium-containing preparation. Those receiving Bifidobacterium species showed increased Bifidobacterium within fecal matter, improved tumor control, and increased T-cell activity and intratumoral T-cell infiltration (Figure 1).44 Comparatively, CD8-depleted mice receiving Bifidobacterium or mice receiving a killed Bifidobacterium did not display therapeutic benefit, suggesting the necessities of inherent host immunity and live bacteria interaction. One possible explanation to account for improved tumor control in both JAX fecal transplant and Bifidobacterium recipient mice is the corresponding increase in dendritic cell activation and maturation. This, in turn, leads to improved function among CD8+ intratumoral T cells, allowing for more effective host antitumor immune function and increased efficacy of CPI immunotherapy.44

The relationship between host microbiome and CPIs appears to extend to CTLA4 antibody therapy, as investigated by Vétizou et al.1 These researchers studied the activity of a CTLA4 monoclonal antibody against sarcoma in mice that were raised in specific pathogen-free (SPF) and germ-free (GF) conditions. Mice raised in SPF conditions responded to the immunotherapy with reduced tumor progression, while mice raised in GF conditions did not. Moreover, mice treated with broad-spectrum antibiotics (BSA) had a lower response to therapy. Mice living in GF conditions and those that were treated with antibiotics also had less splenic CD4+ T-cell activation and TIL activity. This differential response was also seen in mice with RET melanoma and colon cancer. The researchers then explored the effect of CPIs on the host microbiome. Overall, treatment with the CTLA4 antibody led to decreased fecal Bacteroidales and Burkholderiales species, an increased fecal Clostridiales population, and increased Bacteroides species in the small intestinal mucosa. 

To evaluate the importance of this compositional change, mice given a BSA and those living in GF conditions were fed mixed bacterial products, some of which contained Bacteroides fragilis (Bf) and then treated with a CTLA4 antibody (Figure 2). In both groups, only those mice fed Bf-containing mixtures had an antitumor response to therapy, which correlated with an increased response in T-helper type 1 (Th1) cells within tumor-draining lymph nodes. The effect of these Th1 memory cells appears to hinge upon the associated microbe. Transfer of Bf-induced Th1 cells into mice given a BSA or those living in GF conditions led to tumor suppression with CPIs, whereas transfer of B. distasonis-induced Th1 cells into these mice did not lead to tumor control with CPI therapy. Lastly, investigators transferred Bacteroidales-containing fecal matter from human patients with melanoma following anti-CTLA4 therapy to mice raised in GF conditions, which resulted in an improved response to anti-CTLA4 therapy.1 This work by Vétizou et al suggests that both eradication of GMB species and selection of specific populations can alter the efficacy of immunotherapy. Furthermore, a treatment-responsive microbiome can be transferred to alter outcomes to immunotherapy.

Routy et al applied these findings to a retrospective analysis of 249 patients with non–small cell lung cancer (NSCLC), renal cell carcinoma (RCC), or urothelial cancer. Among these patients, 28% were prescribed antibiotics (beta-lactam +/- beta-lactamase inhibitor, macrolides, or fluoroquinolone) within 2 months before or 1 month after initiation of a PD-1 or PD-L1 antibody.4 In a combined analysis of patients with NSCLC and those with RCC, progression-free survival (PFS) and overall survival (OS) were significantly shorter in patients given antibiotics-supporting the theory that the GMB affects immunotherapy response. Routy et al advanced the study by taking fecal material from 4 of the nonresponding and responding patients with NSCLC and transplanting the material into mice that were pretreated with antibiotics. These mice were then inoculated with sarcoma cells and given a PD-1 monoclonal antibody. Mice receiving a fecal transplant from responding patients showed a greater response to the CPI and increased CD4 cells within the TME. 

The above findings offer exciting insight on what may be a new frontier for immunotherapy. Although some of the studies identified different microbes that conferred a therapeutic response, a notable similarity was the transference of a response through fecal transplant. Additionally, the observations that mice reared in GF environments derived less benefit from CPIs underscores the importance of commensal bacteria and, potentially, of microbial diversity. This is supported by observational data regarding CPIs and antibiotic use among patients with RCC or NSCLC. In patients with either cancer, antibiotic use 30 days prior to initiation of a CPI was associated with significant decreases in PFS and OS compared with those that did not receive antibiotic therapy. When the window for antibiotic use was extended to 60 days prior to CPI initiation, OS remained significantly lower in patients with NSCLC and there was a nonsignificant trend towards decreased OS in patients with RCC.45 These observations support a theory linking the GMB and CPI efficacy and highlight the importance of commensal gut bacteria.46

In a recent, novel prospective study, Gopalakrishnan et al investigated the murine-based findings of CPI response and fecal transplant described above in humans with metastatic melanoma.3 Patients with melanoma were treated with a PD-1 inhibitor and divided into responder and nonresponder categories based on Response Evaluation Criteria in Solid Tumors 6 months after treatment initiation. Responders had a significant difference in gut microbiome diversity and a higher population of the Ruminococcaceae family microbes, genus Faecalibacterium and order Clostridiales, whereas nonresponders had a higher population of the genus Bacteroidales. Further analysis of the TME showed that patients with gut microbes predominated by the Ruminococcaceae family, Faecalibacterium genus or Clostridiales order had higher populations of CD8 TILs and systemic circulating CD4 and CD8 cells, and preserved cytokine activity, whereas patients with a Bacteroidales-based GMB had more regulatory T cells and myeloid-derived suppressor cells, and reduced cytokine activity. Next, stool from responding and nonresponding patients after anti–PD-1 therapy was transplanted into mice from a GF environment with melanoma. Mice receiving a stool transplant from responding patients showed a reduction in tumor size and a greater response to anti–PD-1 therapy, and a shift in the GMB population with a higher Faecalibacterium abundance. There was also a change in the TME post transplant, with recipients given responder stool showing higher amounts of TILs and effector T cells, and recipients given nonresponder stool having higher amounts of regulatory and suppressor cells.3

To date, the benefits of immune CPI therapy have not applied widely to treating patients with prostate cancer; however, the development of 2 different prostate cancer-specific vaccines suggests that prostate cancer is an immune-responsive malignancy.47 Notably, a phase III trial showing improved OS in patients with metastatic, castrate-resistant prostate cancer (mCRPC) given sipuleucel-T-an activated cancer vaccine-provides clinical evidence that manipulating T-cell activity may lead to an additional route for tumor control.48 Vaccine recipients had significant increases in both antibodies against prostate-derived proteins and T-cell proliferation with a subsequent increase in OS compared with placebo recipients. Unfortunately, results from 2 phase III trials of CPIs in mCRPC have not shown improvement in survival.49 It remains unclear why prostate cancer is less responsive to CPIs. The relatively low prevalence of microsatellite instability likely factors into the reduced response rate;50 however, as seen in other cancerous processes, there may be a compositional difference in the GMB of patients with adenocarcinoma of the prostate, or at least in those patients that were studied. A single-center, case-controlled study comparing patients with benign prostatic hypertrophy to those with prostate adenocarcinoma showed significant differences in their GMB populations.51 In particular, those with benign prostatic disease had a higher proportion of a Faecalibacterium species that is known to be a high butyrate-producing species. Although the sample size was small, this study provides some evidence that the GMB is influenced by the systemic processes promoting prostate cancer or can influence the development of prostate cancer. Of note, in a phase III trial with ipilimumab, patients receiving the CPI had significantly increased PFS compared with those receiving placebo. A post hoc analysis showed that patients with favorable prostate cancer traits had significantly increased OS and PFS with ipilimumab compared with placebo within the subgroup.52 Additionally, case reports and early findings in a phase II trial showed positive responses among patients with metastatic prostate cancer treated with a CPI.53-55

There are likely multiple factors that influenced the clinical findings in the studies above, and one such factor may be a difference in the microbial populations between the 2 groups. If this proves to be the case, then successful transfer of CPI efficacy between patients through fecal transplant could provide a promising option for surpassing barriers of CPI therapy in prostate cancer. Within the field of prostate cancer, it is also important to highlight the effects of sex hormones and androgen-deprivation therapy (ADT) on immunity and the GMB. It is suspected that part of the sex difference noted in auto-immunity between men and women may be due to the immune-stimulating effects of estrogens versus the anti-inflammatory effects of androgens.56 The effect that sex hormones have on GMB development is less clear; however, a small cross-sectional study of 30 men showed that patients with prostate cancer that received ADT had a significantly different GMB compared with men with prostate cancer not receiving ADT and men without prostate cancer. Interestingly, patients within this study that received ADT had a higher population of gut flora that were previously associated with improved response to CPIs.57 This will be an important factor to consider when investigating CPIs and the GMB in humans with prostate cancer.   

Currently, there are 4 human trials investigating fecal transplants and CPIs in patients with advanced melanoma that are in the recruitment phase (NCT03817125, NCT03772899, NCT03341143, NCT03353402). There is one human trial of fecal transplant in mCRPC (NCT04116775). Success in these trials will provide a novel approach to navigating variable responses among CPIs and, hopefully, a method to expand the use of CPIs into a variety of different cancers.


As is often the case, this review brings about as many new questions as it tries to answer. The strongest conclusion one can draw from the material within is that cancer is a profoundly complex process that involves far more than cellular mutation. By expanding our understanding of the pathophysiology of cancer, we can continue to develop new targets to potentially treat cancer or improve the efficacy of established therapies. It can also be surmised that, although CPIs are meant to target a local structure, their efficacy is driven by a systemic pathway that includes their first point of contact in the gastrointestinal tract. This review also greatly underscores the pivotal importance of gut bacteria and supports current efforts to restrict antibiotic use only to those cases where there is a clear indication. Given the discrepancy among tumor suppressive microbes in the findings discussed above, further research is needed to clarify which microbes help protect against cancer, or if the composition of a treatment-specific GMB differs with each cancer subtype. Hopefully, this question will be clarified through current clinical trials involving CPIs and fecal transplants. The findings of these trials will be paramount to testing the hypothesis that treatment response can be transferred through fecal transplantation and provide a new pathway for circumventing the poor outcomes of treatment-refractory malignancies.


Financial Disclosure: The authors have no significant financial interest in or other relationship with the manufacturer of any product or provider of any service mentioned in this article.



1.     Vétizou M, Pitt JM, Daillère R, et al. Anticancer immunotherapy by CTLA-4 blockade relies on the gut microbiota. Science. 2015;350(6264):1079-1084. doi: 10.1126/science.aad1329.

2.     Iida N, Dzutsev A, Stewart CA, et al. Commensal bacteria control cancer response to therapy by modulating the tumor microenvironment. Science. 2013;342(6161):967-970. doi: 10.1126/science.1240527.

3.     Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 2018;359(6371):97-103. doi: 10.1126/science.aan4236.

4.     Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science. 2018;359(6371):91-97. doi: 10.1126/science.aan3706.

5.     Mahmoudi M, Farokhzad OC. Cancer immunotherapy: wound-bound checkpoint blockade. Nat Biomed Eng. 2017;1:0031.

6.     Wei SC, Duffy CR, Allison JP. Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discov. 2018;8(9):1069-1086. doi: 10.1158/2159-8290.CD-18-0367.

7.     Hooper LV, Littman DR, Macpherson AJ. Interactions between the microbiota and the immune system. Science. 2012;336(6086):1268-1273. doi: 10.1126/science.1223490.

8.     Whiteside TL. The tumor microenvironment and its role in promoting tumor growth. Oncogene. 2008;27(45):5904-5912. doi: 10.1038/onc.2008.271.

9.     Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol. 2013;14(10):1014-1022. doi: 10.1038/ni.2703.

10.  Drake CG, Jaffee E, Pardoll DM. Mechanisms of immune evasion by tumors. Adv Immunol. 2006;90:51-81. doi: 10.1016/S0065-2776(06)90002-9.

11.  Khong HT, Restifo NP. Natural selection of tumor variants in the generation of “tumor escape” phenotypes. Nat Immunol. 2002;3(11):999-1005. doi: 10.1038/ni1102-999.

12.  Mantovani A, Sozzani S, Locati M, Allavena P, Sica A. Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends Immunol. 2002;23(11):549-555. doi: 10.1016/s1471-4906(02)02302-5.

13.  Condeelis J, Pollard JW. Macrophages: obligate partners for tumor cell migration, invasion, and metastasis. Cell. 2006;124(2):263-266.

14.  Schietinger A, Philip M, Krisnawan VE, et al. Tumor-specific T cell dysfunction is a dynamic antigen-driven differentiation program initiated early during tumorigenesis. Immunity. 2016;45(2):389-401. doi: 10.1016/j.immuni.2016.07.011.

15.  Binnewies M, Roberts EW, Kersten K, et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med. 2018;24(5):541-550. doi: 10.1038/s41591-018-0014-x.

16.  Zou W, Wolchok JD, Chen L. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: mechanisms, response biomarkers, and combinations. Sci Transl Med. 2016;8(328):328rv4. doi: 10.1126/scitranslmed.aad7118.

17.  Nirschl CJ, Drake CG. Molecular pathways: coexpression of immune checkpoint molecules: signaling pathways and implications for cancer immunotherapy. Clin Cancer Res. 2013;19(18):4917-4924. doi: 10.1158/1078-0432.CCR-12-1972.

18.  Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer. 2012;12(4):252-264. doi: 10.1038/nrc3239.

19.  Harding FA, McArthur JG, Gross JA, Raulet DH, Allison JP. CD28-mediated signalling co-stimulates murine T cells and prevents induction of anergy in T-cell clones. Nature. 1992;356(6370):607-609. doi: 10.1038/356607a0.

20.  Peggs KS, Quezada SA, Korman AJ, Allison JP. Principles and use of anti-CTLA4 antibody in human cancer immunotherapy. Curr Opin Immunol. 2006;18(2):206-213. doi: 10.1016/j.coi.2006.01.011.

21.  Topalian SL, Hodi FS, Brahmer JR, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. New Engl J Med. 2012;366(26):2443-2454. doi: 10.1056/NEJMoa1200690.

22.  Beyer M, Schultze JL. Regulatory T cells in cancer. Blood. 2006;108(3):804-811. doi: 10.1182/blood-2006-02-002774.

23.  Buchbinder EI, Desai A. CTLA-4 and PD-1 pathways: similarities, differences, and implications of their inhibition. Am J Clin Oncol. 2016;39(1):98-106. doi: 10.1097/COC.0000000000000239.

24.  Chen L. Co-inhibitory molecules of the B7-CD28 family in the control of T-cell immunity. Nat Rev Immunol. 2004;4(5):336-347. doi: 10.1038/nri1349.

25.  Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell. 2015;27(4):450-461. doi: 10.1016/j.ccell.2015.03.001.

26.  Webster RM. The immune checkpoint inhibitors: where are we now? Nat Rev Drug Discov. 2014;13(12):883-884. doi: 10.1038/nrd4476.

27.  David LA, Maurice CF, Carmody RN, et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature. 2014;505(7484):559-563. doi: 10.1038/nature12820.

28.  Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486(7402):207-214. doi: 10.1038/nature11234.

29.  Bull MJ, Plummer NT. Part 1: the human gut microbiome in health and disease. Integr Med (Encinitas). 2014;13(6):17-22.

30.  Kau AL, Ahern PP, Griffin NW, Goodman AL, Gordon JI. Human nutrition, the gut microbiome and the immune system. Nature. 2011;474(7351):327-336. doi: 10.1038/nature10213.

31.  Kamada N, Seo SU, Chen GY, Núñez G. Role of the gut microbiota in immunity and inflammatory disease. Nat Rev Immunol. 2013;13(5):321-335. doi: 10.1038/nri3430.

32.  Ivanov, II, Frutos Rde L, Manel N, et al. Specific microbiota direct the differentiation of IL-17-producing T-helper cells in the mucosa of the small intestine. Cell Host Microbe. 2008;4(4):337-349. doi: 10.1016/j.chom.2008.09.009.

33.  Atarashi K, Tanoue T, Shima T, et al. Induction of colonic regulatory T cells by indigenous Clostridium species. Science. 2011;331(6015):337-341. doi: 10.1126/science.1198469.

34.  Clarke TB, Davis KM, Lysenko ES, Zhou AY, Yu Y, Weiser JN. Recognition of peptidoglycan from the microbiota by Nod1 enhances systemic innate immunity. Nat Med. 2010;16(2):228-231. doi: 10.1038/nm.2087.

35.  Ganal SC, Sanos SL, Kallfass C, et al. Priming of natural killer cells by nonmucosal mononuclear phagocytes requires instructive signals from commensal microbiota. Immunity. 2012;37(1):171-186. doi: 10.1016/j.immuni.2012.05.020.

36.  Holmes E, Li JV, Athanasiou T, Ashrafian H, Nicholson JK. Understanding the role of gut microbiome-host metabolic signal disruption in health and disease. Trends Microbiol. 2011;19(7):349-359. doi: 10.1016/j.tim.2011.05.006.

37.  Garrett WS. Cancer and the microbiota. Science. 2015;348(6230):80-86. doi: 10.1126/science.aaa4972.

38.  Lofgren JL, Whary MT, Ge Z, et al. Lack of commensal flora in Helicobacter pylori-infected INS-GAS mice reduces gastritis and delays intraepithelial neoplasia. Gastroenterology. 2011;140(1):210-220. doi: 10.1053/j.gastro.2010.09.048.

39.  Bultman SJ. Molecular pathways: gene-environment interactions regulating dietary fiber induction of proliferation and apoptosis via butyrate for cancer prevention. Clin Cancer Res. 2014;20(4):799-803. doi: 10.1158/1078-0432.CCR-13-2483.

40.  Donohoe DR, Holley D, Collins LB, et al. A gnotobiotic mouse model demonstrates that dietary fiber protects against colorectal tumorigenesis in a microbiota- and butyrate-dependent manner. Cancer Discov. 2014;4(12):1387-1397. doi: 10.1158/2159-8290.CD-14-0501.

41.  P, Hold GL, Flint HJ. The gut microbiota, bacterial metabolites and colorectal cancer. Nat Rev Microbiol. 2014;12(10):661-672. doi: 10.1038/nrmicro3344.

42.  Arpaia N, Campbell C, Fan X, et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature. 2013;504(7480):451-455. doi: 10.1038/nature12726.

43.  Dalgleish AG. Cytokines in the genesis and treatment of cancer. Br J Cancer. 2007;97:1598-1599.

44.  Sivan A, Corrales L, Hubert N, et al. Commensal Bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science. 2015;350(6264):1084-1089. doi: 10.1126/science.aac4255.

45.  Derosa L, Hellmann MD, Spaziano M, et al. Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer. Ann Oncol. 2018;29(6):1437-1444. doi: 10.1093/annonc/mdy103.

46.  Le Chatelier E, Nielsen T, Qin J, et al. Richness of human gut microbiome correlates with metabolic markers. Nature. 2013;500(7464):541-546. doi: 10.1038/nature12506.

47.  Goswami S, Aparicio A, Subudhi SK. Immune checkpoint therapies in prostate cancer. Cancer J. 2016;22(2):117-120. doi: 10.1097/PPO.0000000000000176.

48.  Kantoff PW, Higano CS, Shore ND, et al; IMPACT Study Investigators. Sipuleucel-T immunotherapy for castration-resistant prostate cancer. New Engl J Med. 2010;363(5):411-422. doi: 10.1056/NEJMoa1001294.

49.  Boettcher AN, Usman A, Morgans A, VanderWeele DJ, Sosman J, Wu JD. Past, current, and future of immunotherapies for prostate cancer. Front Oncol. 2019;9:884. doi: 10.3389/fonc.2019.00884.

50.  Abida W, Cheng ML, Armenia J, et al. Analysis of the prevalence of microsatellite instability in prostate cancer and response to immune checkpoint blockade. JAMA Oncol. 2019;5(4):471-478. doi: 10.1001/jamaoncol.2018.5801.

51.  Golombos DM, Ayangbesan A, O'Malley P, et al. The role of gut microbiome in the pathogenesis of prostate cancer: a prospective, pilot study. Urology. 2018;111:122-128. doi: 10.1016/j.urology.2017.08.039.

52.  Kwon ED, Drake CG, Scher HI, et al; CA184-043 Investigators. Ipilimumab versus placebo after radiotherapy in patients with metastatic castration-resistant prostate cancer that had progressed after docetaxel chemotherapy (CA184-043): a multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 2014;15(7):700-712. doi: 10.1016/S1470-2045(14)70189-5.

53.  Graff JN, Alumkal JJ, Drake CG, et al. Early evidence of anti-PD-1 activity in enzalutamide-resistant prostate cancer. Oncotarget. 2016;7(33):52810-52817. doi: 10.18632/oncotarget.10547.

54.  Graff JN, Drake CG, Beer TM. Complete biochemical (prostate-specific antigen) response to sipuleucel-T with enzalutamide in castration-resistant prostate cancer: a case report with implications for future research. Urology. 2013;81(2):381-383. doi: 10.1016/j.urology.2012.10.044.

55.  Graff JN, Puri S, Bifulco CB, Fox BA, Beer TM. Sustained complete response to CTLA-4 blockade in a patient with metastatic, castration-resistant prostate cancer. Cancer Immunol Res. 2014;2(5):399-403. doi: 10.1158/2326-6066.CIR-13-0193.

56.  Gomez A, Luckey D, Taneja V. The gut microbiome in autoimmunity: sex matters. Clin Immunol. 2015;159(2):154-162. doi: 10.1016/j.clim.2015.04.016.

57.  Sfanos KS, Markowski MC, Peiffer LB, et al. Compositional differences in gastrointestinal microbiota in prostate cancer patients treated with androgen axis-targeted therapies. Prostate Cancer Prostatic Dis. 2018;21(4):539-548. doi: 10.1038/s41391-018-0061-x.

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