The DOI matches its Crossref record; 80 of the 84 references it cites were found in a registry or an index; 14 of the 26 sources its claims cite were checked for support.
Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients
Open accessAbstract
Good bacteria help fight cancer Resident gut bacteria can affect patient responses to cancer immunotherapy (see the Perspective by Jobin). Routy et al. show that antibiotic consumption is associated with poor response to immunotherapeutic PD-1 blockade. They profiled samples from patients with lung and kidney cancers and found that nonresponding patients had low levels of the bacterium Akkermansia muciniphila . Oral supplementation of the bacteria to antibiotic-treated mice restored the response to immunotherapy. Matson et al. and Gopalakrishnan et al. studied melanoma patients receiving PD-1 blockade and found a greater abundance of “good” bacteria in the guts of responding patients. Nonresponders had an imbalance in gut flora composition, which correlated with impaired immune cell activity. Thus, maintaining healthy gut flora could help patients combat cancer. Science , this issue p. 91 , p. 104 , p. 97 ; see also p. 32
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Claims the paper makes
38 Own result · 4 Supported so far · 4 Own interpretation · 2 Partly supported · 2 Own method · 1 Mixed support · 1 No full text of the sources · 1 Not checked yet · accuracy not yet measured
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“It has recently emerged that factors beyond tumor genomics influence cancer development and therapeutic responses (4–7), including host factors such as the gastrointestinal (gut) microbiome (8–10).”
What the sources say
- Supportedcites [4] source
The Abstract and Introduction describe immunity as a host factor that can suppress or promote tumor development. The section “Personalized immunotherapy and genomics: the antigen landscape” discusses how tumor immunogenicity may affect response to checkpoint-blockade therapy. The gut microbiome is cited separately (8–10) in the citing sentence, not attributed to this source (4–7). Page numbers are unavailable in our copy. (LLM, conf=0.87)
- Not checked — no full text of the sourcecites [5] source
- Not checked — no full text of the sourcecites [6] source
- Supportedcites [7] source
The citation group (4–7) supports the first clause, about influences beyond tumor genomics; the gut microbiome is attributed to a different citation group (8–10). The Introduction describes immune cells and the inflammatory microenvironment as affecting cancer growth and identifies infiltrating immune cells as relevant to therapeutic response and resistance. The paper discusses these points chiefly in haematological malignancies. (LLM, conf=0.88)
- Not checked — no full text of the sourcecites [8] source
- Not checked — no full text of the sourcecites [9] source
- Supportedcites [10] source
The Conclusion describes both pathogenic and protective roles of the gut microbiota in colorectal cancer and says it may enhance antitumour T-cell responses after chemotherapy and immunotherapy. The ‘Microbial modulation of sensitivity to treatment’ section also reports microbiota-dependent responses to several cancer therapies. These passages support the claim attributed to this source. (LLM, conf=0.91)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“We compared the tumor-associated immune infiltrates via multi-parameter immunohistochemistry (IHC) and observed a higher density of CD8+ T cells in baseline samples of R versus NR (p=0.04), consistent with prior reports (Fig. 4A and fig. S18) (18, 37).”
What the sources say
- Not checked — no full text of the sourcecites [18] source
- Supportedcites [37] source
The passage labeled Abstract reports higher pretreatment CD8+ cell densities at the invasive tumour margin in patients who responded than in patients whose disease progressed. The p=0.04 value describes the citing authors’ own observation, not a result attributed to this source. (LLM, conf=0.92)
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“A number of studies have shown that the gut microbiome may influence anti-tumor immune responses via innate and adaptive immunity (11, 12)”
What the sources say
- Supportedcites [11] source
The Introduction (page not available in our copy) reports that gut-microbe translocation after irradiation led to LPS–TLR4 signaling, increased dendritic-cell and tumor-specific CD8+ T-cell activation, and greater tumor regression in mice. This supports the claim that gut microbes can influence antitumor responses through innate and adaptive immunity, in the studied immunotherapy setting. (LLM, conf=0.92)
- Not checked yetcites [12] source
Checked before — its earlier verdict is held back until a new check runs.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“No associations were seen between CD8+ T cell density and diversity or crOTU community type membership (fig. S21).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Moreover, FMT from R locally increased the number of CD45+ immune and CD8+ T cells in the gut compared to NR-FMT (Fig. 4K and fig. S26B, bottom series).”
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Conversely, patients with a high abundance of Bacteroidales had a shortened PFS compared to those with a low abundance (p=0.05, Fig. 3D).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A similar pattern was also noted for KO-abundances with 70.6% and 37.5% response rates (fig. S17).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“No significant differences in enrichment were noted in the oral microbiome of R versus NR (fig. S9, B and D, and fig. S10).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“These studies demonstrated that tumors of mice receiving R-FMT had a higher density of CD8+ T cells than mice receiving NR-FMT, consistent with human data (Fig. 4J and fig. S26B, top series).”
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our final multivariate model was selected by forward stepwise selection and included Faecalibacterium abundance (HR=2.95, 95% C.I.=1.31-7.29, p=0.03) and prior immunotherapy (HR=2.87, 95% C.I.=1.10-7.89, p=0.03) (table S6).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Probably not a substantial claim. 6
- It may state two separate claims as one. 13
Some cited sources support this claim and some don’t — read each source’s verdict below.
In the paper
“however responses to these therapies are often heterogeneous and not durable (1–3).”
What the sources say
- Partly supportedcites [1] sourceExperimental — accuracy not yet measured
The Fig. 2 discussion describes varied outcomes after ipilimumab treatment in advanced melanoma, and reports that only 20%–26% of patients survived to the apparent three-year plateau. This supports heterogeneous outcomes and limited long-term benefit for many patients, but the paper does not establish that initial responses are often lost or extend that finding to other checkpoint inhibitors and cancers. The paper also emphasizes durable survival in a subset. (LLM, conf=0.85)
- Disputedcites [2] sourceExperimental — accuracy not yet measured
The Rates of Response section (page unavailable) shows varied response rates in advanced melanoma, but the Discussion (page unavailable) explicitly says responses appeared durable in all treatment groups: 93.0% of pembrolizumab responses and 87.8% of ipilimumab responses were ongoing at data cutoff. This contradicts the claim that responses were often not durable. The trial did not study other cancers. (LLM, conf=0.87)
Checked by a reasoning model — may be wrong.
- Disputedcites [3] sourceExperimental — accuracy not yet measured
The Discussion reports varied outcomes with nivolumab, including a 40% objective response rate, but describes the responses as durable—not often short-lived. Its Figure 2 discussion says 12 of 84 nivolumab responders did not have a durable response; the median response duration had not been reached. The study concerns melanoma without a BRAF mutation, not other cancers. (LLM, conf=0.85)
Checked by a reasoning model — may be wrong.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“and that therapeutic responses may be improved via its modulation (13, 14)”
What the sources say
- Supportedcites [13] source
The passage labeled Abstract explicitly highlights the potential to improve cancer treatment by manipulating the human gut microbiota. The claim’s tentative wording matches that conclusion; the reported experiments were in mice. (LLM, conf=0.94)
- Not checked — no full text of the sourcecites [14] source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Loss of microbial diversity (dysbiosis) is associated with chronic health conditions (26–28) and cancer (8–10), and is also associated with poor outcomes to certain forms of cancer therapy including allogeneic stem cell transplant (29).”
What the sources say
- Supportedcites [26] source
The citation to this source is attached to the chronic-health-conditions portion of the sentence, not the separately cited cancer or transplant-outcome portions. In “Microbial diversity of healthy humans,” the paper links low gut microbial diversity to obesity and inflammatory bowel disease. (LLM, conf=0.91)
- Not checked — no full text of the sourcecites [27] source
- Could not verifycites [28] sourceExperimental — accuracy not yet measured
The gene-catalogue section (p. 2) reports lower bacterial diversity in patients with inflammatory bowel disease, but the citation in the citing sentence is attached to outcomes of cancer therapy, including allogeneic stem cell transplant. Searches for transplant, cancer therapy, and treatment outcomes found no passage addressing that association in our copy. (LLM, conf=0.76)
- Not checked — no full text of the sourcecites [8] source
- Not checked — no full text of the sourcecites [9] source
- Partly supportedcites [10] sourceExperimental — accuracy not yet measured
This source is cited for the cancer portion of the sentence, not for chronic conditions or transplant outcomes, which have separate citations. The ‘Protective roles of the microbiota in CRC’ section links loss of diversity to dysbiosis in a colorectal-cancer susceptibility model, while ‘Microbial initiators and progressors of tumorigenesis’ says dysbiosis may contribute to colorectal cancer progression. It does not establish loss of diversity as a general feature of cancer, and it notes that dysbiosis may take many forms. (LLM, conf=0.84)
- Supportedcites [29] source
Citation (29) supports the allogeneic stem cell transplant portion of the sentence, not the separately cited claims about chronic conditions or cancer. The Results and Discussion report that lower intestinal microbial diversity at engraftment was associated with higher overall and transplant-related mortality after allo-HSCT; the Discussion does not claim the relationship is causal. Page numbers were not provided in the supplied passages. (LLM, conf=0.94)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Comparisons of pathway enrichment across these groups showed changes in metabolic functions, with anabolic functions predominating in R including amino acid biosynthesis (Fig. 3E), which may promote host immunity (36), whereas catabolic functions predominated in NR (Fig. 3E, fig. S16, and table S7).”
What the sources say
- Partly supportedcites [36] sourceExperimental — accuracy not yet measured
The citation is attached to the suggestion that amino acid biosynthesis may promote host immunity, not to the responder/non-responder comparison, which the citing sentence assigns to its own figures. In “Microbiome modulation of the gastrointestinal metabolite configuration” (page unavailable), the source describes tryptophan as immunomodulatory, but it does not establish that amino acid biosynthesis itself promotes immunity. (LLM, conf=0.78)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Partly supported
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We found that patients segregated into 2 distinct community types. Type 1 comprised entirely of R and was enriched for Clostridiales, whereas Type 2 comprised a mixture of R and NR (p=0.02) and was enriched for Bacteroidales (Fig. 3A).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this cohort, the total number and specific melanoma driver mutations were within comparable parameters between R and NR following anti-PD-1 therapy (fig. S3)”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“No major differences were observed in the oral microbiome between R and NR, with the exception of higher Bacteroidales in NR to anti-PD-1 therapy (fig. S11).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“demonstrating that distinct sets of rare low abundance OTUs were associated with response to anti-PD-1 therapy, with enrichment of Clostridiales in R and Bacteroidales in NR in the gut microbiome (p<0.01, Fig. 2, A and B, and fig. S9, A and C).”
- Also stated in: § Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients · boosted
“which again demonstrated differentially abundant bacteria in the fecal microbiome of R versus NR to anti-PD-1 therapy, with Clostridiales/Ruminococcaceae enriched in R and Bacteroidales enriched in NR (Fig. 2, C and D).”
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Also stated in: § Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients · boosted
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“we found a notable clustering effect by response status in the gut microbiome of these patients, which was not observed in the oral microbiome (Fig. 1F and fig. S8E).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“demonstrating a statistically significant positive correlation between the CD8+ T cell infiltrate in the tumor and abundance of the Faecalibacterium genus, the Ruminococcaceae family and the Clostridiales order in the gut and a non-significant but negative correlation with Bacteroidales (Fig. 4, B and C, and figs. S19 and S20).”
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“whereas patients with a higher abundance of Bacteroidales in the gut microbiome had higher levels of regulatory T cells (Treg) and myeloid derived suppressor cells (MDSC) in the systemic circulation, with a blunted cytokine response (Fig. 4D and figs. S22 and S23).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“noting that both communities were relatively diverse, with a high abundance of Lactobacillales in the oral microbiome and Bacteroidales in the fecal microbiome (Fig. 1B).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Metagenomic WGS further confirmed enrichment of Faecalibacterium species in addition to others in R, while Bacteroides thetaiotaomicron, Escherichia coli, and Anaerotruncus colihominis were enriched in NR (Fig. 2F and table S4).”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“There was no association found between PFS and stage in our cohort.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Of note, patients in R versus NR groups were similar with respect to age, gender, primary type, prior therapy, concurrent systemic therapy and serum lactate dehydrogenase (LDH) (table S2).”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Bipartite network analysis (25) demonstrated a clear separation of community structure between the oral and fecal microbiomes in terms of both matched and aggregate samples (fig. S4), suggesting that these communities are distinct.”
What the sources say
- Not checked — no full text of the sourcecites [25] source
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper relies on this without support.
The role of the gut microbiome in cancer patients has not been extensively studied.
“however this has not been extensively studied in cancer patients.”
The paper relies on this without support.
FMT from human donors into germ-free mice provides evidence about causal effects of the human gut microbiome on anti-PD-1 response in melanoma patients.
“To investigate a causal link between a “favorable” gut microbiome and response to immune checkpoint blockade, we performed Fecal Microbiome Transplantation (FMT) experiments in germ-free recipient mice (Fig. 4G).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Intestinal dysbiosis, broadly defined as an imbalance in the composition or function of the gut microbiota, is a significant contributor to resistance against immune checkpoint inhibitor (ICI) therapies.1–16,”
From Gut dysbiosis in oncology: a risk factor for immunoresistance (2026) · cites this paper as [5]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These new results in two independent cohorts, together with previous studies,4,6,9,11,12,14,15 confirm that a high abundance of F. prausnitzii in stools at baseline is predictive of a positive response to ICI in multiple cancer types.”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Recently, Gopalakrishnan et al. 35 reported that patients with a high diversity of gut microbiome favored the clinical outcomes of anti-PD-1 immunotherapy in melanoma patients in the Western population.”
From The Diversity of Gut Microbiome is Associated With Favorable Responses to Anti–Programmed Death 1 Immunotherapy in Chinese Patients With NSCLC (2019) · cites this paper as [35]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“There are several previous studies reporting the association of gram-negative bacteria, such as Akkermansia muciniphila, Alistipes, and Porphyromonas with better clinical response to immunotherapy.14,15,36”
From The Diversity of Gut Microbiome is Associated With Favorable Responses to Anti–Programmed Death 1 Immunotherapy in Chinese Patients With NSCLC (2019) · cites this paper as [14]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Two additional studies have identified an association of the commensal microbiome with anti–PD-1 mAb efficacy in different solid cancers (7,14).”
From The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients (2018) · cites this paper as [14]
Experimental — accuracy not yet measured
The cited source says what the claim attributes to it.
In the citing paper
“We next tested the generalizability of the balance described in Fig. 2a by computing it for patients from six independent melanoma cohorts5,7–10,12. Despite small sample sizes and large heterogeneity in terms of DNA isolation protocols and sequencing platforms (Supplementary Table 6), this analysis showed that the balance achieves a comparable AUC in several of the independent cohorts (Extended”
From Longitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma (2024) · cites this paper as [9]
The cited source says what the claim attributes to it.
In the citing paper
“Multiple studies have reported significant differences in microbial diversity and composition between responding and non-responding melanoma, non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC) patients treated with anti-PD-1 alone or in combination with anti-CTLA-4 agents (ipilimumab).2,4-8”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
The cited source says what the claim attributes to it.
In the citing paper
“The gut microbiome can modulate tumor response to immunotherapy, but its effect on HCC remains unclear.”
From Gut microbiota and metabolites associate with outcomes of immune checkpoint inhibitor–treated unresectable hepatocellular carcinoma (2022) · cites this paper as [11]
The cited source says what the claim attributes to it.
In the citing paper
“A human study demonstrated that patients with melanoma who were responders to anti-PD-1 immunotherapy had a higher alpha diversity of fecal microbiota and higher relative abundance of Ruminococcaceae than non-responders.11”
From Gut microbiota and metabolites associate with outcomes of immune checkpoint inhibitor–treated unresectable hepatocellular carcinoma (2022) · cites this paper as [11]
The cited source says what the claim attributes to it.
In the citing paper
“antitumor immunity was enhanced in germ-free mice receiving fecal transfer from the responding patients [9, 10].”
From Relating the gut metagenome and metatranscriptome to immunotherapy responses in melanoma patients (2019) · cites this paper as [9]
The cited source says what the claim attributes to it.
In the citing paper
“In human melanoma patients undergoing immunotherapy, gut microbiome composition has been significantly associated with clinical response [9–12]”
From Relating the gut metagenome and metatranscriptome to immunotherapy responses in melanoma patients (2019) · cites this paper as [9]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Studies in mouse models have provided compelling evidence that gut microbiota modifications resulting from faecal microbiota transplantation (FMT) improve ICI response rates38,42,91; however, the magnitude of these antitumour responses depends of factors such as the mouse strain or provider, mouse sex and individual experimental conditions106.”
From Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy (2023) · cites this paper as [38]
Experimental — accuracy not yet measuredIn the citing paper
“The three studies all demonstrated that gut microbiota composition and diversity were predictive of response to ICI immunotherapy [31–33].”
From Gut microbiota influence immunotherapy responses: mechanisms and therapeutic strategies (2022) · cites this paper as [32]
In the citing paper
“A similar finding was that fecal microbiota transplantation (FMT) from ICI responding patients to germ-free or antibiotic-treated mice could improve tumor control and ameliorate responses to ICI, whereas FMT from non-responders failed to do so [31–33].”
From Gut microbiota influence immunotherapy responses: mechanisms and therapeutic strategies (2022) · cites this paper as [32]
In the citing paper
“Recently, several studies have indicated that FMT could augment the antitumor effect of ICI and overcome resistance to immunotherapy [31–33].”
From Gut microbiota influence immunotherapy responses: mechanisms and therapeutic strategies (2022) · cites this paper as [32]
In the citing paper
“Moreover, specific gut microbes, such as Bifidobacterium [16, 33, 51, 141], Akkermansia [31, 38], Enterococcus [15, 33, 141], Faecalibacterium [49, 142], and Ruminococcaceae [32], play the role of immune adjuvants in ICI immunotherapy.”
From Gut microbiota influence immunotherapy responses: mechanisms and therapeutic strategies (2022) · cites this paper as [32]
In the citing paper
“Notably, α-diversity at baseline has been associated with favorable clinical outcomes in ICI therapies.5,147”
From Gut dysbiosis in oncology: a risk factor for immunoresistance (2026) · cites this paper as [5]
In the citing paper
“First, in pre-clinical models, experiments with germ-free or antibiotic (ATB)treated mice unraveled that the antitumor activity of ICI requires the presence of gut microbial components 19 .”
From Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer (2022) · cites this paper as [19]
In the citing paper
“These results support the possibility that Akk could promote the elicitation or recirculation of Th1 cells into the tumor microenvironment, as previously shown in mouse models 18,19 .”
From Intestinal Akkermansia muciniphila predicts clinical response to PD-1 blockade in patients with advanced non-small-cell lung cancer (2022) · cites this paper as [19]
In the citing paper
“For each individual study, we only observed a marked difference in beta-diversity between the R and NR groups in the Gopalakrishnan et al. data set (15) (Figure 2A).”
From Meta-analysis of the gut microbiota in predicting response to cancer immunotherapy in metastatic melanoma (2020) · cites this paper as [15]
In the citing paper
“Previous studies have suggested that the gut microbiome influences the response to checkpoint inhibitors (CPIs) in patients with cancer.”
From Nivolumab plus ipilimumab with or without live bacterial supplementation in metastatic renal cell carcinoma: a randomized phase 1 trial (2022) · cites this paper as [2]
In the citing paper
“For example, melanoma patients are more likely to have a favorable response to immune checkpoint blockade and exhibit improved systemic and antitumor immunity if they have a more diverse intestinal microbiome11.”
From Gut microbiome diversity is an independent predictor of survival in cervical cancer patients receiving chemoradiation (2021) · cites this paper as [11]
In the citing paper
“Studies have suggested that dysbiosis of the gut microbiome confers a predisposition to certain malignancies and influences the body’s response to a variety of cancer therapies, including chemotherapy, radiotherapy, and immunotherapy6,8–11.”
From Gut microbiome diversity is an independent predictor of survival in cervical cancer patients receiving chemoradiation (2021) · cites this paper as [11]
In the citing paper
“Although multiple studies have reported that a favorable gut microbiome is associated with response to anti–PD-1 in cancer patients, its precise composition is not yet fully understood (10–12).”
From Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients (2021) · cites this paper as [10]
In the citing paper
“Specifically in melanoma, key bacterial species belonging to various phyla, including Actinobacteria (Bifidobacteriaceae spp. and Coriobacteriaceae spp.) and Firmicutes (Ruminococcaceae spp. and Lachnospiraceae spp.), are associated with favorable response to mAbs targeting PD-1 in cancer patients, although limited concordance among the identified species has been reported in different studies (10”
From Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients (2021) · cites this paper as [10]
In the citing paper
“we observed that gut bacterial commensals that were previously shown to increase (F. prausnitzii and Akkermansia muciniphila) and decrease (Bacteroides genus) responses to anti–PD-1 (10) were negatively and positively correlated with CXCL8 (IL-8), respectively.”
From Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients (2021) · cites this paper as [10]
In the citing paper
“administration of certain gut commensals or fecal microbiota transplantation (FMT) promotes anti–PD-1 efficacy in melanoma-bearing mice (10–12).”
From Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients (2021) · cites this paper as [10]
In the citing paper
“In mice, composition of the gut microbiome modulates therapeutic activity of anti–PD-1 and anti–programmed death-ligand 1 (PD-L1)”
From Fecal microbiota transplant overcomes resistance to anti–PD-1 therapy in melanoma patients (2021) · cites this paper as [10]
In the citing paper
“Recently, the gut microbiota has emerged as a potent new factor associated with the efficacy of anti–CTLA4, anti–PD-1, and anti–PD-L1 treatment (8-14).”
From Enterococcus peptidoglycan remodeling promotes checkpoint inhibitor cancer immunotherapy (2021) · cites this paper as [11]
In the citing paper
“Gut bacteria modulate the response to immune checkpoint blockade (ICB) treatment in cancer”
From Dietary fiber and probiotics influence the gut microbiome and melanoma immunotherapy response (2021) · cites this paper as [4]
In the citing paper
“single studies in patients with melanoma receiving ICIs identified an enrichment of species such as F. prausnitzii, Bifidobacterium longum and Bacteroides caccae in samples from patients with a response (‘responders’)38,44,91, although the concordance of these microbiome characteristics with treatment response across studies was low97.”
From Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy (2023) · cites this paper as [38]
In the citing paper
“Over the past decade, following the epidemiological demonstration of the negative effect of antibiotics on the efficacy of ICIs13,42,90, specific microbial taxa have been associated with response or resistance to ICIs across distinct cancer types26,38–40,42,91–100.”
From Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy (2023) · cites this paper as [38]
In the citing paper
“we performed a meta-analysis and mega-analysis of stools taxonomically profiled with MetaPhlAn 4 (ref. 37) and from patients enrolled in 12 cohorts from eight published studies26,38–44 across three cancer types, and classified as responders (n = 248) or non-responders (n = 513) based on RECIST1.1 criteria response rates”
From Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy (2023) · cites this paper as [38]
In the citing paper
“Our meta-analysis of microbial sequencing data from nine independent αPD-1-treated melanoma cohorts82–88 revealed a higher abundance of pfl, a key enzyme in bacterial formate production, linked to ICI efficacy.”
From Exercise-induced microbiota metabolite enhances CD8 T cell antitumor immunity promoting immunotherapy efficacy (2025) · cites this paper as [85]
In the citing paper
“However, there is limited concordance among species identified across studies, which included small numbers of patients and used different analytical approaches, not always adjusted for multiple testing4,5,12,13.”
From Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1 (2022) · cites this paper as [4]
In the citing paper
“The intestinal microbiome has emerged as a tumor-extrinsic predictive biomarker to immune checkpoint blockade (ICB)1–6.”
From Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1 (2022) · cites this paper as [4]
In the citing paper
“Administration of certain gut commensals promotes efficacy of anti-programmed cell death protein-1 (PD-1) therapy in mice, providing evidence that microbiota can drive immunotherapy outcomes4–6.”
From Intestinal microbiota signatures of clinical response and immune-related adverse events in melanoma patients treated with anti-PD-1 (2022) · cites this paper as [4]
In the citing paper
“These results confirm previous observations of biphasic effects for the Bacteroides genus dependent on the specific treatment agent(s) used9,40,41.”
From Longitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma (2024) · cites this paper as [9]
In the citing paper
“With regard to adaptive immunity, distinct gut microbial genera and species are associated with CD8+ T cell infiltration and survival in patients with melanoma.”
From Melanoma and microbiota: Current understanding and future directions (2024) · cites this paper as [16]
In the citing paper
“First, correlations have been drawn across cancer indications and geographical sites between the taxonomic composition of the gut (and to some degree tumor) microbiota, and ICI responses in patients with melanoma and other cancers.”
From Melanoma and microbiota: Current understanding and future directions (2024) · cites this paper as [16]
In the citing paper
“Several studies have examined the stool composition of patients on checkpoint blockade with melanoma, non-small cell lung cancer (NSCLC), and renal cell cancer (RCC) (5–10). These studies have implicated increased alpha-diversity (8), along with specific members of each of the major bacterial phyla colonizing humans”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“Several studies, small in size and using variable analytical methods, suggest the gut microbiome may be a novel, modifiable biomarker for tumor response rates, but the specific bacteria or bacterial communities putatively impacting ICI responses have been inconsistent across the studied populations.”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“Overall, the majority of these studies used non-parametric testing but did not apply multiple hypothesis testing correction in the initial analysis, with the exception of the Gopalakrishnan cohort (8).”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“These results indicate that data from our standardized methodology for 16S rRNA amplicon data produces comparable relative abundance profiles, including for high-interest species such as Faecalibacterium prausnitzii and Akkermansia muciniphila (Fig S1).”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“While individually significant, a feature of these studies is that each has largely identified different sets of microbes and, overall, there is a lack of consensus regarding the microbial signals associated with clinical response and/or whether putative microbiota signals are tumor-specific or impacted by other clinical metadata.”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“In contrast, the gut microbiota of non-responding patients seemed to be less diverse, with the genera Bacteroides (phylum Bacteroidetes), Ruminococci and Roseburia (both Firmicutes) being prominent.”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“we confirmed that higher alpha diversity (richness and evenness) correlated with tumor response to checkpoint inhibition in the Gopalakrishan cohort (Fig. S2B) (8)”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [8]
In the citing paper
“Recent studies have shown that higher diversity and relative abundance of fecal Ruminococcaceae are associated with response to ICIs in patients with melanoma26.”
From Neoadjuvant nivolumab or nivolumab plus ipilimumab in operable non-small cell lung cancer: the phase 2 randomized NEOSTAR trial (2021) · cites this paper as [26]
In the citing paper
“Similarly, Akkermansia muciniphila was associated with favorable clinical outcomes in patients with melanoma, NSCLC and renal cell carcinoma receiving ICIs in previous studies26,27.”
From Neoadjuvant nivolumab or nivolumab plus ipilimumab in operable non-small cell lung cancer: the phase 2 randomized NEOSTAR trial (2021) · cites this paper as [26]
In the citing paper
“The gut microbiome has been shown to have multiple effects on tumor biology, such as the transformation process, tumor progression, and the response to anticancer therapies including immunotherapy (21-29).”
From The human tumor microbiome is composed of tumor type–specific intracellular bacteria (2020) · cites this paper as [23]
In the citing paper
“For example, several bacterial biomarkers have been reported for response to checkpoint inhibitors in non-GI cancer indications (Frankel et al., 2017; Gopalakrishnan et al., 2018; Matson et al., 2018; Peters et al., 2019; Routy et al., 2018).”
From Gut microbiome stability and dynamics in healthy donors and patients with non-gastrointestinal cancers (2021) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“as the gut and tumour microbiota can affect the survival of patients with cancer and their responses to therapy8,14,40–42,50”
From Identification of bacteria-derived HLA-bound peptides in melanoma (2021) · cites this paper as [40]
In the citing paper
“In previous studies, a significantly higher relative abundance of Ruminococcaceae was identified in melanoma patients responding to anti-PD-1 immunotherapy [7]”
From Gut microbiome affects the response to anti-PD-1 immunotherapy in patients with hepatocellular carcinoma (2019) · cites this paper as [7]
In the citing paper
“Gopalakrishnan et al. compared the tumor-associated immune infiltrates via multi-parameter immunohistochemistry (IHC) and found a statistically significant positive correlation between CD8+ T cell infiltrate in the tumor and the Faecalibacterium genus as well as the Ruminococcaceae family”
From Gut microbiome affects the response to anti-PD-1 immunotherapy in patients with hepatocellular carcinoma (2019) · cites this paper as [7]
In the citing paper
“The role of the gut microbiome in modulating tumor responses to immunotherapy in melanoma [5–7], non-small cell lung cancer, renal cell carcinoma, and urothelial carcinoma [6, 8] has received increased attention across a series of studies in recent years.”
From Gut microbiome affects the response to anti-PD-1 immunotherapy in patients with hepatocellular carcinoma (2019) · cites this paper as [7]
In the citing paper
“Microbial taxa associated with response to ICB in cancer patients differed among different reports (Gopalakrishnan et al., 2018; Matson et al., 2018; Routy et al., 2018).”
From Microbiota triggers STING-type I IFN-dependent monocyte reprogramming of the tumor microenvironment (2021) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“The analysis of 112 buccal and fecal samples from patients with metastatic melanoma also showed that the response to anti-PD-1 therapy depends on differences in the diversity and composition of the patient gut microbiota of responders vs. non-responders (179).”
From Immunosenescence and Its Hallmarks: How to Oppose Aging Strategically? A Review of Potential Options for Therapeutic Intervention (2019) · cites this paper as [179]
In the citing paper
“These data demonstrated that, in responding patients, there was a relative abundance of bacteria of the Ruminococcaceae family.”
From Immunosenescence and Its Hallmarks: How to Oppose Aging Strategically? A Review of Potential Options for Therapeutic Intervention (2019) · cites this paper as [179]
In the citing paper
“A muciniphila195 and Faecalibacterium196 have been associated with greater efficacy of PDCD1 blocking agents—possibly by increasing recruitment of T cells to tumors and their functions there.”
From Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer (2020) · cites this paper as [196]
In the citing paper
“Such as Bacteroides fragilis, Bacteroides thetaiotaomicron, Bifidobacterium, Akkermansia muciniphila and Faecalibacterium spp. have been shown to have favourable responses to cancer immunotherapy in both preclinical tumour models and patients with cancer.12–15”
In the citing paper
“Studies in humans were further able to link the presence of fecal A. muciniphila, Ruminococcaceae, and Faecalibacterium to a favorable outcome to anti-PD-1 treatment (98, 126)”
From Anti-PD-1 and Anti-CTLA-4 Therapies in Cancer: Mechanisms of Action, Efficacy, and Limitations (2018) · cites this paper as [126]
In the citing paper
“These studies suggest that gut bacteria influences the activation of the immune system, promoting cancer-associated inflammation and ultimately affecting tumor responses to therapies.”
From Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes (2019) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“The key role of the gut microbiota as a host factor mediating tumor responses to chemotherapy and immunotherapy in patients with melanoma and lung cancers has been recently highlighted”
From Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes (2019) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Furthermore, recent studies also demonstrated the positive effects of immunotherapy on melanoma with FMT in an animal model and clinical trial.45,46”
From Fecal microbiota transplantation: Review and update (2019) · cites this paper as [45]
In the citing paper
“Responses to ICTs have been correlated with commensal gut flora, and there appear to be substantial differences in the diversity and composition in patients who respond to ICT versus nonresponders (205,206).”
From The Next Decade of Immune Checkpoint Therapy (2021) · cites this paper as [206]
In the citing paper
“Moreover, observations in humans and mice of gut microbes that stratify therapy response, particularly immunotherapy (16, 17, 21, 26), have not uncommonly shown varying taxonomic differences that persist despite uniform bioinformatic re-analyses, although there is greater concordance when examining functional profiles (161, 162).”
From The microbiome and human cancer (2021) · cites this paper as [16]
In the citing paper
“Recent data have shown that commensal microbiota can affect the outcomes of immunotherapeutic interventions in human cancers (Gopalakrishnan et al., 2018; Routy et al., 2018).”
From Commensal Microbiota Promote Lung Cancer Development via γδ T Cells (2019) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“The microbiome has been described to majorly impact tumor immunity and response to ICI10–17”
From Dietary tryptophan metabolite released by intratumoral Lactobacillus reuteri facilitates immune checkpoint inhibitor treatment (2023) · cites this paper as [16]
In the citing paper
“and additionally showed that modulation of the gut microbiome of germ-free mice via FMT from patients could alter anti-tumor immunity and response to ICI therapy in gnotobiotic mice11–13.”
From Fecal microbiota transplantation for refractory immune checkpoint inhibitor-associated colitis (2018) · cites this paper as [11]
In the citing paper
“Previously, we demonstrated that differential bacterial signatures comprise the gut microbiome of responders versus non-responders to ICI therapy”
From Fecal microbiota transplantation for refractory immune checkpoint inhibitor-associated colitis (2018) · cites this paper as [11]
In the citing paper
“The gut microbiota influences the clinical responses of cancer patients to immunecheckpoint inhibitors (ICIs).”
From Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome (2024) · cites this paper as [8]
In the citing paper
“Indeed, clinical benefit to immune-checkpoint inhibitors (ICIs) or chimeric antigen receptor-T cell therapy has been linked to the presence or absence of distinct intestinal commensals across various malignancies.”
From Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome (2024) · cites this paper as [8]
In the citing paper
“SIG2 contained Lachnospiraceae (species from the genus Blautia, Roseburia, Dorea, and Eubacterium) and Oscillospiraceae family members (Faecalibacterium prausnitzii, Ruminococcus bicirculans, and R. lactaris), which were previously associated with general health and favorable clinical responses to ICIs.”
From Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome (2024) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Instead, SIG2 was composed of 45 species gathering Lachnospiraceae and Oscillospiraceae family members that are strongly associated with healthy status and favorable clinical responses.4”
From Custom scoring based on ecological topology of gut microbiota associated with cancer immunotherapy outcome (2024) · cites this paper as [8]
In the citing paper
“A high level of Faecalibacterium prausnitzii have been associated with a positive response to ICI in multiple cancer types.”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“Simultaneously, a second study on 43 patients with metastatic melanoma treated with anti-PD-1 agents showed the same results, with high F. prausnitzii relative abundance reported as the strongest signal of response to ICI.6”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“A meta-analysis found that high abundance of Faecalibacterium genus was the strongest signal associated with response to ICI, using either anti-PD-1 or anti-CTLA-4 antibodies.5–7,12,13”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“There is thus increasing evidence to suggest that the abundance of F. prausnitzii in the gut may impact clinical response to ICI across multiple cancers.”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“Interestingly, the positive response to ICI in this context was also associated with higher F. prausnitzii levels.6”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“A causality link was then established by showing that mice colonized with microbiota from human patients that responded to ICI had a better response to ICI in a melanoma model than their counterparts colonized with the microbiota from non-responders.6”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“In this context, the gut microbiota has been involved in response to cancer treatments, and in particular to immunotherapy.2,6,7,32”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“In patients with cancer, specific taxa, including F. prausnitzii, A. muciniphila and Bifidobacteria, have been associated with improved clinical responses to ICI.2,6,7”
From Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors (2024) · cites this paper as [6]
In the citing paper
“The effects of the gut microbiota on the anti-tumor response has been demonstrated in preclinical models as well as in patients with melanoma, renal cell carcinoma and NSCLC”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“The gut and tumor microbiome have been associated with anti-tumor responses and, in some cases, response to immune checkpoint blockade”
From Hallmarks of response, resistance, and toxicity to immune checkpoint blockade (2021) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Tumor-challenged mice that received FMT from patients responsive to anti-PD-1 had significantly reduced tumor growth compared with mice receiving FMT from nonresponders (Derosa et al., 2020; Gopalakrishnan et al., 2018; Routy et al., 2018b).”
From Microbiota-centered interventions to boost immune checkpoint blockade therapies (2025) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Certain bacteria are linked to favorable outcomes, including the mucin-consuming anaerobic bacterium Akkermansia muciniphila (Derosa et al., 2022; Routy et al., 2018b), Faecalibacterium prausnitzii (Gopalakrishnan et al., 2018), and Bifidobacterium spp. (Sivan et al., 2015), particularly Bifidobacterium longum (Matson et al., 2018).”
From Microbiota-centered interventions to boost immune checkpoint blockade therapies (2025) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Thomas Gajewski in Chicago, Jennifer Wargo at the MD Anderson Cancer Centre, and our laboratory at the Gustave Roussy Cancer Centre in Paris later published seminal studies in the same 2018 issue of Science, demonstrating direct links between gut microbiota composition and the success of ICB in different cancer populations, including melanoma, non–small-cell lung cancer (NSCLC), and urothelial and”
From Microbiota-centered interventions to boost immune checkpoint blockade therapies (2025) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“However, although indices like Shannon or Chao1 can show that immunotherapy responders possess greater microbial diversity (Gopalakrishnan et al., 2018), it has become clear that these metrics alone do not fully capture how individual taxa drive or mitigate disease outcomes, as evident in lung or kidney cancer patients (Gupta et al., 2020).”
From Microbiota-centered interventions to boost immune checkpoint blockade therapies (2025) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“higher abundances of the commensals Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium stimulate a more favorable T cell-mediated response to anti-PD-1 therapy in both preclinical models and patients suffering from metastasized melanoma.190–192”
From Interaction between microbiota and immunity in health and disease (2020) · cites this paper as [191]
In the citing paper
“For instance, broad-spectrum antibiotic treatment reduced the intestinal abundances of microbes in our patients such as Roseburia, Bifidobacterium or Ruminococcus spp., which were previously associated with beneficial outcomes of ICB cancer immunotherapies1,36.”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [1]
In the citing paper
“Increasing evidence suggests that the gut microbiome may modulate the efficacy of cancer immunotherapy.”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [1]
In the citing paper
“Gut microbes such as Akkermansia muciniphila, Faecalibacterium prausnitzii and Bifidobacterium longum have been associated with improved responses to immune checkpoint blockade (ICB)1–3”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [1]
In the citing paper
“For instance, broad-spectrum antibiotic treatment reduced the intestinal abundances of microbes in our patients such as Roseburia, Bifidobacterium or Ruminococcus spp., which were previously associated with beneficial outcomes of ICB cancer immunotherapies1,36.”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [1]
In the citing paper
“There is mounting evidence supporting the role of the microbiome in response to cancer therapy”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“several recent studies demonstrating the influence of the gut microbiome specifically on the response to immune checkpoint blockade across cancer types”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“NR had significantly lower diversity of gut bacteria and higher abundance of Bacteroidales”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“patients who responded to anti-PD-1 therapy had a significantly higher diversity of bacteria in their gut microbiota as well as a higher relative abundance of Clostridiales, Ruminococcaceae, and Faecalibacterium”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“patients with a “favorable” gut microbiota had increased expression of cytolytic T cell markers and antigen processing and presentation compared to patients with “unfavorable” gut microbiota”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“multiple studies published in the past several months demonstrating a role for the gut microbiota in patients on immune checkpoint blockade”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“mice receiving FMT from R had significantly delayed tumor outgrowth and enhanced response to treatment with immune checkpoint blockade”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Bacterial taxa within the Ruminococaceae family of the Firmicutes phylum (such as F. prausnitzii) have been associated with both response and toxicity to immune checkpoint blockade across studies”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Bacteroidetes have also been associated with response (such as Akkermansia muciniphila, Bifidobacterium longum and Bifidobacterium adolescentis, and Colinsela aerofaciens) and non-response (such as Actinomyces viscosus, Garnderella vaginalis) (Frankel et al., 2017, Gopalakrishnan et al., 2018, Matson et al., 2018, Routy et al., 2018).”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“bacterial taxa within the Bacteroidales order of the Bacteroidetes phylum have been associated with a lack of response to immune checkpoint blockade (Bacteroidales), while a higher abundance of these taxa within the gut are also generally associated with a lower incidence of toxicity”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“The microbiota is emerging as a determinant of responses to various anticancer therapies, including immunotherapy122–125.”
From Enhancing cancer immunotherapy using antiangiogenics: opportunities and challenges (2018) · cites this paper as [123]
In the citing paper
“Similar findings for anti-PD-1 therapy have been reported, although different microbes have been implicated (100, 101).”
From Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance (2021) · cites this paper as [100]
In the citing paper
“Significant differences in microbial diversity and composition have been noted between responding and non-responding melanoma patients treated with anti-PD-1 therapy; different studies suggest different species may be enriched in responding versus non-responding patients [30, 31].”
From Immune-related adverse events and anti-tumor efficacy of immune checkpoint inhibitors (2019) · cites this paper as [30]
In the citing paper
“Furthermore, mice transplanted with stool from responding patients also had higher levels of CD8 T-cell concentrations in the gut than those transplanted with stool from non-responders.”
From Immune-related adverse events and anti-tumor efficacy of immune checkpoint inhibitors (2019) · cites this paper as [30]
In the citing paper
“Mice that were transplanted with stool from patients responding to anti-PD-1 antibodies had higher levels of CD8 T-cell density in tumor tissue.”
From Immune-related adverse events and anti-tumor efficacy of immune checkpoint inhibitors (2019) · cites this paper as [30]
In the citing paper
“A recent publication cited above suggests IRAE sites associated with ICI efficacy may have more to do with shared antigens between tumor and involved site rather than any intrinsic association between checkpoint inhibitor and IRAE site [30].”
From Immune-related adverse events and anti-tumor efficacy of immune checkpoint inhibitors (2019) · cites this paper as [30]
In the citing paper
“They showed an abundance of Clostridiales/Ruminococcaceae/Faecalibacterium in R and Bacteroidales/Escherichia coli in NR (Figure 2) (57).”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [57]
In the citing paper
“Moreover, Gopalakrishnan et al. (57) evaluated the oral and gut microbiome of 112 melanoma patients treated with PD-1 blockade via 16S sequencing and discovered a higher multiplicity of bacteria in patients with prolonged PFS.”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [57]
In the citing paper
“In contrast, patients with more NR microorganisms often had a shortened PFS and a higher level of Tregs with a blunted cytokine response.”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [57]
In the citing paper
“Compared to NR-FMT mice, transplantation of fecal microbiota from R patients delayed tumor growth, increased the accumulation of CXCR3CD4+ T cells and CD8+ T cells, and upregulated PD-L1 expression in the TME, thereby counteracting the impaired anticancer ability against PD-L1 blockade.”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [57]
In the citing paper
“Patients with more Faecalibacterium also had a significantly prolonged PFS with higher level of effector T cells and a stabilized cytokine response to PD-1 blockade.”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [57]
In the citing paper
“Multiple translational studies, published in 2018, further support the pivotal role of the gut microbiome in modulating the response to immune checkpoint blockade [170,171,172].”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [171]
In the citing paper
“Functional studies performed with FMT in germ free mice further demonstrated how treating mice with the identified bacteria, along with the anti-PD1 therapy, enhanced the anti-cancer effects and reduces the melanoma growth [171].”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [171]
In the citing paper
“In parallel, Gopalakrishnan et al. [171] demonstrated through metagenomics analysis of melanoma patients’ fecal samples that the anti-PD1 responders’ microbiome was different in composition compared with that of non-responders.”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [171]
In the citing paper
“Given the multiplicity of effects that gut microbiome may play on the host’s immune system, it is not surprising that emerging studies strongly linked the patients’ microbiome composition with the intrinsic efficacy of immune checkpoint inhibitors-based immunotherapy, in the treatments of different solid tumors [170,171,172].”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [171]
In the citing paper
“The authors observed in patient’s gut microbiome an increase in the abundance of Clostridiales, Ruminococcaceae and Faecalibacteriae.”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [171]
In the citing paper
“recent studies confirm the potential importance of patient stratification on the basis of gut microbiome composition to identify responders and nonresponders to immunotherapy for the treatment of epithelial tumors and melanomas (Gopalakrishnan et al., 2018;Jobin, 2018;Routy et al., 2018)”
From Gut reactions: Breaking down xenobiotic–microbiome interactions (2019) · cites this paper as Gopalakrishnan et al., 2018
In the citing paper
“Besides, manipulating gut microbiota composition could improve the response to α-PD-1/PD-L1 [311, 314–316].”
From Combination strategies with PD-1/PD-L1 blockade: current advances and future directions (2022) · cites this paper as [315]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients
“A similar pattern was also noted for KO-abundances with 70.6% and 37.5% response rates (fig. S17).”
§ Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients
“metagenomic WGS sequencing (n=25) in R (n=14) vs NR (n=11).”
Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
Fast gapped-read alignment with Bowtie 2
Langmead, B., & Salzberg, S. L. (2012) · Nature Methods · doi:10.1038/nmeth.1923 · Cited by 56,400
A Mathematical Theory of Communication
Shannon, C. E. (1948) · The MIT Press eBooks · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 50,387
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077
QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
The SILVA ribosomal RNA gene database project: improved data processing and web-based tools
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., & Glöckner, F. O. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1219 · Cited by 33,055
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,989
The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M., et al. (2010) · Genome Research · doi:10.1101/gr.107524.110 · Cited by 27,895
Research works printed but not linked: 3
- 10.1145/584091.584093 · DOI
- N. Pons J.-M. Batto S. Kennedy M. Almeida F. Boumezbeur paper presented at the Annual Conference of the JOBIM (Journées Ouvertes en Biologie Informatique et Mathématique) Montpellier France 7 to 9 September 2010.
- National Research Council Guide for the Care and Use of Laboratory Animals (National Academies Press ed. 8 2011) pp. 1–220.
Cited by
Sorted by citations
Items 401–500 of 4,878
The Role of Gut Microbial β-Glucuronidase in Estrogen Reactivation and Breast Cancer
Sui, Y., Wu, J., & Chen, J. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.631552 · Cited by 175
The Impact of the Microbiome on Immunity to Vaccination in Humans
de Jong, S. E., Olin, A., & Pulendran, B. (2020) · Cell Host & Microbe · doi:10.1016/j.chom.2020.06.014 · Cited by 160
GMrepo: a database of curated and consistently annotated human gut metagenomes
Wu, S., Sun, C., Li, Y., Wang, T., Jia, L., Lai, S., Yang, Y., Luo, P., Dai, D., Yang, Y.-Q., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz764 · Cited by 158
Self-citationGut microbes impact stroke severity via the trimethylamine N-oxide pathway
Zhu, W., Romano, K. A., Li, L., Buffa, J. A., Sangwan, N., Prakash, P., Tittle, A. N., Li, X. S., Fu, X., Androjna, C., et al. (2021) · Cell Host & Microbe · doi:10.1016/j.chom.2021.05.002 · Cited by 167
Modulating inflammation for cancer therapy
Ritter, B., & Greten, F. R. (2019) · The Journal of Experimental Medicine · doi:10.1084/jem.20181739 · Cited by 162
Halsey, T. M., Thomas, A. S., Hayase, T., Ma, W., Abu-Sbeih, H., Sun, B., Parra, E. R., Jiang, Z.-D., DuPont, H. L., Sanchez, C., et al. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.abq4006 · Cited by 161
Self-citationImmuno-Metabolism and Microenvironment in Cancer: Key Players for Immunotherapy
Giannone, G., Ghisoni, E., Genta, S., Scotto, G., Tuninetti, V., Turinetto, M., & Valabrega, G. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21124414 · Cited by 159
“The most relevant ones are if the dose used was sufficient to inhibit IDO1 activity in the TME (with pharmacodynamical data on IDO1 inhibition from Phase I trials only giving an indirect suggestion of activity) and, above all, if targeting only IDO1 is sufficient to control tryptophan catabolism or if the use of a dua…”
BackgroundInfluentialChng, K. R., Ghosh, T. S., Tan, Y. H., Nandi, T., Lee, I. R., Ng, A. H. Q., Li, C., Ravikrishnan, A., Lim, K. M., Lye, D. C., et al. (2020) · Nature Ecology & Evolution · doi:10.1038/s41559-020-1236-0 · Cited by 171
Immune-related adverse events in various organs caused by immune checkpoint inhibitors
Okiyama, N., & Tanaka, R. (2022) · Allergology International · doi:10.1016/j.alit.2022.01.001 · Cited by 170
Immunotherapy for Malignant Glioma: Current Status and Future Directions
Wang, H., Xu, T., Huang, Q., Jin, W., & Chen, J. (2020) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2019.12.003 · Cited by 159
Rizvi, Z. A., Dalal, R., Sadhu, S., Kumar, Y., Kumar, S., Gupta, S. K., Tripathy, M. R., Rathore, D. K., & Awasthi, A. (2021) · Science Advances · doi:10.1126/sciadv.abg5016 · Cited by 160
Modulating gut microbiome in cancer immunotherapy: Harnessing microbes to enhance treatment efficacy
Kang, X., Lau, H. C.-H., & Yu, J. Q. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101478 · Cited by 172
Gut Microbiota-Derived Short-Chain Fatty Acids: Impact on Cancer Treatment Response and Toxicities
Al-Qadami, G. H., Secombe, K. R., Subramaniam, C. B., Wardill, H. R., & Bowen, J. M. (2022) · Microorganisms · doi:10.3390/microorganisms10102048 · Cited by 162
“[1] clearly showed significant differences in both the diversity and composition of the gut microbiota of people who responded to PD-1 inhibitor immunotherapy for melanoma compared to non-responders.”
BackgroundProto, C., Ferrara, R., Signorelli, D., Russo, G. L., Galli, G., Imbimbo, M., Prelaj, A., Zilembo, N., Ganzinelli, M., Pallavicini, L. M., et al. (2019) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2019.03.004 · Cited by 158
Synthetic bacterial vesicles combined with tumour extracellular vesicles as cancer immunotherapy
Park, K., Svennerholm, K., Crescitelli, R., Lässer, C., Gribonika, I., & Lötvall, J. O. (2021) · Journal of Extracellular Vesicles · doi:10.1002/jev2.12120 · Cited by 161
Immunotherapy for osteosarcoma: Where do we go from here?
Wedekind, M. F., Wagner, L. M., & Cripe, T. P. (2018) · Pediatric Blood & Cancer · doi:10.1002/pbc.27227 · Cited by 163
Zheng, D., Deng, W., Song, W., Wu, C., Liu, J., Hong, S., Zhuang, Z., Cheng, H. L., Sun, Z., & Zhang, X. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00807-9 · Cited by 163
Fecal Microbiota Transplantation as New Therapeutic Avenue for Human Diseases
Biazzo, M., & Deidda, G. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11144119 · Cited by 172
Microbiota and cancer immunotherapy: in search of microbial signals
Gharaibeh, R. Z., & Jobin, C. (2019) · Gut · doi:10.1136/gutjnl-2018-317220 · Cited by 144
Molecular mechanisms of the preventable causes of cancer in the United StatesPreprint
Golemis, E. A., Scheet, P. A., Beck, T. N., Scolnick, E. M., Hunter, D. J., Hawk, E. T., & Hopkins, N. H. (2018) · Genes & Development · doi:10.1101/gad.314849.118 · Cited by 164
Opzoomer, J. W., Sosnowska, D., Anstee, J. E., Spicer, J. F., & Arnold, J. N. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.01654 · Cited by 155
“Since robust immune-mediated tumor killing can be unmasked in a subset of patients through the use of ICIs in the absence of CCTs (50), and the rare cases of spontaneous tumor remission (51), it is likely that ICD can also occur without the need for an adjuvant.”
BackgroundInfluentialWilson, B. E., Routy, B., Nagrial, A., & Chin, V. T. (2020) · Cancer Immunology, Immunotherapy · doi:10.1007/s00262-019-02453-2 · Cited by 152
Artacho, A., Isaac, S., Nayak, R. R., Flor‐Duro, A., Alexander, M., Koo, I., Manasson, J., Smith, P. B. W., Rosenthal, P., Homsi, Y., et al. (2020) · Arthritis & Rheumatology · doi:10.1002/art.41622 · Cited by 162
Dietary Lactobacillus -Derived Exopolysaccharide Enhances Immune-Checkpoint Blockade Therapy
Kawanabe-Matsuda, H., Takeda, K., Nakamura, M., Makino, S., Karasaki, T., Kakimi, K., Nishimukai, M., Ohno, T., Omi, J., Kano, K., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0929 · Cited by 158
“Host gut microbiota is now established as one of critical parameters to improve or impair the efficacy of ICB therapies (10–13).”
Genomics and emerging biomarkers for immunotherapy of colorectal cancer
Kather, J. N., Halama, N., & Jaeger, D. (2018) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2018.02.010 · Cited by 154
Gut Microbiota Modulation on Intestinal Mucosal Adaptive Immunity
Wang, L., Zhu, L., & Qin, S. (2019) · Journal of Immunology Research · doi:10.1155/2019/4735040 · Cited by 157
“FMT in GF mice has demonstrated that activation of Th17 cells and the polarization of IL-17A production in the tumor microenvironment are essentially mediated by components of the microbiota [43].”
BackgroundVitamin D regulates microbiome-dependent cancer immunity
Giampazolias, E., Pereira da Costa, M., Lam, K. C., Lim, K. H. J., Cardoso, A., Piot, C., Chakravarty, P., Blasche, S., Patel, S., Biram, A., et al. (2024) · Science · doi:10.1126/science.adh7954 · Cited by 151
Self-citationGlaviano, A., Lau, H., Carter, L. M., Lee, E. H. C., Lam, H. Y., Okina, E., Tan, D. J. J., Tan, W., Ang, H. L., Carbone, D., et al. (2025) · Journal of Hematology & Oncology · doi:10.1186/s13045-024-01634-6 · Cited by 169
Towards modulating the gut microbiota to enhance the efficacy of immune-checkpoint inhibitors
Simpson, R. C., Shanahan, E. R., Scolyer, R. A., & Long, G. V. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00803-9 · Cited by 153
Hu, Y., Li, J., Ni, F., Yang, Z., Gui, X., Bao, Z., Zhao, H., Wei, G., Wang, Y., Zhang, M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32960-3 · Cited by 155
“…fecal samples from 43 melanoma patients treated with anti-programmed cell death 1 protein (PD-1) immunotherapy, signi fi cantly higher alpha diversity and abundance of Clostridiales/Ruminococcaceae were found in responders, whereas Bacteroidales were signi fi cantly enriched in non-responders 19 .”
BackgroundInfluentialPD-1 blockade exacerbates Mycobacterium tuberculosis infection in rhesus macaques
Kauffman, K. D., Sakai, S., Lora, N. E., Namasivayam, S., Baker, P. J., Kamenyeva, O., Foreman, T. W., Nelson, C. E., Oliveira-de-Souza, D., Vinhaes, C. L., et al. (2021) · Science Immunology · doi:10.1126/sciimmunol.abf3861 · Cited by 151
“Of note, the abundance of Ruminococcaceae has previously been reported to associate with tumor reductions after PD-1 blockade (29), and here this family was strongly enriched in the monkeys that developed increased Mtb burdens after PD-1 blockade.”
BackgroundThe molecular and functional landscape of resistance to immune checkpoint blockade in melanoma
Lim, S. Y., Shklovskaya, E., Lee, J., Pedersen, B., Stewart, A., Ming, Z., Irvine, M., Shivalingam, B., Saw, R. P. M., Menzies, A. M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36979-y · Cited by 161
Self-citationLongitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma
Björk, J. R., Bolte, L. A., Maltez Thomas, A., Lee, K. A., Rossi, N., Wind, T. T., Smit, L. M., Armanini, F., Asnicar, F., Blanco-Miguez, A., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02803-3 · Cited by 156
“For example, Thomas et al. 21 found that Eubacterium sp. AM28 29 (SGB6796 group) was associated with response in nine melanoma cohorts, four of which were not included in our study 5,9,11,36 .”
Self-citationGut Microbiota, Fusobacteria, and Colorectal Cancer
Kelly, D., Yang, L., & Pei, Z. (2018) · Diseases · doi:10.3390/diseases6040109 · Cited by 152
Vernocchi, P., Gili, T., Conte, F., CHIERICO, F. D., Conta, G., Miccheli, A., Botticelli, A., Paci, P., Caldarelli, G., Nuti, M., et al. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21228730 · Cited by 155
“Recently, several studies suggested the role of the GM in modulating patient response to immunotherapy in cancer [16,17,36,62,63].”
BackgroundGuo, W., Zhang, Y., Guo, S., Mei, Z., Liao, H., Dong, H. Y., Wu, K., Ye, H., Zhang, Y., Zhu, Y., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-02557-5 · Cited by 150
Self-citationNutritional regulation of microbiota-derived metabolites: Implications for immunity and inflammation
Arifuzzaman, M., Collins, N., Guo, C., & Artis, D. (2024) · Immunity · doi:10.1016/j.immuni.2023.12.009 · Cited by 159
Metabolic programs tailor T cell immunity in viral infection, cancer, and aging
Møller, S. H., Hsueh, P., Yu, Y.-R., Zhang, L., & Ho, P. (2022) · Cell Metabolism · doi:10.1016/j.cmet.2022.02.003 · Cited by 154
Zhu, G., Su, H., Johnson, C. H., Khan, S. A., Kluger, H. M., & Lu, L. (2021) · European Journal of Cancer · doi:10.1016/j.ejca.2021.03.053 · Cited by 150
The effect of physical exercise on anticancer immunity
Fiuza‐Luces, C., Valenzuela, P. L., Gálvez, B. G., Ramírez, M. R., López‐Soto, A., Simpson, R. J., & Lucía, A. (2023) · Nature reviews. Immunology · doi:10.1038/s41577-023-00943-0 · Cited by 164
“For example, a higher alpha diversity with a high abundance of Faecalibacterium has been associated with enhanced systemic and local antitumour immunity, mediated through increased antigen presentation and improved effector T cell function in the blood and the tumour microenvironment 96 .”
Sipos, A., Ujlaki, G., Mikó, E., Maka, E., Szabó, J., Uray, K., Krasznai, Z. T., & Bai, P. (2021) · Molecular Medicine · doi:10.1186/s10020-021-00295-2 · Cited by 153
“In contrast, a more immunogenic microbiome supports immunotherapy (Routy et al. 2018a; Gopalakrishnan 2018), but in turn induce higher oxidative stress and increase the risk for mutations and may sustain tumorigenic inflammation (Buchta Rosean et al.”
BackgroundHayase, E., & Jenq, R. R. (2021) · Genome Medicine · doi:10.1186/s13073-021-00923-w · Cited by 145
“Ruminococcaceae family members in melanoma patients responding to anti-PD-1 antibody [26].”
BackgroundSelf-citationThe breakthrough of the microbiota
Kroemer, G., & Zitvogel, L. (2018) · Nature Reviews Immunology · doi:10.1038/nri.2018.4 · Cited by 147
Self-citationSfanos, K. S., Markowski, M. C., Peiffer, L. B., Ernst, S. E., White, J. R., Pienta, K. J., Antonarakis, E. S., & Ross, A. E. (2018) · Prostate Cancer and Prostatic Diseases · doi:10.1038/s41391-018-0061-x · Cited by 151
“Much excitement has been generated after the publication of a series of human studies in melanoma patients [9, 11] and in patients with epithelial tumors [10], all indicating that the presence of certain types of bacteria including Ruminococcaceae, Bifidobacteriaceae, and Akkermansia muciniphila are associated with a…”
BackgroundGut microbiota shapes cancer immunotherapy responses
Lei, W., Zhou, K., Lei, Y., Li, Q., & Zhu, H. (2025) · npj Biofilms and Microbiomes · doi:10.1038/s41522-025-00786-8 · Cited by 182
“Currently,ICIshavebeenwidelyusedinthe treatmentofavarietyofcancers.”
InfluentialCancer Immunotherapy: Beyond Checkpoint Blockade
Dougan, M. L., Dranoff, G., & Dougan, S. K. (2018) · Annual Review of Cancer Biology · doi:10.1146/annurev-cancerbio-030518-055552 · Cited by 151
“…to checkpoint blockade is dependent on the microbiome (Sivan et al. 2015, Vetizou et al. 2015), and experiments to establish whether the microbiome correlates with immunotherapy response in patients have shown similar results (Gopalakrishnan et al. 2018, Matson et al. 2018, Routy et al. 2018).”
ResultSantiago-Rodríguez, T. M., & Hollister, E. B. (2019) · Viruses · doi:10.3390/v11070656 · Cited by 150
(2020) · doi:10.1101/2020.11.19.388223 · Cited by 2,303
“…mechanisms of multi-organism biochemical responses in the environment (Alivisatos et al., 2015; Blaser et al., 2016) , or the epidemiology of the human microbiome for biomarkers and therapy (Gopalakrishnan et al., 2018; Le Chatelier et al., 2013; Thomas et al., 2019; Zeller et al., 2014) .”
BackgroundWang, T., Zheng, N., Luo, Q., Jiang, L., He, B., Yuan, X., & Shen, L. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.01235 · Cited by 148
Strain-level epidemiology of microbial communities and the human microbiome
Yan, Y., Nguyen, L. H., Franzosa, E. A., & Huttenhower, C. (2020) · Genome Medicine · doi:10.1186/s13073-020-00765-y · Cited by 152
Mikulak, J., Oriolo, F., Bruni, E., Roberto, A., Colombo, F., VILLA, A. M., Bosticardo, M., Bortolomai, I., Presti, E. L., Meraviglia, S., et al. (2019) · JCI Insight · doi:10.1172/jci.insight.125884 · Cited by 145
“Results are represented as the fold change (2) of target gene relative to a Ctrl samples and normalized to housekeeping genes GAPDH and S18.”
BackgroundInfluentialMuzaffar, J., Bari, S., Kirtane, K., & Chung, C. H. (2021) · Cancers · doi:10.3390/cancers13020338 · Cited by 152
“Microbiome diversity was also greater among responders, and fecal microbiota transplant (FMT) of these organisms into germ-free mice led to increased responses [102].”
BackgroundThe gut microbiome: what the oncologist ought to know
Lee, K. A., Luong, M., Shaw, H. M., Nathan, P., Bataille, V. A., & Spector, T. D. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01467-x · Cited by 154
“faecal samples from melanoma patients, that the anti-PD-1 responders’ GM was different in composition compared to nonresponders [59].”
BackgroundResultTeh, J. L. F., & Aplin, A. E. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-1967 · Cited by 148
Microbiome dysbiosis in lung cancer: from composition to therapy
Liu, N., Ma, Q., Ge, Y., Yi, C., Wei, L., Tan, J.-C., Chu, Q., Li, J., Zhang, P., & Wang, H. (2020) · npj Precision Oncology · doi:10.1038/s41698-020-00138-z · Cited by 148
Wu, H., Leng, X., Liu, Q., Mao, T., Jiang, T., Liu, Y., Li, F., Cao, C., Fan, J., Chen, L., et al. (2023) · Cancer Research · doi:10.1158/0008-5472.can-22-2593 · Cited by 154
The model of cytokine release syndrome in CAR T-cell treatment for B-cell non-Hodgkin lymphoma
Wei, J., Liu, Y., Wang, C., Zhang, Y., Tong, C., Dai, G., Wang, W., Rasko, J. E. J., Melenhorst, J. J., Qian, W., et al. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00256-x · Cited by 146
Self-citationZhang, J., Zhang, F., Zhao, C., Xu, Q., Liang, C., Yang, Y., Wang, H., Shang, Y., Wang, Y., Mu, X., et al. (2018) · Endocrine · doi:10.1007/s12020-018-1831-x · Cited by 146
Self-citationHallmarks of Resistance to Immune-Checkpoint Inhibitors
Karasarides, M., Cogdill, A. P., Robbins, P. B., Bowden, M., Burton, E. M., Butterfield, L. H., Cesano, A., Hammer, C., Haymaker, C., Horak, C. E., et al. (2022) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-20-0586 · Cited by 154
“Efforts to better understand gut microbiome signatures associated with ICI resistance include shotgun metagenomic sequencing of patient stools at diagnosis, with samples currently being evaluated in metastatic melanoma (148), kidney (149), and lung cancers (142).”
BackgroundSelf-citationGut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy
Thomas, A. M., Fidelle, M., Routy, B., Kroemer, G., Wargo, J. A., Segata, N., & Zitvogel, L. (2023) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-023-00785-8 · Cited by 141
Self-citationThe intimate relationship between gut microbiota and cancer immunotherapy
Elkrief, A., Derosa, L., Zitvogel, L., Kroemer, G., & Routy, B. (2018) · Gut Microbes · doi:10.1080/19490976.2018.1527167 · Cited by 143
“were overrepresented in responder patients.(18) Further confirming that the gut microbiome composition influences clinical response in melanoma patients, Matson et al.”
BackgroundSelf-citationOptimizing therapeutic outcomes of immune checkpoint blockade by a microbial tryptophan metabolite
Renga, G., Nunzi, E., Pariano, M., Puccetti, M., Bellet, M. M., Pieraccini, G., D’Onofrio, F., Santarelli, I., Stincardini, C., Aversa, F., et al. (2022) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2021-003725 · Cited by 147
Emerging roles of intratumor microbiota in cancer metastasis
Fu, A., Yao, B., Dong, T., & Cai, S. (2022) · Trends in Cell Biology · doi:10.1016/j.tcb.2022.11.007 · Cited by 146
Dall’Olio, F. G., Rizzo, A., Mollica, V., Massucci, M., Maggio, I., & Massari, F. (2020) · Immunotherapy · doi:10.2217/imt-2020-0179 · Cited by 140
Butyrate as a promising therapeutic target in cancer: From pathogenesis to clinic (Review)
Sun, J., Chen, S., Zang, D., Sun, H., Sun, Y., & Chen, J. (2024) · International Journal of Oncology · doi:10.3892/ijo.2024.5632 · Cited by 157
Advances and prospects of biomarkers for immune checkpoint inhibitors
Yamaguchi, H., Hsu, J.-M., Sun, L., Wang, S., & Hung, M. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101621 · Cited by 152
Core Gut Bacteria Analysis of Healthy Mice
Wang, J., Lang, T., Shen, J., Dai, J., Tian, L., & Wang, X. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.00887 · Cited by 141
The Tumor Microbiome in Pancreatic Cancer: Bacteria and Beyond
McAllister, F. M., Khan, M. A. W., Helmink, B. A., & Wargo, J. A. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.11.004 · Cited by 143
Self-citationColorectal cancer and gut microbiota studies in China
Wang, Z., Dan, W., Zhang, N., Fang, J., & Yang, Y. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2236364 · Cited by 151
Role of the microbiota in response to and recovery from cancer therapy
Blake, S. J., Wolf, Y., Boursi, B., & Lynn, D. J. (2023) · Nature reviews. Immunology · doi:10.1038/s41577-023-00951-0 · Cited by 151
The microbiome and breast cancer: a review
Chen, J. H., Douglass, J., Prasath, V., Neace, M., Atrchian, S., Manjili, M. H., Shokouhi, S., & Habibi, M. (2019) · Breast Cancer Research and Treatment · doi:10.1007/s10549-019-05407-5 · Cited by 137
Microbial markers in colorectal cancer detection and/or prognosis
Villéger, R., Lopès, A., Véziant, J., Gagnière, J., Barnich, N., Billard, E., Boucher, D., & Bonnet, M. (2018) · World Journal of Gastroenterology · doi:10.3748/wjg.v24.i22.2327 · Cited by 146
Short-chain fatty acids in cancer pathogenesis
Feitelson, M. A., Arzumanyan, A. L., Medhat, A., & Spector, I. (2023) · Cancer and Metastasis Reviews · doi:10.1007/s10555-023-10117-y · Cited by 151
“…between the gut microbiota and immunotherapy was highlighted by findings that antibiotic treatment negatively impacted the clinical outcome of immunotherapy with anti-PD-1/PD-L1 [160] and that this was associated with a reduced abundance of gut bacteria that normally produce SCFAs [161, 162].”
BackgroundZhao, W., Lei, J., Ke, S., Chen, Y., Xiao, J., Wang, L., Wang, L., Ren, Y., Alnaggar, M., Qiu, H., et al. (2023) · EClinicalMedicine · doi:10.1016/j.eclinm.2023.102315 · Cited by 156
“19,35,36 Baruch et al. conducted a phase I trial to evaluate the combination of FMT and re-induction of ICIs in 10 patients with anti-PD-1-refractory metastatic melanoma, with 2 PR and 1 CR observed.”
BackgroundNext-generation probiotics: a promising approach towards designing personalized medicine
Singh, T. P., & Nataraj, B. H. (2021) · Critical Reviews in Microbiology · doi:10.1080/1040841x.2021.1902940 · Cited by 150
“…blockade (ICB) therapy used for tumour amelioration which is evident from the increased CD8þ T-cell infiltration within the tumour environment in addition to the enhanced frequency of effector CD4þ and CD8þ T-cells in the periphery (Chaput et al. 2017; Gopalakrishnan et al. 2018; Park et al. 2018).”
BackgroundDaisley, B. A., Chanyi, R. M., Abdur-Rashid, K., Al, K. F., Gibbons, S., Chmiel, J. A., Wilcox, H., Reid, G., Anderson, A., Dewar, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18649-5 · Cited by 128
“The three PC patient groups examined included (1) patients not receiving any active treatment, (2) patients receiving ADT alone, and (3) patients receiving both ADT and treatment with orally administered AA.”
Role of gut microbiome in cancer immunotherapy: from predictive biomarker to therapeutic target
Zhang, M., Liu, J., & Xia, Q. (2023) · Experimental Hematology and Oncology · doi:10.1186/s40164-023-00442-x · Cited by 153
“A higher density of immune cells and antigen processing/presentation markers were found in patients with high enrichment of Faecalibacterium [29].”
BackgroundInfluentialMohiuddin, J. J., Chu, B. K., Facciabene, A., Poirier, K., Wang, X., Doucette, A. G., Zheng, C., Xu, W., Anstadt, E. J., Amaravadi, R. K., et al. (2020) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djaa057 · Cited by 141
The microbiome and cancer for clinicians
Picardo, S. L., Coburn, B. A., & Hansen, A. R. (2019) · Critical Reviews in Oncology/Hematology · doi:10.1016/j.critrevonc.2019.06.004 · Cited by 141
Cascone, T., Kar, G., Spicer, J. D., García-Campelo, R., Weder, W., Daniel, D. B., Spigel, D. R., Hussein, M., Mazières, J., Oliveira, J., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-0436 · Cited by 142
“The association between microbiome and response was not as profound as reported in other studies (27, 28, 33), which may be influenced by the global geography of the NeoCOAST patient population; the microbial composition would likely be less homogeneous than restricted to a smaller geographic area.”
Self-citationCurrent and future perspectives of PD-1/PDL-1 blockade in cancer immunotherapy
Makuku, R., Khalili, N., Razi, S., Keshavarz-Fathi, M., & Rezaei, N. (2021) · Journal of Immunology Research · doi:10.1155/2021/6661406 · Cited by 136
“Similar findings were observed in the gut microbiome profile of patients with hepatocellular carcinoma (HCC) [109] and melanoma [110] who were treated with anti-PD-1 immunotherapy.”
ResultGao, J., Zhang, Y., Gerhard, M., Mejías‐Luque, R., Zhang, L., Vieth, M. W., Ma, J., Bajbouj, M., Suchánek, Š., Liu, W., et al. (2018) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2018.00202 · Cited by 135
“, 2018), or probiotics enhancing immunotherapy response of cancer patients (Gopalakrishnan et al., 2018), while little has been reported about microbiota composition in precancerous lesions.”
BackgroundSelf-citationSims, T. T., El Alam, M. B., Karpinets, T. V., Dorta-Estremera, S., Hegde, V. L., Nookala, S., Yoshida-Court, K., Wu, X., Biegert, G. W. G., Delgado Medrano, A. Y., et al. (2021) · Communications Biology · doi:10.1038/s42003-021-01741-x · Cited by 135
Self-citationUnlocking the power of postbiotics: A revolutionary approach to nutrition for humans and animals
Zhao, X., Liu, S., Li, S., Jiang, W., Wang, J., Xiao, J., Chen, T., Ma, J., Khan, M. Z., Wang, W., et al. (2024) · Cell Metabolism · doi:10.1016/j.cmet.2024.03.004 · Cited by 153
Exploring the Emerging Role of the Gut Microbiota and Tumor Microenvironment in Cancer Immunotherapy
Qiu, Q., Lin, Y., Ma, Y., Li, X., Liang, J. B., Chen, Z., Liu, K., Huang, Y., Luo, H., Huang, R., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2020.612202 · Cited by 140
Fusobacterium and Colorectal Cancer
Zhou, Z., Chen, J., Yao, H., & Hu, H. (2018) · Frontiers in Oncology · doi:10.3389/fonc.2018.00371 · Cited by 140
Huang, X.-Z., Gao, P., Song, Y.-X., Xu, Y., Sun, J.-X., Chen, X.-W., Zhao, J.-H., & Wang, Z.-N. (2019) · OncoImmunology · doi:10.1080/2162402x.2019.1665973 · Cited by 132
“, Ruminococcaceae family, Faecalibacterium, and Akkermansia muciniphila).(10,33) In addition, several studies have reported that the anti-tumor effects of ICIs were improved in germ-free or ATB-treated mice receiving a fecal microbiota transplantation from responders rather than non-responders, and a favorable gut mic…”
BackgroundImmune Checkpoint Inhibitor-Associated Colitis: From Mechanism to Management
Tang, L., Wang, J., Lin, N., Zhou, Y., He, W., Liu, J., & Ma, X. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.800879 · Cited by 139
“The combination of nivolumab and ipilimumab contributed to prolonged overall survival (OS) and progression-free survival (PFS) in patients with NSCLC (15–17).”
BackgroundInfluentialZhu, Z., Cai, J., Hou, W., Xu, K., Wu, X., Song, Y., Bai, C., Mo, Y., & Zhang, Z. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2166700 · Cited by 134
“As an antitumor strategy, oral administration of commensal bacteria has attracted much attention.(3,4,34) For example, oral administration of Bifidobacteria has been proven to have an antitumor effect.”
BackgroundThe biological underpinnings of therapeutic resistance in pancreatic cancerPreprint
Beatty, G. L., Werba, G., Lyssiotis, C. A., & Simeone, D. M. (2021) · Genes & Development · doi:10.1101/gad.348523.121 · Cited by 139
“Similar observations have been made in melanoma patients (Gopalakrishnan et al. 2018; Matson et al. 2018), suggesting that the microbiome may be a strategy for potentiating the activity of ICB.”
BackgroundPrecision medicine using microbiota
Jobin, C. (2018) · Science · doi:10.1126/science.aar2946 · Cited by 133
The microbiome in precision medicine: the way forward
Petrosino, J. F. (2018) · Genome Medicine · doi:10.1186/s13073-018-0525-6 · Cited by 137
“revealed that the relative levels of the bacterial genus Faecalibacterium were elevated in patients who responded better to PD-1 checkpoint therapy, while the levels of bacteria belonging to the order Bacteroidales were increased in fecal samples from patients who responded poorly to treatment [5].”
Self-citationSex Hormones and Anticancer Immunity
Özdemir, B. C., & Dotto, G. P. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-0137 · Cited by 134
“Fecal transplants from responders to germ-free or antibiotics-treated mice resulted in increased antitumor immunity with reduced tumor growth (61, 62).”
BackgroundChiou, S.-H., Tseng, D., Reuben, A., Mallajosyula, V., Molina, I. S., Conley, S., Wilhelmy, J., McSween, A. M., Yang, X., Nishimiya, D., et al. (2021) · Immunity · doi:10.1016/j.immuni.2021.02.014 · Cited by 133
Self-citationLing, Z., Shao, L., Liu, X., Cheng, Y., Yan, C., Mei, Y., Ji, F., & Liu, X. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00533 · Cited by 135
Choi, Y., Lichterman, J. N., Coughlin, L. A., Poulides, N., Li, W., Del Valle, P., Palmer, S. N., Gan, S., Kim, J., Zhan, X., et al. (2023) · Science Immunology · doi:10.1126/sciimmunol.abo2003 · Cited by 132
The role of neoantigen in immune checkpoint blockade therapy
Yi, M., Qin, S., Zhao, W., Yu, S., Chu, Q., & Wu, K. (2018) · Experimental Hematology and Oncology · doi:10.1186/s40164-018-0120-y · Cited by 132
RIG-I activation is critical for responsiveness to checkpoint blockade
Heidegger, S. M., Wintges, A., Stritzke, F., Bek, S., Steiger, K., Koenig, P.-A., Göttert, S., Engleitner, T., Öllinger, R., Nedelko, T., et al. (2019) · Science Immunology · doi:10.1126/sciimmunol.aau8943 · Cited by 136
Treatment and the prognosis of hepatocellular carcinoma in Asia
Torimura, T., & Iwamoto, H. (2021) · Liver International · doi:10.1111/liv.15130 · Cited by 135
Considerations for designing preclinical cancer immune nanomedicine studies
Jiang, W., Wang, Y., Wargo, J. A., Lang, F. F., & Kim, B. Y. S. (2020) · Nature Nanotechnology · doi:10.1038/s41565-020-00817-9 · Cited by 137
Self-citation
Metadata
- Authors
- Gopalakrishnan, V., Spencer, C. N., Nezi, L., Reuben, A., Andrews, M. C., Karpinets, T. V., Prieto, P. A., Vicente, D., Hoffman, K., Wei, S. C., Cogdill, A. P., Zhao, L., Hudgens, C. W., Hutchinson, D. S., Manzo, T., Petaccia de Macedo, M., Cotechini, T., Kumar, T., Chen, W. S., Reddy, S. M., Szczepaniak Sloane, R., Galloway-Pena, J., Jiang, H., Chen, P. L., Shpall, E. J., Rezvani, K., Alousi, A. M., Chemaly, R. F., Shelburne, S., Vence, L. M., Okhuysen, P. C., Jensen, V. B., Swennes, A. G., McAllister, F., Marcelo Riquelme Sanchez, E., Zhang, Y., Le Chatelier, E., Zitvogel, L., Pons, N., Austin-Breneman, J. L., Haydu, L. E., Burton, E. M., Gardner, J. M., Sirmans, E., Hu, J., Lazar, A. J., Tsujikawa, T., Diab, A., Tawbi, H., Glitza, I. C., Hwu, W. J., Patel, S. P., Woodman, S. E., Amaria, R. N., Davies, M. A., Gershenwald, J. E., Hwu, P., Lee, J. E., Zhang, J., Coussens, L. M., Cooper, Z. A., Futreal, P. A., Daniel, C. R., Ajami, N. J., Petrosino, J. F., Tetzlaff, M. T., Sharma, P., Allison, J. P., Jenq, R. R., & Wargo, J. A.
- Affiliations
- The University of Texas MD Anderson Cancer Center (US)
- Baylor College of Medicine (US)
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- Oregon Health & Science University (US)
- Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- Department of Infectious Diseases, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
- Centre de Recherche de Jouy-en-Josas, Institut National de la Recherche Agronomique, 78352 Jouy-en-Josas, France.
- Institut Gustave Roussy (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Corresponding author
- Gopalakrishnan, V.
- Spencer, C. N.
- Nezi, L.
- Jenq, R. R.
- Wargo, J. A.
- ORCID
- Gopalakrishnan, V.
- Spencer, C. N.
- Nezi, L.
- Reuben, A.
- Andrews, M. C.
- Karpinets, T. V.
- Prieto, P. A.
- Vicente, D.
- Hoffman, K.
- Wei, S. C.
- Cogdill, A. P.
- Zhao, L.
- Hudgens, C. W.
- Hutchinson, D. S.
- Manzo, T.
- Cotechini, T.
- Kumar, T.
- Chen, W. S.
- Reddy, S. M.
- Szczepaniak Sloane, R.
- Jiang, H.
- Chen, P. L.
- Shpall, E. J.
- Rezvani, K.
- Alousi, A. M.
- Chemaly, R. F.
- Shelburne, S.
- Vence, L. M.
- Okhuysen, P. C.
- Jensen, V. B.
- Swennes, A. G.
- McAllister, F.
- Marcelo Riquelme Sanchez, E.
- Zhang, Y.
- Le Chatelier, E.
- Zitvogel, L.
- Pons, N.
- Austin-Breneman, J. L.
- Haydu, L. E.
- Burton, E. M.
- Gardner, J. M.
- Hu, J.
- Lazar, A. J.
- Tsujikawa, T.
- Diab, A.
- Tawbi, H.
- Glitza, I. C.
- Hwu, W. J.
- Patel, S. P.
- Woodman, S. E.
- Amaria, R. N.
- Davies, M. A.
- Gershenwald, J. E.
- Hwu, P.
- Lee, J. E.
- Zhang, J.
- Coussens, L. M.
- Cooper, Z. A.
- Futreal, P. A.
- Daniel, C. R.
- Ajami, N. J.
- Petrosino, J. F.
- Tetzlaff, M. T.
- Sharma, P.
- Allison, J. P.
- Jenq, R. R.
- Wargo, J. A.
- Venue
- Science
- Published
- 2018-01-05
- Volume
- 359
- Issue
- 6371
- Pages
- 97-103
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC5827966
- OpenAlex
- W2766903152
- Semantic Scholar
- 9974af509fc6a420b2e11c14e602fcf26cea86ee
- Cited by
- 4,812
- References
- 84
- Citations by year
- 2026: 544 · 2025: 574 · 2024: 555 · 2023: 568 · 2022: 645 · 2021: 610 · 2020: 592 · 2019: 404 · 2018: 305
- FWCI
- 159.05
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion, other-oa)
- Institutional Research Information System University of Turin (University of Turin) (submittedVersion)
- Funders
- Melanoma Research Alliance
- Dr. Miriam and Sheldon G. Adelson Medical Research Foundation
- United States - Israel Binational Science Foundation
- Stand Up To Cancer
- Parker Institute for Cancer Immunotherapy
- Kenedy Foundation
- McCarthy Skin Cancer Research Fund
- MD Anderson Melanoma Moon Shot
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- gut microbiota, anti-PD-1 therapy, melanoma, Akkermansia muciniphila, antibiotic use, cancer immunotherapy response, gut dysbiosis, lung cancer, kidney cancer, immune cell activity
- MeSH terms
- Gastrointestinal Microbiome, Fecal Microbiota Transplantation, Animals, Humans, Immunotherapy, Melanoma, Skin Neoplasms, Mice, Metagenome, Programmed Cell Death 1 Receptor
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