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.
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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.
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- Load-bearing: unclear — It is unclear whether 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
“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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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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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.
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- 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.
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- 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
“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 measuredThe 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
“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]
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
“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]
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
“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]
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 801–900 of 4,878
Tsikala-Vafea, M., Belani, N., Vieira, K., Khan, H., & Farmakiotis, D. (2021) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2021.03.063 · Cited by 76
Dong, C., Yu, J., Yang, Y., Zhang, F., Su, W., Fan, Q., Wu, C., & Wu, S. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.111595 · Cited by 77
Emerging Trends in Immunotherapy for Cancer
Mishra, A., Ali, A., Dutta, S., Banday, S., & Malonia, S. K. (2022) · Diseases · doi:10.3390/diseases10030060 · Cited by 79
Huang, P., Ji, F., Cheung, A. H. K., Fu, K., Zhou, Q., Ding, X. Q., Chen, D., Lin, Y., Wang, L., Jiao, Y., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.07.001 · Cited by 81
Yang, Q., Chen, M., Gu, J., Niu, K., Zhao, X., Zheng, L., Xu, Z., Yu, Y., Li, F., Meng, L., et al. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.665133 · Cited by 77
de Clercq, N. C., van den Ende, T., Prodan, A., Hemke, R., Davids, M., Pedersen, H., Nielsen, H. B., Groen, A. K., de Vos, W. M., van Laarhoven, H. W. M., et al. (2021) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-20-4918 · Cited by 77
“Translational studies found a link between several different microbial species and the response to checkpoint inhibitors (19, 20).”
BackgroundUnraveling the Role of the Human Gut Microbiome in Health and Diseases
Khalil, M., Ciaula, A. D., Mahdi, L., Jaber, N., Palo, D. M. D., Graziani, A., Baffy, G., & Portincasa, P. (2024) · Microorganisms · doi:10.3390/microorganisms12112333 · Cited by 100
“Specifically, responders’ microbiota are enriched with bacterial taxa commonly linked to health, including Akkermansia , Faecalibacterium , and Bifidobacterium , all of which are often depleted in non-responders [361–363].”
Fecal microbiota transplantation: no longer cinderella in tumour immunotherapy
Yang, Y., An, Y., Dong, Y., Chu, Q., Wei, J., Wang, B., & Cao, H. (2024) · EBioMedicine · doi:10.1016/j.ebiom.2024.104967 · Cited by 84
“15,16 However, even among these tumours the outcomes of ICIs sometimes turn out to be regrettably unfavourable.”
BackgroundVéziant, J., Villéger, R., Barnich, N., & Bonnet, M. (2021) · Cancers · doi:10.3390/cancers13092215 · Cited by 76
“Moreover, in 2018, two studies published in Science confirmed that the gut microbiota composition influences clinical response to anti-PD-1 therapy in melanoma patients [71,73].”
BackgroundMethodA dysbiotic microbiome promotes head and neck squamous cell carcinoma
Frank, D. N., Qiu, Y., Cao, Y. Q., Zhang, S., Lu, L., Kofonow, J. M., Robertson, C. E., Liu, Y., Wang, H., Levens, C. L., et al. (2022) · Oncogene · doi:10.1038/s41388-021-02137-1 · Cited by 81
Che, H., Xiong, Q., Ma, J., Chen, S., Wu, H., Xu, H., & Hou, B. (2022) · BMC Cancer · doi:10.1186/s12885-022-10004-9 · Cited by 74
“The utilization of ICIs is considered a revolution in cancer therapy that changes the poor prognosis of many advanced-stage cancers, and the tumor response to ICIs was found to have a strong association with gut microbiota in both clinical cohorts and preclinical mouse models [25–29].”
InfluentialMicrobiome as an immune regulator in health, disease, and therapeutics
Juarez, V. M., Montalbine, A. N., & Singh, A. K. (2022) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2022.114400 · Cited by 77
Lu, L., Dong, J., Liu, Y., Qian, Y., Zhang, G., Zhou, W., Zhao, A., Ji, G., & Xu, H. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.964793 · Cited by 73
“V. Gopalakrishnan et al. (Gopalakrishnan et al., 2018) reported that melanoma patients who responded to anti-PD1 blockade had high abundance of Faecalibacterium species, and this population had longer PFS and higher levels of effector CD4+ and CD8+ T cells in systemic circulation.”
BackgroundZhu, X., Hu, M., Huang, X., Li, L., Lin, X., Shao, X., Li, J., Du, X., Zhang, X., Sun, R., et al. (2025) · Cell Metabolism · doi:10.1016/j.cmet.2024.12.013 · Cited by 83
Self-citationDerosa, L., Routy, B., Kroemer, G., & Zitvogel, L. (2018) · OncoImmunology · doi:10.1080/2162402x.2018.1434468 · Cited by 74
“The role of antibiotics induced gut dysbiosis in mice highlighted the contribution of commensals Bacteroides fragilis on the anti-CTLA-4 mAb response.6 In parallel, another group demonstrated the importance of Bifidobacterium in maturing intratumoral DC after anti-PDL-1 mAb.7 Recently, three independent groups, Routy…”
BackgroundInfluentialSelf-citationTargeting the PD-1/PD-L1 Axis for the Treatment of Non-Small-Cell Lung Cancer
Meyers, D. E., Bryan, P., Banerji, S. O., & Morris, D. G. (2018) · Current Oncology · doi:10.3747/co.25.3976 · Cited by 74
A dynamic atlas of immunocyte migration from the gut
Galván-Peña, S., Zhu, Y., Hanna, B. S., Mathis, D., & Benoist, C. (2024) · Science Immunology · doi:10.1126/sciimmunol.adi0672 · Cited by 74
Gut microbiota dysbiosis is associated with Henoch-Schönlein Purpura in children
Wang, X., Zhang, L., Wang, Y., Liu, X., Zhang, H., Liu, Y., Shen, N., Yang, J., & Gai, Z. (2018) · International Immunopharmacology · doi:10.1016/j.intimp.2018.03.003 · Cited by 75
The gut microbiome and cancer response to immune checkpoint inhibitors
Gazzaniga, F. S., & Kasper, D. L. (2025) · Journal of Clinical Investigation · doi:10.1172/jci184321 · Cited by 86
The human archaeome: methodological pitfalls and knowledge gaps
Mahnert, A., Blohs, M., Pausan, M.-R., & Moissl‐Eichinger, C. (2018) · Emerging Topics in Life Sciences · doi:10.1042/etls20180037 · Cited by 69
Li, N., Bai, C., Zhao, L., Sun, Z., Ge, Y., & Li, X. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.781697 · Cited by 76
“longum (27), Faecalibacterium (10, 28, 29), and A.”
MethodInfluentialSelf-citationChau, J., Yadav, M., Liu, B., Furqan, M., Dai, Q., Shahi, S. K., Gupta, A. A., Mercer, K. N., Eastman, E., Hejleh, T. A., et al. (2021) · BMC Cancer · doi:10.1186/s12885-021-08530-z · Cited by 77
“This surrogacy is of particular interest in lung cancer: though the microbiome in distant body sites were previously found not to correlate with immunotherapy response in melanoma patients [22], it remains paramount to ascertain whether the respiratory tract microenvironment correlates to immunotherapy response and to…”
BackgroundSelf-citationInfluence of gut and intratumoral microbiota on the immune microenvironment and anti-cancer therapy
Chen, Y., Liu, B., Yuan, W., & Kuang, D. (2021) · Pharmacological Research · doi:10.1016/j.phrs.2021.105966 · Cited by 74
Microbiome, bile acids, and obesity: How microbially modified metabolites shape anti‐tumor immunity
Sipe, L. M., Chaib, M., Pingili, A. K., Pierre, J. F., & Makowski, L. (2020) · Immunological Reviews · doi:10.1111/imr.12856 · Cited by 75
Immune-checkpoint inhibitors for combating T-cell dysfunction in cancer
Grywalska, E., Pasiarski, M., Góźdź, S. S., & Roliński, J. (2018) · OncoTargets and Therapy · doi:10.2147/ott.s150817 · Cited by 82
Dovrolis, N., Michalopoulos, G., Theodoropoulos, G. E., Arvanitidis, K. I., Kolios, G. C., Sechi, L. A., Eliopoulos, A. G., & Gazouli, M. (2020) · Microorganisms · doi:10.3390/microorganisms8030438 · Cited by 73
“Recent data expand these experimental findings to melanoma patients by identifying microbial signatures associated with response to anti-PD1 immunotherapy [52].”
BackgroundLopes, S., Pabst, L., Dory, A., Klotz, M., Gourieux, B., Michel, B., & Mascaux, C. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1070076 · Cited by 75
Galli, G., Triulzi, T., Proto, C., Signorelli, D., Imbimbo, M., Poggi, M. M., Fucà, G., Ganzinelli, M., Vitali, M., Palmieri, D., et al. (2019) · Lung Cancer · doi:10.1016/j.lungcan.2019.04.008 · Cited by 73
Anderson, R., Theron, A. J., & Rapoport, B. L. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02254 · Cited by 73
The heightened importance of the microbiome in cancer immunotherapy
Villemin, C., Six, A., Neville, B. A., Lawley, T. D., Robinson, M. J., & Bakdash, G. (2022) · Trends in Immunology · doi:10.1016/j.it.2022.11.002 · Cited by 81
Results and challenges of immune checkpoint inhibitors in colorectal cancer
Emambux, S., Tachon, G., Junca, A., & Tougeron, D. (2018) · Expert Opinion on Biological Therapy · doi:10.1080/14712598.2018.1445222 · Cited by 74
Targeted Anti‐Tumor Immunotherapy Using Tumor Infiltrating Cells
Xie, Y., Xie, F., Zhang, L., Zhou, X., Huang, J., Wang, F., Jin, J., Zhang, L., Zeng, L., & Zhou, F. (2021) · Advanced Science · doi:10.1002/advs.202101672 · Cited by 72
Spahn, S., Roessler, D., Pompilia, R., Gabernet, G., Gladstone, B. P., Horger, M., Biskup, S., Feldhahn, M., Nahnsen, S., Hilke, F. J., et al. (2020) · Cancers · doi:10.3390/cancers12123830 · Cited by 75
“This is of interest because an increase in relative abundance of species affiliated with the Ruminococcus family has already been described in responding melanoma patients and a higher relative abundance of Akkermansia muciniphila has been determined in responding patients with renal cell carcinoma and non-small cell…”
BackgroundFaecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors
Bredon, M., Danne, C., Pham, H. P., Ruffié, P., Bessede, A., Rolhion, N., Creusot, L., Brot, L., Alonso, I., Langella, P., et al. (2024) · OncoImmunology · doi:10.1080/2162402x.2024.2374954 · Cited by 74
“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.”
Self-citationAlterations in the intestinal microbiome associated with PCOS affect the clinical phenotype
Wang, L., Zhou, J., Gober, H.-J., Leung, W. T., Huang, Z., Pan, X., Li, C., Zhang, N., & Wang, L. (2020) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2020.110958 · Cited by 73
Antibiotic use influences outcomes in advanced pancreatic adenocarcinoma patients
Mohindroo, C., Hasanov, M., Rogers, J. E., Dong, W., Prakash, L. R., Baydogan, S., Mizrahi, J. D., Overman, M. J., Varadhachary, G. R., Wolff, R. A., et al. (2021) · Cancer Medicine · doi:10.1002/cam4.3870 · Cited by 76
Self-citationThe microbiome in rheumatology: Where are we and where should we go?
Manasson, J., Blank, R. B., & Scher, J. U. (2020) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2019-216631 · Cited by 73
Usyk, M., Pandey, A., Hayes, R. B., Moran, U., Pavlick, A. C., Osman, I., Weber, J. S., & Ahn, J. (2021) · Genome Medicine · doi:10.1186/s13073-021-00974-z · Cited by 75
“Although our study is in line with others that report the activity of Bacteroides with regard to ICB outcomes in melanoma [33–35], other groups have proposed other markers for treatment response, such as Ruminococcaceae and Faecalibacterium [5].”
ResultHussain, N., Naeem, M., & Pinato, D. J. (2021) · Human Vaccines & Immunotherapeutics · doi:10.1080/21645515.2020.1769398 · Cited by 69
“In a previous study by our group,16 we showed that ATB therapy had a significantly detrimental impact on OS (2 vs 26 months, HR = 7.4; 95% CI: 4.2–12.9; p < .001) only if given within 30 d from ICI commencement, with no significant difference in OS seen in patients who received ATB concurrently with ICI.”
BackgroundInfluentialJiménez, C., Subbiah, V., Stephen, B., Ma, J., Milton, D. R., Xu, M., Zarifa, A., Akhmedzhanov, F., Tsimberidou, A. M., Habra, M. A., et al. (2020) · Cancers · doi:10.3390/cancers12082307 · Cited by 71
“It is possible that the introduction of bacterial non-self antigens that mimic human self antigens, expanding T cells with high-affinity receptors, increases the efficiency of the immune system against MPPGs during exposure to pembrolizumab, which prevents negative immune feedback loops [33,34].”
BackgroundVafa, Z. N., Sohrabi, Y., Sayyed, R. Z., et al. (2021) · Plants · doi:10.3390/plants10040811 · Cited by 71
Ochi, N., Ichihara, E., Takigawa, N., Harada, D., Inoue, K., Shibayama, T., Hosokawa, S., Kishino, D., Harita, S., Oda, N., et al. (2021) · European Journal of Cancer · doi:10.1016/j.ejca.2021.02.040 · Cited by 74
Anti-PD-1 Therapy Response Predicted by the Combination of Exosomal PD-L1 and CD28
Zhang, C., Fan, Y., Che, X., Zhang, M., Li, Z., Li, C., Wang, S., Wen, T., Hou, K., Shao, X., et al. (2020) · Frontiers in Oncology · doi:10.3389/fonc.2020.00760 · Cited by 69
Crespin, A., Bescop, C. L., de Gunzburg, J., Vitry, F., Zalcman, G., Cervesi, J., & Bandinelli, P.-A. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1075593 · Cited by 82
Immune Checkpoint Inhibitor–Mediated Diarrhea and Colitis: A Clinical Review
Gong, Z., & Wang, Y. (2020) · JCO Oncology Practice · doi:10.1200/op.20.00002 · Cited by 71
Oral Dysbiosis in Pancreatic Cancer and Liver Cirrhosis: A Review of the Literature
Mohammed, H., Varoni, E. M., Cochis, A., Cordaro, M., Gallenzi, P., Patini, R., Staderini, E., Lajolo, C., Rimondini, L., & Rocchetti, V. (2018) · Biomedicines · doi:10.3390/biomedicines6040115 · Cited by 71
“The microbiota’s benefits include support during digestion, the synthesis of vitamins B and K, prevention against pathogenic colonization [9–12], and a better outcome of immunotherapy [13].”
BackgroundWang, Y., Ma, R., Liu, F., Lee, S. A., & Zhang, L. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00374 · Cited by 71
“Wargo being the responding author, they further compared the gut microbiota of patients with metastatic melanoma receiving anti-PD-1 therapy (74).”
BackgroundAdverse events induced by immune checkpoint inhibitors
Perdigoto, A. L., Kluger, H. M., & Herold, K. C. (2021) · Current Opinion in Immunology · doi:10.1016/j.coi.2021.02.002 · Cited by 79
“response [91] and antibiotic consumption is associated with reduced response to anti-PD-1 treatment [92]; microbiome manipulation could potentially impact cancer course.”
BackgroundPharmacomicrobiomics: The Holy Grail to Variability in Drug Response?
Sharma, A., Buschmann, M. M., & Gilbert, J. A. (2019) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1437 · Cited by 79
“Authors showed that subjects with higher bacterial diversity of the gut, including enrichment of bacterial genera such as Bifidobacterium, Clostridiales, Ruminococcaceae, and Faecalibacterium, had good anti tumor response.(11) This was further attributed to increased antigen presentation.”
BackgroundAdvances in engineering local drug delivery systems for cancer immunotherapy
Abdou, P., Wang, Z., Chen, Q., Chan, A., Zhou, D. R., Gunadhi, V., & Gu, Z. (2020) · Wiley Interdisciplinary Reviews Nanomedicine and Nanobiotechnology · doi:10.1002/wnan.1632 · Cited by 72
“known that the efficacy of immune checkpoint blockade could be affected by factors related to the gut microbiome (Gopalakrishnan et al., 2018; Sivan et al., 2015; Vétizou et al., 2015), signal transducer and activator of transcription 1 (STAT1) signaling, Toll-like receptor 3 (TLR3) signaling, interleukin-10 (IL-10) s…”
BackgroundGut microbiota: A new piece in understanding hepatocarcinogenesis
Zhou, A., Tang, L., Zeng, S., Lei, Y., Yang, S., & Tang, B. (2020) · Cancer Letters · doi:10.1016/j.canlet.2020.01.002 · Cited by 76
Deciphering mechanisms of brain metastasis in melanoma - the gist of the matter
Redmer, T. (2018) · Molecular Cancer · doi:10.1186/s12943-018-0854-5 · Cited by 67
“A very recent study uncovered the role of the oral and gut microbiome, discriminating melanoma patients who respond and those who do not respond to anti–PD-1 immunotherapy [123].”
BackgroundWang, Z., Qin, X., Hu, D., Huang, J. M., Guo, E., Xiao, R., Li, W., Sun, C., & Chen, G. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111890 · Cited by 72
Microbiota and Cancer: The Emerging Beneficial Role of Bifidobacteria in Cancer Immunotherapy
Longhi, G., van Sinderen, D., Ventura, M., & Turroni, F. (2020) · Frontiers in Microbiology · doi:10.3389/fmicb.2020.575072 · Cited by 72
Cancer Immune Checkpoint Inhibitor Therapy and the Gut Microbiota
Frankel, A. E., Deshmukh, S. K., Reddy, A., Lightcap, J., Hayes, M., McClellan, S. B., Singh, S., Rabideau, B. D., Glover, T. G., Roberts, B., et al. (2019) · Integrative Cancer Therapies · doi:10.1177/1534735419846379 · Cited by 73
“Ruthenibacterium lactatiformans(44) found in normal individuals is more than 99% identical to the keystone microbe Faecalibacterium prausnitzii that was discovered in the ICT response association studies of Chaput et al,(39) Frankel et al,(40) and Gopalakrishnan et al.(41) Ex vivo studies suggest that Bacteroidetes di…”
BackgroundMethodInfluentialLymphatic vessels in the age of cancer immunotherapy
Karakousi, T. R., Mudianto, T., & Lund, A. W. (2024) · Nature reviews. Cancer · doi:10.1038/s41568-024-00681-y · Cited by 79
“(adiposity and systemic chronic inflammation) rather than HFD alone that promotes lymphatic dysfunction, as obesity-resistant mouse models do not exhibit signs of lymphatic vessel dysfunction upon a HFD 214 .”
Landscape of tumoral ecosystem for enhanced anti-PD-1 immunotherapy by gut Akkermansia muciniphila
Zhu, Z., Huang, J., Zhang, Y., Hou, W., Chen, F., Mo, Y., & Zhang, Z. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114306 · Cited by 74
Self-citationGenomic Profiling and Metabolic Homeostasis in Primary Liver Cancers
Gingold, J. A., Zhu, D., Lee, D., Kaseb, A. O., & Chen, J. (2018) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2018.02.006 · Cited by 72
Sampsell, K., Hao, D., & Reimer, R. A. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21239239 · Cited by 74
“Multiple studies have demonstrated the necessity of the gut microbiota for response to the anti-PD-1/PDL-1 blockade [75,79].”
BackgroundMasuda, J., Sakai, H., Tsurutani, J., Tanabe, Y., Masuda, N., Iwasa, T., Takahashi, M., Futamura, M., Matsumoto, K., Aogi, K., et al. (2023) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2023-007126 · Cited by 74
Metabolic checkpoints in immune cell reprogramming: rewiring immunometabolism for cancer therapy
Lv, Y., Li, Z., Liu, S., Zhou, Z., Jinling, S., Ba, Y., Weng, S., Zuo, A., Xu, H. W., Luo, P., et al. (2025) · Molecular Cancer · doi:10.1186/s12943-025-02407-6 · Cited by 93
“For instance, the delivery of NO into M2 macrophages impaired mitochondrial and TCA cycle activity, facilitating the expression of M1 markers and inflammatory cytokines [246].”
Self-citationManipulating Gut Microbiota Composition to Enhance the Therapeutic Effect of Cancer Immunotherapy
Yi, M., Jiao, D., Qin, S., Chu, Q., Li, A., & Wu, K. (2019) · Integrative Cancer Therapies · doi:10.1177/1534735419876351 · Cited by 69
“Further analysis indicated that the level of Faecalibacterium (belonging to the Ruminococcaceae family, Clostridiales order) was higher in responders while Anaerotruncus colihominis, Bacteroides thetaiotaomicron (belonging to Bacteroidales order), and Escherichia coli were significantly enriched in nonresponders.(100)…”
BackgroundResultInfluentialSex differences in colorectal cancer: with a focus on sex hormone–gut microbiome axis
Wu, Z., Huang, Y., Zhang, R., Zheng, C., You, F., Wang, M., Xiao, C., & Li, X. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-024-01549-2 · Cited by 85
“Moreover, higher abundance of Bacteroidetes has been associated with chemotherapy-related adverse effects and poorer prognosis [77, 78].”
BackgroundBarrett, K., & Lange, L. (2019) · Biotechnology for Biofuels · doi:10.1186/s13068-019-1436-5 · Cited by 55
Lin, A., Jiang, A., Huang, L., Yu, H., Zhang, C., Zhu, L., Mou, W., Liu, Z., Zhang, J., Cheng, Q., et al. (2025) · Gut Microbes · doi:10.1080/19490976.2025.2452277 · Cited by 74
Self-citationChat, V., Ferguson, R., Simpson, D., Kazlow, E., Lax, R., Moran, U., Pavlick, A. C., Frederick, D. T., Boland, G. M., Sullivan, R. J., et al. (2019) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-019-02318-8 · Cited by 70
Hopkins, A. M., Kichenadasse, G., McKinnon, R. A., Abuhelwa, A. Y., Logan, J. M., Badaoui, S., Karapetis, C. S., Rowland, A., & Sorich, M. J. (2021) · British Journal of Cancer · doi:10.1038/s41416-021-01606-4 · Cited by 72
Hylander, B. L., & Repasky, E. A. (2019) · International Journal of Hyperthermia · doi:10.1080/02656736.2019.1647356 · Cited by 69
Current Progress and Future Perspectives of Immune Checkpoint in Cancer and Infectious Diseases
Cai, X., Zhan, H., Ye, Y., Yang, J., Zhang, M., Li, J., & Zhuang, Y. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.785153 · Cited by 66
“discovered that Faecalibacterium was enriched in responders, while Bacteroides thetaiotaomicron was enriched in nonresponders in melanoma patients (Gopalakrishnan et al., 2018).”
BackgroundBeyond PD-L1 Markers for Lung Cancer Immunotherapy
Wojas‐Krawczyk, K., Kalinka‐Warzocha, E., Grenda, A., Krawczyk, P. A., & Milanowski, J. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20081915 · Cited by 71
“indicated that high abundance of Faecalibacterium and Clostridales (especially Ruminococcaceae family) belonging to the Firmicutes, as well as high diversity of gut microbiome, elevated response rate in patients receiving anti-PD-1 treatment [75].”
BackgroundA systems approach to clinical oncology uses deep phenotyping to deliver personalized care
Yurkovich, J. T., Tian, Q., Price, N. D., & Hood, L. (2019) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-019-0273-6 · Cited by 73
Nitric Oxide-Mediated Enhancement and Reversal of Resistance of Anticancer Therapies
Hays, E., & Bonavida, B. (2019) · Antioxidants · doi:10.3390/antiox8090407 · Cited by 70
“Another study found that responding versus nonresponding patients to anti-PD-1 immunotherapy have significant differences in the bacterial composition of their gut microbiome [33].”
Patra, V., Sérézal, I. G., & Wolf, P. (2020) · Nutrients · doi:10.3390/nu12061795 · Cited by 73
“Finally, recent reports have shown that antibiotic treatment or selective enrichment of certain microbial species in the gut can indeed limit the effectiveness of immune check point therapy in cutaneous melanoma [97,98].”
BackgroundChyuan, I., Chu, C., & Hsu, P. (2021) · Cancers · doi:10.3390/cancers13061188 · Cited by 68
“A study involving 16S rRNA gene sequencing of oral and fecal samples from patients with melanoma treated with anti-PD1 showed that Faecalibacterium was positively correlated with progression-free survival, whereas Bacteroidales increased the risk of relapse [79].”
BackgroundFecal Microbiota Transplantation: Current Status in Treatment of GI and Liver Disease
Vaughn, B. P., Rank, K. M., & Khoruts, A. (2018) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2018.07.026 · Cited by 72
Pulanco, M. C., Madsen, A. T., Tanwar, A., Corrigan, D. T., & Zang, X. (2023) · Cellular and Molecular Immunology · doi:10.1038/s41423-023-01019-8 · Cited by 69
“Decreased bacterial diversity in the microbiome is associated with resistance to ICB in some studies [200, 201], while others showed that the enrichment of specific microbes could predict outcomes [201, 202].”
BackgroundGut microbiota as a new target for anticancer therapy: from mechanism to means of regulation
Sun, J., Song, S., Liu, J., Chen, F., Li, X., & Wu, G. (2025) · npj Biofilms and Microbiomes · doi:10.1038/s41522-025-00678-x · Cited by 78
“During anti-PD-1/PD-L1 therapy, antibiotic-naïve melanoma patients have signi fi cantly higher survival rates than those treated with antibiotics, and responders have shown greater diversity in their gut microbiota compared with non-PD-1 inhibitor responders 36 – 38 .”
The immunosuppressive microenvironment and immunotherapy in human glioblastoma
Zhang, X., Zhao, L., Zhang, H., Zhang, Y., Ju, H., Wang, X., Ren, H., Zhu, X. G., & Dong, Y. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1003651 · Cited by 75
Self-citationStatistical normalization methods in microbiome data with application to microbiome cancer research
Xia, Y. (2023) · Gut Microbes · doi:10.1080/19490976.2023.2244139 · Cited by 76
“In RNA-seq and micorbiome literatures, the “reads per kilobase per million” (RPKM)(128) normalization was often used.(18,105,140)”
BackgroundMethodLocal tumor microbial signatures and response to checkpoint blockade in non-small cell lung cancer
Boesch, M., Baty, F., Albrich, W. C., Flatz, L., Rodriguez, R., Rothschild, S. I., Joerger, M., Früh, M., & Brutsche, M. H. (2021) · OncoImmunology · doi:10.1080/2162402x.2021.1988403 · Cited by 75
“In comparison, a higher gut microbial diversity clearly represents a predictive biomarker in anti-PD -1-treated melanoma.(13) Our finding that Gammaproteobacteria correlate with low PD-L1 expression and poor ICI-related survival suggests a new potential biomarker for ICI response prediction in NSCLC while leaving unan…”
BackgroundThe potential role of the microbiota in prostate cancer pathogenesis and treatment
Pernigoni, N., Guo, C. W., Gallagher, L., Yuan, W., Colucci, M., Troiani, M., Liu, L., Maraccani, L., Guccini, I., Migliorini, D., et al. (2023) · Nature Reviews Urology · doi:10.1038/s41585-023-00795-2 · Cited by 72
“…is also a key modulator of innate and adaptive immune response, with growing evidence supporting its role in response to immunotherapies 45–48, 51, 52, The abundance of specific microbial species identified in the host microbiota before commencing checkpoint inhibition has also been shown to…”
BackgroundResultInfluentialYang, F., Wang, J., Wang, Y., Liu, B., & Molina, J. R. (2021) · Cancers · doi:10.3390/cancers14010109 · Cited by 73
Sensitizing the Tumor Microenvironment to Immune Checkpoint Therapy
Zemek, R. M., Chin, W. L., Nowak, A. K., Millward, M., Lake, R., & Lesterhuis, W. J. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.00223 · Cited by 73
Tibbs, T., Lopez, L. R., & Arthur, J. C. (2019) · Microbial Cell · doi:10.15698/mic2019.08.685 · Cited by 74
“Faecalibacterium, an abundant Gram-positive genus of commensals in the human gut, was also enriched in PD1-responders [61].”
BackgroundOverview of microbial profiles in human hepatocellular carcinoma and adjacent nontumor tissues
He, Y., Zhang, Q., Yu, X., Zhang, S., & Guo, W. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-03938-6 · Cited by 70
Modulation of Gut Microbiota to Enhance Effect of Checkpoint Inhibitor Immunotherapy
Wu, J., Wang, S., Zheng, B. J., Qiu, X., Wang, H., & Chen, L. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.669150 · Cited by 72
“Clostridiales order and Ruminococcaceae family and Faecalibacterium genus were enriched in responders and Bacteroidales order was enriched in non-responders (17).”
BackgroundResultInfluentialPavlick, A. C., Ariyan, C. E., Buchbinder, E. I., Davar, D., Gibney, G. T., Hamid, O., Hieken, T. J., Izar, B., Johnson, D. B., Kulkarni, R. P., et al. (2023) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2023-006947 · Cited by 74
Self-citationRezasoltani, S., Yadegar, A., Aghdaei, H. A., & Zali, M. R. (2020) · Cancer Medicine · doi:10.1002/cam4.3694 · Cited by 67
Elkrief, A., Méndez-Salazar, E. O., Maillou, J., Vanderbilt, C. M., Gogia, P., Desilets, A., Messaoudene, M., Kelly, D., Ladanyi, M., Hellmann, M. D., et al. (2024) · npj Precision Oncology · doi:10.1038/s41698-024-00630-w · Cited by 68
Self-citationFernandez, E., Wargo, J. A., & Helmink, B. A. (2025) · JAMA · doi:10.1001/jama.2025.2191 · Cited by 82
Self-citationChen, J., Levy, A., Tian, A.-L., Huang, X., Cai, G., Fidelle, M., Rauber, C., Ly, P., Pizzato, E., Sitterle, L., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.02.010 · Cited by 67
Self-citationLiu, X., Wang, L., Jing, N., Jiang, G., & Liu, Z. (2020) · Microorganisms · doi:10.3390/microorganisms8020175 · Cited by 68
Stein, C., Burtey, S., Mancini, J., Pelletier, M., Sallée, M., Brunet, P., Berbis, P., Grob, J., Honoré, S., Gaudy‐Marqueste, C., et al. (2020) · Nephrology Dialysis Transplantation · doi:10.1093/ndt/gfaa137 · Cited by 67
Nagaoka, K., Shirai, M., Taniguchi, K., Hosoi, A., Sun, C., Kobayashi, Y., Maejima, K., Fujita, M., Nakagawa, H., Nomura, S., et al. (2020) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2020-001358 · Cited by 68
Joachim, L., Göttert, S., Sax, A., Steiger, K., Neuhaus, K., Heinrich, P., Fan, K., Orberg, E. T., Kleigrewe, K., Ruland, J., et al. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104834 · Cited by 72
“20,23,24,29 Bacterial-derived metabolites were suggested to act as potential mediators of varying anti-tumour immune responses.”
BackgroundEmerging Evidence of the Gut Microbiome in Chemotherapy: A Clinical Review
Oh, B., Boyle, F. M., Pavlakis, N., et al. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.706331 · Cited by 67
“(24) 2020 Israel BCa and gynaecology cancer (n=33) Age range (18-75) BCa (n=28) Ovarian/ endometrial cancer (n=5) Neoadjuvant and adjuvant CTX Collected data on use of antibiotics before CTX but excluded antibiotic user during CTX 1x before chemotherapy Metagenome Gut weig No w Weig”
BackgroundLlosa, N. J., Luber, B. S., Tam, A. J., Smith, K. N., Siegel, N. M., Awan, A. H., Fan, H., Oke, T. F., Zhang, J., Domingue, J. C., et al. (2019) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-19-0114 · Cited by 67
“Second, the detection of an IL17 immune signature is a predominant element in the TiME of patients with colorectal cancer that may impact their response to immune checkpoint blockade and which should be taken into account for guiding immunotherapy decisions as suggested previously (23, 24).”
BackgroundSelf-citationFriend or Foe? Recent Strategies to Target Myeloid Cells in Cancer
Chaib, M., Chauhan, S. C., & Makowski, L. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2020.00351 · Cited by 65
Bacterial community structure alterations within the colorectal cancer gut microbiome
Loftus, M. G., Hassouneh, S. A.-D., & Yooseph, S. (2021) · BMC Microbiology · doi:10.1186/s12866-021-02153-x · Cited by 69
Jang, B., Chang, J. H., Chie, E. K., Kim, K., Park, J. W., Kim, M. J., Song, E., Nam, Y., Kang, S. W., Jeong, S., et al. (2020) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2020.04.015 · Cited by 66
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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