The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index; 6 of the 13 sources its claims cite were checked for support.
The commensal microbiome is associated with anti-PD-1 efficacy in metastatic 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
26 Own result · 6 Own interpretation · 4 No full text of the sources · 4 Own method · 2 Supported · 2 Supported so far · 1 Not checked yet · accuracy not yet measured
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In the paper
“Two additional studies have identified an association of the commensal microbiome with anti–PD-1 mAb efficacy in different solid cancers (7,14).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Not checked — no full text of the sourcecites [7] source
- Supportedcites [14] sourceExperimental — accuracy not yet measured
The opening summary and patient-cohort results report an association between gut microbiome composition and response to anti-PD-1 therapy in melanoma, a solid cancer. This paper supports the claim as one of the two cited studies; it need not establish the findings of the other study. Page numbers are not supplied in our copy. (LLM, conf=0.92)
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
“To determine whether the difference in tumor control could be attributed to host immunity, interferon-γ (IFN-γ) enzyme-linked immunosorbent spot (ELISPOT) of ex vivo SIY-stimulated splenocytes was performed and indicated an increased frequency of activated T cells from R microbiota-reconstituted mice 3 weeks after inoculation with B16.SIY melanoma cells (Fig. 3C).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
hedgeddirect- Asserted: passes — The authors put it forward as true.
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In the paper
“A significant association was observed between commensal microbial composition and clinical response.”
- Also stated in: § Abstract · hedged
“Together, our data suggest that the composition of the commensal microbiota in patients is associated with therapeutic efficacy of anti–PD-1 monoclonal antibody (mAb).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Also stated in: § Abstract · hedged
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
“After removing OTUs present in less than 10% of the samples, the 16S sequencing revealed 62 OTUs of different abundance in R versus NR [P < 0.05, unadjusted, permutation test with Quantitative Insights Into Microbial Ecology (QIIME)] (table S2).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Quantitative PCR results for these 10 species were integrated into a summation quantitative PCR score for each patient, which was significantly higher in responders (P = 0.004) (Fig. 2D).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“The human microbiota-colonized mouse groups segregated into two phenotypes with respect to tumor growth rate: (i) a faster growing group and (ii) a slower growing group (Fig. 3A).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“A principal component analysis (PCA) of the 63 OTUs revealed separation of R from NR (Fig. 1B).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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
“Hierarchical clustering of samples based on relative abundance of these OTUs revealed that most patients were accurately grouped according to clinical response (fig. S2).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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
“Thus, the ability of the human microbiota to support improved tumor control in mice usually, but not always, paralleled the clinical response to anti–PD-1 seen in the donor patient.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
hedgedcorrelational- 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
“the microbiota parameters still markedly separated responders and nonresponders.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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- Probably not a substantial claim. 10
- It may state two separate claims as one. 17
Every source the paper cites for this claim was checked and supports it.
In the paper
“prior work in mice has indicated that some commensals have the potential to be immune-inhibitory—for example, through the induction of FoxP3+ regulatory T cells (11,12).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Supportedcites [11] source
The Abstract reports that indigenous Clostridium species promoted the accumulation of Foxp3+ regulatory T cells in the colons of mice. It also describes intestinal Foxp3+ Tregs as immunosuppressive, supporting the claim's qualified description of some commensals as potentially immune-inhibitory. (LLM, conf=0.93)
- Supportedcites [12] source
The Abstract reports that colonizing germ-free animals with the commensal B. fragilis induces Foxp3+ regulatory T cells and increases their suppressive capacity. The Discussion links this Treg induction to protection from experimental colitis, supporting the claim's example of immune inhibition in mice. (LLM, conf=0.94)
hedgedconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- 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
“Tumor-intrinsic activation of the Wnt/β-catenin pathway (15) and deletion or mutation of Pten (16) have been shown to lead to deficient T cell infiltration into the tumor microenvironment and resistance to checkpoint blockade immunotherapy.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Not checked — no full text of the sourcecites [15] source
- Supportedcites [16] source
Citation (16) is attached to the PTEN part of the sentence, not the Wnt/β-catenin part. The Results report that PTEN deletions and loss-of-function mutations are enriched in non-T-cell-inflamed melanomas, that PTEN-loss tumors have less CD8+ T-cell infiltration, and that patients with PTEN-absent tumors had poorer tumor-size responses to anti-PD-1 treatment. No page numbers are available in our copy. (LLM, conf=0.92)
boosteddirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
Every source the paper cites for this claim was checked and supports it.
In the paper
“There were 16 responders (from here on, referred to as R) and 26 nonresponders (NR), yielding a response rate of 38%, which is in line with published clinical data of anti–PD-1 therapy in metastatic melanoma patients (5, 6).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Supportedcites [5] source
The citing paper reports the 38% rate for its own patients; it cites this source for the comparison with published anti–PD-1 melanoma results. In Results > Clinical Activity, the source reports melanoma response rates of 19–41% across dose levels, a range that includes 38%. Its overall melanoma response rate was 28%, not 38%. (LLM, conf=0.90)
- Supportedcites [6] source
The Rates of Response section reports pembrolizumab response rates of 33.7% and 32.9% in patients with advanced melanoma. The citing paper's 38% is its own result; the cited trial supports the comparison to published anti-PD-1 clinical data, not an exact 38% rate. (LLM, conf=0.91)
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- 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
“Anti–PD-L1 was markedly efficacious in mice colonized with R microbiota yet completely ineffective in NR-derived mice (Fig. 3F), demonstrating a profound impact of the commensal microbiota on immunotherapy efficacy in vivo.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
boosteddirect- 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
“When plotted against the absolute change in tumor size as assessed with RECIST, a clean correlation was observed so that patients with a ratio over 1.5 all showed clinical response (Fig. 2E).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
- Rests on an assumption: OTUs more abundant in responders are beneficial and those more abundant in nonresponders are non-beneficial.
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
“Exome sequencing followed by enumeration of nonsynonymous somatic mutations showed a trend of higher frequency in R, as did levels of PD-L1 and PD-1 mRNA (fig. S6, C to E) and enumeration of baseline CD8+ T cells by means of immunohistochemistry (fig. S6F). Although these trends not reaching statistical significance level of 0.05 were likely limited by sample size, the microbiota parameters still”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
hedgedcorrelational- 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
“Potential species matches were identified for 43 of the original 63 OTUs (table S4).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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
“Interrogation of fecal DNA from these mice by means of quantitative PCR recapitulated the results from our analysis of patients. Of the PCR reactions validated in patients, six were observed in re-constituted mice, with the same pattern of enrichment as was seen in patients (Fig. 2G).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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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
“Two of three mouse cohorts reconstituted with R fecal material had slower baseline tumor growth, and two of the three cohorts reconstituted from NR showed faster baseline tumor growth.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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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
“Analysis of the tumor microenvironment also showed a significantly greater number of SIY–specific CD8+ T cells, but not of FoxP3+CD4+ regulatory T cells, in these mice (Fig. 3, D and E), which is consistent with increased priming of tumor antigen-specific CD8+ T cells.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaindirect- 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
“A BLAST search of the 63 OTUs against the NCBI database of bacterial sequences returned for most OTUs multiple species with ≥98% identity (table S3).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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 B16.SIY melanoma tumor growth in GF mice was similar to that in specific pathogen–free (SPF) mice (both from Taconic), and colonization of GF mice with feces from Taconic SPF mice did not affect this baseline growth rate (fig. S8).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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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
“One Bifidobacteriaceae OTU was significantly more abundant in R, and a second Bifidobacteriaceae OTU (559527) had borderline significance (P = 0.058, unadjusted) and was included in the analyses (total = 63 OTUs).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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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
“Groups C and D, which did not show the same pattern of tumor control as the therapeutic outcome in the original human donors, showed a large degree of difference of microbiota composition from the original human donors (fig. S9). In agreement, a binary Bray-Curtis dissimilarity index for each donor/recipient pair was highest, at 0.7, for cohorts C and D versus 0.5 to 0.6 for the rest of the groups”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“For example, Akkermansia muciniphila OTU (185186), in line with the study of anti–PD-1 efficacy in epithelial cancers by Routy et al. (7), was detected by means of 16S sequencing in four patients, and all were responders, but statistical analysis of the entire cohort is limited by the number of samples above the detection threshold.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Not checked — no full text of the sourcecites [7] source
plaincorrelationaln = 4- 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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It may state two separate claims as one.
A conclusion the paper draws from its own results — 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 conclude that whereas reconstitution of GF mice with human fecal material often recapitulates the microbial composition and the phenotype of the human donor, in some cases there is a high degree of drift so that some bacteria expand and others contract to a degree that is sufficient to change phenotype.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
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
“No major differences in patient characteristics were observed in R versus NR, except a borderline difference in prior (but not current) smoking history (table S1).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Decreased regulatory T cells, increased Batf3 DCs, and augmented TH1responses would all be expected to improve immune-mediated tumor control.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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. It may state two separate claims as one.
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
“Clinical response rate was determined in a blinded manner from biomarker results by using Response Evaluation Criteria In Solid Tumors (RECIST) version 1.1.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
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.
A conclusion the paper draws from its own results — 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 results suggest a reduced spontaneous immune-mediated tumor control inherent to GF mice, which makes them suitable recipients for human-derived microbiota, with an opportunity to detect improved antitumor immunity depending on microbial composition.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
hedgeddirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
In the paper
“An increased frequency of the Batf3-lineage dendritic cells (DCs) and greater T helper cell 1 (TH1) responses were also found with bacteria currently identified to be more abundant in responders (13).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Not checked — no full text of the sourcecites [13] source
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.
In the paper
“Germline polymorphisms in immune regulatory genes also have the potential to influence the magnitude of spontaneous anti-tumor T cell responses (17).”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
What the sources say
- Not checked — no full text of the sourcecites [17] source
hedgedconditional- 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.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This list of species is likely an underestimate of the total number of entities showing differential abundance in R versus NR because of the stringency of this composite analysis.”
§ The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients > Abstract
hedged- Asserted: passes — The authors put it forward as true.
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- 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.
OTUs more abundant in responders are beneficial and those more abundant in nonresponders are non-beneficial.
“the total numbers of potentially “beneficial” and “non-beneficial” OTUs were scored for each patient (fig. S5), and a ratio was calculated.”
“a ratio of “beneficial” OTUs to “nonbeneficial” OTUs was the strongest predictor of clinical response.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Intestinal dysbiosis, broadly defined as an imbalance in the composition or function of the gut microbiota, is a significant contributor to resistance against immune checkpoint inhibitor (ICI) therapies.1–16,”
From Gut dysbiosis in oncology: a risk factor for immunoresistance (2026) · cites this paper as [7]
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
“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 [91]
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
“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 [7]
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
“Bifidobacterium, Akkermansia, and Roseburia have been associated with improved tumor immunotherapy in clinic34–37.”
From Combining gut microbiota modulation and chemotherapy by capecitabine-loaded prebiotic nanoparticle improves colorectal cancer therapy (2023) · cites this paper as [36]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Besides, reconstitution of germ-free mice with fecal material from responding patients could lead to improved tumor control, augmented T cell responses, and greater efficacy of anti-PD-L1 therapy.14”
From Gut microbiota and metabolites associate with outcomes of immune checkpoint inhibitor–treated unresectable hepatocellular carcinoma (2022) · cites this paper as [14]
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 [10]
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 [10]
In 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 [33]
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 [33]
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 [33]
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 [33]
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 [4]
In the citing paper
“in preclinical models, transplantation of fecal material enriched with Bifidobacterium spp. alone (even without CPIs) was sufficient to delay tumor growth4,5.”
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 [4]
In the citing paper
“The intestinal microbiota has been shown to directly impact on the efficacy of specific cancer immune therapies1–3.”
From Microbial short-chain fatty acids modulate CD8+ T cell responses and improve adoptive immunotherapy for cancer (2021) · cites this paper as [2]
In the citing paper
“Multiple landmark studies have identified a role for the gut microbiome in modifying ICI treatment response1,2”
From Gut microbiota-derived hexa-acylated lipopolysaccharides enhance cancer immunotherapy responses (2025) · cites this paper as [1]
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 [11]
In the citing paper
“As previously reported1,2, broad-spectrum antibiotics significantly abrogated anti-PD-1-induced tumour reduction”
From Gut microbiota-derived hexa-acylated lipopolysaccharides enhance cancer immunotherapy responses (2025) · cites this paper as [1]
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 [11]
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 [11]
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 [11]
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 [13]
In the citing paper
“Multiple analyses of the commensal microbiome from human cohorts treated with immunotherapies targeting PD-1 have revealed that the bacterial genus Enterococcus is enriched in responding patients (12, 13).”
From Enterococcus peptidoglycan remodeling promotes checkpoint inhibitor cancer immunotherapy (2021) · cites this paper as [13]
In the citing paper
“the detection of potential NlpC/p60 orthologs in other genera such as Lactobacillus (Fig. 2C, Table S5), which has also been identified in immunotherapy-responsive patients (13), may provide additional specific microbiota correlations to predict and improve patient outcomes.”
From Enterococcus peptidoglycan remodeling promotes checkpoint inhibitor cancer immunotherapy (2021) · cites this paper as [13]
In the citing paper
“consistent with enhanced priming of a tumor antigen-specific immune response (9, 13).”
From Enterococcus peptidoglycan remodeling promotes checkpoint inhibitor cancer immunotherapy (2021) · cites this paper as [13]
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 [3]
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 [91]
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 [91]
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 [83]
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 [10]
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 [5]
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 [5]
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 [5]
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 [5]
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 [5]
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 [5]
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 [5]
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 [5]
In the citing paper
“In contrast, B. thetaiotaomicron was reported as enriched in R in the Frankel and Matson cohorts (5,7) whereas, using a consistent re-analysis approach for all cohorts, this species was enriched in NR.”
From A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors (2021) · cites this paper as [5]
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 [24]
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 Matson et al., 2018
In the citing paper
“Furthermore, melanoma patients treated with anti-PD-L1 had higher levels of Bifdobacterium longum, Collinsella aerofaciens, and Enterococcus faecium, highlighting the importance of the microbiome [122].”
From Immune Checkpoint Inhibitors in Cancer Therapy (2022) · cites this paper as [122]
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 [41]
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 [5]
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 Matson et al., 2018
In the citing paper
“Specific antitumor effects of microbiota have been associated with changes in T cell activation and/or recruitment into the tumor or tumor-draining lymph nodes (Matson et al., 2018; Routy et al., 2018; Shi et al., 2020a; Sivan et al., 2015; Tanoue et al., 2019; Vetizou et al., 2015).”
From Microbiota triggers STING-type I IFN-dependent monocyte reprogramming of the tumor microenvironment (2021) · cites this paper as Matson et al., 2018
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 Matson 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 Matson et al., 2018
In the citing paper
“Bifidobacterium-treated mice showed increased IFN-γ production, followed by stronger tumor-specific T cell responses and slower tumor growth [36].”
From Gut microbiota-mediated immunomodulation in tumor (2021) · cites this paper as [36]
In the citing paper
“Recolonized germ-free mice with fecal samples from responders or dominant microbiota in responders could improve antitumor effects of ICIs [36, 94].”
From Gut microbiota-mediated immunomodulation in tumor (2021) · cites this paper as [36]
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 [205]
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 [21]
In the citing paper
“The composition of the commensal microbiota in patients is associated with the therapeutic efficacy of anti-PD-1 monoclonal antibody.42”
In the citing paper
“Very recent reports highlighted that the composition of gut microbiota may dictate, at least in part, the anticancer activity of ICI.”
From Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer (2018) · cites this paper as [22]
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 [13]
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 [12]
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 [12]
In the citing paper
“Given these considerations, it is perhaps even more striking that bacteria generally associated with health (such as Clostridiales, Ruminococcacae, Faecalibacterium spp., Akkermansia muciniphila, B. fragilis,a n dBifidobacteria) (13, 14, 18-20) or immunogenicity (Enterococci, Collinsella, and Alistipes)( 11, 13, 14, 20) were found to be abundant in responding patients.”
From The microbiome in cancer immunotherapy: Diagnostic tools and therapeutic strategies (2018) · cites this paper as [20]
In the citing paper
“One of the striking findings that distinguishes cancer patient responders from nonresponders after PD-1 blockade immunotherapy is the ratio of putatively favorable to unfavorable bacteria (20).”
From The microbiome in cancer immunotherapy: Diagnostic tools and therapeutic strategies (2018) · cites this paper as [20]
In the citing paper
“Notably, fecal microbial transplantation (FMT) o ff e c e sf r o mp a t i e n t s( w h os h o w e dc l i n i c a lr esponse to immune checkpoint blockade) transferred a”
From The microbiome in cancer immunotherapy: Diagnostic tools and therapeutic strategies (2018) · cites this paper as [20]
In the citing paper
“16S ribosomal RNA (rRNA)-based sequencing of gene amplicons and shotgun DNA sequencing of patient stool samples have identified subsets of bacteria more abundant in responding versus nonresponding patients.”
From The microbiome in cancer immunotherapy: Diagnostic tools and therapeutic strategies (2018) · cites this paper as [20]
In the citing paper
“To date, Bifidobacteria spp.(15, 20), Akkermansia muciniphilia (14), E. hirae (16), and Bacteroides spp.(13) have been shown to improve antitumor T cell responses and support better tumor control in vivo.”
From The microbiome in cancer immunotherapy: Diagnostic tools and therapeutic strategies (2018) · cites this paper as [20]
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 [7]
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 [7]
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 [7]
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 Matson 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 Matson 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 Matson 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 [190]
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 [3]
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 [3]
In the citing paper
“These microbes were also previously reported to be associated with better response to ICB immunotherapy2,3,38,39.”
From A non-antibiotic-disrupted gut microbiome is associated with clinical responses to CD19-CAR-T cell cancer immunotherapy (2023) · cites this paper as [3]
In the citing paper
“These effects were mediated by increased densities of CD8+ T-cells and reduced FoxP3+CD4+ Tregs in the tumor microenvironment”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Matson et al., 2018
In the citing paper
“mice that received responder-stool growing tumors at slower rate and having markedly improved efficacy to anti-PD- L1 immunotherapy when compared to mice that received non-responder stool”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Matson et al., 2018
In the citing paper
“patients who responded to anti-PD-1 therapy had enrichment of Bifidobacterium longum, Collinsella aerofaciens and Enterococcus faecium in baseline fecal samples”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Matson et al., 2018
In the citing paper
“at lower levels of taxonomy within these phyla these generalizations do not apply, as some taxa within Firmicutes have been associated with a lack of response (Roseburia, Streptococcus)”
From The Influence of the Gut Microbiome on Cancer, Immunity, and Cancer Immunotherapy (2018) · cites this paper as Matson 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 Matson 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 [125]
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 [31]
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 [31]
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 [31]
In the citing paper
“They collected stool materials from 42 patients with metastatic melanoma before administering PD-1 blockade, and the clinical response rate was 38%, showing that there were 16 responders (R) and 26 non-responders (NR).”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [55]
In the citing paper
“As expected, PD-1 inhibitor exerted its antitumor activity in mice colonized with R bacteria but was ineffective in NR bacteria colonized mice, thus confirming in vivo the influence of gut microbiome on human immunity.”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [55]
In the citing paper
“The authors selected 10 bacterial species that were different between R and NR, 8 of those were found to be more abundant in R (including Bifidobacterium, also observed in preclinical studies).”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [55]
In the citing paper
“For instance, some researchers calculated the proportion of “beneficial” and “non-beneficial” operational taxonomic units and their ratio for every patient and reached a limit conclusion—a ratio of over 1.5 indicated clinical benefit (55).”
From Gut Microbiome as a Potential Factor for Modulating Resistance to Cancer Immunotherapy (2020) · cites this paper as [55]
In the citing paper
“Along the same line, Matson et al. [172] performed a metagenomics characterization of stools samples from melanoma patients treated with immune checkpoint inhibitors, further corroborating the finding that responders showed a different microbiome compared to those not responding to therapy.”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [172]
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 [172]
In the citing paper
“They identified and functionally proven in vivo the importance of Bifidobacterium longum, Enterococcus faecium and Collinsella aerofaciens in ameliorating anti-PD-L1 efficacy [172].”
From Gut Microbiota and Cancer: From Pathogenesis to Therapy (2019) · cites this paper as [172]
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 [172]
In the citing paper
“It was reported that the gut microbiota of immunotherapy-sensitive patients was distinct from that of immunotherapy-resistant populations [311, 312].”
From Combination strategies with PD-1/PD-L1 blockade: current advances and future directions (2022) · cites this paper as [312]
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
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
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
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data
Wang, K., Li, M., & Hakonarson, H. H. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq603 · Cited by 14,724
Safety, activity, and immune correlates of anti–PD-1 antibody in cancer
Topalian, S. L., Hodi, F. S., Brahmer, J. R., Gettinger, S. N., Smith, D. C., McDermott, D. F., Powderly, J. D., Carvajal, R. D., Sosman, J. A., Atkins, M. B., et al. (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1200690 · Cited by 12,628
Aligning sequence reads, clone sequences and assembly contigs with BWA-MEMPreprint
Li, H. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1303.3997 · Cited by 10,846
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,944
Near-optimal probabilistic RNA-seq quantification
Bray, N. L., Pimentel, H., Melsted, P., & Pachter, L. (2016) · Nature Biotechnology · doi:10.1038/nbt.3519 · Cited by 9,723
Cited by
Sorted by citations
Items 901–1,000 of 3,140
Cross-reactivity between microbial and tumor antigens
Zitvogel, L., & Kroemer, G. (2022) · Current Opinion in Immunology · doi:10.1016/j.coi.2022.102171 · Cited by 40
Han, L., Peng, K., Qiu, L., Li, M., Ruan, J., He, L., & Yuan, Z. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.679602 · Cited by 43
Yang, D., Wang, X., Zhou, X., Zhao, J., Yang, H., Wang, S., Morse, M. A., Wu, J., Yuan, Y., Li, S., et al. (2021) · OncoImmunology · doi:10.1080/2162402x.2021.1976953 · Cited by 40
Hyperprogression: A novel response pattern under immunotherapy
Han, X., Alu, A., Xiao, Y., Wei, Y., & Wei, X. (2020) · Clinical and Translational Medicine · doi:10.1002/ctm2.167 · Cited by 41
The Role of Microbiota-Derived Vitamins in Immune Homeostasis and Enhancing Cancer Immunotherapy
Gholami, H., Chmiel, J. A., Burton, J. P., & Vareki, S. M. (2023) · Cancers · doi:10.3390/cancers15041300 · Cited by 40
“In melanoma patients, ICI responders with higher abundances of Faecalibacterium and Ruminococcaceae—auxotrophic for most B vitamins— showed increased CD4+ T- and CD8+ T-cells in their periphery [72,253,256,257].”
BackgroundDe-coding the complex role of microbial metabolites in cancer
Escriva, P. P., Bernardino, C. C. T., & Letellier, E. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115358 · Cited by 48
The Discovery of Biomarkers in Cancer Immunotherapy
George, A. P., Kuzel, T. M., Zhang, Y., & Zhang, B. (2019) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2019.03.015 · Cited by 41
“This study also proposed that increased beneficial bacteria coupled with a lower frequency of bacteria with negative impactwould be a stronger indicator of positive clinical response in cancer immunotherapy [61].”
BackgroundInfluentialProteobacteria impair anti-tumor immunity in the omentum by consuming arginine
Meza‐Perez, S., Liu, M., Silva-Sánchez, A., Morrow, C. D., Eipers, P. G., Lefkowitz, E. J., Ptacek, T., Scharer, C. D., Rosenberg, A. F., Hill, D. D., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.06.003 · Cited by 42
Hu, Y., Lu, Y. C., Xing, F., & Hsu, W. (2022) · Cancer Letters · doi:10.1016/j.canlet.2022.215867 · Cited by 40
Computational methods and challenges in analyzing intratumoral microbiome data
Wang, Q., Liu, Z., Ma, A., Li, Z., Liu, B., & Ma, Q. (2023) · Trends in Microbiology · doi:10.1016/j.tim.2023.01.011 · Cited by 37
“For example, the microbiota can promote lung cancer development via γδ T cell [24] (Figure 3A), and the commensal microbiome, such as Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium, may have a mechanistic impact on antitumor immunity in metastatic melanoma patients [12] (Figure 3B).”
BackgroundThe Mycobiome: Cancer Pathogenesis, Diagnosis, and Therapy
Gamal, A., Elshaer, M. Y. S., Alabdely, M. H., Kadry, A., McCormick, T. S., & Ghannoum, M. A. (2022) · Cancers · doi:10.3390/cancers14122875 · Cited by 42
Biomarkers for predicting the efficacy of immune checkpoint inhibitors
Wang, C., Wang, H.-N., & Wang, L. (2022) · Journal of Cancer · doi:10.7150/jca.65012 · Cited by 39
“[148] found that Bifidobacterium longum, Colinthia, and Enterococcus faecalis were more abundant in the responders, which could be repeated in germ-free mouse by fecal microbiota transplantation from the responders.”
BackgroundMacandog, A. D. G., Catozzi, C., Capone, M., Nabinejad, A., Nanaware, P. P., Liu, S., Vinjamuri, S., Stunnenberg, J. A., Galiè, S., Jodice, M. G., et al. (2024) · Cell Host & Microbe · doi:10.1016/j.chom.2024.10.006 · Cited by 40
The intratumoral microbiota: friend or foe?
Ferrari, V., & Rescigno, M. (2023) · Trends in cancer · doi:10.1016/j.trecan.2023.03.005 · Cited by 44
Influence of the gut microbiota on immune cell interactions and cancer treatment
Liu, C., Fu, L., Wang, Y., & Yang, W. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-05709-3 · Cited by 47
“The administration of broad-spectrum antibiotics reduces the effectiveness of immune checkpoint inhibitors (ICIs) that target cytotoxic T lymphocyte-associated protein 4 or PD-1/PD-L1 [31–33], providing preclinical evidence that the abundance of some gut microorganisms may promote T-cell activation.”
BackgroundMethodMicrobiota in cancer: current understandings and future perspectives
Yao, Y., Zhu, Y., Chen, K., Chen, J., Li, Y., Li, D., & Wei, P. (2026) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02335-3 · Cited by 56
Benefits of using probiotics as adjuvants in anticancer therapy (Review)
Vivarelli, S., Falzone, L., Basile, M. S., Nicolosi, D., Genovese, C., Libra, M., & Salmeri, M. (2019) · World Academy of Sciences Journal · doi:10.3892/wasj.2019.13 · Cited by 41
“Likewise, Matson et al (76), accomplishing the metagenomic analysis of fecal samples from patients with melanoma treated with immune checkpoint inhibitors, found that responders had a different microbiome profile compared to not responders.”
Wadan, A.-H. S., El‐Aziz, M. K. A., & Ellakwa, D. E. (2025) · Naunyn-Schmiedeberg s Archives of Pharmacology · doi:10.1007/s00210-025-04155-2 · Cited by 51
“They may help alleviate chemotherapy-induced nausea and vomiting by stabilizing the gut-brain axis and reducing neuroinflammation (Matson et al. 2018).”
Shoji, F., Yamaguchi, M., Okamoto, M., Takamori, S., Yamazaki, K., Okamoto, T., & Maehara, Y. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.1040424 · Cited by 40
“, 2018), Enterococcus faecium (Fessler et al., 2018), Akkermansia muciniphila (Routy et al.”
BackgroundInfluentialAlistipes finegoldii augments the efficacy of immunotherapy against solid tumors
Wu, Z., Wu, Q., Han, Y., Xiang, S.-J., Wang, Y., Wu, W.-W., Chen, Y., Feng, Z., Wang, Y.-Y., Xu, Z.-G., et al. (2025) · Cancer Cell · doi:10.1016/j.ccell.2025.07.002 · Cited by 46
Colorectal Cancer Immunotherapy: State of the Art and Future Directions
Cornista, A. M., Giolito, M. V., Baker, K., Hazime, H., Dufait, I., Datta, J., Khumukcham, S. S., De Ridder, M., Roper, J., Abreu, M. T., et al. (2023) · Gastro Hep Advances · doi:10.1016/j.gastha.2023.09.007 · Cited by 39
“185 In addition to its established value, preclinical research has demonstrated that radiotherapy has the potential to sensitize tumors to ICIs.”
BackgroundThe microbiome in pancreatic diseases: Recent advances and future perspectives
Ammer‐Herrmenau, C., Pfisterer, N., Weingarten, M. F., & Neeße, A. (2020) · United European Gastroenterology Journal · doi:10.1177/2050640620944720 · Cited by 39
Effects of periodontitis on cancer outcomes in the era of immunotherapy
Pai, S. I., Matheus, H. R., & Guastaldi, F. P. S. (2023) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(23)00021-1 · Cited by 46
The oral microbiome and oral and upper gastrointestinal diseases
Liu, S., Wang, S., Zhang, N., & Li, P. (2024) · Journal of Oral Microbiology · doi:10.1080/20002297.2024.2355823 · Cited by 41
“Conversely, transplantation from non-responders correlated with faster tumor growth [329].”
BackgroundHuman microbiome and prostate cancer development: current insights into the prevention and treatment
Moghadam, S. O., & Momeni, S. A. (2020) · Frontiers of Medicine · doi:10.1007/s11684-019-0731-7 · Cited by 41
Blake, S. J., James, J., Ryan, F. J., Caparros-Martin, J. A., Eden, G. L., Tee, Y. C., Salamon, J., Benson, S. C., Tumes, D. J., Sribnaia, A., et al. (2021) · Cell Reports Medicine · doi:10.1016/j.xcrm.2021.100464 · Cited by 38
The promise and challenge of cancer microbiome research
Manzoor, S. S., Doedens, A. M., & Burns, M. B. (2020) · Genome biology · doi:10.1186/s13059-020-02037-9 · Cited by 42
“These studies can have significant clinical relevance, as the gut microbial composition is a likely determinant of patient response or non-response to anti-PD-1 and anti-PD-L1 therapy [32, 95].”
BackgroundHuman Microbiota and Immunotherapy in Breast Cancer - A Review of Recent Developments
Vitorino, M. M., de Almeida, S. B., Costa, D. A., Faria, A., Calhau, C., & Braga, S. A. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2021.815772 · Cited by 40
“(53) Science 2018 Metastatic melanoma who received PD-1”
BackgroundThe role of the gut microbiota in chemotherapy response, efficacy and toxicity: a systematic review
Böhm, D. T. M. M., Russ, E., Guchelaar, H., Ziemons, J., Penders, J., Smidt, M. L., van Best, N., & Deenen, M. J. (2025) · npj Precision Oncology · doi:10.1038/s41698-025-01034-0 · Cited by 53
T cell exhaustion in human cancers
Kang, K., Lin, X., Chen, P., Liu, H., Liu, F., Xiong, W., Li, G., Yi, M., Li, X., Wang, H., et al. (2024) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2024.189162 · Cited by 49
MAIT Cells: Partners or Enemies in Cancer Immunotherapy?
Cogswell, D. T., Gapin, L., Tobin, H., McCarter, M. D., & Tobin, R. P. (2021) · Cancers · doi:10.3390/cancers13071502 · Cited by 37
“After administration of this bacteria to germ-free mice, this study observed improved tumor control similar to immune checkpoint blockade, and an almost complete tumor reversal when combining oral Bifidobacterium treatment with an immune checkpoint inhibitor [98,99].”
BackgroundLan, X., Ma, J., Huang, Z., Chen, N., Jin, X., 翁玉蓉, Xu, Y., & Hu, Y. (2023) · The Journal of Gene Medicine · doi:10.1002/jgm.3639 · Cited by 42
“14 – 16 Feces AKK is reported to be positively correlated with the efficacy of PD-1mAb against non-small cell lung cancer (NSCLC), renal cell carcinoma, melanoma and HCC. 12,17,18 These observations imply that AKK exerts important effect in antitumor immunotherapy.”
BackgroundWang, B., Qiu, Y., Xie, M., Huang, P., Yu, Y., Sun, Q., Shangguan, W., Li, W., Zhu, Z., Xue, J., et al. (2024) · BMC Microbiology · doi:10.1186/s12866-024-03372-8 · Cited by 39
“However, the dominant microbiota impacting responses might vary across different tumor types and immunotherapies [8].”
BackgroundZhao, J., Wang, Y., Wang, J., Lv, M., Zhou, C., Jia, L., & Geng, W. (2022) · Food & Function · doi:10.1039/d2fo01747d · Cited by 43
Metabolic Implications of Immune Checkpoint Proteins in Cancer
Stirling, E. R., Bronson, S. M., Mackert, J. D., Cook, K. L., Triozzi, P. L., & Soto‐Pantoja, D. R. (2022) · Cells · doi:10.3390/cells11010179 · Cited by 39
Collinsella aerofaciens Produces a pH-Responsive Lipid Immunogen
Kwon, J., Bae, M., Szamosvári, D., Cassilly, C. D., Bolze, A. S., Jackson, D. R., Xavier, R. J., & Clardy, J. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.3c00250 · Cited by 40
Liu, Y., & Jiang, H. (2020) · Translational Andrology and Urology · doi:10.21037/tau-20-566 · Cited by 36
“Transfer of chemotherapeutic response has been achieved by administrating human feces into murine, and the benefits of specific microbials in progression-free survival rates have been identified among patient cohorts (9-11).”
BackgroundZhu, C., Wang, Y., Zhu, R., Wang, S., Xue, J., Zhang, D., Lan, Z., Zhang, C., Liang, Y., Zhang, N., et al. (2024) · Biomarker Research · doi:10.1186/s40364-024-00607-8 · Cited by 42
“Three studies also showed that the composition and diversity of the gut microbiota correlated with the efficacy of ICI immunotherapy [9, 28, 29].”
BackgroundImmunometabolism of regulatory T cells in cancer
Saravia, J., & Chi, H. (2025) · Oncogene · doi:10.1038/s41388-025-03458-1 · Cited by 45
Mruk-Mazurkiewicz, H., Kulaszyńska, M., Czarnecka, W., Podkówka, A., Ekstedt, N., Zawodny, P., Wierzbicka-Woś, A., Marlicz, W. M., Skupin, B., Stachowska, E., et al. (2024) · Nutrients · doi:10.3390/nu16111695 · Cited by 41
“Although not all of its mechanisms of action in the context of cancer have been understood, evidence suggests that this microorganism can exert a beneficial effect on immunity, with potentially important implications for the success of ongoing therapy [91].”
BackgroundPrognostic and Predictive Biomarkers in the Era of Immunotherapy for Lung Cancer
Pabst, L., Lopes, S., Bertrand, B., Creusot, Q., Kotovskaya, M., Pencreach, E., Beau‐Faller, M., & Mascaux, C. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24087577 · Cited by 37
“, 2018 [143] America 42 Melanoma Anti-PD-1 and anti-CTLA-4 Metagenomic shotgun sequencing, 16rRNA gene sequencing, and polymerase chain reaction Klebsiella pneumoniae, Veillonella parvula, Parabacteroides merdae, Lactobacillus sp.”
BackgroundDaillère, R., Derosa, L., Bonvalet, M., Segata, N., Routy, B., Gariboldi, M., Budínská, E., de Vries, I. J. M., Naccarati, A., Zitvogel, V., et al. (2020) · OncoImmunology · doi:10.1080/2162402x.2020.1774298 · Cited by 41
“including non-small cell lung cancer, renal cell carcinoma and melanoma.(24,26,27) In all three studies, independent patient populations were subjected to fecal microbial analyses, leading to the identification of bacterial entities that positively correlate”
BackgroundThe gut microbiome and melanoma: A review
Makaranka, S., Scutt, F., Frixou, M., Wensley, K. E., Sharma, R., & Greenhowe, J. (2022) · Experimental Dermatology · doi:10.1111/exd.14639 · Cited by 39
Clinical and research updates on the VISTA immune checkpoint: immuno-oncology themes and highlights
Noelle, R. J., Lines, J. L., Lewis, L. D., Martell, R. E., Guillaudeux, T., Lee, S. W., Mahoney, K. M., Vesely, M. D., Boyd-Kirkup, J. D., Nambiar, D. K., et al. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1225081 · Cited by 41
“The ef fi cacy of anti-PD-1-based immunotherapy has been associated with particular commensal microbial composition (66).”
BackgroundThe variable oligomeric state of Amuc_1100 from Akkermansia muciniphila
Wang, J., Xiang, R., Wang, R., Zhang, B., Gong, W., Zhang, J., Zhang, M., & Wang, M. (2020) · Journal of Structural Biology · doi:10.1016/j.jsb.2020.107593 · Cited by 40
Turchan, W. T., Pitroda, S. P., & Weichselbaum, R. R. (2021) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-21-0145 · Cited by 37
Obesity Is Associated with Altered Tumor Metabolism in Metastatic Melanoma
Hahn, A. W., Menk, A. V., Rivadeneira, D. B., Augustin, R. C., Xu, M., Li, J., Wu, X., Mishra, A. K., Gide, T. N., Quek, C. Y. J., et al. (2022) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-22-2661 · Cited by 39
CAR-T Cell Therapy and the Gut Microbiota
Asokan, S., Cullin, N., Stein‐Thoeringer, C. K., & Elinav, E. (2023) · Cancers · doi:10.3390/cancers15030794 · Cited by 39
Cheng, S., Han, Z., Dai, D., Li, F., Zhang, X., Lu, M. S., Lü, Z., Wang, X., Zhou, J., Li, J., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101355 · Cited by 45
Bachem, A., Clarke, M. V., Kong, G., Tarasova, I., Dryburgh, L., Kosack, L., Lee, A. R., Newland, L. G. M., Wagner, T., Bawden, E., et al. (2025) · Immunity · doi:10.1016/j.immuni.2025.10.004 · Cited by 46
Influence of immunomodulatory drugs on the gut microbiota
Cohen, I., Ruff, W. E., & Longbrake, E. E. (2021) · Translational research · doi:10.1016/j.trsl.2021.01.009 · Cited by 39
The role of gut microbiota in tumorigenesis and treatment
Xu, J., Liu, M.-T., Tao, T., Zhu, X. M., & Fei, F. (2021) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2021.111444 · Cited by 41
Current understanding of the human microbiome in glioma
Liang, J., Li, T., Zhao, J., Wang, C., & Sun, H. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.781741 · Cited by 37
Vaginal microbiomes and ovarian cancer: a review.
Xu, J., Peng, J.-J., Yang, W., Fu, K., & Zhang, Y. (2020) · PubMed Central · Cited by 38
Fukuhara, M., Muto, S., Inomata, S., Yamaguchi, H., Mine, H., Takagi, H., Ozaki, Y., Watanabe, M., Inoue, T., Yamaura, T., et al. (2021) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-021-03067-3 · Cited by 40
Modulation of Anti-Tumour Immune Responses by Probiotic Bacteria
Aindelis, G., & Chlichlia, K. (2020) · Vaccines · doi:10.3390/vaccines8020329 · Cited by 39
“This dependency of PD-1 based immunotherapy on the microbiota has also been tested in clinical settings in metastatic melanoma patients [77,78].”
BackgroundWu, Z., Zhang, S., Li, L., Huang, Z., Huang, D., & Hu, Y. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.887383 · Cited by 38
“Among these enriched microbiota components, Alipes (14), Bacteroides fragilis (8), Eubacterium siraeum (14), Ruminococcus bromii (19), Collinsella aerofacien and Parabacteroides merdae (25), Bacteroides caccae CAG_21 (26), and Bacteroides salyersiae and Bacteroides xylanisolvens (27) were previously reported to be fav…”
BackgroundUnveiling the intratumoral microbiota within cancer landscapes
Che, S., Yan, Z., Feng, Y., & Hai, Z. (2024) · iScience · doi:10.1016/j.isci.2024.109893 · Cited by 41
Microbial modulation of intestinal T helper cell responses and implications for disease and therapy
Geuking, M. B., & Burkhard, R. (2020) · Mucosal Immunology · doi:10.1038/s41385-020-00335-w · Cited by 38
Pistollato, F., Forbes-Hernández, T. Y., Iglesias, R. C., Ruíz, R., Elexpuru-Zabaleta, M., Azpíroz, I. D., Cianciosi, D., Quiles, J. L., Giampieri, F., & Battino, M. A. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.11.017 · Cited by 38
Wekking, D., van den Ende, T., Bijlsma, M. F., Vidal-Itriago, A., Nieuwdorp, M., & van Laarhoven, H. W. M. (2025) · Cancer Treatment Reviews · doi:10.1016/j.ctrv.2025.103025 · Cited by 43
Human Microbiome as an Immunoregulatory Axis: Mechanisms, Dysbiosis, and Therapeutic Modulation
Cortes, M., Olate, P., Rodríguez, R., Díaz, R., Martínez, A., Hernández, G., Sepúlveda, N., Paz, E. A., & Quiñones, J. (2025) · Microorganisms · doi:10.3390/microorganisms13092147 · Cited by 45
“The gut–lung microbiome axis and its interaction with the immune system influence pulmonary inflammation and disease progression [114,116].”
InfluentialGut microbiota, an emergent target to shape the efficiency of cancer therapy
Kouidhi, S., Zidi, O., Belkhiria, Z., Raïs, H., Ayadi, A., Ayed, F. B., Mosbah, A., Cherif, A., & Gaaied, A. B. A. E. (2023) · Exploration of Targeted Anti-tumor Therapy · doi:10.37349/etat.2023.00132 · Cited by 37
“Two of three mouse cohorts implanted with responder feces showed slower tumor growth, whereas two mice transplanted with non-responder feces showed quicker baseline tumor growth [208].”
BackgroundHost–MicroRNA–Microbiota Interactions in Colorectal Cancer
Yuan, C., Steer, C. J., & Subramanian, S. (2019) · Genes · doi:10.3390/genes10040270 · Cited by 38
Cancer Resistance to Immunotherapy: Molecular Mechanisms and Tackling Strategies
Vu, S. H., Vetrivel, P., Kim, J., & Lee, M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231810906 · Cited by 37
“Similarly, a clear linkage was found between commensal microbial composition and clinical response in metastatic melanoma patients treated with anti-PD1 therapy [116].”
BackgroundHow gut microbes are joining the fight against cancer
Guglielmi, G. (2018) · Nature · doi:10.1038/d41586-018-05208-8 · Cited by 36
The Vaginal Microbiome is Associated with Endometrial Cancer Grade and Histology
Hakimjavadi, H., George, S. H. L., Taub, M., Dodds, L. V., Covarrubias, A. P. S., Huang, M. S., Pearson, J. M., Slomovitz, B. M., Kobetz, E. N., Gharaibeh, R. Z., et al. (2022) · Cancer Research Communications · doi:10.1158/2767-9764.crc-22-0075 · Cited by 38
“It has also been shown to improve immune-mediated tumor control (25).”
Shen, Y.-C., Lee, P.-C., Kuo, Y.-L., Wu, W.-K., Chen, C.-C., Lei, C.-H., Yeh, C.-P., Hsu, C., Hsu, C.-H., Lin, Z.-Z., et al. (2021) · Journal of Hepatocellular Carcinoma · doi:10.2147/jhc.s315696 · Cited by 36
Gately, S. T. (2019) · Cancer treatment and research · doi:10.1007/978-3-030-16391-4_10 · Cited by 38
Kim, J.-H., Kim, Y., La, J., Park, W. H., Kim, H.-J., Park, S. H., Ku, K. B., Kang, B. H., Lim, J., Kwon, M. S., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113220 · Cited by 39
Lin, H., Guo, Q., Ran, Y., Lin, L., Chen, P., He, J., Chen, Y., & Wen, J. (2021) · Frontiers in Microbiology · doi:10.3389/fmicb.2021.752102 · Cited by 37
“The bacterial phages carried by Enterococcus have been demonstrated to improve T-cell immunity, and several strains of Enterococcus faecalis has been proven to reverse NEC pathology (Stewart et al., 2012; Matson et al., 2018).”
BackgroundInfluentialYu, Y., Zheng, P., Gao, L., Li, H., Tao, P., Dengfeng, W., Ding, F., Shi, Q., & Chen, H. (2020) · Journal of Immunotherapy · doi:10.1097/cji.0000000000000346 · Cited by 38
“response rate (ORR)], (4) prospective or retrospective study design, and (5) the report was published in English.”
BackgroundChen, C., Su, Q., Zi, M., Hua, X., & Zhang, Z. (2025) · npj Biofilms and Microbiomes · doi:10.1038/s41522-025-00818-3 · Cited by 45
Wu, Q., Liu, J., Wu, S., & Xie, X. (2021) · International Immunopharmacology · doi:10.1016/j.intimp.2020.107303 · Cited by 39
Gut Microbiota Modulation through Akkermansia spp . Supplementation Increases CAR T-cell Potency
Marcos-Kovandzic, L., Avagliano, M., Khelil, M. B., Srikanthan, J., Abdallah, R., Petrocelli, V., Rengassamy, J., Alfaro, A., Bied, M., Fidelle, M., et al. (2025) · Cancer Discovery · doi:10.1158/2159-8290.cd-24-1230 · Cited by 42
Emerging functions and clinical prospects of connexins and pannexins in melanoma
Varela-Vázquez, A., Guitián‐Caamaño, A., Carpintero-Fernández, P., Fonseca, E., Sayedyahossein, S., Aasen, T., Peñuela, S., & Mayán, M. D. (2020) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2020.188380 · Cited by 36
Regulation of tissue-resident memory T cells by the Microbiota
Overacre-Delgoffe, A. E., & Hand, T. W. (2022) · Mucosal Immunology · doi:10.1038/s41385-022-00491-1 · Cited by 40
Castello, A., Rossi, S., Toschi, L., & Lopci, E. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10061251 · Cited by 36
Pharmacomicrobiomics: The Role of the Gut Microbiome in Immunomodulation and Cancer Therapy
Bolte, L. A., Björk, J. R., Gaćeša, R., & Weersma, R. K. (2025) · Gastroenterology · doi:10.1053/j.gastro.2025.04.025 · Cited by 39
Guo, Y., Wang, Q., Li, D., Onyema, O. O., Mei, Z., Manafi, A., Banerjee, A., Mahgoub, B., Stoler, M. H., Barker, T. H., et al. (2019) · American Journal of Transplantation · doi:10.1111/ajt.15523 · Cited by 36
Potential Ability of Probiotics in the Prevention and Treatment of Colorectal Cancer
Zhao, J., Liao, Y., Wei, C., Ma, Y., Wang, F., Chen, Y., Zhao, B., Ji, H., Wang, D., & Tang, D. (2023) · Clinical Medicine Insights Oncology · doi:10.1177/11795549231188225 · Cited by 44
Cervicovaginal microbiota: a promising direction for prevention and treatment in cervical cancer
Shen, J., Sun, H. X., Chu, J., Gong, X., & Liu, X. (2024) · Infectious Agents and Cancer · doi:10.1186/s13027-024-00573-8 · Cited by 36
Exploring the Role of the Gut and Intratumoral Microbiomes in Tumor Progression and Metastasis
Ševčíková, A., Mladosievičová, B., Mego, M., & Čierniková, S. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242417199 · Cited by 37
Microbiota-mediated mechanisms of mucosal immunity across the lifespan
Iliev, I. D., Blander, J. M., Collins, N., Guo, C., Longman, R., Sonnenberg, G. F., Zeng, M. Y., & Artis, D. (2025) · Nature Immunology · doi:10.1038/s41590-025-02281-w · Cited by 55
“Sufficient fiber intake enriches for the Ruminococcaceae family and Faecalibacterium genus and correlates with increased intratumoral IFNγ-producing CD8 + T cells 199,203,207,248 .”
Li, M., Zeng, C., Yao, J., Ge, Y., & An, G. (2020) · International Immunopharmacology · doi:10.1016/j.intimp.2020.106972 · Cited by 35
Mousa, S., Sarfraz, M., & Mousa, W. K. (2023) · Metabolites · doi:10.3390/metabo13050674 · Cited by 37
Ghilardi, G., Paruzzo, L., Svoboda, J., Chong, E. A., Shestov, A. A., Chen, L., Cohen, I., Gabrielli, G., Nasta, S. D., Porazzi, P., et al. (2023) · Blood Advances · doi:10.1182/bloodadvances.2023011492 · Cited by 38
Microbiota: Overview and Implication in Immunotherapy-Based Cancer Treatments
Brandi, G., & Frega, G. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20112699 · Cited by 36
The impact of microbiota on PD-1/PD-L1 inhibitor therapy outcomes: A focus on solid tumors
Najafi, S., Majidpoor, J., & Mortezaee, K. (2022) · Life Sciences · doi:10.1016/j.lfs.2022.121138 · Cited by 38
Lozenov, S., Krastev, B. M., Nikolaev, G., Peshevska-Sekulovska, M., Peruhova, M., & Velikova, T. V. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24065978 · Cited by 35
“This may limit cancer cell proliferation by downregulating the NF-kB signaling pathway [49,50].”
BackgroundHadi, D. K., Baines, K. J., Jabbarizadeh, B., Miller, W. H., Jamal, R., Ernst, S., Logan, D., Bélanger, K., Esfahani, K., Elkrief, A., et al. (2025) · Journal for ImmunoTherapy of Cancer · doi:10.1136/jitc-2025-012659 · Cited by 44
Overcoming Resistance to Immune Checkpoint Inhibitors in Head and Neck Squamous Cell Carcinomas
dos Santos, L. V., Abrahão, C. M., & William, W. N. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.596290 · Cited by 36
Kaur, S., Thukral, S. K., Kaur, P., & Samota, M. K. (2021) · Future Foods · doi:10.1016/j.fufo.2021.100043 · Cited by 37
Liu, Y., Altreuter, J., Bodapati, S., Cristea, S., Wong, C. J., Wu, C. J., & Michor, F. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100444 · Cited by 39
Epigenetic modulation of immunotherapy and implications in head and neck cancer
Zhou, L., Xu, N., Shibata, H., Saloura, V., & Uppaluri, R. (2021) · Cancer and Metastasis Reviews · doi:10.1007/s10555-020-09944-0 · Cited by 36
Takada, K., Shimokawa, M., Takamori, S., Shimamatsu, S., Hirai, F., Tagawa, T., Okamoto, T., Hamatake, M., Tsuchiya‐Kawano, Y., Otsubo, K., et al. (2022) · BMC Cancer · doi:10.1186/s12885-022-09385-8 · Cited by 34
Velikova, T. V., Krastev, B. M., Lozenov, S., Gencheva, R., Peshevska-Sekulovska, M., Nikolaev, G., & Peruhova, M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22041754 · Cited by 38
“It has been demonstrated that normal gut microbiota might enhance the antitumor activity of ICIs by promoting the secretion of IL-12 by local dendritic cells and by changing the local repertoires of Th1 cells to express the intestinal chemokine receptors CCR9 and CXCR3.”
BackgroundResultInfluentialGut-Liver Immune Traffic: Deciphering Immune-Pathogenesis to Underpin Translational Therapy
Bozward, A. G., Ronca, V., Osei‐Bordom, D., & Oo, Y. H. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.711217 · Cited by 36
Uncoupling Therapeutic Efficacy from Immune-Related Adverse Events in Immune Checkpoint Blockade
Hu, W., Wang, G., Wang, Y., Riese, M. J., & You, M. (2020) · iScience · doi:10.1016/j.isci.2020.101580 · Cited by 35
Wang, L., Jing, N., Liu, X., Jiang, G., & Liu, Z. (2019) · Journal of Functional Foods · doi:10.1016/j.jff.2019.103647 · Cited by 36
Metadata
- Authors
- Matson, V., Fessler, J., Bao, R., Chongsuwat, T., Zha, Y., Alegre, M.-L., Luke, J. J., & Gajewski, T. F.
- Affiliations
- University of Chicago (US)
- Corresponding author
- Matson, Vyara
- Fessler, Jessica
- Bao, Riyue
- Gajewski, Thomas F.
- ORCID
- Venue
- Science
- Published
- 2018-01-05
- Volume
- 359
- Issue
- 6371
- Pages
- 104-108
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC6707353
- OpenAlex
- W2782333299
- Cited by
- 3,107
- References
- 55
- Citations by year
- 2026: 342 · 2025: 355 · 2024: 351 · 2023: 406 · 2022: 440 · 2021: 403 · 2020: 366 · 2019: 280 · 2018: 158
- FWCI
- 113.20
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (T32 CA009594)
- Melanoma Research Alliance (CA210098)
- University of Chicago Medicine Comprehensive Cancer Center
- 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, metastatic melanoma, Akkermansia muciniphila, antibiotic use, cancer immunotherapy response, gut dysbiosis, lung cancer, kidney cancer, immune cell activity
- MeSH terms
- Gastrointestinal Microbiome, Bifidobacterium longum, Animals, Antibodies, Monoclonal, Feces, Humans, Immunotherapy, Melanoma, RNA, Ribosomal, 16S, Skin Neoplasms, T-Lymphocytes, Enterococcus faecium, Mice, 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.
A language model drew the claims from the paper on 2026-09-28, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
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