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.
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- 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.
- 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
“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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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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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.
- 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.
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
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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
“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]
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
“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]
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 measured
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
“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
“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]
The cited source says what the claim attributes to it.
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]
The cited source says what the claim attributes to it.
In the citing paper
“We next tested the generalizability of the balance described in Fig. 2a by computing it for patients from six independent melanoma cohorts5,7–10,12. Despite small sample sizes and large heterogeneity in terms of DNA isolation protocols and sequencing platforms (Supplementary Table 6), this analysis showed that the balance achieves a comparable AUC in several of the independent cohorts (Extended”
From Longitudinal gut microbiome changes in immune checkpoint blockade-treated advanced melanoma (2024) · cites this paper as [10]
The cited source says what the claim attributes to it.
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]
The 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
“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
“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
“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 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
“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 2,401–2,500 of 3,140
The gut as a central hub for multi-organ crosstalk in aging
Zhang, X., Li, R., Gao, Y., Zhang, W., Ni, T., & Liu, Y. (2026) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-026-06129-w · Cited by 7
Drymel, B., Tomela, K., Galus, Ł., Olejnik‐Schmidt, A., Mackiewicz, J., Kaczmarek, M., Mackiewicz, A. A., & SCHMIDT, M. T. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252312982 · Cited by 3
Fleischer, A. (2026) · Nutrients · doi:10.3390/nu18142393 · Cited by 2
Abiru, S., Kugiyama, Y., Suehiro, T., Motoyoshi, Y., Saeki, A., Nagaoka, S., Yamasaki, K., Komori, A., & Yatsuhashi, H. (2025) · Frontiers in Medicine · doi:10.3389/fmed.2025.1567849 · Cited by 2
“…and Collinsella and Tyzzerella, which were significantly lower in the lactulose group, have also been reported to have a beneficial effect on cancer (43, 44), and a decrease in these bacteria may be related to a decrease in Flowchart showing participant recruitment in Study 2. anti-tumor effects.”
Yuan, P., Li, S., Xiong, S., et al. (2023) · Journal of Cancer Research and Clinical Oncology · doi:10.1007/s00432-023-05067-5 · Cited by 2
Invisible influencers: the tumor microbiome’s impact on immunotherapy in colorectal cancer (CRC)
Omar, T. M., Al-Hussainy, A. F., Jyothi, S. R., Nayak, P. P., Janney, J. B., Singh, G., Polatova, D., Sameer, H. N., Salih, R. M., Adil, M., et al. (2025) · Expert Review of Anticancer Therapy · doi:10.1080/14737140.2025.2579656 · Cited by 2
“Similarly, in germ-free mice colonized with FMT from ICI responders, tumor progression slowed compared to those receiving material from non-responders, with enhanced anti-PD-L1 efficacy linked to greater CD8 + T-cell activation [146].”
Immune checkpoint inhibitors and the union of bugs against cancer
Silverman, G. J., Azzouz, D. F., & Mor, A. (2018) · Kidney International · doi:10.1016/j.kint.2018.03.003 · Cited by 2
Felchle, H., Gissibl, J., Rotgerink, L. L., Nefzger, S. M., Walther, C. N., Timnik, V. R., Combs, S. E., & Fischer, J. C. (2024) · Clinical and Translational Radiation Oncology · doi:10.1016/j.ctro.2024.100758 · Cited by 3
“…and clinical studies have associated certain gut microbiome profiles with altered systemic treatment responses to chemotherapy and immunotherapy [14 – 17] and strategies targeting the intestinal microbiota in the context of immunotherapy (e.g., using fecal microbiota transplantation, FMT) are…”
The Therapeutic Potential of the “Yin-Yang” Garden in Our Gut
Srikumar, S., & Fanning, S. (2019) · IntechOpen eBooks · doi:10.5772/intechopen.80881 · Cited by 2
“A correlation was observed between commensal microbial composition and clinical response to anti-PD-L1 therapy through abundance of bacterial species like Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium [149].”
BackgroundGut checkpoint: A rising cancer treatment may get a boost from intestinal bacteria
Azvolinsky, A. (2018) · Nature Medicine · doi:10.1038/nm0318-251 · Cited by 2
Almeida, A. S., Tran, T. T. T., Ghosh, T. S., Ribière, C., Foley, C., Azevedo, L. A., Pellanda, P., Frei, W., Hueston, C. M., Kumar, R. S., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.24.432654 · Cited by 2
Wang, W., Wang, X., Zhou, Z.-D., Deng, X.-B., Luo, X.-W., Wang, Q., Zhang, G.-Y., Zhang, Z. G., Li, Z., He, X., et al. (2026) · Journal of Advanced Research · doi:10.1016/j.jare.2026.01.078 · Cited by 3
Javadrashid, D., Baghbanzadeh, A., Hemmat, N., Hajiasgharzadeh, K., Nourbakhsh, N. S., Lotfi, Z., & Baradaran, B. (2021) · Immunology Letters · doi:10.1016/j.imlet.2021.02.009 · Cited by 2
Adverse cardiovascular events in patients treated with mogamulizumab
Kwan, J. M., Henry, M. L., Cook, K., et al. (2021) · American Heart Journal Plus Cardiology Research and Practice · doi:10.1016/j.ahjo.2021.100049 · Cited by 2
“Additionally, genetics, pharmacogenomics and microbiome have been shown to influence response to immunotherapy [22 – 25].”
BackgroundChambers, L., Esakov, E. L., Braley, C., Trestan, L., Alali, Z., Bazeley, P. S., Bayık, D., Lathia, J. D., Sangwan, N., Joehlin-Price, A. S., et al. (2020) · Research Square · doi:10.21203/rs.3.rs-80626/v1 · Cited by 4
Oh, M., & Zhang, L. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.06.443032 · Cited by 2
Zhang, Z., Tao, H., Mao, K., Meng, F., Jiang, S., Chen, J. Q., He, X., & Tian, X. (2026) · Journal of Ethnopharmacology · doi:10.1016/j.jep.2025.121147 · Cited by 2
Ji, S., Liu, Y., Xu, Y., Gao, J., Jin, J., Jiang, P., Li, Y. K., Su, D., Zhao, Y., Yang, S., et al. (2026) · Nature Microbiology · doi:10.1038/s41564-026-02326-2 · Cited by 4
“Because the gut microbiota plays a key role in CRC development and the immune checkpoint inhibitor (ICI) therapy response 1,7,8,11,12 , we conducted a two-sample Mendelian randomization (MR) analysis using 211 taxa as the exposure, and the meta-CRC dataset (CRC cohort 1) as the outcome (Fig.”
Microbiome in urologic neoplasms: focusing on tumor immunity
Zou, J., Xu, B., Gao, H., Luo, P., Chen, T., & Duan, H. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1507355 · Cited by 2
El-Derby, A. M., Schaaf, C. R., Shelkey, E., Cook, K. L., Votanopoulos, K. I., & Söker, S. (2024) · Frontiers in Microbiomes · doi:10.3389/frmbi.2024.1411322 · Cited by 2
“Also, the relationship between specific microbiota species and therapeutic outcomes in cancer patients is not fully understood due to unpredicted and undesigned outcomes of clinical trials (Matson et al., 2018).”
Harnessing biomarkers to guide immunotherapy in esophageal cancer: toward precision oncology
Almars, A. I., Shaheen, S. Y., Ghouth, N. M., Abumansour, I. S., Khogeer, A., Alsulaimani, F., Basri, A. M., Elhawary, N. A., Hasan, T., & Almohaimeed, H. M. (2025) · Clinical & Translational Oncology · doi:10.1007/s12094-025-04051-4 · Cited by 3
Metagenomics-guided reengineering of the gut microbiome
Dhotre, D. P., & Karmarkar, B. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-91631-8.00011-1 · Cited by 1
Virome and Microbiome Interaction and Their Implication in the Human Gut Health
AboNahas, H. H., El‐Maradny, Y. A., Gezaf, S. A., Nouh, F. A. A., AboNahas, Y. H., Landa‐Acuña, D., Gil-Polo, A., Saied, E. M., & Abdel-Azeem, A. M. (2022) · Springer eBooks · doi:10.1007/978-981-16-1626-6_4 · Cited by 2
Han, W., Li, Q., & Yuan, G. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1802676 · Cited by 4
Immunoregulatory role of pulmonary microbiota in lung cancer: a bibliometric analysis
Jia, H., Gong, Y., Wei, H., Zhao, C., Zang, Q., & Lin, C. L. S. (2025) · Discover Oncology · doi:10.1007/s12672-025-02595-z · Cited by 2
Spatial Transcriptomic Approaches for Understanding the Tumor Microenvironment (TME)
Sadeghirad, H., Shiravand, Y., Radfar, P., Ladwa, R., Warkiani, M. E., O'Byrne, K. J., & Kulasinghe, A. (2023) · Interdisciplinary cancer research · doi:10.1007/16833_2022_111 · Cited by 2
Gut markers for metastatic melanoma receiving immunotherapy
Ou, G., Gou, J., Ou, H., Zheng, H., Zhu, Y., Li, J., & Liu, X. (2025) · BMC Cancer · doi:10.1186/s12885-025-14467-4 · Cited by 2
McAdams, Z. L., Busi, S. B., Gustafson, K. L., Bivens, N. J., Franklin, C. L., Wilmes, P., & Ericsson, A. C. (2024) · Applied Microbiology · doi:10.3390/applmicrobiol4040109 · Cited by 2
Abuelainain, D., Abdel‐Aziz, A. K., & Saadeldin, M. K. (2026) · Biochemical Pharmacology · doi:10.1016/j.bcp.2026.117687 · Cited by 3
Shoji, F., Miura, N., Tagawa, T., Tsukamoto, S., Okamoto, T., Yamazaki, K., Hamatake, M., & Takeo, S. (2022) · Thoracic Cancer · doi:10.1111/1759-7714.14640 · Cited by 1
“In addition, gut microbiome diversity or abundance of specific gut microbiome components has been reported to be related to the efficacy of anti-PD-1 antibody in melanoma patients.(6) Moreover, fecal microbiota transplantation (FMT) in murine models might restore the ICI response.”
BackgroundEngineering the Microbiome: a Novel Approach to Managing Autoimmune Diseases
Omar, T. M., Alfarttoosi, K. H., Sanghvi, G. V., Roopashree, R., Kashyap, A., Krithiga, T., Taher, W. M., Alwan, M., Jawad, M. J., & Al-Nuaimi, A. M. A. (2025) · NeuroMolecular Medicine · doi:10.1007/s12017-025-08879-5 · Cited by 3
“…—when administered orally, these specific microbial strains have demonstrated capacity to improve outcomes in immune checkpoint blockade therapy by modifying the tumor milieux and amplifying antigen-specific T cell responses (Gopalakrishnan et al., 2018; Matson et al., 2018; Routy et al., 2018).”
Metabolic reprogramming and immunity in cancer
Chen, Y., & Li, Y. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823397-9.00006-5 · Cited by 2
Microbial-derived immunostimulatory small molecule augments anti-PD-1 therapy in lung cancer
Newsome, R. C., Liu, H., Agbodzi, B., Gharaibeh, R. Z., Zhou, L., & Jobin, C. (2025) · Cell Reports Medicine · doi:10.1016/j.xcrm.2025.102519 · Cited by 3
Russo, E., Boem, F., Curini, L., & Amedei, A. (2022) · Interdisciplinary cancer research · doi:10.1007/16833_2022_6 · Cited by 2
Reconstructing the landscape of gut microbial species across 29,000 diverse individuals
Šegota, I., Watrous, J. D., Kantz, E. D., Nallamshetty, S., Tiwari, S., Cheng, S. C., Jain, M., & Long, T. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad249 · Cited by 2
“(2) An OSU contains strains with the exact same sequence variant, with potentially different copy numbers.”
BackgroundYao, B., Hou, C., Zhang, W., Bao, Z., Li, Y., & Zhang, Z. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2025.1674814 · Cited by 2
Clinical Implications of Urinary Microbiome in Bladder Cancer
Shim, J. H., Gook, J., Chang, I. H., Sohn, J. M., Seong, S.-W., & Chi, B. H. (2021) · Journal of Urologic Oncology · doi:10.22465/kjuo.2021.19.2.71 · Cited by 1
Yamaguchi, K., Sekido, K., Kobayashi, E., Ogura, K., Nishiyama, M., Konno, K., Tanaka, R., Hamana, H., Kishi, H., Sasaki, S., et al. (2026) · Journal of Natural Medicines · doi:10.1007/s11418-025-01999-z · Cited by 2
Fecal microbiota transplantation as a novel therapeutic strategy for pancreatic cancer
Yamamura, R., & Sonoshita, M. (2025) · Translational and Regulatory Sciences · doi:10.33611/trs.2025-003 · Cited by 3
Differential microbiota network according to colorectal cancer lymph node metastasis stages
Yu, Y., Han, D., Kim, H., Kim, Y. H., & Lee, D. (2023) · Journal of genetic medicine · doi:10.5734/jgm.2023.20.2.52 · Cited by 2
Recent Advances in Bacterium‐Based Therapeutic Modalities for Melanoma Treatment
Khan, M., Dong, Y., Ullah, R., Li, M., Huang, Q., Hu, Y., Li, Y., & Luo, Z. Y. (2024) · Advanced Healthcare Materials · doi:10.1002/adhm.202401076 · Cited by 2
Hiddinga, B. I., Bolte, L. A., van der Leest, P., Hijmering-Kappelle, L. B. M., van der Wekken, A. J., Schuuring, E. M. D., Gaćeša, R., Hospers, G. A. P., Weersma, R. K., Björk, J. R., et al. (2023) · medRxiv · doi:10.1101/2023.10.30.23297712 · Cited by 2
“SCFA-producers such as Bifidobacteria [23, 10], Faecalibacterium prausnitzii [9, 26] have been consistently associated with ICI-response across several tumour types including melanoma and renal cell carcinoma [8, 27], geographies [23, 28], and treatment regimen [13, 29].”
BackgroundGao, Y., Zhang, H., Chu, D., & Ning, K. (2025) · mSystems · doi:10.1128/msystems.00312-25 · Cited by 2
Xu, M., Guan, S., Zhong, C., Ma, M., Li, T., & Huang, G. (2025) · iMeta · doi:10.1002/imt2.70081 · Cited by 4
Routy, B., Rafie, E., & Elkrief, A. (2025) · Nature Cancer · doi:10.1038/s43018-025-01055-5 · Cited by 2
Gavi, F., Bracco, M., Testori, N., Rossi, F., Fettucciari, D., Panio, E., Assumma, S., Russo, P., Gandi, C., Foschi, N., et al. (2026) · World Journal of Urology · doi:10.1007/s00345-026-06386-1 · Cited by 3
“The gut microbiome is increasingly recognized as a regulator of systemic immunity and response to cancer therapy [ 9–11 ].”
Pei, X., Zhao, J., Luo, R. K., Da, L., Li, E., Zhu, H., Li, Y., Luo, Y., Tian, K., Wang, Z., et al. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1407312 · Cited by 1
Mujeres deshonradas: injuria y traición en la "Medea" de Eurípides
Cidre, E. R. (2000) · Repositorio Digital Institucional de la Universidad de Buenos Aires (Universidad de Buenos Aires) · doi:10.34096/ahamm.v33.4318 · Cited by 1
Yu, J., Li, Q., Zou, S., Rong, Y., Zhang, Y., & Chen, C. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1733373 · Cited by 1
Mechanism of Action of Intestinal Microorganisms and Progress in Head and Neck TumorsPreprint
Su, X., Fa-qiang, M., & Jin, F. (2024) · Preprints.org · doi:10.20944/preprints202401.0092.v1
L’actualité scientifique vue par les étudiants de l’AMPS
Benani, A., Gaudet, C., Varennes, O., & Vellas, D. (2018) · médecine/sciences · doi:10.1051/medsci/20183404011 · Cited by 1
Rodriguez‐Palacios, A. (2021) · Physiology in health and disease · doi:10.1007/978-3-030-67951-4_14 · Cited by 1
Chowdhary, R., Goyal, M. K., Arora, K., Sehgal, T., Dawer, P., Anirudh, Berinstein, J. A., Bishu, S., & Matt-Amaral, L. B. (2026) · JGH Open · doi:10.1002/jgh3.70409 · Cited by 1
“Patients with higher baseline gut microbial diversity and the presence of certain commensals (like Akkermansia muciniphila, Alistipes putredinis , and Bifidobacterium longum ) had improved objective response rates and longer progression-free survival on anti- PD-1 therapy [7, 25, 71, 72].”
Immune Checkpoint Inhibitors and Anti-Angiogenic Therapy for Cancer
Solimando, A. G., & Ribatti, D. (2023) · Springer eBooks · doi:10.1007/978-3-030-80962-1_163-1 · Cited by 1
Raf kinase inhibitor protein modulator of gut microbiota and immunotherapy responses in cancer
Palma, G., Bruzzese, F., Meo, C., & de Nigris, F. (2025) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2025.189364 · Cited by 1
Liu, G., Wang, J., & An, L. (2026) · Biology and Medical Engineering · doi:10.63808/bm.v2i1.523 · Cited by 1
“…melanoma and epithelial tumors, certain microbial features can predict the effectiveness of anti-PD-1 immunotherapy, and fecal transplants or colonization with specific strains can restore or boost the anti-tumor effects of immune checkpoint inhibitors (Matson et al., 2018; Routy et al., 2018).”
Food antigens suppress small intestinal tumorigenesis
Sasaki, T., Ota, Y., Takikawa, Y., Terooatea, T. W., Kanaya, T., Takahashi, M., Taguchi‐Atarashi, N., Tachibana, N., Yabukami, H., Surh, C. D., et al. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1373766 · Cited by 1
Influence of Intestinal Flora on ICB Therapy for Colorectal Cancer
赵, 飞. (2024) · Advances in Clinical Medicine · doi:10.12677/acm.2024.14123181 · Cited by 2
Decoding the power of the microbiome in human health
Kumar, M., Almohannadi, N., & Khodor, S. A. (2026) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2026.1877371 · Cited by 1
Liu, S., & Zhang, Z. (2025) · Cancer Management and Research · doi:10.2147/cmar.s520098 · Cited by 2
Valaei, A., Zahmatkesh, N., Aghaei, R., Maleki, M., Meskini, M., & Siadat, S. D. (2026) · New Microbes and New Infections · doi:10.1016/j.nmni.2026.101805 · Cited by 2
Microflora impacts immune system and its antitumor function
Rawat, P., Dhingra, M., Kosta, K., & Das, A. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-96128-8.00007-9 · Cited by 1
Su, X., Jin, J., Huang, Y., Hou, H., Li, Z., Cao, C., Wang, X., Li, F., Deng, Z., & Zhang, M. (2026) · Scientific Reports · doi:10.1038/s41598-026-44494-5 · Cited by 2
Yu, S., Shu, W., Zhang, J., Cheng, S., Shen, X., Chen, G., Zhang, T., Dong, K., Zhang, J., Laudański, P., et al. (2026) · International Journal of Women s Health · doi:10.2147/ijwh.s583327 · Cited by 1
“31,32,75,76 However, Xu et al found that Blautia obeum was enriched in patients who were nonreactive to anti-PD-1 and ICI treatments and may have antibiotic properties along with antibiotic resistance.”
Intestinal Microbiome Modulation of Therapeutic Efficacy of Cancer Immunotherapy
Silveira, M. A. D., Rodrigues, R. R., & Trinchieri, G. (2025) · Gastroenterology Clinics of North America · doi:10.1016/j.gtc.2024.10.005 · Cited by 3
Role of the Gut Microbiome in the Modulation of Cancer Immunotherapy Response
Deshmukh, S. K. (2020) · Archives of Cancer Biology and Therapy · doi:10.33696/cancerbiology.1.011 · Cited by 1
“A melanoma study identified a 38% response rate to PD-L1 blockade therapy [20].”
BackgroundInfluentialNovel Methods to Overcome Acquired Resistance to Immunotherapy
Zhao, X., Yuan, C., Rieth, J. M., Wangmo, D., & Subramanian, S. (2019) · Resistance to targeted anti-cancer therapeutics · doi:10.1007/978-3-030-21477-7_4 · Cited by 2
The impact of gut microbiota modulation on responses to immune checkpoint inhibitors in cancer
Ni, Z., & Ye, D. (2025) · Acta Microbiologica et Immunologica Hungarica · doi:10.1556/030.2025.02719 · Cited by 6
Mikrobielle Einflüsse in der Tumorentwicklung und Tumortherapie
Zeißig, S. (2019) · Zeitschrift für Gastroenterologie · doi:10.1055/a-0848-9193 · Cited by 1
“Diese aktuellen Forschungsdaten sollen im Folgenden dargestellt werden und ihre potenzielle Bedeutung für die klinische Diagnostik und Therapie diskutiert werden.”
BackgroundInfluentialNutrition and Breast Cancer Prevention
Andrade, F. D. O., & Hilakivi-Clarke, L. A. (2019) · Royal Society of Chemistry eBooks · doi:10.1039/9781788016506-00368 · Cited by 1
Fernandes, W. M., Harris, N., Zamalloa, A., Adofina, L., Srinivasan, P., Menon, K. V., Heaton, N. D., Miquel, R., Zen, Y., Kelly, G. P., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25168924 · Cited by 1
Mao, H., Tong, J., Yan, X., Liu, C., Yang, M., & Guo, H. (2021) · Research Square · doi:10.21203/rs.3.rs-622772/v1 · Cited by 1
Kim, D., Jang, H., & Koh, H. (2024) · Bioengineering · doi:10.3390/bioengineering11010060 · Cited by 2
Multi-Dimensional Biomarkers for the Personalized Treatment of Melanoma
Levesque, M. P. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11671-x · Cited by 1
Gut microbiota and metabolic control of immune checkpoint blockade in cancer
Gladstone, J. L., & Sonnenberg, G. F. (2026) · Cell Metabolism · doi:10.1016/j.cmet.2026.04.018 · Cited by 4
Zheng, F., Zhang, Y., & Zhong-xin, L. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1890287 · Cited by 2
The influence of gut microbiota on immunotherapy for Colorectal Cancer
de Melo, F. F. (2023) · Gastrointestinal Tract · doi:10.54844/git.2023.421 · Cited by 1
Canine Genetics, Health and Medicine
Rutland, C. S. (2021) · IntechOpen eBooks · doi:10.5772/intechopen.92513 · Cited by 1
Microbiome and cancer: mechanistic insights, diagnostic potential, and therapeutic strategies
Kumar, V., Chaudhary, A., Gautam, M., Verma, P., & Singh, M. (2026) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2026.1844436 · Cited by 3
“Mechanistically, FMT is believed to improve dendritic cell function, promote antigen presentation, and stimulate the production of pro-inflammatory cytokines such as IL-12, which further boosts T cell activation (Matson et al., 2018).”
Integration of donor microbiota following FMT correlates with anti-PD-1 response in melanoma
Fessler, J. L., Olm, M. R., Engleman, E. G., & Sonnenburg, J. L. (2026) · Nature Communications · doi:10.1038/s41467-026-73465-7 · Cited by 5
“To construct a cancer-speci fi c genome database, we leveraged meta-genomes from 10 of these publicly available datasets 7,10,12 – 16, 18, 22, 23 .”
InfluentialSelf-citationFidelle, M., Derosa, L., Routy, B., & Zitvogel, L. (2021) · Bulletin de l Académie Nationale de Médecine · doi:10.1016/j.banm.2021.01.022 · Cited by 2
Chen, Y., Wang, Q., Zhao, Y., Guan, X., Chen, J., Zhu, H., Yu, K., Zheng, W., 司晶星, Li, S., et al. (2026) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2026.03.026 · Cited by 1
Geschlechtsassoziierte Unterschiede beim Harnblasenkarzinom
Gakis, G., & Weckermann, D. (2022) · Die Urologie · doi:10.1007/s00120-022-01914-4 · Cited by 1
“Beim metastasierten malignen Melanom konnte gezeigt werden, dass die Zusammensetzung des Darmmikrobioms die Effektivität der Therapie mit CheckpointInhibitorenbeeinflusst [28].”
Veremme, L., Baudouin, A., Janoly-Duménil, A., & Charpiat, B. (2022) · Annales Pharmaceutiques Françaises · doi:10.1016/j.pharma.2022.11.006 · Cited by 1
Aminzade, Z., Jafari, A., Shirani, A., Karimi, H., Naserpour, M., Javazm, A. R., Shirvani, P., Alijanzadeh, D., Samieefar, N., & Rezaei, N. (2024) · Interdisciplinary cancer research · doi:10.1007/16833_2024_472 · Cited by 1
Microbiome: A Novel Therapeutics in Cancer Management
Oniyangi, A. G., & Nazir, A. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819265-8.00004-8 · Cited by 1
Understanding oncobiosis in ovarian cancer: Emerging concepts in tumor progression
Sharma, P., Das, S., Rituraj, R., & Bhagyashree, B. (2025) · Pathology - Research and Practice · doi:10.1016/j.prp.2025.156026 · Cited by 1
Biomarkers for Predicting Response to Immunotherapy with Immune Checkpoint Inhibitors
Bořilová, S., Grell, P., Bílek, O., & Kišš, I. (2020) · Onkologie · doi:10.36290/xon.2020.075 · Cited by 1
“u myší k větší účinnosti anti-PD-L1 terapie a také ke zvýšení protinádorové T buněčné odpovědi (94).”
Ziogas, D. C., Theocharopoulos, C., Martinos, A., Lyrarakis, G., Stefanou, D. T., Anastasopoulou, A. N., & Gogas, H. (2026) · Current Oncology Reports · doi:10.1007/s11912-026-01744-z · Cited by 2
“In 2018, Matson et al. [ 13] and Gopalakrishnan et al. [14 ] demonstrated that FMT from ICI responders into germ-free mice enhanced tumor control, amplified T-cell responses, and improved the efficacy of anti-PD-L1 therapy compared to FMT from non-responders.”
InfluentialCancer Immunotherapy 2017 (Paris, France). Progress and challenges
Chouaieb, E., Terry, S., Corgnac, S., et al. (2018) · Bulletin du Cancer · doi:10.1016/j.bulcan.2018.02.006 · Cited by 1
Systemic Implications of Melanoma
Svoboda, R. M., Prado, G., & Rigel, D. S. (2021) · Springer eBooks · doi:10.1007/978-3-030-53437-0_4 · Cited by 1
Kuraganti, G., Sujatha, E., & Bramhachari, P. V. (2021) · Springer eBooks · doi:10.1007/978-981-16-3156-6_8 · Cited by 1
Subclinical cholestasis is a hallmark of gut dysbiosis causing resistance to cancer immunotherapy
Varende, A.-L. M. D. L., Tian, A.-L., Thomas, S., Lahmar, I., Messaoudene, M., Li, S., Motiño, O., Guillaume-dit-Taunière, H., Iebba, V., Hurtado, Y., et al. (2026) · Cancer Cell · doi:10.1016/j.ccell.2026.06.022 · Cited by 4
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).
A second model labelled each claim on 2026-09-28 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Cited sources are checked with a language model’s help (gpt-6-sol).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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