The DOI matches its Crossref record; its reference list is not available; 4 of the 55 sources its claims cite were checked for support.
A Uniform Computational Approach Improved on Existing Pipelines to Reveal Microbiome Biomarkers of Nonresponse to Immune Checkpoint Inhibitors
Open accessPublished version of a preprint
Abstract
Purpose: While immune checkpoint inhibitors (ICI) have revolutionized the treatment of cancer by producing durable antitumor responses, only 10%–30% of treated patients respond and the ability to predict clinical benefit remains elusive. Several studies, small in size and using variable analytic 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. Experimental Design: We have reanalyzed the available raw 16S rRNA amplicon and metagenomic sequencing data across five recently published ICI studies (n = 303 unique patients) using a uniform computational approach. Results: Herein, we identify novel bacterial signals associated with clinical responders (R) or nonresponders (NR) and develop an integrated microbiome prediction index. Unexpectedly, the NR-associated integrated index shows the strongest and most consistent signal using a random effects model and in a sensitivity and specificity analysis (P < 0.01). We subsequently tested the integrated index using validation cohorts across three distinct and diverse cancers (n = 105). Conclusions: Our analysis highlights the development of biomarkers for nonresponse, rather than response, in predicting ICI outcomes and suggests a new approach to identify patients who would benefit from microbiome-based interventions to improve response rates.
Overview
Integrity signals
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Statistics
Verification
Claims the paper makes
56 Own result · 20 Not checked yet · 19 Own interpretation · 5 No basis given · 3 Own method · 1 Partly supported · accuracy not yet measured
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In the paper
“When we examined the enrichment of specific species previously reported in each individual study, our results showed variation (Fig. 1).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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In the paper
“Unexpectedly, the NR-associated Integrated Index shows the strongest and most consistent signal using a random effects model and in a sensitivity and specificity analysis (p < 0.01).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Abstract > Results:
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In the 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).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
What the sources say
- Not checked yetcites [5] Matson, 2018, The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients, Science source
- Not checked yetcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science source
- Not checked yetcites [7] Frankel, 2017, Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients, Neoplasia source
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In the paper
“In this latter case, WGS data did not detect the species but 16S rRNA rRNA amplicon data detected them when >0.1% relative abundance.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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In the paper
“We did not observe consistent differences in detection of antibiotic resistance elements or relative abundance rates between R and NR groups within each study (Fig. S6A-C).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Functional characterization of the microbiome
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In the paper
“Unexpectedly, but similar to the individual taxon analyses (Fig. 2), the strongest association emerged with the NR Integrated Index (Fig. 3, top panel).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“Specifically, microbial signals for Faecalibacterium prausnitzii, Bifidobacterium longum, Collinsella aerofaciens, and Enterococcus faecium remained significant using our analysis methodology and FDR correction.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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“Specifically for the Integrated Indices, we did not find significant changes when low prevalence bacteria, such as Prevotella buccalis and Oribacterium sinus, were removed from their respective indices.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“The composite Integrated Index also showed modest improvement compared to the literature-based indices (Fig. 4, right column).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“The overall mean AUC for the Integrated Indices improved when SD patients were removed from the Frankel and Routy cohorts (Figure S4B).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“We also did not observe consistent differences in the presence or absence of specific organism virulence factors between R and NR groups within each study (Fig. S6D-F).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Functional characterization of the microbiome
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In the paper
“However, removal of B. coprocola did not appear to affect the mean AUC sensitivity and specificity across all cohorts.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“In contrast, six additional species reported as significantly associated with ICI response trended towards but were not significantly enriched in R when the data were FDR-corrected.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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In the paper
“The largest reduction in performance occurred in the random effects model with removal of B. coprocola from the NR-associated and composite Integrated Index.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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“Of note, butanoate metabolism was not predicted to be enriched in either group.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Functional characterization of the microbiome
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In the paper
“Individually, upon re-analysis, the Chaput, Frankel, and Matson cohorts did not show any association between alpha diversity and tumor response to checkpoint inhibition.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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In the paper
“Removal of F. prausnitzi and A. muciniphila from the R-associated Integrated Index reduced the overall performance as the mean AUC changed from 61.01% (± 4.06) to 53.36 (± 2.56, p = 0.1320) and 57.82 (±5.50, p = 0.5887), respectively.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“Using this approach, we identified multiple previously unreported OTUs enriched in R, including Roseburia hominis, Oxalobacter formigenes, and Prevotella buccalis (Fig. 2).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Consistent computational analysis across cohorts identifies novel bacterial signatures
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In the paper
“Overall, excluding SD patients modestly improved the AUC of all Integrated, Literature, and Melanoma Literature indices for the Frankel cohort (Figure S4A).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“The data showed that alpha diversity was, unexpectedly, not significantly impacted by antibiotic exposure (Table S5).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Impact of antibiotic use on alpha diversity
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“we confirmed that higher alpha diversity (richness and evenness) correlated with tumor response to checkpoint inhibition in the Gopalakrishan cohort (Fig. S2B) (8)”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
What the sources say
- Not checked yetcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science source
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In the paper
“However, removal of either species from the composite Integrated Index did not impact the overall performance of the index”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“All bacterial signatures, whether R or NR (Fig. 2), with the exception of F. prausnitzii and B. fragilis, displayed low heterogeneity (I2=0%) across studies.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Consistent computational analysis across cohorts identifies novel bacterial signatures
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In the paper
“Further, a sensitivity and specificity analysis suggested that the NR Integrated Index was strongest in predicting tumor outcome to ICI therapy.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“In fact, the NR signal was not significant in either literature-based index.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“Instead, among patients without antibiotic exposure, a trend toward decreased alpha diversity in NR was observed, specifically Chao1 and observed species”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Impact of antibiotic use on alpha diversity
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In the paper
“We also examined specific taxa in longitudinal samples using differential abundance analysis and found no significant changes over time in either study (Fig. S5B and S5D).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Analysis of longitudinal fecal samples
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In the paper
“Only two cohorts, Frankel and Routy, had metadata for individual patients with an SD designation. The other three cohorts utilized SD criteria to determine R vs NR (Table 1) but did not include SD information for individual patients in either the original publication or publically available metadata.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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In the paper
“Although no alpha diversity measure was found to be associated with R using a meta-analysis approach (Fig. S2A)”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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In the paper
“We also identified many species enriched in NR: Veillonella parvula, Bacteroides spp. (fragilis, coprocola, thetaiotaomicron, uniformis), Clostridium spp. (hathewayi, hylemonae, methylpentosum), Parasutterella excrementihominis, Scardovia wiggsiae, Oribacterium sinus, and Megasphaera micronuciformi.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Consistent computational analysis across cohorts identifies novel bacterial signatures
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In the paper
“We were able to use FDR correction to confirm a subset of reported species associated with R previously highlighted in individual studies.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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In the paper
“Moreover, while, in general, lower alpha-diversity has been associated with disease states and higher alpha-diversity with healthy states, we found that alpha-diversity was not consistently predictive of response or nonresponse to ICIs, though we confirmed the association of higher alpha diversity in R as reported by Gopalakrishnan et al (8).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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In the 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.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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In the paper
“However, the AUC for the NSCLC cohort did not perform as well but did improve in the NR-associated Integrated Index when patients with antibiotic exposure were removed (compare middle panels, Fig 5A and 5B; Fig 5D, p = 0.0032).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Evaluation of the Integrated Microbiome Prediction Index in Independent Validation Cohorts
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In the paper
“Combined use of our new microbial R and NR signals resulted in development of NR and Composite Integrated Microbiome Prediction Indexes that outperformed literature-based indexes when assessed using both a random effects model and a sensitivity/specificity analysis.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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In the paper
“We were able to identify new bacterial signatures associated with clinical tumor response or lack of response that were not reported in the original publications, likely because our analysis allows for comparison of individual species across cohorts and a larger sample size.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Of note, we identified several new bacterial signatures enriched in R that have not been previously identified, including Roseburia hominis, Oxalobacter formigenes, and Prevotella buccalis.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“However, the AUC for the NSCLC cohort did not perform as well but did improve in the NR-associated Integrated Index when patients with antibiotic exposure were removed (compare middle panels, Fig 5A and 5B; Fig 5D, p = 0.0032).”
- Also stated in: § Discussion · hedged
“However, modest improvement in AUC occurred when individuals with recent antibiotic exposure were removed from the analysis.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Evaluation of the Integrated Microbiome Prediction Index in Independent Validation Cohorts
plaindirectn = 70- Asserted: passes — The authors put it forward as true.
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- Also stated in: § Discussion · hedged
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In the paper
“However, microbial signals associated with NR were overall stronger and more consistent than signals associated with R, a distinct finding from prior reports.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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In the paper
“Further, we were able to validate the Integrated Microbiome Prediction Index in independent cohorts of two tumor types, melanoma and HCC, albeit with small cohorts using publically available data, whereas 16S rRNA sequences derived from NSCLC patients performed less well overall.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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In the paper
“in fact, we found three other members of the Bacteroides genus enriched in NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“Overall, the Sum Integrated Index performed well for the melanoma and HCC cohorts with AUCs > 80 (Fig 5A,B).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Evaluation of the Integrated Microbiome Prediction Index in Independent Validation Cohorts
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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this combined dataset, the microbiome signals correlating with nonresponse were dominant, suggesting these microbes provide a potentially powerful biomarker for the selection of patients who might not ordinarily respond to checkpoint blockade but might benefit from microbiome-based interventions that reduce or eliminate specific species.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
In the paper
“we selected Resphera Insight as previously published data demonstrate that this pipeline outperforms QIIME RDP and QIIME UCLUST in species level identification using the Human Microbiome Project reference isolate collection (60–70% species identified by Resphera Insight compared to 10–25% by QIIME RDP or QIIME UCLUST) (13).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Introduction
What the sources say
- Not checked yetcites [13] Drewes, 2017, High-resolution bacterial 16S rRNA gene profile meta-analysis and biofilm status reveal common colorectal cancer consortia, NPJ Biofilms Microbiomes source
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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
“likely, in part, due to the strong NR-associated signal in the Integrated Index.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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
“suggesting decreased richness rather than evenness as associated with NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Impact of antibiotic use on alpha diversity
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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
“potentially indicating an association with richness rather than evenness in R.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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 data validate the Integrated Index and further suggest that the Integrated Index may perform better in specific tumor types and will need to be refined as additional data from further studies and tumor types become available.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Evaluation of the Integrated Microbiome Prediction Index in Independent Validation Cohorts
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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 were able to identify new bacterial signatures associated with clinical tumor response or lack of response that were not reported in the original publications, likely because our analysis allows for comparison of individual species across cohorts and a larger sample size.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
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 result is consistent with the hypothesis that molecular mimicry may be one mechanism by which the microbiome triggers R or NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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
“First, the criteria used to determine R versus NR was variable or imprecisely defined among the cohorts and most apparent when considering the status of patients with stable disease and the duration of disease stabilization used to determine classification as R or NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
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 data validate the Integrated Index and further suggest that the Integrated Index may perform better in specific tumor types and will need to be refined as additional data from further studies and tumor types become available.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Evaluation of the Integrated Microbiome Prediction Index in Independent Validation Cohorts
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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
“While resistance to ICI therapy can result from both tumor-intrinsic and -extrinsic factors, the strength of the NR-associated microbiome signals indicates there may also be potential for immunomodulation hindering response based on the presence of specific microbes or microbial communities.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
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
“Thus, use of our standardized computational pipeline allowed for identification of new, previously unreported NR-associated signals.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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 result is not unexpected given the dominant microbiome remodeling induced by antibiotics and reinforces recent observations suggesting that recent antibiotic exposure hinders ICI therapeutic responses (28,29).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: Antibiotics dominantly remodel the gut microbiome.
None of the sources cited for this claim have been checked yet.
In the 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.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [5] Matson, 2018, The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients, Science source
- Not checked yetcites [7] Frankel, 2017, Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients, Neoplasia source
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.
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
“Our analysis is thereby limited by lack of data on prior and concurrent therapies at the time of sample collection.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A 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
“While a more universal microbial signal is ideal for clinical application, the baseline variation could mask some signals.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
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
“However, we note that the consistent signals identified in this study across multiple geographies suggest the signals we identified are robust.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
hedgedcorrelational- 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. 36
- Probably not a substantial claim. 13
The cited sources support only part of this claim — read each source’s verdict below.
In the 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.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Abstract > Purpose:
What the sources say
- Partly supportedcites [5] Matson, 2018, The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients, Science sourceExperimental — accuracy not yet measured
In our copy (section labeled Abstract; page unavailable), the paper reports an association with anti–PD-1 response in 42 melanoma patients, proposes microbiota composition as a predictive biomarker, and notes that other studies used different patient-grouping and analytical methods. It cautions against directly comparing enriched bacteria across publications, but does not establish that the implicated bacteria were inconsistent across populations. Fecal transfer demonstrates that microbiota can be changed in mice; the paper does not show that the proposed biomarker is modifiable in patients. (LLM, conf=0.83)
- Not checked yetcites [6] Routy, 2018, Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors, Science source
- Partly supportedcites [7] Frankel, 2017, Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients, Neoplasia sourceExperimental — accuracy not yet measured
The Results (page unavailable) report microbiome associations with ICI response in 39 melanoma patients and different bacterial signatures by treatment; the Discussion (page unavailable) calls the findings preliminary and notes that antibiotics and diet can alter the microbiome. The paper also contrasts shotgun sequencing with 16S methods. It does not establish that findings from several prior small studies were inconsistent across studied populations; the differing signatures it reports are primarily between treatment groups in its own cohort. (LLM, conf=0.84)
- Partly supportedcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science sourceExperimental — accuracy not yet measured
In the paper’s main text (page unavailable), the authors link gut microbiome composition to anti-PD-1 response and highlight the therapeutic potential of modifying it. The paper does not establish that prior studies used variable analytical methods or that implicated bacteria were inconsistent across populations; it describes one small prior cohort as having findings in line with its own. (LLM, conf=0.84)
- Not checked yetcites [9] Chaput, 2017, Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab, Ann Oncol source
- Supportedcites [10] Gharaibeh, 2019, Microbiota and cancer immunotherapy: in search of microbial signals, Gut source
The paper’s main text says microbial composition may predict response to immune checkpoint blockade and that altering it could be therapeutic. It reports different bacterial signals across three patient cohorts, discusses differences in methods, and calls for larger cohorts to identify response markers. Page numbers are not available in our copy. (LLM, conf=0.91)
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.
It may state two separate claims as one.
- Partly supported
In the paper
“Overall, the majority of these studies used non-parametric testing but did not apply multiple hypothesis testing correction in the initial analysis, with the exception of the Gopalakrishnan cohort (8).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
What the sources say
- Not checked yetcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science source
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.
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
“Herein, we identify novel bacterial signals associated with clinical response (R) or nonresponse (NR) and develop an Integrated Microbiome Prediction Index.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Abstract > Results:
plaincorrelationaln = 105- 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.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Of the 2,132 unique canonically named Bacterial/Archaeal species (i.e. “genus_species”) in the MetaPhlAn2 database, 1,952 (91.56%) are present in the Resphera Insight database.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Materials and Methods > Correlation of relative abundance between 16S rRNA amplicon and WGS datasets.
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
“Notably, in these datasets, taxa relative abundances that do not correlate across 16S rRNA amplicon and WGS data either represent signals occurring at <0.05% relative abundance or represent two taxa (Ruminococcus bromii and Parabacteroides distasonis) derived from only 2 of the included studies.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
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.
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
“Although F. prausnitzii and B. fragilis showed moderate heterogeneity across studies (I2=54% and 26%, respectively), these differences did not reach statistical significance.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Consistent computational analysis across cohorts identifies novel bacterial signatures
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The NR Integrated Index displayed an average area under the curve (AUC) of 70.3% (± 1.66) compared to 47.8% (± 5.01, p = 0.0022) and 52.1% (±4.51, p = 0.0087) using the Literature and Melanoma Literature NR Indices, respectively (Fig. 4, middle column).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In the Routy cohort, we also observed significantly higher alpha diversity associated with R among observed species and Chao1 estimators, but not Shannon or Reciprocal Simpson measures”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Overall, no differences were identified in beta diversity since, as expected (19), longitudinal fecal samples were more similar within patients as compared to between patients, despite some drift with time in the Chaput study (Fig. S5A and S5C).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Analysis of longitudinal fecal samples
What the sources say
- Not checked yetcites [19] Costello, 2009, Bacterial community variation in human body habitats across space and time, Science source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Flagella assembly, bacterial motility proteins, and pantothenate/coenzyme A biosysnthesis were enriched in R, along with phagosome and mTOR pathway modifiers. Nucleotide sugar metabolism, nitrogen metabolism, cyanoamino acid metabolism, and glycosphingolipid biosynthesis were all enriched in NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Functional characterization of the microbiome
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
“While the majority of species enriched in R corresponded to the previously reported results, for all species level assignments, only a subset of microbial signals retained statistical significance after FDR correction (Table S2).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Initial analysis of reported bacterial signatures.
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, the AUCs for the Routy NSCLC cohort improved by 7.59–10.91% for Integrated Indices, but the Routy RCC cohort results did not change.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The Random Effects meta-analysis models were significant individually for R- or NR-associated indices and also as a composite, termed “Integrated Index[Sum]”.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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
“Conversely, the R signal was consistently, but modestly, enriched in the Integrated and Literature Indices, but not significant in the ICI R Melanoma Literature Index.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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 our Integrated Index, utilizing our newly identified R and NR taxa, was compared to either the Literature or Melanoma Literature Indices, the NR and composite signals outperformed the corresponding signals from either the Literature or Melanoma Literature Indices.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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
“These newly identified individual members (Fig. 2, above) enabled us to re-evaluate and develop novel indicator indices for R and NR signals, termed Integrated Microbiome Prediction Indices, or “Integrated Index” for short, along with a composite sum of both signals derived as [R index] – [NR index].”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Development of indicator indices
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.
It may state two separate claims as one.
In the paper
“Moreover, while, in general, lower alpha-diversity has been associated with disease states and higher alpha-diversity with healthy states, we found that alpha-diversity was not consistently predictive of response or nonresponse to ICIs, though we confirmed the association of higher alpha diversity in R as reported by Gopalakrishnan et al (8).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites Gopalakrishnan et al (8)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
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
“F. prausnitzii and A. muciniphila had been previously identified and we confirmed the enrichment of these species in R though neither species met the initial significance cutoff of p ≤0.10 in the random effects model.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“F. prausnitzii and A. muciniphila had been previously identified and we confirmed the enrichment of these species in R though neither species met the initial significance cutoff of p ≤0.10 in the random effects model.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In fact, when we were able to exclude SD patients (only the Frankel and Routy cohorts), our overall Integrated Indices improved, with a notable improvement in the Routy NSCLC cohort.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Further, we were able to validate the Integrated Microbiome Prediction Index in independent cohorts of two tumor types, melanoma and HCC, albeit with small cohorts using publically available data, whereas 16S rRNA sequences derived from NSCLC patients performed less well overall.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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
“Our analyses enabled identification of novel bacterial signatures associated with clinical R and NR to ICI therapy that were not detected in smaller cohorts, and in particular, an unexpected strong microbiome association with ICI NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the 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”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Introduction
What the sources say
- Not checked yetcites [5] Matson, 2018, The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients, Science source
- Not checked yetcites [6] Routy, 2018, Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors, Science source
- Not checked yetcites [7] Frankel, 2017, Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients, Neoplasia source
- Not checked yetcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science source
- Not checked yetcites [9] Chaput, 2017, Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab, Ann Oncol source
- Not checked yetcites [10] Gharaibeh, 2019, Microbiota and cancer immunotherapy: in search of microbial signals, Gut source
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.
In the paper
“only 10–30% of treated patients respond and the ability to predict clinical benefit remains elusive”
- Also stated in: § Introduction · plain
“only ~10–30% of all tumors respond to treatment (3)”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Abstract > Purpose:
What the sources say
- Not checked yetcites [3] Sears, 2018, The intestinal microbiome influences checkpoint blockade, Nat Med source
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.
It may state two separate claims as one.
- Also stated in: § Introduction · plain
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Moreover, use of differing pipelines has limited the interpretability of the data presented to date for prediction of clinical anti-tumor responses, and whether microbiota signals predict non-response to ICIs has received less attention.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Introduction
plaindirect- 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.
None of the sources cited for this claim have been checked yet.
In the 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.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Introduction
What the sources say
- Not checked yetcites [5] Matson, 2018, The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients, Science source
- Not checked yetcites [6] Routy, 2018, Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors, Science source
- Not checked yetcites [7] Frankel, 2017, Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients, Neoplasia source
- Not checked yetcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science source
- Not checked yetcites [9] Chaput, 2017, Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab, Ann Oncol source
- Not checked yetcites [10] Gharaibeh, 2019, Microbiota and cancer immunotherapy: in search of microbial signals, Gut source
hedgedcorrelational- 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.
None of the sources cited for this claim have been checked yet.
In the 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.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Introduction
What the sources say
- Not checked yetcites [5] Matson, 2018, The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients, Science source
- Not checked yetcites [6] Routy, 2018, Gut microbiome influences efficacy of PD-1–based immunotherapy against epithelial tumors, Science source
- Not checked yetcites [7] Frankel, 2017, Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients, Neoplasia source
- Not checked yetcites [8] Gopalakrishnan, 2018, Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients, Science source
- Not checked yetcites [9] Chaput, 2017, Baseline gut microbiota predicts clinical response and colitis in metastatic melanoma patients treated with ipilimumab, Ann Oncol source
- Not checked yetcites [10] Gharaibeh, 2019, Microbiota and cancer immunotherapy: in search of microbial signals, Gut source
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.
None of the sources cited for this claim have been checked yet.
In the paper
“Further Resphera Insight has been validated as largely highly accurate for detection of Bacterioides and Fusobacterium spp. (13) and is also used by the FDA to enhance species identification contaminating the food chain (16,17).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Introduction
What the sources say
- Not checked yetcites [13] Drewes, 2017, High-resolution bacterial 16S rRNA gene profile meta-analysis and biofilm status reveal common colorectal cancer consortia, NPJ Biofilms Microbiomes source
- Not checked yetcites [16] Ottesen, 2016, Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak, BMC Microbiol source
- Not checked yetcites [17] Grim, 2017, High-resolution microbiome profiling for detection and tracking of Salmonella enterica, Front Microbiol source
boosted- 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 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
“Our analysis highlights the development of biomarkers for nonresponse, rather than response, in predicting ICI outcomes and suggests a new approach to identify patients who would benefit from microbiome-based interventions to improve response rates.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Abstract > Conclusions:
hedgedcorrelational- 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 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 stability of the gut microbiome during treatment with checkpoint inhibitors as described in the original reports.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Analysis of longitudinal fecal samples
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Butanoate is the main biosynthetic pathway for butyrate, a short-chain fatty acid considered essential for immune and gut homeostasis.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Functional characterization of the microbiome
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: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“Butyrate and butyrate-producing bacteria such as F. prausnitzii and R. hominis, have been linked to favorable anti-tumor responses in multiple studies (20).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Functional characterization of the microbiome
What the sources say
- Not checked yetcites [20] Skelly, 2019, Mining the microbiota for microbial and metabolite-based immunotherapies, Nat Rev Immunol source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
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
“While these discrepancies could be due to variation(s) among patient cohorts due to regional or other clinical differences, alternatively, this result may argue for functional redundancy among the members of the Bacteroides genus, and in fact, we found three other members of the Bacteroides genus enriched in NR.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
None of the sources cited for this claim have been checked yet.
In the paper
“Third, many of these studies utilized ICIs as monotherapy in a heavily pretreated population whereas current standard first-line therapy often includes a combination of ICIs or ICI with chemotherapy for multiple tumor types (35–40).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [35] George, 2019, Emerging role of combination immunotherapy in the first-line treatment of advanced renal cell carcinoma: a review, JAMA Oncol source
- Not checked yetcites [36] Wolchok, 2017, Overall survival with combined nivolumab and ipilimumab in advanced melanoma, N Engl J Med source
- Not checked yetcites [37] Gandhi, 2018, Pembrolizumab plus chemotherapy in metastatic non–small-cell lung cancer, N Engl J Med source
- Not checked yetcites [38] Horn, 2018, First-line atezolizumab plus chemotherapy in extensive-stage small-cell lung cancer, N Engl J Med source
- Not checked yetcites [39] Hellmann, 2019, Nivolumab plus ipilimumab in advanced non-small-cell lung cancer, N Engl J Med source
- Not checked yetcites [40] Motzer, 2018, Nivolumab plus Ipilimumab versus Sunitinib in advanced renal-cell carcinoma, N Engl J Med source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
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
“Second, our sample analysis was limited by only having data available from pre-treatment samples and a lack of information to stratify patients based on class of antibiotic exposure, exposure timeline, and other concurrent medication usage.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Several retrospective studies have shown the detrimental effect of antibiotic use on overall survival in patients undergoing treatment with checkpoint inhibitors (28,29).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [28] Pinato, 2019, Antibiotic therapy and outcome from immune-checkpoint inhibitors, J Immunother Cancer source
- Not checked yetcites [29] Derosa, 2018, Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer, Ann Oncol source
plaindirect- 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.
None of the sources cited for this claim have been checked yet.
In the paper
“In addition. V. parvula has been previously linked to disease states and specifically enriched in the lung microbiome of patients with a primary lung malignancy (32–34).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [32] Lee, 2016, Characterization of microbiome in bronchoalveolar lavage fluid of patients with lung cancer comparing with benign mass like lesions, Lung Cancer source
- Not checked yetcites [33] Liu, 2018, Difference of lower airway microbiome in bilateral protected specimen brush between lung cancer patients with unilateral lobar masses and control subjects, Int J Cancer source
- Not checked yetcites [34] Tsay, 2018, Airway microbiota is associated with upregulation of the PI3K pathway in lung cancer, Am J Respir Crit Care Med source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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
“Fourth, regional differences in baseline microbiota due to diet or other clinical features could affect the comparison of signals across cohorts.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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
“Given the consistent enrichment of microbial signals in NR across study cohorts, the NR Integrated Index may be a better predictor of the outcome of ICI therapy and serve to identify patients for whom alteration of the intestinal microbiome might offer clinical benefit.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
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.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This result is not unexpected given the dominant microbiome remodeling induced by antibiotics and reinforces recent observations suggesting that recent antibiotic exposure hinders ICI therapeutic responses (28,29).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [28] Pinato, 2019, Antibiotic therapy and outcome from immune-checkpoint inhibitors, J Immunother Cancer source
- Not checked yetcites [29] Derosa, 2018, Negative association of antibiotics on clinical activity of immune checkpoint inhibitors in patients with advanced renal cell and non-small-cell lung cancer, Ann Oncol source
hedgeddirect- 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.
In the paper
“For example, the genus Bacteroides in human stools is often more abundant in patients in the USA compared to global levels while the genus Prevotella is more abundant outside the USA (41).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [41] Gorvitovskaia, 2016, Interpreting prevotella and bacteroides as biomarkers of diet and lifestyle, Microbiome source
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.
In the paper
“Yet recent data identified cross-reactivity between a B. thetaiotaomicron β–galactosidase and myosin peptide associated with development of cardiomyopathy in genetically susceptible individuals (31).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [31] Gil-Cruz, 2019, Microbiota-derived peptide mimics drive lethal inflammatory cardiomyopathy, Science source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Of note, B. thetaiotaomicron is commonly considered a symbiote (30).”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
What the sources say
- Not checked yetcites [30] Xu, 2003, A genomic view of the human-Bacteroides thetaiotaomicron symbiosis, Science source
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 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
“In this combined dataset, the microbiome signals correlating with nonresponse were dominant, suggesting these microbes provide a potentially powerful biomarker for the selection of patients who might not ordinarily respond to checkpoint blockade but might benefit from microbiome-based interventions that reduce or eliminate specific species.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
hedgedcorrelational- 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 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
“In summary, use of a consistent analysis methodology improved on existing pipelines by standardizing critical preprocessing and downstream analysis tools, enabling comprehensive evaluations of taxonomic and functional signals across sequencing datasets that represent patients with melanoma, lung cancer, and renal cell carcinoma.”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
plaindirect- 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.
The authors state this as an assumption.
The random-effects meta-analysis assumes that the true effect size can vary from study to study.
“The fixed effects model assumes a single shared effect size across all analyzed studies, while the random effects model assumes the effect size may vary from study to study (60); in this analysis, we emphasized the random effects model results.”
The paper relies on this without support.
Antibiotics dominantly remodel the gut microbiome.
“given the dominant microbiome remodeling induced by antibiotics”
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?
In the citing paper
“Three meta-analyses including multiple tumors and treatments and applying uniform computational approaches have not explained discrepancies among published cohorts14–16.”
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 [16]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Discussion
“our sample analysis was limited by only having data available from pre-treatment samples”
§ A uniform computational approach improved on existing pipelines to reveal microbiome biomarkers of non-response to immune checkpoint inhibitors > Results > Analysis of longitudinal fecal samples
“Two cohorts, Chaput (n=23) (9) and Routy (n=44) (6), reported on paired samples prior to and during treatment”
Citations
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 60 · Cited by 44
Research works printed but not linked: 2
- Therasse, 2000, New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada, J Natl Cancer Inst, 92, 205, 10.1093/jnci/92.3.205 · DOI · Paper page
- Antonopoulos, 2019, PATRIC as a unique resource for studying antimicrobial resistance, Brief Bioinform, 20, 1094, 10.1093/bib/bbx083 · DOI
Metadata
- Authors
- Shaikh, F. Y., White, J. R., Gills, J. J., Hakozaki, T., Richard, C., Routy, B., Okuma, Y., Usyk, M., Pandey, A., Weber, J. S., Ahn, J., Lipson, E. J., Naidoo, J., Pardoll, D. M., & Sears, C. L.
- Affiliations
- Johns Hopkins University (US)
- Resphera Biosciences (US)
- Tokyo Metropolitan Komagome Hospital (JP)
- Université de Montréal (CA)
- NYU Langone Health (US)
- Corresponding author
- Sears, Cynthia L.
- ORCID
- Venue
- Clinical Cancer Research
- Published
- 2021-02-16
- Volume
- 27
- Issue
- 9
- Pages
- 2571-2583
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- PMC
- PMC9053858
- OpenAlex
- W3129637558
- Cited by
- 44
- References
- 60
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 13 · 2023: 7 · 2022: 12 · 2021: 1
- FWCI
- 3.19
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- NIH (T32CA009071)
- NCATS (KL2TR001077)
- NCI (P30 CA006973)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biotechnology › Bacterial Cancer Therapy
- Keywords
- immune checkpoint inhibitors, gut microbiota, microbiome biomarkers, treatment non-response, predictive biomarkers, 16S rRNA amplicon sequencing, metagenomics, random effects models, sensitivity and specificity, cancer immunotherapy response, microbiota-targeted interventions
- MeSH terms
- Gastrointestinal Microbiome, Whole Genome Sequencing, Immune Checkpoint Inhibitors, Bacteria, Humans, RNA, Ribosomal, 16S, ROC Curve, Reproducibility of Results, Biomarkers, Genome, Bacterial, Computational Biology, Metagenomics, Microbiota
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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