Gut microbiome affects the response to anti-PD-1 immunotherapy in patients with hepatocellular carcinoma
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
Authors
Zheng Y, Wang T, Tu X, Huang Y, Zhang H, Tan D, Jiang W, Cai S, Zhao P, Song R, Li P, Qin N, Fang W
Journal
Journal for immunotherapy of cancer
Year
2019
Keywords:
Anti-PD-1 immunotherapy, Gut microbiome, Hepatocellular carcinoma
BACKGROUND: Checkpoint-blockade immunotherapy targeting programmed cell death protein 1 (PD-1) has recently shown promising efficacy in hepatocellular carcinoma (HCC). However, the factors affecting and predicting the response to anti-PD-1 immunotherapy in HCC are still unclear. Herein, we report the dynamic variation characteristics and specificities of the gut microbiome during anti-PD-1 immunotherapy in HCC using metagenomic sequencing. RESULTS: Fecal samples from patients responding to immunotherapy showed higher taxa richness and more gene counts than those of non-responders. For dynamic analysis during anti-PD-1 immunotherapy, the dissimilarity of beta diversity became prominent across patients as early as Week 6. In non-responders, Proteobacteria increased from Week 3, and became predominant at Week 12. Twenty responder-enriched species, including Akkermansia muciniphila and Ruminococcaceae spp., were further identified. The related functional genes and metabolic pathway analysis, such as carbohydrate metabolism and methanogenesis, verified the potential bioactivities of responder-enriched species. CONCLUSIONS: Gut microbiome may have a critical impact on the responses of HCC patients treated with anti-PD-1 immunotherapy. The dynamic variation characteristics of the gut microbiome may provide early predictions of the outcomes of immunotherapy in HCC, which is critical for disease-monitoring and treatment decision-making.
Experiment 1
Reviewed Marked as Reviewed by Fatima on 2022/09/7
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Response to immunochemotherapy Response to immunochemotherapy,response to immunochemotherapy
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Non-responders
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Responders
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Responders (R, n = 3) were defined by radiographic evidence as complete or partial response, or stable disease lasting for at least six months.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 5
- Group 1 sample size Number of subjects in the case (exposed) group
- 3
Lab analysis
- Sequencing type
- WMS
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- BGISEQ-500 Sequencing
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- LEfSe
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
Alpha Diversity
- Richness Number of species
- increased
Signature 1
Reviewed Marked as Reviewed by Fatima on 2022/10/27
Source: text, Figure 2A, Figure S4
Description: Meta-analysis of the bacteria significantly enriched in R and NR. a Heatmap showing the relative abundance of R-enriched and NR-enriched bacterial species, as identified by LEfSe. Differentially abundant genera (a) and species (b) between R and NR, identified by LEfSe.
Abundance in Group 1: increased abundance in Responders
Signature 2
Reviewed Marked as Reviewed by Fatima on 2022/10/27
Source: text, Figure 2A
Description: Meta-analysis of the bacteria significantly enriched in R and NR. a Heatmap showing the relative abundance of R-enriched and NR-enriched bacterial species, as identified by LEfSe.
Abundance in Group 1: decreased abundance in Responders
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