The Diversity of Gut Microbiome is Associated With Favorable Responses to Anti-Programmed Death 1 Immunotherapy in Chinese Patients With NSCLC

Study information

Reviewed Marked as Reviewed by Fatima on 2022/08/17

study design

prospective cohort

Citation

PMID PubMed identifier for scientific articles.

31026576

DOI Digital object identifier for electronic documents.

10.1016/j.jtho.2019.04.007

URI

https://pubmed.ncbi.nlm.nih.gov/31026576/#:~:text=Patients%20With%20NSCLC-,The%20Diversity%20of%20Gut%20Microbiome%20is%20Associated%20With%20Favorable%20Responses,(8)%3A1378%2D1389.

Authors

Jin Y, Dong H, Xia L, Yang Y, Zhu Y, Shen Y, Zheng H, Yao C, Wang Y, Lu S

Journal

Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer

Year

2019

Keywords:

Advanced NSCLC, Clinical benefit, Gut microbiota, Nivolumab, Systemic immune signatures

INTRODUCTION: Gut microbiome affecting the responses to immune checkpoint inhibitors against advanced NSCLC has been investigated in the Western population. However, considering pre-existing genetic and gut microbiota variation, the relevance remains unknown in the East-Asian NSCLC population. This study is designed to explore the relationship between gut microbiome and clinical outcomes in Chinese patients with NSCLC who have received treatment using an anti-programmed death 1 (PD-1) blockade. METHODS: Thirty-seven patients with advanced NSCLC receiving treatment with nivolumab were enrolled in CheckMate 078 (NCT02613507) and CheckMate 870 (NCT03195491). Fecal samples were collected at the starting point, when patients received nivolumab, at clinical evaluation, and when disease progression was noted. 16S ribosome RNA gene sequencing was applied to assess gut microbiota profiles. Peripheral immune signatures were determined by multicolor flow cytometry in parallel. RESULTS: When subgrouping patients into responder (R) and nonresponder according to the clinical response assessed using Response Evaluation Criteria in Solid Tumor version 1.1, R patients harbored higher diversity of gut microbiome at the starting point with stable composition during the treatment. Patients with high microbiome diversity had significantly prolonged progression-free survival when compared to those with low diversity. Compositional difference was observed between the two groups as well with the enrichment of Alistipes putredinis, Bifidobacterium longum, and Prevotella copri in R whereas Ruminococcus_unclassified enriched in nonresponding patients. Analysis of systemic immune responses using multicolor flow cytometry revealed that patients with a high abundance of microbiome diversity in the gut had a greater frequency of unique memory CD8+ T cell and natural killer cell subsets in the periphery in response to anti-PD-1 therapy. CONCLUSIONS: Our results reveal strong correlation between gut microbiome diversity and the responses to anti-PD-1 immunotherapy in Chinese patients with advanced NSCLC. Patients with favorable gut microbiome (such as those with high diversity) exhibit enhanced memory T cell and natural killer cell signatures in the periphery. These findings provide important implications for the prediction and the evaluation of anti-PD-1 immunotherapy against NSCLC in the Chinese population.

Experiment 1

Edit History Delete

Flag for review

Your review change was submittedDuplicate this Experiment Add a new Signature

Reviewed Marked as Reviewed by Fatima on 2022/08/17

Curated date: 2022/07/25

Curator: Sharmilac

Revision editor(s): Sharmilac, Fatima, Peace Sandy

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: Patients in this study were defined as responder (R) (with partial response or stable disease)

Group 0 sample size Number of subjects in the control (unexposed) group: 14

Group 1 sample size Number of subjects in the case (exposed) group: 23

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V3-V4

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: relative abundances

Statistical test: Kruskall-Wallis

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: increased

Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa: increased

Signature 1

Edit History Delete

Flag for review

Your review change was submitted

Reviewed Marked as Reviewed by Fatima on 2022/08/17

Curated date: 2022/07/25

Curator: Sharmilac

Revision editor(s): Sharmilac

Source: Figures 3a,b & c

Description: Comparison of gut microbiota composition between responders (R) and non responders (NR). (A) Heatmap of seven bacterial genera with statistically differential abundance in R (n ¼ 13) and NR (n ¼ 12) at baseline. (B) Histogram of two representative differentially abundant genera at baseline. (C) Histogram of Bifidobacterium longum and Prevotella copri at baseline (left) and T1 timepoint (right). Statistical analysis was performed by Mann-Whitney test. **p < 0.01, * p < 0.05.

Abundance in Group 1: increased abundance in Responders

NCBI	Quality Control	Links
Alistipes putredinis
Bifidobacterium longum
Lachnobacterium
Lachnospiraceae
Segatella copri
Shigella

Revision editor(s): Sharmilac

Signature 2

Edit History Delete

Flag for review

Your review change was submitted

Reviewed Marked as Reviewed by Fatima on 2022/08/17

Curated date: 2022/07/25

Curator: Sharmilac

Revision editor(s): Sharmilac

Source: Figure 3a,b,c

Description: Comparison of gut microbiota composition between responders (R) and non responders (NR). (A) Heatmap of seven bacterial genera with statistically differential abundance in R (n ¼ 13) and NR (n ¼ 12) at baseline. (B) Histogram of two representative differentially abundant genera at baseline. (C) Histogram of Bifidobacterium longum and Prevotella copri at baseline (left) and T1 timepoint (right). Statistical analysis was performed by Mann-Whitney test. **p < 0.01, * p < 0.05.

Abundance in Group 1: decreased abundance in Responders

NCBI	Quality Control	Links
unclassified Ruminococcus

Revision editor(s): Sharmilac