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

Jin, Yueping; Dong, Hongyan; Xia, Lixue; Yang, Yi; Zhu, Yaping; Shen, Yan; Zheng, Huajun; Yao, Chengcheng; Wang, Ying; Lü, Shun

doi:10.1016/j.jtho.2019.04.007

Cited by 316 publications

(269 citation statements)

References 53 publications

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“…Components 1 and 2 accounted for 12.6% and 8.7% of the difference in PCoA, respectively. Jin et al . grouped 25 patients who used nivolumab according to responders (R) and nonresponders (NR) and found that the α‐diversity of baseline gut microbiome was significantly higher in the R group ( n = 13) than in the NR group ( n = 12).…”

Section: Discussionmentioning

confidence: 99%

“…reported analysis results of 38 fecal pretreatment samples, showing that Bifidobacterium longum , Collinsella aerofaciens , and Enterococcus faecium were associated with a better prognosis. Jin et al . performed shotgun metagenomic sequencing on 25 Chinese patients and found that unclassified Ruminococcus was enriched in the NR group, while Alistipesputredinis , Prevotella , Bifidobacterium longum , Lachnobacterium , Lachnospiraceae, and Shigella were enriched in R group.…”

Section: Discussionmentioning

confidence: 99%

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Relationship between intestinal flora structure and metabolite analysis and immunotherapy efficacy in Chinese NSCLC patients

et al. 2020

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KeywordsΒ-diversity; intestinal flora; non-small cell lung cancer; programmed cell death 1 (PD-1); programmed cell death 1 ligand(PD-L1). CorrespondenceLi Zhang, AbstractBackground: Many immune checkpoint inhibitors (ICIs) have been approved in China to treat non-small cell lung cancer (NSCLC). However, in the long term, less than 20% of patients benefit from ICIs. To maximize the benefit for NSCLC patients, it is necessary to guide the choice of immunotherapy through biomarkers. Recent studies have shown that gut microbiota can affect tumor response to immunotherapy and might be a potential predictive biomarker. This study analyzed the relationship between intestinal flora structure and metabolomic characteristics in NSCLC and the efficacy of ICIs. Methods: Prospective analysis of samples from 63 patients with advanced NSCLC who attended the Department of Respiratory Medicine of the Peking Union Medical College Hospital from March 2018 to June 2019, and were prescribed programmed cell death 1 (PD-1) inhibitors, was carried out. The followup deadline was 31 December 2019. Stool samples were collected from all patients before the start of immunotherapy. DNA was extracted from all samples and libraries were constructed. This was followed by sequencing using the Illumina sequencing platform, and results were studied using a biological information data analysis process. We divided the data into two groups based on progression-free survival (PFS) ≥ six months and PFS < six months. Results: The median PFS was 7.0 months, not reaching the median overall survival (OS). We obtained 373.5 G of original sequencing data. The phyla Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria accounted for most of the bacterial communities in the stool samples studied. Compared with the PFS < six-month group, the patients in the PFS ≥ six-month group had significantly higher β-diversity in the intestinal microbiome at the baseline level. There were also differences in composition between the two groups. Samples in the PFS ≥ six-month group were rich in Parabacteroides and Methanobrevibacter, while those in the PFS < six-month group were rich in Veillonella, Selenomonadales, and Negativicutes. The KO, COG, and CAZy databases were used to study functional group protein families, yielding 390 (KO), 264 (COG), and 859 (CAZy) functional group abundances, with significant differences between the two groups. Bacterial metabolites analysis suggested significant differences in the metabolic potential of methanol and methane between the two groups. Conclusions: We found a close correlation between intestinal microbiome β-diversity and anti-PD-1 immunotherapy response in Chinese patients with advanced NSCLC. The intestinal flora composition, functional group protein

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Relationship between intestinal flora structure and metabolite analysis and immunotherapy efficacy in Chinese NSCLC patients

et al. 2020

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“…Higher species diversity is correlated with higher response rates to ICIs [30,31], hence we analyzed the alpha diversity. As shown in Figure 2E, compared with the control group or the α-PD-L1 group, the alpha diversity indices of the communities from samples of the α-PD-L1/LCP-chitosan group were significantly decreased, indicating a profound impact of LCP-chitosan on mice gut microbiome.…”

Section: Diversity Of the Gut Microbiome Of Mice With Different Treatmentioning

confidence: 99%

Biostimulating Gut Microbiome with Bilberry Anthocyanin Combo to Enhance Anti-PD-L1 Efficiency against Murine Colon Cancer

et al. 2020

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Recent advances have revealed the essential role of gut microbiomes in the therapeutic efficiency of immune checkpoint inhibitors (ICIs). Inspired by biostimulation, a method using nutrients to accelerate the growth of soil microorganisms and the recovery of soil microbial consortia, here we propose a bilberry anthocyanin combo containing chitosan and low molecular citrus pectin (LCP), in which LCP–chitosan is used to encapsulate anthocyanins so to enhance its digestive stability and, moreover, modulate the microbiome more favorable for the PD-L1 blockade treatment. Using murine MC38 colon cancer as a model system, we examined the effects of the combo on modulating the gut microbiome and therapeutic efficiency of PD-L1 blockade treatment. It was shown that bilberry anthocyanins enriched the subdominant species, increased both the concentration and the proportion of butyrate in feces and enhanced intratumoral CD8+ T cell infiltrations. The application of the bilberry anthocyanin combo restored the species diversity of gut microbiome decreased by LCP–chitosan and achieved the best control of tumor growth. These preliminary results indicated unprecedented opportunities of probiotics combo in improving the therapeutic efficiency of immune checkpoint inhibitor through manipulating gut microbiome.

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“…Conversely, non-genetic factors, including life styles, environmental factors and lung and gut microbes are believed to contribute mostly to the disease. Especially, numerous recent studies have shown that both lung and gut microbiota are involved in the development of LC [6–8]. For example, researchers have used samples from bronchoalveolar fluid (BALF), tissues and spontaneous sputum of lung cancer patients for bacterial identification and microbiome characterization [7, 9–11].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, dysbiosis of gut microbiome has also been associated with many cancers [8, 13, 14], including LC [8]. A previous study suggested an increase in Enterococcus in the stool of patients with LC, compared with the stool of healthy subjects, and a decrease in Bifidobacterium and Actinobacteria [6], which others have shown that the response to immunotherapy (IO) in NSCLC patients is associated with changes of individual species such as Alistipes putredinis, Bifidobacterium longum and Prevotella copri as well as the overall diversity of the gut microbiome [7, 8]. Furthermore, increasing evidence have shown that the gut microbiome may play important roles in cancer by modulating inflammation [15], host immune response [16, 17] and directly interacting with therapeutic drugs [18].…”

Section: Introductionmentioning

confidence: 99%

Alterations of human lung and gut microbiome in non-small cell lung carcinomas and distant metastasis

Lü

Gao

Wei

et al. 2020

Preprint

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25Background 26Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths 27 worldwide. Although dysbiosis of lung and gut microbiota have been associated with 28 NSCLC, their relative contributions are unclear; in addition, their roles in distant metastasis 29 (DM) are still illusive. 30 Results 31We surveyed the fecal and sputum (as a proxy for lung) microbiota in healthy controls and 32 NSCLC patients of various stages, and found significant perturbations of gut-and sputum-33 microbiota in patients with NSCLC and DM. Machine-learning models combining both 34 microbiota (mixed models) performed better than either dataset in patient stratification, 35with the highest area under the curve (AUC) value of 0.842. Sputum-microbiota 36 contributed more than the gut in the mixed models; in addition, sputum-only models 37 performed similarly to the mixed models in most cases. Several microbial-biomarkers were 38 shared by both microbiota, indicating their similar roles at distinct body sites. 39Microbial-biomarkers of distinct disease stages were mostly shared, suggesting 40 biomarkers for distant metastasis could be acquired early. Furthermore, Pseudomonas 41 aeruginosa, a species previously associated with wound infections, was significantly more 42 3 abundant in brain metastasis, indicating distinct types of DMs could have different 43 microbial-biomarkers. 44 Conclusion 45Our results indicate that alterations of sputum-microbiota have stronger relationships with 46 NSCLC and distant metastasis than the gut, and strongly support the feasibility of 47 metagenome-based non-invasive disease diagnosis and risk evaluation. 48 49 Keywords: gut microbiota, lung microbiota, machine learning, patient stratification, 50 NSCLC, distant metastasis, brain metastasis 51 52 4 53 Background 54 Lung cancer (LC) is the leading cause of cancer-related deaths mortality worldwide, with 55 non-small cell lung cancer (NSCLC) being the most common form of LC [1]. Despite the 56 recent development of therapies for NSCLC, tumor metastasis is the main cause of 57 recurrence and mortality in patients with NSCLC [1]. One of the key challenges is the low 58 heritability of lung cancer susceptibility revealed by genetic studies: although numerous 59 studies have established the important roles of somatic mutations as well as inheritable 60 familial risks [2, 3], the genetic influence can only explain 3~15% of the heritability [4, 5], 61 depending on the surveyed population. 62 Conversely, non-genetic factors, including life styles, environmental factors and lung 63 and gut microbes are believed to contribute mostly to the disease. Especially, numerous 64 recent studies have shown that both lung and gut microbiota are involved in the 65 development of LC [6-8]. For example, researchers have used samples from 66 bronchoalveolar fluid (BALF), tissues and spontaneous sputum of lung cancer patients for 67 bacterial identification and microbiome characterization [7, 9-11]. When compared with 68 healthy controls, researchers have id...

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

Cited by 316 publications

References 53 publications

Relationship between intestinal flora structure and metabolite analysis and immunotherapy efficacy in Chinese NSCLC patients

Relationship between intestinal flora structure and metabolite analysis and immunotherapy efficacy in Chinese NSCLC patients

Biostimulating Gut Microbiome with Bilberry Anthocyanin Combo to Enhance Anti-PD-L1 Efficiency against Murine Colon Cancer

Alterations of human lung and gut microbiome in non-small cell lung carcinomas and distant metastasis

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