Dataset Information

Relationship of the lung microbiome with PD-L1 expression and immunotherapy response in lung cancer.

ABSTRACT:

Background

Lung cancer is the primary cause of cancer-related deaths worldwide. The human lung serves as a niche to a unique and dynamic bacterial community that is related to the development of multiple diseases. Here, we investigated the differences in the lung microbiomes of patients with lung cancer.

Methods

16S rRNA sequencing was performed to evaluate the respiratory tract microbiome present in the bronchoalveolar lavage fluid. Patients were stratified based on programmed death-ligand 1 (PD-L1) expression levels and immunotherapy responses.

Results

In total, 84 patients were prospectively analyzed, of which 59 showed low (< 10%), and 25 showed high (≥ 10%) PD-L1 expression levels. The alpha and beta diversities did not significantly differ between the two groups. Veillonella dispar was dominant in the high-PD-L1 group; the population of Neisseria was significantly higher in the low-PD-L1 group than in the high-PD-L1 group. In the immunotherapy responder group, V. dispar was dominant, while Haemophilus influenzae and Neisseria perflava were dominant in the non-responder group.

Conclusion

The abundances of Neisseria and V. dispar differed significantly in relation to PD-L1 expression levels and immunotherapy responses.

SUBMITTER: Jang HJ

PROVIDER: S-EPMC8715618 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Relationship of the lung microbiome with PD-L1 expression and immunotherapy response in lung cancer.

Jang Hye Jin HJ Choi Ji Yeon JY Kim Kangjoon K Yong Seung Hyun SH Kim Yeon Wook YW Kim Song Yee SY Kim Eun Young EY Jung Ji Ye JY Kang Young Ae YA Park Moo Suk MS Kim Young Sam YS Cho Young-Jae YJ Lee Sang Hoon SH

Respiratory research 20211228 1

<h4>Background</h4>Lung cancer is the primary cause of cancer-related deaths worldwide. The human lung serves as a niche to a unique and dynamic bacterial community that is related to the development of multiple diseases. Here, we investigated the differences in the lung microbiomes of patients with lung cancer.<h4>Methods</h4>16S rRNA sequencing was performed to evaluate the respiratory tract microbiome present in the bronchoalveolar lavage fluid. Patients were stratified based on programmed de ...[more]

PMID: 34963470

Similar Datasets

Project description:Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN 177STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P=0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P=0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN 177STYR (H3N4) of IgG4, EEQYN 227STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.

Dataset Information

Relationship of the lung microbiome with PD-L1 expression and immunotherapy response in lung cancer.

Background

Methods

Results

Conclusion

Publications

Relationship of the lung microbiome with PD-L1 expression and immunotherapy response in lung cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets