Dataset Information

The Microbiome in Lung Cancer Tissue and Recurrence-Free Survival.

ABSTRACT:

Background

Human microbiota have many functions that could contribute to cancer initiation and/or progression at local sites, yet the relation of the lung microbiota to lung cancer prognosis has not been studied.

Methods

In a pilot study, 16S rRNA gene sequencing was performed on paired lung tumor and remote normal samples from the same lobe/segment in 19 patients with non-small cell lung cancer (NSCLC). We explored associations of tumor or normal tissue microbiome diversity and composition with recurrence-free (RFS) and disease-free survival (DFS), and compared microbiome diversity and composition between paired tumor and normal samples.

Results

Higher richness and diversity in normal tissue were associated with reduced RFS (richness P = 0.08, Shannon index P = 0.03) and DFS (richness P = 0.03, Shannon index P = 0.02), as was normal tissue overall microbiome composition (Bray-Curtis P = 0.09 for RFS and P = 0.02 for DFS). In normal tissue, greater abundance of family Koribacteraceae was associated with increased RFS and DFS, whereas greater abundance of families Bacteroidaceae, Lachnospiraceae, and Ruminococcaceae were associated with reduced RFS or DFS (P < 0.05). Tumor tissue diversity and overall composition were not associated with RFS or DFS. Tumor tissue had lower richness and diversity (P ≤ 0.0001) than paired normal tissue, though overall microbiome composition did not differ between the paired samples.

Conclusions

We demonstrate, for the first time, a potential relationship between the normal lung microbiota and lung cancer prognosis, which requires confirmation in a larger study.

Impact

Definition of bacterial biomarkers of prognosis may lead to improved survival outcomes for patients with lung cancer.

SUBMITTER: Peters BA

PROVIDER: S-EPMC6449216 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

The Microbiome in Lung Cancer Tissue and Recurrence-Free Survival.

Peters Brandilyn A BA Hayes Richard B RB Goparaju Chandra C Reid Christopher C Pass Harvey I HI Ahn Jiyoung J

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20190207 4

<h4>Background</h4>Human microbiota have many functions that could contribute to cancer initiation and/or progression at local sites, yet the relation of the lung microbiota to lung cancer prognosis has not been studied.<h4>Methods</h4>In a pilot study, 16S rRNA gene sequencing was performed on paired lung tumor and remote normal samples from the same lobe/segment in 19 patients with non-small cell lung cancer (NSCLC). We explored associations of tumor or normal tissue microbiome diversity and c ...[more]

PMID: 30733306

Similar Datasets

Project description:BackgroundCancer recurrence after tumor resection in early-stage non-small cell lung cancer (NSCLC) is common, yet difficult to predict. The lung microbiota and systemic immunity may be important modulators of risk for lung cancer recurrence, yet biomarkers from the lung microbiome and peripheral immune environment are understudied. Such markers may hold promise for prediction as well as improved etiologic understanding of lung cancer recurrence.MethodsIn tumor and distant normal lung samples from 46 stage II NSCLC patients with curative resection (39 tumor samples, 41 normal lung samples), we conducted 16S rRNA gene sequencing. We also measured peripheral blood immune gene expression with nanoString®. We examined associations of lung microbiota and peripheral gene expression with recurrence-free survival (RFS) and disease-free survival (DFS) using 500 × 10-fold cross-validated elastic-net penalized Cox regression, and examined predictive accuracy using time-dependent receiver operating characteristic (ROC) curves.ResultsOver a median of 4.8 years of follow-up (range 0.2-12.2 years), 43% of patients experienced a recurrence, and 50% died. In normal lung tissue, a higher abundance of classes Bacteroidia and Clostridia, and orders Bacteroidales and Clostridiales, were associated with worse RFS, while a higher abundance of classes Alphaproteobacteria and Betaproteobacteria, and orders Burkholderiales and Neisseriales, were associated with better RFS. In tumor tissue, a higher abundance of orders Actinomycetales and Pseudomonadales were associated with worse DFS. Among these taxa, normal lung Clostridiales and Bacteroidales were also related to worse survival in a previous small pilot study and an additional independent validation cohort. In peripheral blood, higher expression of genes TAP1, TAPBP, CSF2RB, and IFITM2 were associated with better DFS. Analysis of ROC curves revealed that lung microbiome and peripheral gene expression biomarkers provided significant additional recurrence risk discrimination over standard demographic and clinical covariates, with microbiome biomarkers contributing more to short-term (1-year) prediction and gene biomarkers contributing to longer-term (2-5-year) prediction.ConclusionsWe identified compelling biomarkers in under-explored data types, the lung microbiome, and peripheral blood gene expression, which may improve risk prediction of recurrence in early-stage NSCLC patients. These findings will require validation in a larger cohort.

Dataset Information

The Microbiome in Lung Cancer Tissue and Recurrence-Free Survival.

Background

Methods

Results

Conclusions

Impact

Publications

The Microbiome in Lung Cancer Tissue and Recurrence-Free Survival.

Similar Datasets

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