Abstract

BackgroundAlthough recent studies have indicated that imbalance in the respiratory microbiome composition is linked to several chronic respiratory diseases, the association between the lung microbiome and lung cancer has not been extensively studied. Conflicting reports of individual studies on respiratory microbiome alterations in lung cancer complicate the matter for specifying how the lung microbiome is linked to lung cancer. Consequently, as the first meta-analysis on this topic, we integrate publicly available 16S rRNA gene sequence data on lung tissue samples of lung cancer patients to identify bacterial taxa which differ consistently between case and control groups.ResultsThe findings of the current study suggest that the relative abundance of several bacterial taxa including Actinobacteria phylum, Corynebacteriaceae and Halomonadaceae families, and Corynebacterium, Lachnoanaerobaculum, and Halomonas genera is significantly decreased (p < 0.05) in lung tumor tissues of lung cancer patients in comparison with tumor-adjacent normal tissues.ConclusionsDespite the underlying need for scrutinizing the findings further, the present study lays the groundwork for future research and adds to our limited understanding of the key role of the lung microbiome and its complex interaction with lung cancer. More data on demographic factors and tumor tissue types would help establish a greater degree of accuracy in characterizing the lung microbial community which accords with subtypes and stages of the disease and fully capturing the changes of the lung microbiome in lung cancer.

Highlights

  • Recent studies have indicated that imbalance in the respiratory microbiome composition is linked to several chronic respiratory diseases, the association between the lung microbiome and lung cancer has not been extensively studied

  • As the first meta-analysis of the lung microbiome in lung cancer (LC) patients, we reprocessed and integrated 16S rRNA gene sequence data on lung biopsy specimens with geographically different sample origins across five studies consisting of 356 tumor tissues and 493 tumor-adjacent normal tissues

  • Regression coefficients from the GAMLSS-BEZI model were retrieved as summary statistics and combined by employing a random-effects meta-analysis model to seek consistent associations between lung cancer and the lung microbiome at various taxonomic levels

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Summary

Introduction

Recent studies have indicated that imbalance in the respiratory microbiome composition is linked to several chronic respiratory diseases, the association between the lung microbiome and lung cancer has not been extensively studied. Contradictory results may stem from the lack of a standard pipeline in preprocessing the metagenomic data, differences in study designs, clinical sample types, and computational methods as well as other confounding factors and inter-study batch effects such as experimental procedures, targeted hypervariable regions of 16S rRNA gene for amplification and sequencing platforms [25]. These limitations hinder the generalizability of the results, necessitating the need for meta-analysis studies. We have aimed to identify the differences in the microbiome between the two groups and determine the possible associations between the taxonomic composition of the lung microbiome and lung cancer

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