Pulmonary Micro-Ecological Changes and Potential Microbial Markers in Lung Cancer Patients

Influence of gut and lung dysbiosis on lung cancer progression and their modulation as promising therapeutic targets: a comprehensive review

Lung cancer (LC) continues to pose the highest mortality and exhibits a common prevalence among all types of cancer. The genetic interaction between human eukaryotes and microbial cells plays a vital role in orchestrating every physiological activity of the host. The dynamic crosstalk between gut and lung microbiomes and the gut-lung axis communication network has been widely accepted as promising factors influencing LC progression. The advent of the 16s rDNA sequencing technique has opened new horizons for elucidating the lung microbiome and its potential pathophysiological role in LC and other infectious lung diseases using a molecular approach. Numerous studies have reported the direct involvement of the host microbiome in lung tumorigenesis processes and their impact on current treatment strategies such as radiotherapy, chemotherapy, or immunotherapy. The genetic and metabolomic cross-interaction, microbiome-dependent host immune modulation, and the close association between microbiota composition and treatment outcomes strongly suggest that designing microbiome-based treatment strategies and investigating new molecules targeting the common holobiome could offer potential alternatives to develop effective therapeutic principles for LC treatment. This review aims to highlight the interaction between the host and microbiome in LC progression and the possibility of manipulating altered microbiome ecology as therapeutic targets.

Mechanisms underlying the effects, and clinical applications, of oral microbiota in lung cancer: current challenges and prospects

The oral cavity contains a site-specific microbiota that interacts with host cells to regulate many physiological processes in the human body. Emerging evidence has suggested that changes in the oral microbiota can increase the risk of lung cancer (LC), and the oral microbiota is also altered in patients with LC. Human and animal studies have shown that oral microecological disorders and/or specific oral bacteria may play an active role in the occurrence and development of LC through direct and/or indirect mechanisms. These studies support the potential of oral microbiota in the clinical treatment of LC. Oral microbiota may therefore be used in the prevention and treatment of LC and to improve the side effects of anticancer therapy by regulating the balance of the oral microbiome. Specific oral microbiota in LC may also be used as screening or predictive biomarkers. This review summarizes the main findings in research on oral microbiome-related LC and discusses current challenges and future research directions.

The Lung Microbiota and Lung Cancer: A Growing Relationship

Simple Summary

In the past few years, the microbiota has emerged as a major player in cancer management. The efficacy of chemotherapy or immunotherapy may be influenced by the concomitant use of antibiotics before, during, or shortly after treatment with immune checkpoint inhibitors. Despite this, the mechanism linking the microbiota, host immunity, and malignancies are not clear, and the role of microbiota manipulation and analyses in cancer management is underway. In this manuscript, we discuss the role of the microbiota in the initiation, progression, and treatment outcomes of lung cancer.

Abstract

The lung is home to a dynamic microbial population crucial to modulating immune balance. Interest in the role of the lung microbiota in disease pathogenesis and treatment has exponentially increased. In lung cancer, early studies suggested an important role of dysbiosis in tumor initiation and progression. These results have helped accelerate research into the lung microbiota as a potential diagnostic marker and therapeutic target. Microbiota signatures could represent diagnostic biomarkers of early-stage disease. Lung microbiota research is in its infancy with a limited number of studies and only single-center studies with a significant methodological variation. Large, multicenter longitudinal studies are needed to establish the clinical potential of this exciting field.

Potential Association Between Changes in Microbiota Level and Lung Diseases: A Meta-Analysis

Objective:

Lung microbiota is increasingly implicated in multiple types of respiratory diseases. However, no study has drawn a consistent conclusion regarding the relationship between changes in the microbial community and lung diseases. This study verifies the association between microbiota level and lung diseases by performing a meta-analysis.

Methods:

Literature databases, including PubMed, ISI Web of Science, Embase, Google Scholar, PMC, and CNKI, were used to collect related articles published before March 20, 2021. The standard mean deviation (SMD) and related 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup, sensitivity, and publication bias analyses were also conducted.

Results:

Six studies, comprising 695 patients with lung diseases and 176 healthy individuals, were included in this meta-analysis. The results indicated that the microbiota level was higher in patients with lung diseases than in healthy individuals (SMD = 0.39, 95% CI = 0.22–0.55, I² = 91.5%, P < 0.01). Subgroup analysis based on country demonstrated that the microbiota level was significantly higher in Chinese (SMD = 1.90, 95% CI = 0.87–2.93, I² = 62.3%, P < 0.01) and Korean (SMD = 0.24, 95% CI = 0.13–0.35, I² = 78.7%, P < 0.01) patients with lung diseases. The microbiota level of patients with idiopathic pulmonary fibrosis (IPF) (SMD = 1.40, 95% CI = 0.42–2.38, I² = 97.3%, P = 0.005), chronic obstructive pulmonary disease (COPD) (SMD = 0.30, 95% CI = 0.09–0.50, I² = 83.9%, P = 0.004), and asthma (SMD = 0.19, 95% CI = 0.06–0.32, I² = 69.4%, P = 0.004) were significantly higher than those of the healthy group, whereas a lower microbiota level was found in patients with chronic hypersensitivity pneumonitis (CHP). The microbiota level significantly increased when the disease sample size was >50. Subgroup analysis based on different microbiota genera, indicated that Acinetobacter baumannii and Pseudomonas aeruginosa were significantly increased in COPD and asthma diseases.

Conclusion:

We observed that patients with IPF, COPD, and asthma had a higher microbiota level, whereas patients with CHP had a lower microbiota level compared to the healthy individuals. The level of A. baumannii and P. aeruginosa were significantly higher in patients with COPD and asthma, and thus represented as potential microbiota markers in the diagnosis and treatment of lung diseases.

Biogeography of the Respiratory Tract Microbiome in Patients With Malignant Tracheal Tumors

Background

This study aimed to characterize the bacterial microbiota in the oral cavity (OC), throat, trachea, and distal alveoli of patients with primary malignant tracheal tumors (PMTT), including squamous cell carcinoma (SCC) and salivary gland carcinoma patients (SGC), for comparison with a matched non-malignant tracheal tumor (NMTT) group.

Methods

Patients with pathological diagnosis of PMTT and NMTT were included in this study. Saliva, throat swab (TS), trachea protected specimen brush (PSB), and bronchoalveolar lavage fluid (BALF) samples were collected for 16S rRNA gene sequencing. The composition, diversity, and distribution of the microbiota were compared among biogeographic sampling sites and patient groups. The relationship between the genera-level taxon abundance and tracheal tumor types was also investigated to screen for candidate biomarkers.

Findings

The most represented phyla in the four sites were Bacteroidetes, Firmicutes, Proteobacteria, and Fusobacteria. In SCC patients, the relative abundance of Bacteroidetes and Firmicutes gradually decreased with increasing depth into the respiratory tract, while the relative abundance of Proteobacteria gradually increased. Bacterial communities at the four biogeographic sites formed two distinct clusters, with OC and TS samples comprising one cluster and PSB and BALF samples comprising the other group. Principal coordinate analysis showed that trachea microbiota in SCC patients were distinct from that of SGC or NMTT patients. In the trachea, AUCs generated by Prevotella and Alloprevotella showed that the abundance of these genera could distinguish SCC patients from both NMTT and SGC patients.

Interpretation

The structure of respiratory tract microbiota in PMTT patients is related to tumor type. Certain bacteria could potentially serve as markers of SCC, although verification with large-sample studies is necessary.

Microbiota Emergencies in the Diagnosis of Lung Diseases: A Meta-Analysis

Although many studies have reported that microbiota emergencies are deeply involved in the occurrence and subsequent progression of lung diseases, the present diagnosis of lung disease depends on microbiota markers, which is still poorly understood. Therefore, a meta-analysis was performed to confirm lung microbiota markers for the diagnosis of lung diseases. Literature databases were searched following the inclusion and exclusion criteria. There are 6 studies including 1347 patients and 26 comparisons to be enrolled, and then the diagnostic effect was evaluated using Stata 14.0 and Meta-disc 1.4 software. The pooled sensitivity (SEN), specificity (SPE), diagnostic likelihood ratio positive (DLR+), diagnostic likelihood ratio negative (DLR-), and diagnostic OR (DOR), as well as area under the curve (AUC) of microbiota markers in the diagnosis of lung diseases were 0.90 (95% CI: 0.83-0.94), 0.89 (95% CI: 0.76-0.95), 7.86 (95% CI: 3.39-18.21), 0.12 (95% CI: 0.06-0.21), 22.254 (95% CI: 12.83-39.59.14), and 0.95 (95% CI: 0.93-0.97), respectively. Subgroup analysis revealed that research based on Caucasian, adult, BAL fluid, PCR, pneumonia obtained higher AUC values. The microbiota markers have shown potential diagnosis value for lung diseases. But further large-scale clinical studies are still needed to verify and replicate the diagnostic value of lung microbiota markers.