The lung is a complex ecosystem of host cells and microbes often disrupted in pathological conditions. Although bacteria have been hypothesized as agents of carcinogenesis, little is known about microbiota profile of the most prevalent cancer subtypes: adenocarcinoma (ADC) and squamous cell carcinoma (SCC). To characterize lung cancer (LC) microbiota a first a screening was performed through a pooled sequencing approach of 16S ribosomal RNA gene (V3-V6) using a total of 103 bronchoalveaolar lavage fluid samples. Then, identified taxa were used to inspect 1009 cases from The Cancer Genome Atlas and to annotate tumor unmapped RNAseq reads. Microbial diversity was analyzed per cancer subtype, history of cigarette smoking and airflow obstruction, among other clinical data. We show that LC microbiota is enriched in Proteobacteria and more diverse in SCC than ADC, particularly in males and heavier smokers. High frequencies of Proteobacteria were found to discriminate a major cluster, further subdivided into well-defined communities’ associated with either ADC or SCC. Here, a SCC subcluster differing from other cases by a worse survival was correlated with several Enterobacteriaceae. Overall, this study provides first evidence for a correlation between lung microbiota and cancer subtype and for its influence on patient life expectancy.

Lung cancer configures as one of the deadliest types of cancer. The future implementation of early screening methods such as exhaled breath condensate analysis and low dose computed tomography (CT) as an alternative to current chest imaging based screening will lead to an increased burden on bronchoscopy units. New approaches for improvement of diagnosis in bronchoscopy units, regarding patient management, are likely to have clinical impact in the future. Diagnostic approaches to address mortality of lung cancer include improved early detection and stratification of the cancers according to its prognosis and further response to drug treatment. In this study, we performed a detailed mass spectrometry based proteome analysis of acellular bronchoalveolar lavage (BAL) fluid samples on an observational prospective cohort consisting of 90 suspected lung cancer cases which were followed during two years. The thirteen new lung cancer cases diagnosed during the follow up time period clustered, based on liquid chromatography-mass spectrometry (LC-MS) data, with lung cancer cases at the time of BAL collection. Hundred and thirty-tree potential biomarkers were identified showing significantly differential expression when comparing lung cancer versus non-lung cancer. The regulated biomarkers showed a large overlap with biomarkers detected in tissue samples.

Acellular bronchoalveolar lavage (BAL) proteomics can partially separate lung cancer from non-lung cancer patients based on principal component analysis and multivariate analysis. Furthermore, the variance in the proteomics data sets is correlated mainly with lung cancer status and, to a lesser extent, smoking status and gender. Despite these advances BAL small and large extracellular vehicles (EVs) proteomes reveal aberrant protein expression in paracrine signaling mechanisms in cancer initiation and progression. We consequently present a case-control study of 24 bronchoalveolar lavage extracellular vesicle samples which were analyzed by state-of-the-art liquid chromatography-mass spectrometry (LC-MS). We obtained evidence that BAL EVs proteome complexity correlated with lung cancer stage 4 and mortality within two years´ follow-up (p value = 0.006). The potential therapeutic target DNMT3B complex is significantly up-regulated in tumor tissue and BAL EVs. The computational analysis of the immune and fibroblast cell markers in EVs suggests that patients who deceased within the follow-up period display higher marker expression indicative of innate immune and fibroblast cells (four out of five cases). This study provides insights into the proteome content of BAL EVs and their correlation to clinical outcomes.