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Abstract Background The relationship between commensal microbiota and lung cancer (LC) has been studied extensively. However, developing replicable microbiological markers for early LC diagnosis across multiple populations has remained challenging. Current studies are limited to a single region, single LC subtype, and small sample size. Therefore, we aimed to perform the first large‐scale meta‐analysis for identifying micro biomarkers for LC screening by integrating gut and respiratory samples from multiple studies and building a machine‐learning classifier. Methods In total, 712 gut and 393 respiratory samples were assessed via 16 s rRNA amplicon sequencing. After identifying the taxa of differential biomarkers, we established random forest models to distinguish between LC populations and normal controls. We validated the robustness and specificity of the model using external cohorts. Moreover, we also used the KEGG database for the predictive analysis of colony‐related functions. Results The α and β diversity indices indicated that LC patients' gut microbiota (GM) and lung microbiota (LM) differed significantly from those of the healthy population. Linear discriminant analysis (LDA) of effect size (LEfSe) helped us identify the top‐ranked biomarkers, Enterococcus, Lactobacillus, and Escherichia, in two microbial niches. The area under the curve values of the diagnostic model for the two sites were 0.81 and 0.90, respectively. KEGG enrichment analysis also revealed significant differences in microbiota‐associated functions between cancer‐affected and healthy individuals that were primarily associated with metabolic disturbances. Conclusions GM and LM profiles were significantly altered in LC patients, compared to healthy individuals. We identified the taxa of biomarkers at the two loci and constructed accurate diagnostic models. This study demonstrates the effectiveness of LC‐specific microbiological markers in multiple populations and contributes to the early diagnosis and screening of LC.

Background: The relationship between commensal microbiota and lung cancer (LC) has been studied extensively. However, developing replicable microbiological markers for early LC diagnosis across multiple populations has remained challenging. Current studies are limited to a single region, single LC subtype, and small sample size. Therefore, we aimed to perform the first large‐scale meta‐analysis for identifying micro biomarkers for LC screening by integrating gut and respiratory samples from multiple studies and building a machine‐learning classifier. Methods: In total, 712 gut and 393 respiratory samples were assessed via 16 s rRNA amplicon sequencing. After identifying the taxa of differential biomarkers, we established random forest models to distinguish between LC populations and normal controls. We validated the robustness and specificity of the model using external cohorts. Moreover, we also used the KEGG database for the predictive analysis of colony‐related functions. Results: The α and β diversity indices indicated that LC patients' gut microbiota (GM) and lung microbiota (LM) differed significantly from those of the healthy population. Linear discriminant analysis (LDA) of effect size (LEfSe) helped us identify the top‐ranked biomarkers, Enterococcus, Lactobacillus, and Escherichia, in two microbial niches. The area under the curve values of the diagnostic model for the two sites were 0.81 and 0.90, respectively. KEGG enrichment analysis also revealed significant differences in microbiota‐associated functions between cancer‐affected and healthy individuals that were primarily associated with metabolic disturbances. Conclusions: GM and LM profiles were significantly altered in LC patients, compared to healthy individuals. We identified the taxa of biomarkers at the two loci and constructed accurate diagnostic models. This study demonstrates the effectiveness of LC‐specific microbiological markers in multiple populations and contributes to the early diagnosis and screening of LC. [ABSTRACT FROM AUTHOR]

Anti-PD-1 antibody-mediated activation of type 17 T-cells undermines checkpoint inhibitor therapy in the LSL-KrasG12D murine lung cancer model. Herein, we establish that the Th17 subset is the primary driver of resistance to therapy demonstrate that the ontogeny of dysplasia-associated Th17 cells is driven by microbiota-conditioned macrophages; and identify the IL-17-COX-2-PGE2 axis as the mediator of CD8+ cytotoxic T-lymphocyte de-sensitization to checkpoint inhibitor therapy. Specifically, anti-PD-1 treatment of LSL-KrasG12D mice, in which CD4+ T-cells were deficient for RORc, resulted in a 60% increase in CTL cytotoxicity and a 2.5-fold reduction in tumor burden confirming the critical role of Th17 cells in resistance to therapy. Lung-specific depletion of microbiota reduced Th17 cell prevalence and tumor burden by 5- and 2.5-fold, respectively; establishing a link between microbiota and Th17 cell-driven tumorigenesis. Importantly, lung macrophages from microbiota sufficient, but not from microbiota-deficient, mice polarized naïve CD4+ T-cells to a Th17 phenotype, highlighting their role in bridging microbiota and Th17 immunity. Further, treatment with anti-PD-1 enhanced COX-2 and PGE2 levels, whereas neutralization of IL-17 diminished this effect. In contrast, inhibition of COX-2 rescued CTL activity and restored tumor suppression in anti-PD-1-treated mice, revealing the molecular basis of IL-17-mediated resistance to checkpoint blockade. Clinical implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

Anti-PD-1 antibody-mediated activation of type 17 T-cells undermines checkpoint inhibitor therapy in the LSL-KrasG12D murine lung cancer model. Herein, we establish that the Th17 subset is the primary driver of resistance to therapy demonstrate that the ontogeny of dysplasia-associated Th17 cells is driven by microbiota-conditioned macrophages; and identify the IL-17-COX-2-PGE2 axis as the mediator of CD8+ cytotoxic T-lymphocyte de-sensitization to checkpoint inhibitor therapy. Specifically, anti-PD-1 treatment of LSL-KrasG12D mice, in which CD4+ T-cells were deficient for RORc, resulted in a 60% increase in CTL cytotoxicity and a 2.5-fold reduction in tumor burden confirming the critical role of Th17 cells in resistance to therapy. Lung-specific depletion of microbiota reduced Th17 cell prevalence and tumor burden by 5- and 2.5-fold, respectively; establishing a link between microbiota and Th17 cell-driven tumorigenesis. Importantly, lung macrophages from microbiota sufficient, but not from microbiota-deficient, mice polarized naïve CD4+ T-cells to a Th17 phenotype, highlighting their role in bridging microbiota and Th17 immunity. Further, treatment with anti-PD-1 enhanced COX-2 and PGE2 levels, whereas neutralization of IL-17 diminished this effect. In contrast, inhibition of COX-2 rescued CTL activity and restored tumor suppression in anti-PD-1-treated mice, revealing the molecular basis of IL-17-mediated resistance to checkpoint blockade. Clinical implications of these findings are discussed. [ABSTRACT FROM AUTHOR]

Resumen: La evidencia científica durante las últimas 2 décadas respalda que la aplicación de técnicas de cribado de cáncer de pulmón mediante tomografía computarizada (TC) de tórax de baja dosis de radiación contribuye a una reducción significativa de la mortalidad, gracias al diagnóstico en estadios potencialmente curativos. En referencia a dicho diagnóstico, existen además métodos novedosos en estudio, como la biopsia líquida, la identificación del microbioma pulmonar y la utilización de técnicas de inteligencia artificial, que desempeñarán un papel clave en un futuro próximo. En la actualidad, existe una tendencia hacia el tratamiento con cirugías cada vez menos invasivas (segmentectomía vs. lobectomía) basada en 2 ensayos clínicos recientes en tumores periféricos menores de 2 cm. A pesar de mostrar similar supervivencia, todavía existe controversia debido a la incertidumbre en cuanto a la tasa de recidiva y reserva funcional. En cuanto a la terapia adyuvante, la inmunoterapia sola o combinada con quimioterapia ofrece resultados alentadores en estadios resecables del cáncer de pulmón localmente avanzado, con respuestas patológicas completas y mejoría en la supervivencia. Tras el tratamiento con cirugía, a pesar de que no hay evidencia sólida del seguimiento a largo plazo de estos pacientes, en la práctica clínica se recomienda la realización de TC periódicas durante los primeros años.En conclusión, en el cáncer de pulmón existen avances importantes, que han mejorado las técnicas diagnósticas utilizando nuevas tecnologías y programas de cribado. Además, el tratamiento de este cáncer cada vez es más personalizado y todo ello se traduce en una mejora de la supervivencia de los pacientes. Abstract: Over the past 2 decades, scientific evidence has strongly supported the use of low-radiation dose chest computed tomography (CT) as a screening technique for lung cancer. This approach has resulted in a significant reduction in mortality rates by enabling the detection of early-stage lung cancer amenable to potentially curative treatments. Regarding diagnosis, there are also novel methods under study, such as liquid biopsy, identification of the pulmonary microbiome, and the use of artificial intelligence techniques, which will play a key role in the near future. At present, there is a growing trend towards less invasive surgical procedures, such as segmentectomy, as an alternative to lobectomy. This procedure is based on 2 recent clinical trials conducted on peripheral tumors measuring less than 2 cm. Although these approaches have demonstrated comparable survival rates, there remains controversy due to uncertainties surrounding recurrence rates and functional capacity preservation. With regard to adjuvant therapy, immunotherapy, either as a monotherapy or in conjunction with chemotherapy, has shown encouraging results in resectable stages of locally advanced lung cancer, demonstrating complete pathologic responses and improved overall survival.After surgery treatment, despite the lack of solid evidence for long-term follow-up of these patients, clinical practice recommends periodic CT scans during the early years.In conclusion, there have been significant advances in lung cancer that have improved diagnostic techniques using new technologies and screening programs. Furthermore, the treatment of lung cancer is increasingly personalized, resulting in an improvement in the survival of patients.

The lung is a complex and unique organ system whose biology is strongly influenced by environmental exposure, oxygen abundance, connection to extrapulmonary systems via a dense capillary network, and an array of immune cells that reside in the tissue at steady state. The lung also harbors a low biomass community of commensal microorganisms that are dynamic during both health and disease with the capacity to modulate regulatory immune responses during diseases such as cancer. Lung cancer is the third most common cancer worldwide with the highest mortality rate amongst cancers due to the difficulty of an early diagnosis. This review discusses the current body of work addressing the interactions between the lung microbiota and the immune system, and how these two components of the pulmonary system are linked to lung cancer development and outcomes. Bringing in lessons from broader studies examining the effects of the gut microbiota on cancer outcomes, we highlight many challenges and gaps in this nascent field. [ABSTRACT FROM AUTHOR]

An immunosuppressive microenvironment in lung concurs to pre-malignant lesions progression to cancer. Here, we explore if perturbing lung microbiota, which contribute to immunosuppression, by antibiotics or probiotic aerosol interferes with lung cancer development in a mouse carcinogen-induced tumor model. Urethane-injected mice were vancomycin/neomycin (V/N)-aerosolized or live or dead L. rhamnosus GG (L.RGG)-aerosolized, and tumor development was evaluated. Transcriptional profiling of lungs and IHC were performed. Tumor nodules number, diameter and area were reduced by live or heat-killed L.RGG, while only a decrease in nodule diameter was observed in V/N-treated lungs. Both L.RGG and V/N reduced Tregs in the lung. In L.RGG-treated groups, the gene encoding the joining chain (J chain) of immunoglobulins was increased, and higher J chain protein and IgA levels were observed. An increased infiltration of B, NK and myeloid-derived cells was predicted by TIMER 2.0. The Kaplan–Meier plotter revealed an association between high levels of J chain mRNA and good prognosis in lung adenocarcinoma patients that correlated with increased B and CD4 T cells and reduced Tregs and M2 macrophages. This study highlights L.RGG aerosol efficacy in impairing lung cancer growth by promoting local immunity and points to this non-invasive strategy to treat individuals at risk of lung cancer. [ABSTRACT FROM AUTHOR]

Recent evidence suggests that lung microbiota can be recognized as one of the ecological determinants of various respiratory diseases. However, alterations in the lung microbiota and associated lung immunity in these respiratory diseases remain unclear. To compare the lung microbiota and lung immune profiles in common respiratory diseases, a total of 78 patients were enrolled in the present study, including 21 patients with primary pulmonary tuberculosis (PTB), eight patients with newly diagnosed lung cancer (LC), and 49 patients with community-acquired pneumonia (CAP). Bronchoalveolar lavage fluid (BALF) was collected for microbiota and cytokine analyses. With MiSeq sequencing system, increased bacterial alpha- diversity and richness were observed in patients with LC than in those with PTB and CAP. Linear discriminant analysis effect size revealed that CAP-associated pulmonary microbiota were significantly different between the PTB and LC groups. More key functionally different genera were found in the PTB and LC groups than in the CAP group. The interaction network revealed stronger positive and negative correlations among these genera in the LC group than in the other two groups. However, increased BALF cytokine profiles were observed in the PTB group than in the other two groups, while BALF cytokines were correlated with key functional bacteria. This comparative study provides evidence for the associations among altered lung microbiota, BALF inflammation, and different respiratory disorders, which provides insight into the possible roles and mechanisms of pulmonary microbiota in the progression of respiratory disorders. [ABSTRACT FROM AUTHOR]

BackgroundLung cancer is the leading malignant disease and cause of cancer-related death worldwide. Most patients with lung cancer had insignificant early symptoms so that most of them were diagnosed at an advanced stage. In addition to factors such as smoking, pollution, lung microbiome and its metabolites play vital roles in the development of lung cancer. However, the interaction between lung microbiota and carcinogenesis is lack of systematically characterized and controversial. Therefore, the purpose of this study was to excavate the features of the lung microbiota and metabolites in patients and verify potential biomarkers for lung cancer diagnosis.MethodsLung tissue flushing solutions and bronchoalveolar lavage fluid samples came from patients with lung cancer and non-lung cancer. The composition and variations of the microbiota and metabolites in samples were explored using muti-omics technologies including 16S rRNA amplicon sequencing, metagenomics and metabolomics.ResultsThe metabolomics analysis indicated that 40 different metabolites, such as 9,10-DHOME, sphingosine, and cysteinyl-valine, were statistically significant between two groups (VIP > 1 and P < 0.05). These metabolites were significantly enriched into 11 signal pathways including sphingolipid, autophagy and apoptosis signaling pathway (P < 0.05). The analysis of lung microbiota showed that significant changes reflected the decrease of microbial diversity, changes of distribution of microbial taxa, and variability of the correlation networks of lung microbiota in lung cancer patients. In particular, we found that oral commensal microbiota and multiple probiotics might be connected with the occurrence and progression of lung cancer. Moreover, our study found 3 metabolites and 9 species with significantly differences, which might be regarded as the potential clinical diagnostic markers associated with lung cancer.ConclusionsLung microbiota and metabolites might play important roles in the pathogenesis of lung cancer, and the altered metabolites and microbiota might have the potential to be clinical diagnostic markers and therapeutic targets associated with lung cancer.

Lung cancer is becoming one of the most detrimental cancers with the highest morbidity and mortality rate of all cancers, posing a significant burden for the global health system. Nonetheless, the therapeutic efficacy of traditional lung cancer therapies still remains relatively unsatisfying with varied responsiveness and unexpected adverse effects. Fortunately, studies have reported that an intimate relationship might exist between microbiota and lung carcinoma. Notably, microbial dysbiosis might result in changes in the metabolism, induction of immunosuppression, and recruitment of inflammatory factors, thereby driving lung carcinogenesis. Certain microbial strains were identified to be specifically enriched in the lung tumor beds, indicating their predictive role in lung cancer. Furthermore, the particular microbial composition was also proved to potentiate the outcomes of lung cancer therapies, suggesting that lung and gut microbiome were promising to be clinically applied for lung cancer therapy. In this review, we will comprehensively summarize the recent findings on how microbes mediate the initiation, progression, and treatment of lung cancer, illustrating the potential mechanisms and probing into the putative manipulation of microbiota to facilitate lung cancer treatments.

Abstract Background While well-characterised on its molecular base, non-small cell lung cancer (NSCLC) and its interaction with local microbiota remains scarcely explored. Moreover, current studies vary in source of lung microbiota, from bronchoalveolar lavage fluid (BAL) to tissue, introducing potentially differing results. Therefore, the objective of this study was to provide detailed characterisation of the oral and multi-source lung microbiota of direct interest in lung cancer research. Since lung tumours in lower lobes (LL) have been associated with decreased survival, characteristics of the microbiota in upper (UL) and lower tumour lobes have also been examined. Methods Using 16S rRNA gene sequencing technology, we analysed microbiota in saliva, BAL (obtained directly on excised lobe), non-malignant, peritumoural and tumour tissue from 18 NSCLC patients eligible for surgical treatment. Detailed taxonomy, diversity and core members were provided for each microbiota, with analysis of differential abundance on all taxonomical levels (zero-inflated binomial general linear model with Benjamini-Hochberg correction), between samples and lobe locations. Results Diversity and differential abundance analysis showed clear separation of oral and lung microbiota, but more importantly, of BAL and lung tissue microbiota. Phylum Proteobacteria dominated tissue samples, while Firmicutes was more abundant in BAL and saliva (with class Clostridia and Bacilli, respectively). However, all samples showed increased abundance of phylum Firmicutes in LL, with decrease in Proteobacteria. Also, clades Actinobacteria and Flavobacteriia showed inverse abundance between BAL and extratumoural tissues depending on the lobe location. While tumour microbiota seemed the least affected by location, peritumoural tissue showed the highest susceptibility with markedly increased similarity to BAL microbiota in UL. Differences between the three lung tissues were however very limited. Conclusions Our results confirm that BAL harbours unique lung microbiota and emphasise the importance of the sample choice for lung microbiota analysis. Further, limited differences between the tissues indicate that different local tumour-related factors, such as tumour type, stage or associated immunity, might be the ones responsible for microbiota-shaping effect. Finally, the “shift” towards Firmicutes in LL might be a sign of increased pathogenicity, as suggested in similar malignancies, and connected to worse prognosis of the LL tumours. Trial registration ClinicalTrials.gov ID: NCT03068663 . Registered February 27, 2017.

Background: Lung cancer is the leading cause of cancer-related deaths worldwide (Ferlay et al., Int J Cancer 136:E359–386, 2015). In addition, lung cancer is associated with the highest mortality among all cancer types (Wu et al., Exp Ther Med 16:3004–3010, 2018). Previous studies report that microbiota play an important role in lung cancer. Notably, changes in lung and gut microbiota, are associated with progression of lung cancer. Several studies report that lung and gut microbiome promote lung cancer initiation and development by modulating metabolic pathways, inhibiting the function of immune cells, and producing pro-inflammatory factors. In addition, some factors such as microbiota dysbiosis, affect production of bacteriotoxins, genotoxicity and virulence effect, therefore, they play a key role in cancer progression. These findings imply that lung and gut microbiome are potential markers and targets for lung cancer. However, the role of microbiota in development and progression of lung cancer has not been fully explored. Purpose: The aim of this study was to systemically review recent research findings on relationship of lung and gut microbiota with lung cancer. In addition, we explored gut–lung axis and potential mechanisms of lung and gut microbiota in modulating lung cancer progression. Conclusion: Pulmonary and intestinal flora influence the occurrence, development, treatment and prognosis of lung cancer, and will provide novel strategies for prevention, diagnosis, and treatment of lung cancer. [ABSTRACT FROM AUTHOR]

An immunosuppressive microenvironment in lung concurs to pre-malignant lesions progression to cancer. Here, we explore if perturbing lung microbiota, which contribute to immunosuppression, by antibiotics or probiotic aerosol interferes with lung cancer development in a mouse carcinogen-induced tumor model. Urethane-injected mice were vancomycin/neomycin (V/N)-aerosolized or live or dead L. rhamnosus GG (L.RGG)-aerosolized, and tumor development was evaluated. Transcriptional profiling of lungs and IHC were performed. Tumor nodules number, diameter and area were reduced by live or heat-killed L.RGG, while only a decrease in nodule diameter was observed in V/N-treated lungs. Both L.RGG and V/N reduced Tregs in the lung. In L.RGG-treated groups, the gene encoding the joining chain (J chain) of immunoglobulins was increased, and higher J chain protein and IgA levels were observed. An increased infiltration of B, NK and myeloid-derived cells was predicted by TIMER 2.0. The Kaplan–Meier plotter revealed an association between high levels of J chain mRNA and good prognosis in lung adenocarcinoma patients that correlated with increased B and CD4 T cells and reduced Tregs and M2 macrophages. This study highlights L.RGG aerosol efficacy in impairing lung cancer growth by promoting local immunity and points to this non-invasive strategy to treat individuals at risk of lung cancer.

The advances in molecular biology and the emergence of Next Generation Sequencing (NGS) have revealed that microbiome composition is closely related with health and disease, including cancer. This relationship affects different levels of cancer such as development, progression, and response to treatment including immunotherapy. The efficacy of immune checkpoint inhibitors (ICIs) may be influenced by the concomitant use of antibiotics before, during or shortly after treatment with ICIs. Nevertheless, the linking mechanism between microbiote, host immunity and cancer is not clear and the role of microbiota manipulation and analyses in cancer management has not been clinically validated yet. Regarding the use of microbiome as biomarker to predict ICI efficacy it has been recently shown that the use of biochemical serum markers to monitor intestinal permeability and loss of barrier integrity, like citrulline, could be useful to monitor microbiota changes and predict ICI efficacy. There are still many unknowns about the role of these components, their relationship with the microbiota, with the use of antibiotics and the response to immunotherapy. The next challenge in microbiome research will be to identify individual microbial species that causally affect lung cancer phenotypes and response to ICI and disentangle the underlying mechanisms. Thus, further analyses in patients with lung cancer receiving treatment with ICIs and its correlation with the composition of the microbiota in different organs including the respiratory tract, peripheral blood and intestinal tract could be useful to predict the efficacy of ICIs and its modulation with antibiotic use.

The advances in molecular biology and the emergence of Next Generation Sequencing (NGS) have revealed that microbiome composition is closely related with health and disease, including cancer. This relationship affects different levels of cancer such as development, progression, and response to treatment including immunotherapy. The efficacy of immune checkpoint inhibitors (ICIs) may be influenced by the concomitant use of antibiotics before, during or shortly after treatment with ICIs. Nevertheless, the linking mechanism between microbiote, host immunity and cancer is not clear and the role of microbiota manipulation and analyses in cancer management has not been clinically validated yet. Regarding the use of microbiome as biomarker to predict ICI efficacy it has been recently shown that the use of biochemical serum markers to monitor intestinal permeability and loss of barrier integrity, like citrulline, could be useful to monitor microbiota changes and predict ICI efficacy. There are still many unknowns about the role of these components, their relationship with the microbiota, with the use of antibiotics and the response to immunotherapy. The next challenge in microbiome research will be to identify individual microbial species that causally affect lung cancer phenotypes and response to ICI and disentangle the underlying mechanisms. Thus, further analyses in patients with lung cancer receiving treatment with ICIs and its correlation with the composition of the microbiota in different organs including the respiratory tract, peripheral blood and intestinal tract could be useful to predict the efficacy of ICIs and its modulation with antibiotic use. [ABSTRACT FROM AUTHOR]

Background: While well-characterised on its molecular base, non-small cell lung cancer (NSCLC) and its interaction with local microbiota remains scarcely explored. Moreover, current studies vary in source of lung microbiota, from bronchoalveolar lavage fluid (BAL) to tissue, introducing potentially differing results. Therefore, the objective of this study was to provide detailed characterisation of the oral and multi-source lung microbiota of direct interest in lung cancer research. Since lung tumours in lower lobes (LL) have been associated with decreased survival, characteristics of the microbiota in upper (UL) and lower tumour lobes have also been examined. Methods: Using 16S rRNA gene sequencing technology, we analysed microbiota in saliva, BAL (obtained directly on excised lobe), non-malignant, peritumoural and tumour tissue from 18 NSCLC patients eligible for surgical treatment. Detailed taxonomy, diversity and core members were provided for each microbiota, with analysis of differential abundance on all taxonomical levels (zero-inflated binomial general linear model with Benjamini-Hochberg correction), between samples and lobe locations. Results: Diversity and differential abundance analysis showed clear separation of oral and lung microbiota, but more importantly, of BAL and lung tissue microbiota. Phylum Proteobacteria dominated tissue samples, while Firmicutes was more abundant in BAL and saliva (with class Clostridia and Bacilli, respectively). However, all samples showed increased abundance of phylum Firmicutes in LL, with decrease in Proteobacteria. Also, clades Actinobacteria and Flavobacteriia showed inverse abundance between BAL and extratumoural tissues depending on the lobe location. While tumour microbiota seemed the least affected by location, peritumoural tissue showed the highest susceptibility with markedly increased similarity to BAL microbiota in UL. Differences between the three lung tissues were however very limited. Conclusions: Our results confirm that BAL harbours unique lung microbiota and emphasise the importance of the sample choice for lung microbiota analysis. Further, limited differences between the tissues indicate that different local tumour-related factors, such as tumour type, stage or associated immunity, might be the ones responsible for microbiota-shaping effect. Finally, the "shift" towards Firmicutes in LL might be a sign of increased pathogenicity, as suggested in similar malignancies, and connected to worse prognosis of the LL tumours. Trial registration: ClinicalTrials.gov ID: NCT03068663. Registered February 27, 2017. [ABSTRACT FROM AUTHOR]

Respiratory bacterial microbiota plays a key role in human health. Lung cancer microbiome is a significant yet an understudied area while bronchiectasis microbiome is often studied. We assessed the bacterial microbiota in the upper and lower respiratory tract of the patients with lung cancer and bronchiectasis against a healthy group and their variations in individuality. 16S rRNA gene based metagenomic sequencing was used to detect entire bacterial community along with conventional aerobic bacterial culturing. In comparison to healthy, increased bacterial diversity was observed in diseased population. Abundance of more than 1% was considered and bacteria were identified in 97% similarity. Only lung cancer patients exhibited bacteria specific to the disease: Corynebacterium tuberculostearicum and Keratinibaculum paraultunense. However, Enterococcus faecalis and Delftia tsuruhatensis were also observed limited to lung cancer and bronchiectasis respectively, in less than 1% but supported with bacterial culturing. In conclusion the disease condition and intra-group variability should be considered in future with larger cohorts to understand individual patient variability highlighting the social habits and gender of the individual. [ABSTRACT FROM AUTHOR]

Bacteria influence site-specific disease etiology and the host's ability to metabolize xenobiotics, such as polycyclic aromatic hydrocarbons (PAHs). Lung cancer in Xuanwei, China has been attributed to PAH-rich household air pollution from burning coal. This study seeks to explore the role of lung microbiota in lung cancer among never smoking Xuanwei women and how coal burning may influence these associations. DNA from sputum and buccal samples of never smoking lung cancer cases ( n = 8, in duplicate) and controls ( n = 8, in duplicate) in two Xuanwei villages was extracted using a multi-step enzymatic and physical lysis, followed by a standardized clean-up. V1-V2 regions of 16S rRNA genes were PCR-amplified. Purified amplicons were sequenced by 454 FLX Titanium pyrosequencing and high-quality sequences were evaluated for diversity and taxonomic membership. Bacterial diversity among cases and controls was similar in buccal samples ( P = 0.46), but significantly different in sputum samples ( P = 0.038). In sputum, Granulicatella (6.1 vs. 2.0%; P = 0.0016), Abiotrophia (1.5 vs. 0.085%; P = 0.0036), and Streptococcus (40.1 vs. 19.8%; P = 0.0142) were enriched in cases compared with controls. Sputum samples had on average 488.25 species-level OTUs in the flora of cases who used smoky coal (PAH-rich) compared with 352.5 OTUs among cases who used smokeless coal (PAH-poor; P = 0.047). These differences were explained by the Bacilli species ( Streptococcus infantis and Streptococcus anginosus). Our small study suggests that never smoking lung cancer cases have differing sputum microbiota than controls. Further, bacteria found in sputum may be influenced by environmental exposures associated with the type of coal burned in the home. Environ. Mol. Mutagen. 55:643-651, 2014. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

[Display omitted] • Respiratory microbiome is a promising and unexplored topic for cancer research. • Lung cancer is enriched in peculiar microbial communities. • Differences in microbiome composition/diversity are reported in lung cancer patients. • Lung microbiome detection and modulation in lung cancer deserves dedicated studies. Giving the potential contribute in cancer initiation and progression, lung microbiota represents a promising topic in cancer research, although still unexplored. We performed a systematic literature search to identify clinical studies evaluating lung microbiota composition, its correlation with lung cancer patients' clinico-pathological features and prognosis. Of the identified 370 studies, 21 were eligible and included. Although studies were heterogeneous, lung cancer resulted to be enriched in peculiar microbial communities, with differences in composition and diversity according to clinico-pathological parameters. Few studies explored how lung microbiota influences cancer outcome. In light of these findings and borrowing the suggestions coming from gut microbiota, we speculate that respiratory microbiome may influence pathogenesis, progression and outcome of lung cancer. Taking advantage of the experience of chronical lung diseases, prospective studies should be designed to evaluate lung microbiota changes throughout any phase of lung cancer course, particularly with the advent of immunotherapy as pivotal treatment. [ABSTRACT FROM AUTHOR]