Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1011043 | ENA |
REPOSITORIES: ENA
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Project description:In this study, we assessed lower airway microbiome from a cohort of patients to determine whether specific microbiome taxa correlate with with specific metabolic activities. In a subset of 12 patients, transcriptomic expression were analyzed to compare host mucosa immune response We collected peripheral airway brushings from the 12 subjects whose lung microbiome were analyzed; Total RNA were obtained from the peripheral airway epithelium.
2016-03-29 | E-GEOD-73585 | biostudies-arrayexpress
Project description:Bronchoalveolar lavage is commonly performed to examine inflammation and responsible pathogens in lung diseases, and its findings may be used to assess the immune profile of the lung tumor microenvironment (TME). To investigate whether analyses of bronchoalveolar lavage fluid (BALF) can help identify non-small cell lung cancer (NSCLC) patients who respond to immune checkpoint inhibitors (ICIs), BALF and blood were prospectively collected before initiating nivolumab. The secreted molecules, microbiome, and cellular profiles based on BALF and blood analysis were compared regarding therapeutic effect in 12 patients. Compared to non-responders, responders showed significantly higher CXCL9 levels and greater diversity in the lung microbiome profile in BALF, and greater frequency of CD56+ subset in blood T cells, whereas no significant difference was found in PD-L1 expression of tumor cells. Antibiotic treatment in a preclinical lung cancer model significantly decreased CXCL9 in the lung TME, resulting in reduced sensitivity to nivolumab, which was reversed by CXCL9 induction in tumor cells. Thus, CXCL9 and the microbiome in the lung TME might be associated with each other, and their balance could contribute to nivolumab sensitivity in NSCLC patients. BALF analysis can help predict the efficacy of ICIs when performed along with currently approved examinations.
2022-04-07 | GSE193049 | GEO
Project description:Pancreatic cancer is the 3rd most prevalent cause of cancer related deaths in United states alone, with over 55000 patients being diagnosed in 2019 alone and nearly as many succumbing to it. Late detection, lack of effective therapy and poor understanding of pancreatic cancer systemically contributes to its poor survival statistics. Obesity and high caloric intake linked co-morbidities like type 2 diabetes (T2D) have been attributed as being risk factors for a number of cancers including pancreatic cancer. Studies on gut microbiome has shown that lifestyle factors as well as diet has a huge effect on the microbial flora of the gut. Further, modulation of gut microbiome has been seen to contribute to effects of intensive insulin therapy in mice on high fat diet. In another study, abnormal gut microbiota was reported to contribute to development of diabetes in Db/Db mice. Recent studies indicate that microbiome and microbial dysbiosis plays a role in not only the onset of disease but also in its outcome. In colorectal cancer, Fusobacterium has been reported to promote therapy resistance. Certain intra-tumoral bacteria have also been shown to elicit chemo-resistance by metabolizing anti-cancerous agents. In pancreatic cancer, studies on altered gut microbiome have been relatively recent. Microbial dysbiosis has been observed to be associated with pancreatic tumor progression. Modulation of microbiome has been shown to affect response to anti-PD1 therapy in this disease as well. However, most of the studies in pancreatic cancer and microbiome have remained focused om immune modulation. In the current study, we observed that in a T2D mouse model, the microbiome changed significantly as the hyperglycemia developed in these animals. Our results further showed that, tumors implanted in the T2D mice responded poorly to Gemcitabine/Paclitaxel (Gem/Pac) standard of care compared to those in the control group. A metabolomic reconstruction of the WGS of the gut microbiota further revealed that an enrichment of bacterial population involved in drug metabolism in the T2D group.
2020-11-30 | E-MTAB-8739 | biostudies-arrayexpress
Project description:We developed a free-flow isoelectric focusing (FFIEF) based metaproteomics workflow to reduce the host interferences and enrich the low-abundant bacteria for better interpretation of salivary microbiome. We firstly tested the pretreatment module that could significantly reduce the host interferences by differential centrifugation and filtration. Then the FFIEF module was applied to separate the microbes and enrich the low-abundant bacteria, which showed a significant improvement in the identification efficiency of microbiome sample. Applying our method to lung cancer, we successfully identified Fusobacterium, Neisseriaceae, Actinomycetaceae, Burkholderiales, and Spirochaetia were associated with lung cancer as previous sequencing studies did, along with other 16 significantly different species. The dysregulated functions in lung cancer microbiome were also explained in details. Our workflow provides improved efficiency in identification and characterization of the salivary microbiome with great reproducibility. The ability of enriching low-abundant bacteria and functions enables in-deep analysis of previously underestimated information.
2022-11-17 | PXD026727 | Pride
Project description:Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in chronic obstructive pulmonary disease patients with emphysema. The antimicrobial effects of AZM on the lung microbiome are not known and may contribute to its beneficial effects. Methods. Twenty smokers with emphysema were randomized to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements included: rDNA gene quantity and sequence. Results. Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Conclusions. AZM treatment the lung microbiome Randomized trial comparing azithromycin (AZM) treatment with placebo for eight weeks. Bronchoalveolar lavage (BAL) samples were obtained before and after treatment to explore the effects of AZM on microbiome, in the lower airways. 16S rRNA was quantified and sequenced (MiSeq) The amplicons from total 39 samples are barcoded and the barcode is provided in the metadata_complete.txt file.
2016-07-19 | E-GEOD-74396 | biostudies-arrayexpress
Project description:We preformed a systems biological assessment of lower respiratory tract host immune responses and microbiome dynamics in COVD-19 patients, using bulk RNA-sequencing, single-cell RNA sequencing, and techniques, and microbiome analysis. Are focus was on differential gene expression in severe COVID-19 patients who developed ventilator associated pneumonia (VAP) during their course versus severe COVID-19 patients who did not develop VAP. We found early impairment in antibacterial immune signaling in patients two or more weeks prior to the development of VAP, compared to COVID-19 patients who did not develop VAP. There was no signficant difference in viral load, but an association of disruption in lung microbiome by alpha and beta diversity metrics was also found.
2021-03-03 | GSE168018 | GEO
Project description:We preformed a systems biological assessment of lower respiratory tract host immune responses and microbiome dynamics in COVD-19 patients, using bulk RNA-sequencing, single-cell RNA sequencing, and techniques, and microbiome analysis. Are focus was on differential gene expression in severe COVID-19 patients who developed ventilator associated pneumonia (VAP) during their course versus severe COVID-19 patients who did not develop VAP. We found early impairment in antibacterial immune signaling in patients two or more weeks prior to the development of VAP, compared to COVID-19 patients who did not develop VAP. There was no signficant difference in viral load, but an association of disruption in lung microbiome by alpha and beta diversity metrics was also found.
2021-03-03 | GSE168017 | GEO
Project description:One unmet challenge in current lung cancer diagnosis is to accurately differentiate lung cancer patients from those with other lung diseases with similar clinical symptoms and radiological features. Previous studies have reported cases of misdiagnosis for patients with lung cancer mimicking pulmonary tuberculosis (TB) or for TB patients with multiple lung nodules mimicking lung cancer progression, which is concerning for clinical practice in TB-endemic countries/regions. Here, we develop a molecular signature composed of non-canonical small non-coding RNAs in human peripheral blood mononuclear cells (PBMCs), including tRNA-derived small RNAs (tsRNAs), rRNA-derived small RNAs (rsRNAs), and YRNA-derived small RNAs (ysRNAs). This signature consists of i) the tsRNAs derived from tRNA-Ala, tRNA-Asn, tRNA-Leu, tRNA-Lys, and tRNA-Tyr that are upregulated in the lung cancer patients relative to the healthy controls and patients with pulmonary TB, ii) the rsRNAs derived from rRNA-5S that are upregulated in the lung cancer patients but downregulated in TB patients relative to the controls, and iii) the ysRNAs originating from YRNA-RNY1 that are downregulated in the lung cancer patients but upregulated in the TB patients compared with the controls. This diagnostic signature discriminates between healthy controls, lung cancer patients, and pulmonary TB subjects with high accuracy in both the discovery and validation cohorts. We conclude that the PBMC tsRNAs, rsRNAs, and ysRNAs are informative for both screening for and discriminating between lung cancer and pulmonary TB.
2020-11-16 | GSE148862 | GEO