Abnormal methylation of N6 adenosine (m6A) in RNA plays a crucial role in the pathogenesis of many types of tumors. However, little is known about m6A RNA methylation in lung adenocarcinoma. This study aimed to identify the value of m6A RNA methylation regulators in the malignant progression and clinical prognosis of lung adenocarcinoma. The RNA-seq transcriptome data and corresponding clinical information of lung adenocarcinoma were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database. Then the identification of differentially expressed m6A RNA methylation regulators between cancer samples and normal control samples, different subgroups by consensus expression of these regulators and the prognostic signature were achieved using R software with multiple corresponding packages. The results showed that the expression levels of HNRNPC, YTHDF1, KIAA1429, RBM15, YTHDF2, and METTL3 in cancer group were significantly up-regulated ( P < 0.05), while expression levels of FTO, ZC3H13, METTL14, YTHDC1 and WTAP in cancer group were significantly down-regulated ( P < 0.05) compared with control group. Two subgroups identified by consensus expression of these regulators were closely related to the clinicopathological features, clinical outcomes and malignancy of lung adenocarcinoma. In addition, a 3-gene risk signature including KIAA1429, RBM15, and HNRNPC was constructed and the lung adenocarcinoma patients in TCGA database were divided into high-risk group and low-risk group based on the median risk score. In conclusion, the prognostic signature-based risk score calculated according to the expression levels of KIAA1429, RBM15, and HNRNPC, was not only strongly associated with clinical outcomes and clinicopathological features, but also an independent prognostic factor in lung adenocarcinoma.

Discontinuation of antiviral drugs may be the reason for recovered COVID-19 patients testing positive again. Br J Hosp Med. 2020.

Background Liquid biopsies based on blood samples have been widely accepted as a diagnostic and monitoring tool for cancers, but extremely high sensitivity is frequently needed due to the very low levels of the specially selected DNA, RNA, or protein biomarkers that are released into blood. However, routine blood indices tests are frequently ordered by physicians, as they are easy to perform and are cost effective. In addition, machine learning is broadly accepted for its ability to decipher complicated connections between multiple sets of test data and diseases. Objective The aim of this study is to discover the potential association between lung cancer and routine blood indices and thereby help clinicians and patients to identify lung cancer based on these routine tests. Methods The machine learning method known as Random Forest was adopted to build an identification model between routine blood indices and lung cancer that would determine if they were potentially linked. Ten-fold cross-validation and further tests were utilized to evaluate the reliability of the identification model. Results In total, 277 patients with 49 types of routine blood indices were included in this study, including 183 patients with lung cancer and 94 patients without lung cancer. Throughout the course of the study, there was correlation found between the combination of 19 types of routine blood indices and lung cancer. Lung cancer patients could be identified from other patients, especially those with tuberculosis (which usually has similar clinical symptoms to lung cancer), with a sensitivity, specificity and total accuracy of 96.3%, 94.97% and 95.7% for the cross-validation results, respectively. This identification method is called the routine blood indices model for lung cancer, and it promises to be of help as a tool for both clinicians and patients for the identification of lung cancer based on routine blood indices. Conclusions Lung cancer can be identified based on the combination of 19 types of routine blood indices, which implies that artificial intelligence can find the connections between a disease and the fundamental indices of blood, which could reduce the necessity of costly, elaborate blood test techniques for this purpose. It may also be possible that the combination of multiple indices obtained from routine blood tests may be connected to other diseases as well.

The purpose of this study was to identify potential molecular markers of lung squamous cell carcinoma (LUSC). Three datasets containing LUSC mRNA sequencing data were downloaded from the Gene Expression Omnibus, The Cancer Genome Atlas and the Gene Expression Profiling Interactive Analysis databases. These datasets were used to identify significantly differentially expressed genes (DEGs) in LUSC. A protein-protein interaction network of the DEGs was constructed followed by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes and overall survival analyses of the DEGs. A total of 37 DEGs between LUSC and normal tissues were identified, including 26 downregulated genes and 11 upregulated genes. Biological Process enrichment analysis revealed that the DEGs were mainly enriched in ‘cell adhesion’, ‘cell-matrix adhesion’, ‘anatomical structure morphogenesis’, ‘ECM-receptor interaction’ and ‘focal adhesion’. Overall survival analysis demonstrated that transcription factor 21, α-2-macroglobulin, acyl-CoA synthetase long chain family member 5, integrin subunit β8, meiotic nuclear divisions 1 and secretoglobin family 1A member 1 were significantly associated with the occurrence and development of lung cancer, and these genes were selected as hub genes. The results obtained in the present study may aid the elucidation of the molecular mechanisms involved in the development of LUSC and may provide potential targets for LUSC treatment.

BACKGROUND: COPD and bronchiectasis frequently coexist, which creates an emerging phenotype with a worse prognosis. However, the impact of bronchiectasis on the natural history of COPD has not been fully evaluated and is still controversial. This meta-analysis was performed to clarify the associations of the presence of bronchiectasis with the prognosis and quality of life of patients with COPD. METHODS: A systematic review and meta-analysis was performed following a search of medical databases, and included articles published up to April 2019. The following outcome measures were analyzed: age, sex, smoking history, body mass index, exacerbation rate, lung function, inflammatory biomarkers, albumin, colonization by potentially pathogenic microorganisms, Pseudomonas aeruginosa isolates, Haemophilus influenzae isolates, hospital admissions, and mortality. RESULTS: A total of 415,257 subjects with COPD from 18 observational studies were eligible; bronchiectasis was present in 25,929 subjects (6.24%). The coexistence of COPD and bronchiectasis occurred more often in older subjects with lower body mass index. The presence of bronchiectasis in the subjects with COPD increased the risk of daily sputum production (odds ratio [OR] 1.80, 95% CI 1.24-2.61), exacerbation (weighted mean difference [WMD] 0.72 times, 95% CI 0.59-0.85), frequent hospital admissions (WMD 0.35 times, 95% CI 0.21-0.49), and follow-up (>3 years) mortality (OR 2.26, 95% CI 0.95-5.36). The subjects with COPD and bronchiectasis showed poorer pulmonary function (FEV 1 /FVC: WMD-3.37%, 95% CI-5.63 to-1.11), lower albumin (Standardized mean difference [SMD]-0.17, 95% CI-0.26 to-0.08), elevated C-reactive protein (SMD 0.40, 95% CI 0.06-0.74), a greater proportion of chronic colonization by potentially pathogenic microorganisms (OR 6.65, 95% CI 4.44-9.95), and a higher isolation rate of P. aeruginosa (OR 5.13, 95% CI 4.89-5.38) or H. influenzae (OR 1.90, 95% CI 1.29-2.79) than the subjects with COPD without bronchiectasis. CONCLUSIONS: This meta-analysis confirmed the significant associations of the presence of bronchiectasis with the natural history, disease course, and outcomes in COPD. The COPDbronchiectasis phenotype had adverse effects on subjects' health condition and prognosis.

The expression of micro RNA (miR)‐140‐5p is known to be reduced in both pulmonary arterial hypertension ( PAH ) patients and monocrotaline‐induced PAH models in rat. Identification of target genes for miR‐140‐5p with bioinformatics analysis may reveal new pathways and connections in PAH . This study aimed to explore downstream target genes and relevant signaling pathways regulated by miR‐140‐5p to provide theoretical evidences for further researches on role of miR‐140‐5p in PAH . Multiple downstream target genes and upstream transcription factors ( TF s) of miR‐140‐5p were predicted in the analysis. Gene ontology ( GO ) enrichment analysis indicated that downstream target genes of miR‐140‐5p were enriched in many biological processes, such as biological regulation, signal transduction, response to chemical stimulus, stem cell proliferation, cell surface receptor signaling pathways. Kyoto Encyclopedia of Genes and Genome ( KEGG ) pathway analysis found that downstream target genes were mainly located in Notch, TGF ‐beta, PI 3K/Akt, and Hippo signaling pathway. According to TF –mi RNA – mRNA network, the important downstream target genes of miR‐140‐5p were PPI , TGF ‐betaR1, smad4, JAG 1, ADAM 10, FGF 9, PDGFRA , VEGFA , LAMC 1, TLR 4, and CREB . After thoroughly reviewing published literature, we found that 23 target genes and seven signaling pathways were truly inhibited by miR‐140‐5p in various tissues or cells; most of these verified targets were in accordance with our present prediction. Other predicted targets still need further verification in vivo and in vitro .

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