Pulmonary embolism (PE) is gradually considered to be the third most common disease in the vascular disease category. Lung cancer is the most frequently diagnosed cancer and the leading cause of cancer death among males worldwide. Although initially appearing as distinct entities, lung cancer is a great risk factor for the development of PE. Pulmonary embolism is common in lung cancer patients, with a pooled incidence of 3.7%, and unsuspected pulmonary embolism (UPE) is also non-negligible with a rough rate ranging from 29.4% to 63%. Many risk factors of PE have been detected and could be classified into three categories: lung cancer-related, patient-related, and treatment-related factors. Decreased mean survival time could be significantly observed in lung cancer patients with PE or UPE compared to those only, but suspected PE has higher mortality than UPE. Prophylactic anticoagulant therapy benefit might be highest in patients with stage IV non-small cell lung cancer (NSCLC) or limited small cell lung cancer (SCLC), and heparin seems superior to warfarin for thrombotic prophylaxis. Periodically reassessing the risk-benefit ratio of anticoagulant treatment will be an efficient treatment strategy in lung cancer patients with PE.
Background Interstitial lung diseases (ILDs), a diverse group of diffuse lung diseases, mainly affect the lung parenchyma. The low-throughput ‘omics’ technologies (genomics, transcriptomics, proteomics) and relative drug information have begun to reshaped our understanding of ILDs, whereas, these data are scattered among massive references and are difficult to be fully exploited. Therefore, we manually mined and summarized these data at a database (ILDGDB, http://ildgdb.org/) and will continue to update it in the future. Main body The current version of ILDGDB incorporates 2018 entries representing 20 ILDs and over 600 genes obtained from over 3000 articles in four species. Each entry contains detailed information, including species, disease type, detailed description of gene (e.g. official symbol of gene), and the original reference etc. ILDGDB is free, and provides a user-friendly web page. Users can easily search for genes of interest, view their expression pattern and detailed information, manage genes sets and submit novel ILDs-gene association. Conclusion The main principle behind ILDGDB’s design is to provide an exploratory platform, with minimum filtering and interpretation, while making the presentation of the data very accessible, which will provide great help for researchers to decipher gene mechanisms and improve the prevention, diagnosis and therapy of ILDs.
Background: Rapid advances in genetic and genomic technologies have begun to reshape our understanding of idiopathic pulmonary fibrosis (IPF). Ferroptosis, an iron-dependent form of regulated cell death, play an important role in the development of IPF. Therefore, our study aimed to explore the role of ferroptosis-related genes (FRGs) and their correlation with lung dysfunction and quality of life in patients with IPF. Methods: Datasets were acquired by researching the Gene Expression Omnibus. FRGs were acquired by researching GeneCard database and PubMed. Ferroptosis-related differentially expressed genes (FRDEGs) were identified according to integrating FRGs and the DEGs identified in the GSE110147 dataset. Candidate key genes were identified from the miRNA-target FRDEGs network and protein-protein interactions (PPI) network. The relationship between key genes and lung function or quality of life was calculated using the GSE32537 datasets.Results: 293 FRGs were obtained, and 71 FRDEGs were identified. According to enrichment analysis, cell growth and death and pathways associated cancer were the important pathways, and significant biological processes were mainly consisted of cellular responses to stimulus and various situations. In addition, this study constructed an PPI network and a miRNA-target network based on the 71 FRDEGs, determined 19 candidate key genes. Furthermore, acyl-CoA synthetase long chain family member 1 (ACSL1), integrin subunit beta 8 (ITGB8) and ceruloplasmin (CP) were identified as the key genes. The expression level of ACSL1 was the strongest predictor for lung function (negatively) including percent predicted forced vital capacity (FVC% predicted) and percent predicted diffusion capacity of the lung for carbon monoxide (Dlco% predicted) and quality of life (negatively). In addition, ITGB8 and CP were negatively associated with FVC% predicted. According to DrugBank and PubMed, 4 drugs and 16 drugs have been found to act on ACSL1 and CP, respectively. Conclusion: These results imply that FRGs may shed new understanding on disease mechanism and provide potential biomarkers and therapy target to predict IPF progression.
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