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      High expression of SPP1 in patients with chronic obstructive pulmonary disease (COPD) is correlated with increased risk of lung cancer

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          Abstract

          Chronic obstructive pulmonary disease (COPD) is characterized by persistent airway inflammation and fixed airflow obstruction. Patients with COPD have increased risk of lung cancer (LC), and the coexistence of both diseases is associated with poorer survival. However, the mechanisms predisposing patients with COPD to LC development and poor prognosis remain unclear. Gene expression profiles were downloaded from the Gene Expression Omnibus. Twenty‐two data sets were included ( n = 876). We identified 133 DEGs and 145 DEGs in patients with COPD and LC compared with healthy controls, respectively. There were 1544 DEGs in patients with LC and coexisting COPD compared with COPD, and these DEGs are mainly involved in the cell cycle, DNA replication, p53 signalling and insulin signalling. The biological processes primarily associated with these DEGs are oxidation reduction and apoptosis. SPP1 was the only overlapping DEG that was up‐regulated in patients with COPD and/or LC, and this was validated by qPCR in an independent cohort. The area under the curve value for SPP1 was 0.893 (0.822–0.963) for the prediction of LC in patients with COPD. High expression of SPP1 in patients with LC was associated with shorter survival time. Up‐regulation of SPP1 may be associated with increased risk of LC in patients with COPD and therefore may have potential as a therapeutic target for LC in patients with COPD.

          Abstract

          SPP1 is progressively up‐regulated in the lungs of patients with COPD, lung cancer (LC) and LC coexisting with COPD, as shown by bioinformatic analysis. Up‐regulation of SPP1 expression in COPD and its further up‐regulation in NSCLC coexisting with COPD were confirmed by qPCR. The area under the curve value for SPP1 was 0.893 (0.822–0.963) for the prediction of LC in patients with COPD. Thus, up‐regulation of SPP1 may be associated with increased risk of LC in patients with COPD.

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

            Reliable and timely information on the leading causes of death in populations, and how these are changing, is a crucial input into health policy debates. In the Global Burden of Diseases, Injuries, and Risk Factors Study 2010 (GBD 2010), we aimed to estimate annual deaths for the world and 21 regions between 1980 and 2010 for 235 causes, with uncertainty intervals (UIs), separately by age and sex. We attempted to identify all available data on causes of death for 187 countries from 1980 to 2010 from vital registration, verbal autopsy, mortality surveillance, censuses, surveys, hospitals, police records, and mortuaries. We assessed data quality for completeness, diagnostic accuracy, missing data, stochastic variations, and probable causes of death. We applied six different modelling strategies to estimate cause-specific mortality trends depending on the strength of the data. For 133 causes and three special aggregates we used the Cause of Death Ensemble model (CODEm) approach, which uses four families of statistical models testing a large set of different models using different permutations of covariates. Model ensembles were developed from these component models. We assessed model performance with rigorous out-of-sample testing of prediction error and the validity of 95% UIs. For 13 causes with low observed numbers of deaths, we developed negative binomial models with plausible covariates. For 27 causes for which death is rare, we modelled the higher level cause in the cause hierarchy of the GBD 2010 and then allocated deaths across component causes proportionately, estimated from all available data in the database. For selected causes (African trypanosomiasis, congenital syphilis, whooping cough, measles, typhoid and parathyroid, leishmaniasis, acute hepatitis E, and HIV/AIDS), we used natural history models based on information on incidence, prevalence, and case-fatality. We separately estimated cause fractions by aetiology for diarrhoea, lower respiratory infections, and meningitis, as well as disaggregations by subcause for chronic kidney disease, maternal disorders, cirrhosis, and liver cancer. For deaths due to collective violence and natural disasters, we used mortality shock regressions. For every cause, we estimated 95% UIs that captured both parameter estimation uncertainty and uncertainty due to model specification where CODEm was used. We constrained cause-specific fractions within every age-sex group to sum to total mortality based on draws from the uncertainty distributions. In 2010, there were 52·8 million deaths globally. At the most aggregate level, communicable, maternal, neonatal, and nutritional causes were 24·9% of deaths worldwide in 2010, down from 15·9 million (34·1%) of 46·5 million in 1990. This decrease was largely due to decreases in mortality from diarrhoeal disease (from 2·5 to 1·4 million), lower respiratory infections (from 3·4 to 2·8 million), neonatal disorders (from 3·1 to 2·2 million), measles (from 0·63 to 0·13 million), and tetanus (from 0·27 to 0·06 million). Deaths from HIV/AIDS increased from 0·30 million in 1990 to 1·5 million in 2010, reaching a peak of 1·7 million in 2006. Malaria mortality also rose by an estimated 19·9% since 1990 to 1·17 million deaths in 2010. Tuberculosis killed 1·2 million people in 2010. Deaths from non-communicable diseases rose by just under 8 million between 1990 and 2010, accounting for two of every three deaths (34·5 million) worldwide by 2010. 8 million people died from cancer in 2010, 38% more than two decades ago; of these, 1·5 million (19%) were from trachea, bronchus, and lung cancer. Ischaemic heart disease and stroke collectively killed 12·9 million people in 2010, or one in four deaths worldwide, compared with one in five in 1990; 1·3 million deaths were due to diabetes, twice as many as in 1990. The fraction of global deaths due to injuries (5·1 million deaths) was marginally higher in 2010 (9·6%) compared with two decades earlier (8·8%). This was driven by a 46% rise in deaths worldwide due to road traffic accidents (1·3 million in 2010) and a rise in deaths from falls. Ischaemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lower respiratory infections, lung cancer, and HIV/AIDS were the leading causes of death in 2010. Ischaemic heart disease, lower respiratory infections, stroke, diarrhoeal disease, malaria, and HIV/AIDS were the leading causes of years of life lost due to premature mortality (YLLs) in 2010, similar to what was estimated for 1990, except for HIV/AIDS and preterm birth complications. YLLs from lower respiratory infections and diarrhoea decreased by 45-54% since 1990; ischaemic heart disease and stroke YLLs increased by 17-28%. Regional variations in leading causes of death were substantial. Communicable, maternal, neonatal, and nutritional causes still accounted for 76% of premature mortality in sub-Saharan Africa in 2010. Age standardised death rates from some key disorders rose (HIV/AIDS, Alzheimer's disease, diabetes mellitus, and chronic kidney disease in particular), but for most diseases, death rates fell in the past two decades; including major vascular diseases, COPD, most forms of cancer, liver cirrhosis, and maternal disorders. For other conditions, notably malaria, prostate cancer, and injuries, little change was noted. Population growth, increased average age of the world's population, and largely decreasing age-specific, sex-specific, and cause-specific death rates combine to drive a broad shift from communicable, maternal, neonatal, and nutritional causes towards non-communicable diseases. Nevertheless, communicable, maternal, neonatal, and nutritional causes remain the dominant causes of YLLs in sub-Saharan Africa. Overlaid on this general pattern of the epidemiological transition, marked regional variation exists in many causes, such as interpersonal violence, suicide, liver cancer, diabetes, cirrhosis, Chagas disease, African trypanosomiasis, melanoma, and others. Regional heterogeneity highlights the importance of sound epidemiological assessments of the causes of death on a regular basis. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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              Mutational landscape and significance across 12 major cancer types

              The Cancer Genome Atlas (TCGA) has used the latest sequencing and analysis methods to identify somatic variants across thousands of tumours. Here we present data and analytical results for point mutations and small insertions/deletions from 3,281 tumours across 12 tumour types as part of the TCGA Pan-Cancer effort. We illustrate the distributions of mutation frequencies, types and contexts across tumour types, and establish their links to tissues of origin, environmental/carcinogen influences, and DNA repair defects. Using the integrated data sets, we identified 127 significantly mutated genes from well-known(forexample, mitogen-activatedprotein kinase, phosphatidylinositol-3-OH kinase,Wnt/β-catenin and receptor tyrosine kinase signalling pathways, and cell cycle control) and emerging (for example, histone, histone modification, splicing, metabolism and proteolysis) cellular processes in cancer. The average number of mutations in these significantly mutated genes varies across tumour types; most tumours have two to six, indicating that the numberof driver mutations required during oncogenesis is relatively small. Mutations in transcriptional factors/regulators show tissue specificity, whereas histone modifiers are often mutated across several cancer types. Clinical association analysis identifies genes having a significant effect on survival, and investigations of mutations with respect to clonal/subclonal architecture delineate their temporal orders during tumorigenesis. Taken together, these results lay the groundwork for developing new diagnostics and individualizing cancer treatment.
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                Author and article information

                Contributors
                fu.juanjuan@scu.edu.cn
                Journal
                FEBS Open Bio
                FEBS Open Bio
                10.1002/(ISSN)2211-5463
                FEB4
                FEBS Open Bio
                John Wiley and Sons Inc. (Hoboken )
                2211-5463
                07 March 2021
                April 2021
                : 11
                : 4 , In the Limelight: Bioplastics ( doiID: 10.1002/feb4.v11.4 )
                : 1237-1249
                Affiliations
                [ 1 ] Respiratory Group Department of Integrated Traditional Chinese and Western Medicine West China Hospital Sichuan University Chengdu China
                [ 2 ] West China Biobanks Department of Clinical Research Management West China Hospital Sichuan University Chengdu China
                [ 3 ] Research Core Facility West China Hospital Sichuan University Chengdu China
                Author notes
                [*] [* ] *Correspondence

                J. ‐J. Fu, Respiratory Group, Department of Integrated Traditional Chinese and Western Medicine, West China Hospital, Sichuan University, NO.37 Guoxue Alley, Wuhou District, Chengdu City, Sichuan Province, China

                Tel: +86 028 85422210

                E‐mail: fu.juanjuan@ 123456scu.edu.cn

                Author information
                https://orcid.org/0000-0003-3705-1568
                Article
                FEB413127
                10.1002/2211-5463.13127
                8016137
                33626243
                9f61dc9a-41f0-49da-ad05-5fb8aa6ac909
                © 2021 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 February 2021
                : 27 October 2020
                : 22 February 2021
                Page count
                Figures: 8, Tables: 2, Pages: 13, Words: 7333
                Funding
                Funded by: Thousand Talents Program
                Award ID: 0082204151045
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 81870014
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                April 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.1 mode:remove_FC converted:01.04.2021

                bioinformatics,chronic obstructive pulmonary disease,lung cancer,meta‐analysis,spp1

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