A bioinformatics analysis to identify novel biomarkers for prognosis of pulmonary tuberculosis
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RESEARCH ARTICLE
Open Access
A bioinformatics analysis to identify novel biomarkers for prognosis of pulmonary tuberculosis Yahong Sun1†, Gang Chen1†, Zhihao Liu1, Lina Yu1 and Yan Shang2*
Abstract Background: Due to the fact that pulmonary tuberculosis (PTB) is a highly infectious respiratory disease characterized by high herd susceptibility and hard to be treated, this study aimed to search novel effective biomarkers to improve the prognosis and treatment of PTB patients. Methods: Firstly, bioinformatics analysis was performed to identify PTB-related differentially expressed genes (DEGs) from GEO database, which were then subjected to GO annotation and KEGG pathway enrichment analysis to initially describe their functions. Afterwards, clustering analysis was conducted to identify PTB-related gene clusters and relevant PPI networks were established using the STRING database. Results: Based on the further differential and clustering analyses, 10 DEGs decreased during PTB development were identified and considered as candidate hub genes. Besides, we retrospectively analyzed some relevant studies and found that 7 genes (CCL20, PTGS2, ICAM1, TIMP1, MMP9, CXCL8 and IL6) presented an intimate correlation with PTB development and had the potential serving as biomarkers. Conclusions: Overall, this study provides a theoretical basis for research on novel biomarkers of PTB, and helps to estimate PTB prognosis as well as probe into targeted molecular treatment. Keywords: Pulmonary tuberculosis, Clustering analysis, Enrichment analysis, Hub gene, PPI network
Background Tuberculosis (TB) is a kind of chronic infectious disease induced by Mycobacterium tuberculosis (MTB) with a relatively high rate of morbidity and mortality, and it has developed as a threatening public health issue globally (www.who.int/tb/publications/global_report/en/). According to the statistics reported by the World Health Organization in 2019, there were approximately 10 million newly diagnosed TB cases and about 1.4 million deaths worldwide (including HIV-positive people), and the top * Correspondence: [email protected] † Ya Hong Sun and Gang Chen contributed equally to this work. 2 Department of Respiratory and Critical Care Medicine, Changhai Hospital, Naval Medical University (Second Military Medical University), No. 168 Changhai Road, Yangpu District, Shanghai 200433, China Full list of author information is available at the end of the article
death toll was observed in low- and middle-income countries (http://apps.who.int/iris). Pulmonary tuberculous (PTB) is the most common TB form [1], and the prevention of PTB-related death can be greatly achieved via early effective diagnosis [2]. Therefore, mining potential biomarkers associated with PTB occurrence and development is vital for PTB early diagnosis, prognosis assessment and individualized treatment. Clinically, disease-related biomarkers that are able to predict possible responses before the start of treatment or monitor follow-up therapeutic responses are crucial for PTB treatment, as
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