1. Integrative genomic expression analysis reveals stable differences between lung cancer and systemic sclerosis
- Author
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Shuhui Meng, Zhenyou Jiang, Rui Liao, Dongzhou Liu, Liping Ding, Tingting Wang, Heng Li, Xiaoping Hong, and Yulan Chen
- Subjects
0301 basic medicine ,Cancer Research ,Lung Neoplasms ,Bioinformatics ,Population ,Datasets as Topic ,Disease ,Biology ,lcsh:RC254-282 ,03 medical and health sciences ,0302 clinical medicine ,Risk Factors ,Protein Interaction Mapping ,Genetics ,medicine ,Biomarkers, Tumor ,Humans ,Gene Regulatory Networks ,Protein Interaction Maps ,KEGG ,Lung cancer ,education ,Gene ,education.field_of_study ,Innate immune system ,Scleroderma, Systemic ,Chromatin binding ,Gene Expression Profiling ,Immunity ,Computational Biology ,Cell cycle ,medicine.disease ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,Healthy Volunteers ,Gene Expression Regulation, Neoplastic ,030104 developmental biology ,Oncology ,030220 oncology & carcinogenesis ,Case-Control Studies ,Systemic sclerosis ,Research Article - Abstract
BackgroundThe incidence and mortality of lung cancer are the highest among all cancers. Patients with systemic sclerosis show a four-fold greater risk of lung cancer than the general population. However, the underlying mechanism remains poorly understood.MethodsThe expression profiles of 355 peripheral blood samples were integratedly analyzed, including 70 cases of lung cancer, 61 cases of systemic sclerosis, and 224 healthy controls. After data normalization and cleaning, differentially expressed genes (DEGs) between disease and control were obtained and deeply analyzed by bioinformatics methods. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed online by DAVID and KOBAS. The protein–protein interaction (PPI) networks were constructed from the STRING database.ResultsFrom a total of 14,191 human genes, 299 and 1644 genes were identified as DEGs in systemic sclerosis and lung cancer, respectively. Among them, 64 DEGs were overlapping, including 36 co-upregulated, 10 co-downregulated, and 18 counter-regulated DEGs. Functional and enrichment analysis showed that the two diseases had common changes in immune-related genes. The expression of innate immune response and response to virus-related genes increased significantly, while the expression of negative regulation of cell cycle-related genes decreased notably. In contrast, the expression of mitophagy regulation, chromatin binding and fatty acid metabolism-related genes showed distinct trends.ConclusionsStable differences and similarities between systemic sclerosis and lung cancer were revealed. In peripheral blood, enhanced innate immunity and weakened negative regulation of cell cycle may be the common mechanisms of the two diseases, which may be associated with the high risk of lung cancer in systemic sclerosis patients. On the other hand, the counter-regulated DEGs can be used as novelbiomarkers of pulmonary diseases. In addition, fat metabolism-related DEGs were consideredto be associated with clinical blood lipid data.
- Published
- 2021