Bioinformatics Analyses Reveals a Comprehensive Landscape of CXC Chemokine Family Functions in Non-Small Cell Lung Cancer

• Published in: BioMed research international 2021-01, Vol.2021, p.1-34
• Main Authors: Tian, He, Wang, Liyu, Liu, Yu, Wang, Yalong, Zheng, Yujia, Fan, Tao, Zheng, Bo, Tan, Fengwei, Xue, Qi, Gao, Shugeng, Li, Chunxiang, He, Jie
• Format: Article
• Language: English
• Subjects: Analysis; Angiogenesis; Bioinformatics; Biomarkers; Care and treatment; Chemokines; Computational biology; Correlation analysis; CXC chemokines; CXCL10 protein; CXCL11 protein; CXCL12 protein; CXCL13 protein; Datasets; Diagnosis; DNA methylation; Gene expression; Genomes; Genomics; Immune system; Interstitial cells; Lung cancer; Lung cancer, Non-small cell; Medical prognosis; Metastases; Metastasis; Mutation; Non-small cell lung carcinoma; Principal components analysis; Prognosis; Proteins; Risk factors; Small cell lung carcinoma; Survival analysis; Target recognition; Transcription; Tumor markers; Tumor microenvironment; Tumorigenesis; Tumors
• ISSN: 2314-6133; 2314-6141
• DOI: 10.1155/2021/6686158

Backgrounds. Lung cancer is a major source of tumor-related death each year with non-small cell lung cancer (NSCLC) being a prevalent subtype. The metastasis from NSCLC to the brain usually imposes many neuron disorders. Previous studies have suggested that communications among cancer cells and interstitial cells are essential in tumorigenesis and are influenced by chemokines. In the tumor microenvironment, CXC chemokines can participate in the shifting of immune cells and manage tumor cell condition, thus affecting the progression of cancer and patient destinies. However, the expression and values of CXC chemokine family in NSCLC have not been systematically illustrated using public databases. Methods. UALCAN, STRING, ONCOMINE, GeneMANIA, cBioPortal, GEPIA, TISIDB, TRRUST, TIMER, Kaplan-Meier Plotter, and R software were utilized in this study. Results. Based on the TIMER and UACLCAN databases, in LUAD patients, the expression levels of CXCL10, CXCL13, and CXCL14 were significantly elevated while the transcriptional levels of CXCL2/3/4/7/12/16 were significantly reduced; in LUSC patients, the expression levels of CXCL6/10/13/14 were significantly elevated while the expression levels of CXCL2/3/4/5/7/11/12/16/17 were significantly reduced. We found remarkable relevance between the pathological stages of LUAD patients and the expressions of CXCL8 (positive) and CXCL17 (negative). Similarly, there are significant correlations between the pathological stages of LUSC patients and the expressions of CXCL1/2/6/17. In LUAD, patients with low expression levels of CXCL1/4/7/8 and patients with high expression levels of CXCL12/14/16 were associated with a significantly better prognosis. But in LUSC, all correlations between chemokines and prognosis are statistically insignificant. Pairwise expression correlation analysis among CXC chemokines shows that there are 7 significant correlations (between CXCL1 and CXCL2, between CXCL1 and CXCL3, between CXCL1 and CXCL8, between CXCL2 and CXCL3, between CXCL4 and CXCL7, between CXCL9 and CXCL10, and between CXCL9 and CXCL11) in LUAD and 4 significant correlations (between CXCL1 and CXCL8, between CXCL2 and CXCL3, between CXCL4 and CXCL7, and between CXCL10 and CXCL11) in LUSC. Significant correlations between the expressions of CXC chemokines and the infiltration of six common types of immune cells were also discovered in both LUAD and LUSC. Conclusions. We provided a comprehensive landscape of the CXC chemokine family in L