Identification of prognostic markers by weighted gene co‐expression network analysis in non-small cell lung cancer
Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-01-01
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| Series: | Bioengineered |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/21655979.2021.1960764 |
| Summary: | Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8+ T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (AURKB, CDC20, TPX2 and KIF2C) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of AURKB, CDC20, TPX2, and KIF2C correlated with the poor prognosis of these patients. In vitro experiments confirmed that CDC20 knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8+ T cell infiltration-related biomarkers and therapeutic targets. |
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| ISSN: | 2165-5979 2165-5987 |