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. 2020 Jul 31;40(7):BSR20193468.
doi: 10.1042/BSR20193468.

KRT8 and KRT19, associated with EMT, are hypomethylated and overexpressed in lung adenocarcinoma and link to unfavorable prognosis

Affiliations

KRT8 and KRT19, associated with EMT, are hypomethylated and overexpressed in lung adenocarcinoma and link to unfavorable prognosis

Wenlong Wang et al. Biosci Rep. .

Abstract

Background: Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer. To date, the prognosis of patients with LUAD remains dismal.

Methods: Three datasets were downloaded from the GEO database. Differentially expressed genes (DEGs) were obtained. FunRich was used to perform pathway enrichment analysis. Protein-protein interaction (PPI) networks were established and hub genes were obtained by Cytoscape software. GEPIA was utilized to conduct correlation and survival analysis. Upstream miRNAs of DEGs were predicted via miRNet database, and methylation status of promoters of DEGs was determined through UALCAN database.

Results: A total of 375 DEGs, including 105 and 270 up-regulated and down-regulated genes in LUAD, were commonly appeared in three datasets. These DEGs were significantly enriched in mesenchymal-to-epithelial transition (MET) and epithelial-to-mesenchymal transition (EMT). About 8 up-regulated and 5 down-regulated DEGs were commonly appeared in EMT/MET-related gene set and the top 50 hub gene set. Among the 13 genes, increased expression of KRT8 and KRT19 indicated unfavorable prognosis whereas high expression of DCN and CXCL12 suggested favorable prognosis in LUAD. Correlation analysis showed that KRT8 (DCN) expression was linked to KRT19 (CXCL12) expression. Further analysis displayed that KRT8 and KRT19 could jointly forecast poor prognosis in LUAD. About 42 and 2 potential miRNAs were predicted to target KRT8 and KRT19, respectively. Moreover, methylation level analysis demonstrated that KRT8 and KRT19 were significantly hypomethylated in LUAD compared with normal controls.

Conclusions: All these findings suggest that KRT8 and KRT19 are hypomethylated and overexpressed in LUAD and associated with unfavorable prognosis.

Keywords: Lung adenocarcinoma (LUAD); bioinformatic analysis; epithelial-to-mesenchymal transition (EMT); mesenchymal-to-epithelial transition (MET); methylation.

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Conflict of interest statement

The authors declare that there are no competing interests associated with the manuscript.

Figures

Figure 1
Figure 1. Volcano plots of differentially expressed genes (DEGs) from there datasets (GSE7670, GSE10072 and GSE32863)
(A) The detailed information of three selected datasets for differential expression analysis. (B) DEGs identified in GSE7670 dataset. (C) DEGs identified in GSE10072. (D) DEGs identified in GSE32863. Note: These volcano plots showed all of the DEGs. The black dots represent genes that are not differentially expressed between lung adenocarcinoma tissues and normal lung tissues, and the green dots and red dots represent the down-regulated and up-regulated genes in cancer samples, respectively. Adj. P-value < 0.05 and |log2FC| > 1 were set as the cut-off criteria.
Figure 2
Figure 2. Pathway enrichment analysis for these DEGs commonly appeared in all three datasets
(A) The intersection of up-regulated DEGs in all the three datasets. (B) Pathway enrichment analysis for these up-regulated DEGs that are commonly appeared in the three datasets using FunRich software. (C) The intersection of down-regulated DEGs in the three datasets. (D) Pathway enrichment analysis for these down-regulated DEGs that are commonly appeared in the three datasets using FunRich software.
Figure 3
Figure 3. Identification of hub genes in the protein-protein interaction (PPI) networks of upregulated and downregulated significant DEGs
(A) Establishment of PPI network of the up-regulated DEGs using STRING database. (B) The top 10 hub genes in the PPI network of the up-regulated DEGs according to node degree. (C) Establishment of PPI network of the down-regulated DEGs using STRING database. (D) The top 10 hub genes in the PPI network of the down-regulated DEGs according to node degree.
Figure 4
Figure 4. Screening of key genes in LUAD
(A) Up-regulated genes (CEACAM5, NQO1, LCN2, CDH1, KRT8, EPCAM, ELF3 and KRT19) that are commonly appeared in EMT/MET pathway and the top 50 hub genes. (B) The prognostic value of KRT8 in patients with LUAD. (C) The prognostic value of KRT19 in patients with LUAD. (D) Down-regulated genes (DCN, SERPING1, GNG11, CXCL12 and CAV1) that are commonly appeared in EMT/MET pathway and the top 50 hub genes. (E) The prognostic value of DCN in patients with LUAD. (F) The prognostic value of CXCL12 in patients with LUAD.
Figure 5
Figure 5. The correlation and joint prognostic values of KRT8–KRT19 and DCN–CXCL12 pairs in LUAD
(A) The association between KRT8 expression and KRT19 expression in LUAD. (B) The association between DCN expression and CXCL12 expression in LUAD. (C) The joint prognostic value of KRT8–KRT19 pair in LUAD. (D) The joint prognostic value of DCN–CXCL12 pair in LUAD. P-value < 0.05 or logrank P-value < 0.05 was considered as statistically significant.
Figure 6
Figure 6. The potential mechanisms of KRT8 and KRT19 in LUAD
(A) The potential miRNAs-KRT8 network constructed using miRNet database. (B) The potential miRNAs-KRT19 network constructed using miRNet database. (C) The methylation level of promoter of KRT8 in LUAD determined by UALCAN database. (D) The methylation level of promoter of KRT19 in LUAD determined by UALCAN database. P<0.05 was considered as statistically significant.

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References

    1. Torre L.A., Bray F., Siegel R.L., Ferlay J., Lortet-Tieulent J. and Jemal A. (2015) Global cancer statistics, 2012. CA Cancer J. Clin. 65, 87–108 - PubMed
    1. Wu X.Y. and Yu X.Y. (2018) Overexpression of KCNJ4 correlates with cancer progression and unfavorable prognosis in lung adenocarcinoma., e22270 - PubMed
    1. Chen W., Zheng R., Baade P.D. et al. . (2016) Cancer statistics in China, 2015. CA Cancer J. Clin. 66, 115–132 - PubMed
    1. Hsu C.L., Chen K.Y., Shih J.Y. et al. . (2012) Advanced non-small cell lung cancer in patients aged 45 years or younger: outcomes and prognostic factors. BMC Cancer 12, 241 10.1186/1471-2407-12-241 - DOI - PMC - PubMed
    1. Clough E. and Barrett T. (2016) The Gene Expression Omnibus Database. Methods Mol. Biol. 1418, 93–110 10.1007/978-1-4939-3578-9_5 - DOI - PMC - PubMed

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