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. 2021 Jul 29:9:e11893.
doi: 10.7717/peerj.11893. eCollection 2021.

Network analysis of miRNA targeting m6A-related genes in patients with esophageal cancer

Lili Li  1   2 , Rongrong Xie  2 , Qichun Wei  1
Affiliations

Network analysis of miRNA targeting m6A-related genes in patients with esophageal cancer

Lili Li et al. PeerJ. .

Abstract

Background: We investigated the miRNA-m6A related gene network and identified a miRNA-based prognostic signature in patients with esophageal cancer using integrated genomic analysis.

Methods: We obtained expression data for m6A-related genes and miRNAs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Survival analysis was conducted to identify potential prognostic biomarkers. LASSO Cox regression was performed to construct the overall survival (OS) associated prediction signature. We used the Kaplan-Meier (K-M) curve and receiver operating characteristic (ROC) curves to explore the signature's efficiency and accuracy. Interactions between the m6A-related genes and miRNAs were identified in starBase3.0 and used to construct the miRNA-m6A related gene network.

Results: We found that HNRNPC, YTHDF, ZC3H13, YTHDC2, and METTL14 were dysregulated in esophageal cancer tissues. Multivariate Cox regression analysis revealed that HNRNPC may be an independent risk factor for OS. Five hundred twenty-two potential upstream miRNAs were obtained from starBase3.0. Four miRNAs (miR-186, miR-320c, miR-320d, and miR-320b) were used to construct a prognostic signature, which could serve as a prognostic predictor independent from routine clinicopathological features. Finally, we constructed a key miRNA-m6A related gene network and used one m6A-related gene and four miRNAs associated with the prognosis. The results of our bioinformatics analysis were successfully validated in the human esophageal carcinoma cell lines KYSE30 and TE-1.

Conclusion: Our study identified a 4-miRNA prognostic signature and established a key miRNA-m6A related gene network. These tools may reliably assist with esophageal cancer patient prognosis.

Keywords: Esophageal cancer; HNRNPC; N6-methyladenosine; Overall survival; Prognosis.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. Bioinformatics analysis of the expression patterns of m6A-related genes in esophageal cancer.
(A) The heatmap indicated the expression of m6A-related genes in esophageal cancer (T, n = 162) and normal tissues (N, n = 11) based on the data from TCGA. *P < 0.05; **P < 0.01; ***P < 0.001. (B) Volcano plot showed gene expression profiles in esophageal cancer (red, n = 162) and normal tissues (blue, n = 11).
Figure 2
Figure 2. The correlation between the expression levels of m6A-related genes and overall survival (OS) rates in esophageal cancer patients (n = 162).
(A–C) Kaplan–Meier OS curve based on ALKBH5 expression (A), HNRNPC expression (B) and WTAP expression (C) in TCGA dataset. (D–E) Univariate (D) and multivariate (E) analyses of m6A-related genes associated with OS.
Figure 3
Figure 3. Construction and validation of the miRNA-based prognostic signature.
(A) The relationship between the 13 target genes and their corresponding miRNAs was shown. (B) Volcano plot showed miRNA expression profiles in esophageal cancer (red, n = 185) and normal tissues (blue, n = 13). (C–D) Univariate (C) and multivariate (D) analyses of seven miRNAs associated with overall survival (OS) rates in esophageal cancer patients (n = 164). (E–F) The process of using four miRNAs to build the signature. (G, I) Kaplan–Meier OS curves for patients assigned to high-risk and low-risk groups based on the risk score in the TCGA (G) and GEO (I) datasets. (H, J) The receiver operating characteristic (ROC) curves of the risk signature in the TCGA (H) and GEO (J) datasets.
Figure 4
Figure 4. Univariate (A) and multivariate (B) Cox regression analyses of the association between clinicopathological factors (including the risk score) and overall survival of esophageal cancer patients (n = 107).
Figure 5
Figure 5. The key miRNA-m6A related gene network in esophageal cancer.
Figure 6
Figure 6. Silencing of HNRNPC suppressed proliferation, migration and invasion of KYSE30 and TE-1 Cells.
(A) The mRNA expression levels of HNRNPC in esophageal cancer cell lines (KYSE30 and TE-1) and normal esophageal epithelial cell line HEEC were determined by qRT-PCR. (B) The HNRNPC knockdown efficiency was confirmed at the mRNA levels in KYSE30 and TE-1 cells by qRT-PCR. (C–D) MTT assay was performed to determine the cell proliferation in KYSE30 (C) and TE-1 cells (D). (E–F) Transwell assay was performed to assess the cell migration and invasion capacity in KYSE30 (E) and TE-1 (F) cells. **P < 0.01; ***P < 0.001; ****P < 0.0001.
Figure 7
Figure 7. miR-186 targeted HNRNPC and suppressed HNRNPC expression.
(A) The relative expression of 4 miRNAs (miR-186, miR-320c, miR-320d, miR-320b) were detected in esophageal cancer cell lines (KYSE30 and TE-1) and normal esophageal epithelial cell line HEEC. (B) Potential binding site of miR-186 in HNRNPC. Detection of miR-186 mimics on luciferase activity of wild-type or mutant HNRNPC by luciferase reporter assay. (C–D) The mRNA expression levels of HNRNPC were assessed by qRT-PCR. *P < 0.05; **P < 0.01; ****P < 0.0001.
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