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High expression of ELAVL1 predicts poor prognosis of Esophageal Carcinoma

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Abstract N6-methyladenosine (m6A) is the most prevalent RNA epigenetic regulation in eukaryotic cells. However, understanding of m6A in Esophageal carcinoma (ESCA) is very limited. We designed this study to investigate the role of m6A in ESCA. Expression pattern of m6A regulatory genes were extracted from gene array of 21cases of ESCA and public datasets to investigate the clinical relevance of m6A regulatory genes in ESCA. Next, we used public datasets to evaluate the relationship between m6A regulatory genes change and survival rates by the Kaplan-Meier analysis method. KEGG Pathway Enrichment Analysis and Gene Set Enrichment Analysis to identify the signaling pathways. The differences of immune cell subtypes were evaluated based on CIBERSORT algorithm. High expression level of ELAVL1 was significantly associated with worse overall survival (OS) of ESCA (P < 0.05). The levels of ELAVL1 were positively associated with macrophages M0(R=0.34, P=0.025), T follicular helper cells (R=0.44, P=0.0035), while Plasma cells (R=0.59, P=0.000041), and CD8 T cells (R=0.44, P=0.0038) exhibited an opposite result. ELAVL was in positive association with PSMC3IP. Our findings highlight the function and prognostic value of ELAVL1 in ESCA and extend the understanding of the importance of RNA epigenetics in cancer biology.
Title: High expression of ELAVL1 predicts poor prognosis of Esophageal Carcinoma
Description:
Abstract N6-methyladenosine (m6A) is the most prevalent RNA epigenetic regulation in eukaryotic cells.
However, understanding of m6A in Esophageal carcinoma (ESCA) is very limited.
We designed this study to investigate the role of m6A in ESCA.
Expression pattern of m6A regulatory genes were extracted from gene array of 21cases of ESCA and public datasets to investigate the clinical relevance of m6A regulatory genes in ESCA.
Next, we used public datasets to evaluate the relationship between m6A regulatory genes change and survival rates by the Kaplan-Meier analysis method.
KEGG Pathway Enrichment Analysis and Gene Set Enrichment Analysis to identify the signaling pathways.
The differences of immune cell subtypes were evaluated based on CIBERSORT algorithm.
High expression level of ELAVL1 was significantly associated with worse overall survival (OS) of ESCA (P < 0.
05).
The levels of ELAVL1 were positively associated with macrophages M0(R=0.
34, P=0.
025), T follicular helper cells (R=0.
44, P=0.
0035), while Plasma cells (R=0.
59, P=0.
000041), and CD8 T cells (R=0.
44, P=0.
0038) exhibited an opposite result.
ELAVL was in positive association with PSMC3IP.
Our findings highlight the function and prognostic value of ELAVL1 in ESCA and extend the understanding of the importance of RNA epigenetics in cancer biology.

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