EFNA1 expression in various
cancers was analyzed according to the data in the TCGA database. The clinical data were integrated, to analyze the relationship with ESCA clinical parameters and prognosis, and
EFNA1 expression in ESCA tissue samples was detected by immunohistochemistry (IHC). Based on bioinformatics, the functional background of
EFNA1 overexpression was analyzed.
EFNA1 knockout cell model was established by EFNA1-shRNA transfecting ESCA cells, and the effect of knocking down
EFNA1 on the proliferation of ESCA cells was detected by MTT.
RESULTS: Among 7563 samples from TCGA, the
EFNA1 gene highly expressed in 15 samples with common
cancers and endangered the prognosis of patients with
tumors. Its overexpression in ESCA and its influence on the prognosis were most significant.
EFNA1 expression in 80 samples with ESCA and their paired samples was tested by IHC to verify its high expression (paired t test, P < 0.001) in ESCA tissues. It was found that
EFNA1 expression was related to clinical factors (TNM staging, P = 0.031;
lymph node metastasis, P = 0.043; infiltration, P = 0.016). Meanwhile,
EFNA1 was found to be an independent risk factor based on the COX multi-factor analysis. And to further explore the importance of
EFNA1 in
tumors, EC-9706 and ECA109 cells were screened from 8 ESCA-related cell lines to build
EFNA1 knockdown cell models. The results showed that
EFNA1 knockdown significantly inhibited the proliferation of
tumor cells (P < 0.05). In terms of molecular mechanism,
EFNA1 related genes were significantly enriched in the proliferative pathway according to the pathway enrichment analysis. It was found that knocking down
EFNA1 did inhibit cell proliferation based on cell experiments.
CONCLUSIONS: