Impact of AADAC gene expression on prognosis in patients with Borrmann type III advanced gastric cancer

Abstract

Background: The prognosis of Borrmann type III advanced gastric cancer (AGC) is known to vary significantly among patients. This study aimed to determine which differentially expressed genes (DEGs) are directly related to the survival time of Borrmann type III AGC patients and to construct a prognostic model.

Methods: We selected 25 patients with Borrmann type III AGC who underwent radical gastrectomy. According to the difference in overall survival (OS), the patients were divided into group A (OS<1 year, n=11) and group B (OS>3 years, n=14). DEGs related to survival time in patients with Borrmann type III AGC were determined by mRNA sequencing. The prognosis and functional differences of DEGs in different populations were determined by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) public databases. The expression of mRNA and protein in cell lines was detected by quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) and Western blot (WB). Immunohistochemical (IHC) staining was used to detect protein expression in the paraffin-embedded tissues of 152 patients with Borrmann type III AGC who underwent radical gastrectomy. After survival analysis, nomograms were constructed to predict the prognosis of patients with Borrmann type III AGC.

Results: Arylacetamide deacetylase (AADAC) is a survival-related DEG in patients with Borrmann type III AGC. The higher the expression level of its mRNA and protein is, the better the prognosis of patients. Bioinformatics analysis found that AADAC showed significant differences in prognosis and function in European and American populations and Asian populations. In addition, the mRNA and protein expression levels of AADAC were high in differentiated gastric cancer (GC) cells. We also found that AADAC was an independent prognostic factor for patients with Borrmann type III AGC, and its high expression was significantly correlated with better OS and disease-free survival (DFS). Nomogram models of AADAC expression level combined with clinicopathological features can be used to predict the OS and DFS of Borrmann type III AGC.

Conclusion: AADAC can be used as a biomarker to predict the prognosis of Borrmann type III AGC and has the potential to become a new therapeutic target for GC.

Keywords: AADAC; Borrmann type III; Gastric cancer; Prognosis.