BIOINFORMATICS-BASED PREDICTION OF THE IMPACT OF ASCL2 ON THE PROGNOSIS OF ESOPHAGEAL CANCER

Objective: To investigate the expression characteristics, clinical significance, molecular mechanisms, and drug sensitivity of Achaete-scute family BHLH transcription factor 2 (ASCL2) in esophageal cancer, and to clarify its value as a prognostic marker and potential therapeutic target for esophageal cancer. Methods: RNA sequencing data and clinical information of esophageal cancer were downloaded from The Cancer Genome Atlas (TCGA) database. After standardization, 163 samples were included. Bioinformatics methods were used to analyze the expression difference of ASCL2 and its correlation with clinicopathological features and prognosis. Maftools package was employed for gene mutation characteristic analysis, immunedeconv package for immune scoring and immune checkpoint-related gene analysis, Limma package and ClusterProfiler package for differential gene screening and GO/KEGG enrichment analysis, and Genomics of Drug Sensitivity in Cancer (GDSC) database for drug sensitivity prediction. Meanwhile, 20 pairs of esophageal cancer tissue samples were collected, and the expression level of ASCL2 was verified by quantitative real-time PCR (qRT-PCR). Results: Both bioinformatics analysis and clinical sample verification showed that the expression of ASCL2 in esophageal cancer tissues was significantly higher than that in adjacent normal tissues, and its expression was partially correlated with tumor differentiation grade and clinical stage. Survival analysis revealed that the median overall survival (OS) of patients in the ASCL2 high-expression subgroup was significantly shorter than that in the low-expression subgroup (1.9 years vs 3.2 years), and the area under the curve (AUC) of ASCL2 for predicting 5-year survival rate was 0.732, indicating that ASCL2 could serve as an independent prognostic factor for the overall survival of esophageal cancer patients. Differential gene and enrichment analysis showed that ASCL2-related differential genes were mainly enriched in lipid metabolism reprogramming, DNA damage repair, cell cycle regulation, as well as Wnt and TGF-beta signaling pathways. Drug sensitivity prediction indicated that the ASCL2 high-expression subgroup had significantly reduced sensitivity to paclitaxel and cisplatin. Conclusion: ASCL2 is highly expressed in esophageal cancer tissues and is closely associated with lymph node metastasis and poor prognosis of patients, which can be used as a potential biomarker for prognostic evaluation of esophageal cancer. ASCL2 may promote the malignant progression of esophageal cancer by interacting with TP53, constructing an inhibitory tumor immune microenvironment, regulating tumor-related signaling pathways, and reducing chemotherapeutic drug sensitivity, thus providing a new target for the personalized treatment of esophageal cancer.