Background: Extensive research has indicated that tumor stemness promotes tumor progression. However, the underlying role of stemness-related genes (SRGs) in esophageal cancer (ESCA) remains unclear.Methods: This study identified differentially expressed stemness-related (DESR) messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) in ESCA, and correlated them with the clinical features of patients with ESCA to develop a prognostic risk assessment model. Functional analysis, protein-protein interaction (PPI) analysis, competing endogenous RNA (ceRNA) networks, and tumor-infiltrating immune cell analyses were performed to corroborate the results obtained from the model.Results: Correlation analysis of the stemness enrichment scores revealed 1,106 DESR genes (DESRGs), 84 DESRmiRNAs, and 320 DESRlncRNAs were identified from The Cancer Genome Atlas Esophageal Carcinoma (TCGA-ESCA) dataset. Network clustering was performed and the top 20 connection points were identified, including CDC20 that connects to 136 adjacent nodes. A ceRNA network was constructed, including 17 DESRmiRNAs, 44 DESRlncRNAs, and 55 DESRGs.Conclusions: NCAPG [log 2 fold change (FC) =1.81; q value =2.68×10 −11 ] was significantly upregulated in ESCA and positively correlated with resting natural killer (NK) cells, suggesting that human NK cells rest via the overexpression of NCAPG in ESCA. hsa-miR-1269a is significantly upregulated in ESCA patients with poor prognostic features. CD4 + resting memory T cells (P<0.01) were significantly negatively correlated with hsa-miR-1269a. The insights presented in this study will contribute to the development of innovative therapeutics for the treatment of patients with ESCA.