Abstract
Cancer stem cells (CSCs) have been shown to accelerate tumor recurrence, radiotherapy, and chemotherapy resistance. Immunotherapy is a powerful anticancer treatment that can significantly prolong the overall survival of patients with lung adenocarcinoma (LUAD). However, little is known about the function of genes related to tumor stemness and immune infiltration in LUAD. After integrating the tumor stemness index based on mRNA expression (mRNAsi), immune score, mRNA expression, and clinical information from the TCGA database, we screened 380 tumor stemness and immune (TSI)-related genes and constructed a five TSI-specific-gene (CPS1, CCR2, NT5E, ANLN, and ABCC2) signature (TSISig) using a machine learning method. Survival analysis indicated that TSISig could stably predict the prognosis of patients with LUAD. Comparison of mRNAsi and immune score between high- and low-TSISig groups suggested that TSISig characterized tumor stemness and immune infiltration. In addition, enrichment of immune subpopulations showed that the low-TSISig group held more immune subpopulations. GSEA revealed that TSISig had a strong association with the cell cycle and human immune response. Further analysis revealed that TSISig not only had a good predictive ability for prognosis but could also serve as an excellent predictor of tumor recurrence and response to radiotherapy and immunotherapy in LUAD patients. TSISig might regulate the development of LUAD by coordinating tumor stemness and immune infiltration. Finally, a connectivity map (CMap) analysis demonstrated that the HDAC inhibitor could target TSISig.