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.