The study by Luo et al. [33] first used machine learning methods to construct an immunotherapy resistance score (TSIRS) based on tumor neoantigen burden (TNB) and cancer stemness and subsequently investigated the efficacy of the TSIRS in predicting outcomes of patients undergoing anti-PD1/PDL1 therapy. The gene discussed is PDCD1; the disease is cancer.