The invention provides a group of biomarkers for predicting
nasopharyngeal carcinoma immunotherapy benefit and application thereof,
transcriptome data of a non-metastatic
primary treatment local advanced
nasopharyngeal carcinoma patient is analyzed to obtain a three-classification model which uses 318 genes as characteristics and is based on a recent systolic
centroid classification method; compared with a
standard treatment group, the event-free
survival rate of a type 1 patient subjected to anti-PD-1
immunotherapy in the model is remarkably improved, the model can reflect the biological heterogeneity of the
nasopharyngeal carcinoma patient, the
immunotherapy benefit condition of the nasopharyngeal
carcinoma patient can be more accurately predicted, and clinical medication can be better guided. According to the method for predicting nasopharynx
cancer immunotherapy benefit, paraffin
tissue sample detection can be utilized,
large sample quantity clustering is not depended on, a patient can be subjected to
typing at a
single sample level, feasibility is high, popularization is easy, and the method has important significance on nasopharynx
cancer immunotherapy.