Abstract
Cervical cancer is the fourth most prevalent cancer in women, which decreases quality of life of the patients. Traditional interventions have failed to improve the overall survival period of patients due to high tumor recurrence after treatment or late diagnosis. Fortunately, preliminary evidence suggests that anti-angiogenic and immunotherapy can efficiently treat against cervical cancer. However, there is no clear evidence on the efficacy of immunotherapy in cervical cancer. Therefore, in this study, we classified cervical cancers in the TCGA dataset using various algorithms and explored the relationship between the immune profile and corresponding sensitivity of the tumors to immunotherapy. Results showed that patients with tumors had higher expression of immunocytes and longer overall survival time. In addition, we build a scoring system based on the immune landscape of the tumor microenvironment of cervical cancer. Tumors with higher scores exhibited better survival outcomes and were more sensitive to immunotherapy. In this study, the immune landscape of cervical cancer was analyzed, and the subtype of cervical cancer based on that difference was proposed. Besides, the subtype of cervical cancer showed different sensitivity to immunotherapeutic response which further confirmed its relationship with tumor immune landscape.