Prognosis prediction signature of seven immune genes based on HPV status in cervical cancer

Abstract

Cervical cancer (CC) has a high incidence and mortality rate, with a low 5-year survival rate, and human papillomavirus (HPV) is one of its carcinogenic risks. However, little evidence exists on the impact of HPV infection on the survival of patients with CC. In the present study, the CC cohort and immune genes were downloaded from the TCGA database and the ImmPort database, respectively. Subsequently, the Gene Set Enrichment Analysis was performed and found that HPV status was involved in multiple immune signaling pathways, which revealed that HPV infection might play critical roles in the immune response. Then seven prognostic immune genes were identified according to HPV status in CC. Using the seven immune genes, we established an immune risk score (IRS) signature and the Kaplan-Meier curve showed that high IRS was significantly correlated with poor prognosis of CC in both the training sets (HR = 2.32, 95% CI = 1.66–3.33; AUC = 0.712) and the validation sets (HR = 1.38, 95% CI = 1.02–1.85 and AUC = 0.583 in TCGA-HNSCC; HR = 2.58, 95% CI = 1.364–4.893, AUC = 0.676 in GSE44001). A nomogram of IRS combined with clinical features was established, and further analyses demonstrated that the power of the nomogram to predict the prognosis of CC was more reliable than that of a single independent factor. In conclusion, this study provided a more comprehensive understanding of the correlation between HPV and immune mechanisms as well as a novel signature that can effectively predict the prognosis of CC patients.