Identification of a prognostic immune signature for cervical cancer to predict survival and response to immune checkpoint inhibitors

• Published in: Oncoimmunology 2019-12, Vol.8 (12), p.e1659094-e1659094
• Main Authors: Yang, Si, Wu, Ying, Deng, Yujiao, Zhou, Linghui, Yang, Pengtao, Zheng, Yi, Zhang, Dai, Zhai, Zhen, Li, Na, Hao, Qian, Song, Dingli, Kang, Huafeng, Dai, Zhijun
• Format: Article
• Language: English
• Subjects: cervical cancer; immune checkpoint inhibitor response; Immune signature; Original Research; prognosis; tumor immune microenvironment
• ISSN: 2162-4011; 2162-402X; 2162-402X
• DOI: 10.1080/2162402X.2019.1659094

Cervical cancer (CC) is a leading cause of cancer-related death in women. Limited studies have investigated whether immune-related genes (IRGs) or tumor immune microenvironment (TIME) could be indicators for CC prognoses. The aim of this study was to develop an improved prognostic signature for CC based on IRGs or TIME to predict survival and response to immune checkpoint inhibitors (ICIs). A prognostic signature was constructed using bioinformatics method and its predictive capability was validated. The mechanisms underlying the signature's predictive capability were explored with CIBERSORT algorithm and mutation analysis. Immunophenoscore (IPS) is validated for ICIs response, and was therefore explored in relation to the signature. A prognostic signature based on 11 IRGs was developed. A multivariate analysis revealed that the 11-IRG signature was an independent prognostic factor for overall survival (OS) and progression-free interval in CC patients. In the 11-IRG signature high-risk group, CD8 T cells and resting mast cells, which are found to associate with better OS in our study, were lower; activated mast cells, associated with poorer OS, were higher, compared with the low-risk group. An IPS analysis suggested that the 11-IRG signature low-risk group, which possessed a higher IPS, represented a more immunogenic phenotype that was more inclined to respond to ICIs. In short, an 11-IRG prognostic signature for predicting CC patients' survival and response to ICIs was firmly established. The predictive capability of this model in CC requires further testing with the goal of better prognostic stratification and treatment management.