1038 - Neutrophil Profiling Reveals Distinct Subsets in Predicting Chemoradiotherapy Efficacy in Cervical Cancer
Presenter(s)
Q. Wang1, W. Yang2, C. Liu3, and Q. Hu2; 1Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, Hubei, China, 2Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China, 3Department of Radiation Oncology, Peking University First Hospital, Beijing, China
Purpose/Objective(s): Neutrophils exhibit a dual nature in their impact on chemoradiotherapy efficacy, which highlights their complex interactions within the tumor microenvironment and underscores the need for further research to elucidate the underlying mechanisms. This study aims to systematically construct a cervical cancer (CC) neutrophil atlas and investigate the distinct roles that neutrophils play in the chemoradiotherapy response of CC.
Materials/Methods: Integrating single-cell RNA sequencing data from 15 in-house and 8 publicly available CC cases, we identified neutrophil subpopulations by dimensionality reduction and clustering analyses, and further systematically characterized their transcriptional profiles. Leveraging clinical data from 187 chemoradiotherapy-treated CC patients, survival analysis revealed specific tumor-infiltrating neutrophil subpopulations that were positively or negatively correlated with chemoradiotherapy prognosis. Ultimately, Cox univariate regression analysis was conducted on the top 30 DEGs of each tumor-enriched neutrophil subset positively or negatively correlated with chemoradiotherapy, which proposed a prognostic gene set for CC chemoradiotherapy.
Results: Among the 10 neutrophil subsets, Neu-1-IL1B, Neu-3-CCL4, Neu-5-SLPI, and Neu-7-HSP were associated with inferior chemoradiotherapy prognosis, demonstrating characteristics linked to inflammatory responses, chemotactic properties, angiogenesis, and responsiveness to hypoxia and temperature, respectively. In contrast, Neu-4-IFIT2 and Neu-10-CD74 were correlated with favorable chemoradiotherapy outcomes, exhibiting features related to interferon responses, and antigen processing and presentation. Furthermore, we established a gene signature of tumor-associated neutrophils for predicting chemoradiotherapy prognosis, termed as NRS1 or NRS2 score based on subpopulations positively or negatively associated with chemoradiotherapy outcomes.
Conclusion: We constructed a comprehensive single-cell atlas of CC neutrophils, systematically delineating their heterogeneity and prognostic associations with chemoradiotherapy. Furthermore, we defined a gene signature of tumor-associated neutrophils for predicting chemoradiotherapy prognosis, offering critical insights for optimizing therapeutic precision in CC management.