Integrating single-cell and bulk RNA sequencing data identifies hypoxia as a predictive signature in cervical cancer

Background In the past three decades, the incidence rate of cervical cancer has declined in high-income countries, but it remaines an important public health problem in low - and middle-income countries, with cervical squamous cell carcinoma (CSCC) being the main type. Patients with advanced recurrence and metastasis have a poor prognosis. Cervical cancer exhibits extensive intra-tumoral phenotypic heterogeneity and plasticity. Methods We analyzed the single-cell RNA sequencing data of cervical squamous cell carcinoma available in the Comprehensive Gene Expression Database (GEO) and identified the tumor cell subtype exhibiting hypoxic characteristics. We extracted differentially expressed genes (HRDEGs) between this hypoxia-related cluster and other tumor cells. Based on the CSCC bulk RNA sequencing data published in the Cancer Genome Atlas (TCGA), this subtype was identified to be closely associated with poor prognosis in CSCC.101 combinations consisting of 10 machine learning were used for screening prognostic biomarkers in HRDEGs, and a hypoxia signature was established by multivariate COX regression. Results The hypoxia signature was validated using the GEO external database. Correlation analysis identified the hypoxia signature as significantly associated with hypoxia and tumor invasion, and verified that higher hypoxia signature are closely related to poorer immune infiltration and responses of immunotherapy and chemotherapy. In addition, the key gene P4HA2 in the hypoxia signature has been demonstrated to be associated with the malignant phenotypes of tumor cells and the regulation of HIF-1α stability. Conclusions Overall, this hypoxia signature is a promising independent prognostic factor, provides new biomarkers for the prognosis of CSCC and a good reference for personalized and precision medicine.