Identification and validation of a prognostic signature related to hypoxic tumor microenvironment in cervical cancer

Abstract

Background Hypoxia is a common microenvironment condition in most malignant tumors and has been shown to be associated with adverse outcomes of cervical cancer patients. In this study, we investigated the effects of hypoxia-related genes on tumor progress to characterize the tumor hypoxic microenvironment. Methods We retrieved a set of hypoxia-related genes from the Molecular Signatures Database and evaluated their prognostic value for cervical cancer. A hypoxia-based prognostic signature for cervical cancer was then developed and validated using tumor samples from two independent cohorts (TCGA-CESC and CGCI-HTMCP-CC cohorts). Finally, we validated the hypoxia prediction of ccHPS score in eight human cervical cancer cell lines treated with the hypoxic and normoxic conditions, and 286 tumor samples with hypoxic category (more or less) from Gene Expression Omnibus (GEO) database with accession GSE72723. Results A risk signature model containing nine hypoxia-related genes was developed and validated in cervical cancer. Further analysis showed that this risk model could be an independent prognosis factor of cervical cancer, which reflects the condition of the hypoxic tumor microenvironment and its remodeling of cell metabolism and tumor immunity. Furthermore, a nomogram integrating the novel risk model and lymphovascular invasion status was developed, accurately predicting the 1-, 3- and 5-year prognosis with AUC values of 0.928, 0.916 and 0.831, respectively. These findings provided a better understanding of the hypoxic tumor microenvironment in cervical cancer and insights into potential new therapeutic strategies in improving cancer therapy.

Prediction of Prognosis and Chemotherapeutic Sensitivity Based on Cuproptosis-Associated lncRNAs in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

“…In predicting CESC prognosis, the AUC value of this risk model was relatively high, at 0.727. Compared with previous cervical cancer biomarkers, although the AUC value of our risk model is not the highest, similar to many previous risk models, our risk model can not only predict prognosis better but also serves as an independent prognostic model [48][49][50][51]. These results also suggest that we may need to further refine our models.…”

Exploring the role of disulfidptosis-related signatures in immune microenvironment, prognosis and therapeutic strategies of cervical cancer

“…The patients in the low-risk group exhibited better prognoses in both internal and external datasets. Unlike many previous cervical cancer prognostic models trained and tested internally using the TCGA database, our validation extended to external datasets, providing a more comprehensive evaluation [40] , [41] , [42] . Furthermore, our risk model consistently achieved a 5-year AUC value of 0.7, distinguishing itself from many cervical cancer biomarkers that primarily predicted OS by excelling in predicting both OS and PFS [43] , [44] , [45] .…”

Comprehensive analysis of hypoxia-related gene signature in cervical cancer

“…Several studies have demonstrated the crucial role of multigene signatures in predicting the prognosis of CC [37,38]. For instance, one study constructed a four immune-related gene model for the prediction of CC prognosis, Xie et al [39] constructed an eight-gene model to predict the prognosis of CC after radiotherapy, while another study established a model based on 70 genes to predict the prognosis of advanced CC [39][40][41].…”