HPV-ferroptosis related genes as biomarkers to predict the prognosis of cervical cancer.

BACKGROUND

Ferroptosis can be used as a powerful predictor of cancer prognosis. HPV persistent infection is the main cause of cervical cancer, so it is very important to improve the prognosis of patients. Therefore, it is necessary to explore the value of HPV-ferroptosis related genes as prognostic biomarkers of cervical cancer patients.

METHODS

In this study, differentially expressed HPV-ferroptosis related genes were obtained from GSE7410, HPV gene set crossed with iron death genes. Five HPV-ferroptosis related genes with prognostic features were finally identified: CYBB, VEGFA, CKB, EFNA1 and HELLS. Multifactorial Cox regression was applied to establish and validate the prognostic model, and drug susceptibility and immune infiltration analyses were also performed.

RESULTS

The prognostic model was validated in the training set (TCGA) and validation set (GSE44001). Kaplan-Meier curves reveal significant differences in overall survival (OS) between high-risk and low-risk groups. Receiver operating characteristic (ROC) curve reflects the stability and accuracy of the prognostic model established in this study. In terms of immune function, T cell costimulation was better in the low-risk group than in the high-risk group (P < 0.01). The therapeutic effects of cisplatin, paclitaxel, docetaxel and cyclophosphamide, commonly used chemotherapy drugs for cervical cancer, are better in the high-risk group than in the low-risk group (P < 0.001).

CONCLUSION

HPV-ferroptosis related gene prognostic model not only has good stability and accuracy in predicting the prognosis of cervical cancer patients, but also has certain guiding value for clinicians in terms of drug sensitivity and immune microenvironment.