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Identification and Validation a Necroptosis-Related Prognostic Signature in Cervical Cancer

Authors :
Zerui Yang
Junren Li
Yubo Tang
Lili Zou
Source :
Reproductive Sciences.
Publication Year :
2022
Publisher :
Springer Science and Business Media LLC, 2022.

Abstract

Necroptosis is a promising novel target for cervical cancer therapy. Nevertheless, differentially expressed necroptosis-related genes (NRGs) in cervical cancer and their associations with prognosis are far from fully clarified. In this study, differentially expressed NRGs (DE-NRGs) were screened out and their bio-function was elucidated. Subsequently, a prognostic scoring model based on the regression coefficients of the screened out NRGs and their corresponding mRNA expressions were constructed and validated. Finally, the survival probability of cervical cancer patients based on the constructed prognostic scoring model in 3 and 5 years was predicted and assessed. We found 17 DE-NRGs in cervical cancer tissues which were closely related to cancer progression, and most of them were significantly highly expressed. Furthermore, 3 NRG were confirmed as the prognostic signature genes from 17 DE-NRGs by regression analysis. Overall survival predicted through our prognostic scoring model was lower in the high-risk group than in the low-risk group (p 0.05) in both the TCGA cohort and the external GEO44001 validation cohort. What's more, the prediction performance of our prognostic scoring models well verified by the ROC curve, and the risk score calculated could act as an independent prognostic factor for cervical cancer patients. The calibration curve and C-index (0.776) of the nomogram analysis suggested that the predictive performance of the nomogram was satisfactory. Our study identified and validated a necroptosis-related prognostic signature in cervical cancer, which could well predict the prognosis for cervical cancer patients.

Subjects

Subjects :
Obstetrics and Gynecology

Details

ISSN :
19337205 and 19337191
Database :
OpenAIRE
Journal :
Reproductive Sciences
Accession number :
edsair.doi.dedup.....7b2c97fd3c111962759c4afaf66cc365
Full Text :
https://doi.org/10.1007/s43032-022-01155-y