Identification and Validation a Necroptosis-Related Prognostic Signature in Cervical Cancer
- PMID: 36576713
- DOI: 10.1007/s43032-022-01155-y
Identification and Validation a Necroptosis-Related Prognostic Signature in Cervical Cancer
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.
Keywords: Cervical cancer; Necroptosis; Prognostic signature; Risk score.
© 2022. The Author(s), under exclusive licence to Society for Reproductive Investigation.
Similar articles
-
Identification of a necroptosis-related prognostic gene signature associated with tumor immune microenvironment in cervical carcinoma and experimental verification.World J Surg Oncol. 2022 Oct 17;20(1):342. doi: 10.1186/s12957-022-02802-z. World J Surg Oncol. 2022. PMID: 36253777 Free PMC article.
-
Construction and validation of a prognostic signature based on necroptosis-related genes in hepatocellular carcinoma.PLoS One. 2023 Feb 16;18(2):e0279744. doi: 10.1371/journal.pone.0279744. eCollection 2023. PLoS One. 2023. PMID: 36795724 Free PMC article.
-
Establishment and Validation of the Novel Necroptosis-related Genes for Predicting Stemness and Immunity of Hepatocellular Carcinoma via Machine-learning Algorithm.Comb Chem High Throughput Screen. 2025;28(1):146-165. doi: 10.2174/0113862073271292231108113547. Comb Chem High Throughput Screen. 2025. PMID: 39641162
-
Identification and validation of necroptosis-related prognostic gene signature and tumor immune microenvironment infiltration characterization in esophageal carcinoma.BMC Gastroenterol. 2022 Jul 15;22(1):344. doi: 10.1186/s12876-022-02423-6. BMC Gastroenterol. 2022. PMID: 35840882 Free PMC article.
-
A novel necroptosis-related gene index for predicting prognosis and a cold tumor immune microenvironment in stomach adenocarcinoma.Front Immunol. 2022 Oct 27;13:968165. doi: 10.3389/fimmu.2022.968165. eCollection 2022. Front Immunol. 2022. PMID: 36389725 Free PMC article. Review.
Cited by
-
RIPK1 and RIPK3 are positive prognosticators for cervical cancer patients and C2 ceramide can inhibit tumor cell proliferation in vitro.Front Oncol. 2023 May 1;13:1110939. doi: 10.3389/fonc.2023.1110939. eCollection 2023. Front Oncol. 2023. PMID: 37197430 Free PMC article.
-
Exploring program-cell death patterns to predict prognosis and sensitivity of cervical cancer immunotherapy via multi-omics analysis and clinical samples.Discov Oncol. 2025 May 28;16(1):940. doi: 10.1007/s12672-025-02622-z. Discov Oncol. 2025. PMID: 40434537 Free PMC article.
References
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Medical