Prediction of Cervical Cancer Outcome by Identifying and Validating a NAD+ Metabolism-Derived Gene Signature.
Journal of personalized medicine
confidence
Key findings
Identified 21 NAD+ metabolism-related genes as independent prognostic indicators for cervical cancer survival; no clinical/biological endpoints reported.
View source on PubMed (PMID 36556252) ↗
- Sample size
- 293 cervical cancer patients
- Population
- Cervical cancer patients (293 patients and normal tissues from TCGA)
- Dosing
- Not applicable
- Duration
- Not reported
- Route
- Not applicable
- Blinding
- not_reported
- Controls
- none
- Drug class
- coenzyme
Full abstract
Cervical cancer (CC) is the second most common female cancer. Excellent clinical outcomes have been achieved with current screening tests and medical treatments in the early stages, while the advanced stage has a poor prognosis. Nicotinamide adenine dinucleotide (NAD+) metabolism is implicated in cancer development and has been enhanced as a new therapeutic concept for cancer treatment. This study set out to identify an NAD+ metabolic-related gene signature for the prospect of cervical cancer survival and prognosis. Tissue profiles and clinical characteristics of 293 cervical cancer patients and normal tissues were downloaded from The Cancer Genome Atlas database to obtain NAD+ metabolic-related genes. Based on the differentially expressed NAD+ metabolic-related genes, cervical cancer patients were divided into two subgroups (Clusters 1 and 2) using consensus clustering. In total, 1404 differential genes were acquired from the clinical data of these two subgroups. From the NAD+ metabolic-related genes, 21 candidate NAD+ metabolic-related genes (ADAMTS10, ANGPTL5, APCDD1L, CCDC85A, CGREF1, CHRDL2, CRP, DENND5B, EFS, FGF8, P4HA3, PCDH20, PCDHAC2, RASGRF2, S100P, SLC19A3, SLC6A14, TESC, TFPI, TNMD, ZNF229) were considered independent indicators of cervical cancer prognosis through univariate and multivariate Cox regression analyses. The 21-gene signature was significantly different between the low- and high-risk groups in the training and validation datasets. Our work revealed the promising clinical prediction value of NAD+ metabolic-related genes in cervical cancer.