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- Title
A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.
- Authors
Peng, Liu; Guo, Jin-Cheng; Long, Lin; Pan, Feng; Zhao, Jian-Mei; Xu, Li-Yan; Li, En-Min
- Abstract
Flavoproteins and their interacting proteins play important roles in mitochondrial electron transport, fatty acid degradation, and redox regulation. However, their clinical significance and function in esophageal squamous cell carcinoma (ESCC) are little known. Here, using survival analysis and machine learning, we mined 179 patient expression profiles with ESCC in GSE53625 from the Gene Expression Omnibus (GEO) database and constructed a signature consisting of two flavoprotein genes (GPD2 and PYROXD2) and four flavoprotein interacting protein genes (CTTN, GGH, SRC, and SYNJ2BP). Kaplan–Meier analysis revealed the signature was significantly associated with the survival of ESCC patients (mean survival time: 26.77 months in the high-risk group vs. 54.97 months in the low-risk group, P<0.001, n = 179), and time-dependent ROC analysis demonstrated that the six-gene signature had good predictive ability for six-year survival for ESCC (AUC = 0.86, 95% CI: 0.81–0.90). We then validated its prediction performance in an independent set by RT-PCR (mean survival: 15.73 months in the high-risk group vs. 21.1 months in the low-risk group, P=0.032, n = 121). Furthermore, RNAi-mediated knockdown of genes in the flavoprotein signature led to decreased proliferation and migration of ESCC cells. Taken together, CTTN, GGH, GPD2, PYROXD2, SRC, and SYNJ2BP have an important clinical significance for prognosis of ESCC patients, suggesting they are efficient prognostic markers and potential targets for ESCC therapy.
- Subjects
SQUAMOUS cell carcinoma; CELL proliferation; CARRIER proteins; CELL motility; CONFIDENCE intervals; DATABASES; ESOPHAGEAL tumors; MACHINE learning; MICROFILAMENT proteins; OXIDOREDUCTASES; POLYMERASE chain reaction; PROTEIN-tyrosine kinases; PROTEOLYTIC enzymes; SURVIVAL analysis (Biometry); TUMOR markers; PREDICTIVE tests; GENE expression profiling; KAPLAN-Meier estimator; PROGNOSIS
- Publication
BioMed Research International, 2019, p1
- ISSN
2314-6133
- Publication type
Article
- DOI
10.1155/2019/3869825