ArticlePloS one2014
Downregulation of 14-3-3σ correlates with multistage carcinogenesis and poor prognosis of esophageal squamous cell carcinoma.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 19 citations in OpenAlex.
- Article
- Role and clinical significance of the DNA methylation of 14-3-3σ in cancer (Review).Oncology letters · 2025Review
- Article
- Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.BMC cancer · 2021Article
- The mechanobiome: a goldmine for cancer therapeutics.American journal of physiology. Cell physiology · 2021Review
- Identification of Key Genes and Pathways Associated With Paclitaxel Resistance in Esophageal Squamous Cell Carcinoma Based on Bioinformatics Analysis.Frontiers in genetics · 2021Article
- 14-3-3σ and Its Modulators in Cancer.Pharmaceuticals (Basel, Switzerland) · 2020Review
- Expression and Significance of TRIM 28 in Squamous Carcinoma of Esophagus.Pathology oncology research : POR · 2019Article
- 14-3-3 Proteins Are on the Crossroads of Cancer, Aging, and Age-Related Neurodegenerative Disease.International journal of molecular sciences · 2019Review
- Expression and significance of ASPP2 in squamous carcinoma of esophagus.The Kaohsiung journal of medical sciences · 2018Article
- Discovery of Novel and Clinically Relevant Markers in Formalin-Fixed Paraffin-Embedded Esophageal Cancer Specimen.Frontiers in oncology · 2018Article
- PTTG1 cooperated with GLI1 leads to epithelial-mesenchymal transition in esophageal squamous cell cancer.Oncotarget · 2017Article
- MiR-424-5p participates in esophageal squamous cell carcinoma invasion and metastasis via SMAD7 pathway mediated EMT.Diagnostic pathology · 2016Article
- Global proteomic profiling in multistep hepatocarcinogenesis and identification of PARP1 as a novel molecular marker in hepatocellular carcinoma.Oncotarget · 2016Article
- Identification of 14-3-3 Proteins Phosphopeptide-Binding Specificity Using an Affinity-Based Computational Approach.PloS one · 2016Article
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsThe asymptomatic nature of early-stage esophageal squamous cell carcinoma (ESCC) results in late presentation and consequent dismal prognosis This study characterized 14-3-3σ protein expression in the multi-stage development of ESCC and determined its correlation with clinical features and prognosis. MATERIALS AND
methodsWestern blot was used to examine 14-3-3σ protein expression in normal esophageal epithelium (NEE), low grade intraepithelial neoplasia (LGIN), high grade intraepithelial neoplasia (HGIN), ESCC of TNM I to IV stage and various esophageal epithelial cell lines with different biological behavior. Immunohistochemistry was used to estimate 14-3-3σ protein in 110 biopsy samples of NEE, LGIN or HGIN and in 168 ESCC samples all of whom had follow-up data. Support vector machine (SVM) was used to develop a classifier for prognosis.
results14-3-3σ decreased progressively from NEE to LGIN, to HGIN, and to ESCC. Chemoresistant sub-lines of EC9706/PTX and EC9706/CDDP showed high expression of 14-3-3σ protein compared with non-chemoresistant ESCC cell lines and immortalized NEC. Furthermore, the downregulation of 14-3-3σ correlated significantly with histological grade (P = 0.000) and worse prognosis (P = 0.004). Multivariate Cox regression analysis indicated that 14-3-3σ protein (P = 0.016) and T stage (P = 0.000) were independent prognostic factors for ESCC. The SVM ESCC classifier comprising sex, age, T stage, histological grade, lymph node metastasis, clinical stage and 14-3-3σ, distinguished significantly lower- and higher-risk ESCC patients (91.67% vs. 3.62%, P = 0.000).
conclusionsDownregulation of 14-3-3σ arises early in the development of ESCC and predicts poor survival, suggesting that 14-3-3σ may be a biomarker for early detection of high-risk subjects and diagnosis of ESCC. Our seven-feature SVM classifier for ESCC prognosis may help to inform clinical decisions and tailor individual therapy.
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