Overexpression of E-Cadherin Is a Favorable Prognostic Biomarker in Oral Squamous Cell Carcinoma: A Systematic Review and Meta-Analysis.
Alejandro Ismael Lorenzo-PousoFábio França-Vieira E SilvaAlba Pérez JardónCintia Micaela Chamorro-PetronacciMônica Ghislaine Oliveira AlvesÓscar Álvarez-Calderón IglesiasVito Carlo Alberto CaponioMorena PintiVittoria PerrottiMário Pérez-SayánsPublished in: Biology (2023)
Oral squamous cell carcinoma (OSCC) is characterized by poor survival, mostly due to local invasion, loco-regional recurrence, and metastasis. Given that the weakening of cell-to-cell adhesion is a feature associated with the migration and invasion of cancer cells, different studies have explored the prognostic utility of cell adhesion molecules such as E-cadherin (E-cad). This study aims to summarize current evidence in a meta-analysis, focusing on the prognostic role of E-cad in OSCC. To find studies meeting inclusion criteria, Scopus, Web of Science, EMBASE, Medline, and OpenGrey databases were systematically assessed and screened. The selection process led to 25 studies, which were considered eligible for inclusion in the meta-analysis, representing a sample of 2553 patients. E-cad overexpression was strongly associated with longer overall survival (OS) with Hazard Ratio (HR) = 0.41 95% confidence interval (95% CI) (0.32-0.54); p < 0.001 and disease-free survival with HR 0.47 95% CI (0.37-0.61); p < 0.001. In terms of OS, patients with tongue cancer experienced better survivability when expressing E-cad with HR 0.28 95% CI (0.19-0.43); p < 0.001. Globally, our findings indicate the prognostic role of the immunohistochemical assessment of E-cad in OSCC and its expression might acquire a different role based on the oral cavity subsites.
Keyphrases
- free survival
- cell adhesion
- coronary artery disease
- case control
- systematic review
- end stage renal disease
- cell proliferation
- chronic kidney disease
- ejection fraction
- poor prognosis
- transcription factor
- machine learning
- public health
- newly diagnosed
- papillary thyroid
- randomized controlled trial
- deep learning
- single cell
- peritoneal dialysis
- binding protein
- squamous cell
- big data
- lymph node metastasis
- artificial intelligence
- wild type