Combined Expression of HGFR with Her2/neu, EGFR, IGF1R, Mucin-1 and Integrin α2β1 Is Associated with Aggressive Epithelial Ovarian Cancer.
Bastian CzogallaKatharina DötzerNicole SigrünerFranz Edler von KochChristine E BrambsSabine AnthuberSergio FranginiAlexander BurgesJens WernerSven MahnerBarbara MayerPublished in: Biomedicines (2022)
Hepatocyte growth factor receptor (HGFR), also known as c-mesenchymal-epithelial transition factor (c-MET), plays a crucial role in the carcinogenesis of epithelial ovarian cancer (EOC). In contrast, the mechanisms contributing to aberrant expression of HGFR in EOC are not fully understood. In the present study, the expression of HGFR with its prognostic and predictive role was evaluated immunohistochemically in a cohort of 42 primary ovarian cancer patients. Furthermore, we analyzed the dual expression of HGFR and other druggable biomarkers. In the multivariate Cox regression analysis, high HGFR expression was identified as an independent prognostic factor for a shorter progression-free survival (PFS) (hazard ratio (HR) 2.99, 95% confidence interval (CI95%) 1.01-8.91, p = 0.049) and overall survival (OS) (HR 5.77, CI95% 1.56-21.34, p = 0.009). In addition, the combined expression of HGFR, human epidermal growth factor receptor 2 (Her2/neu), epithelial growth factor receptor (EGFR), insulin-like growth factor 1 (IGF1R), Mucin-1 and Integrin α2β1 further significantly impaired PFS, platinum-free interval (PFI) and OS. Protein co-expression analyses were confirmed by transcriptomic data in a large, independent cohort of patients. In conclusion, new biomarker-directed treatment targets were identified to fight poor prognosis of primary EOC.
Keyphrases
- poor prognosis
- growth factor
- long non coding rna
- epidermal growth factor receptor
- binding protein
- tyrosine kinase
- small cell lung cancer
- prognostic factors
- free survival
- end stage renal disease
- chronic kidney disease
- magnetic resonance imaging
- single cell
- newly diagnosed
- artificial intelligence
- rna seq
- small molecule
- data analysis
- electronic health record
- growth hormone
- cell adhesion
- patient reported