Prognostic significance of LRIG2 and LRIG3 proteins in urothelial bladder carcinoma.
Marwa M Serag El-DienShereen Fathy MahmoudAlshimaa Mahmoud AlhanafyFouad Mohamed ZanatyNanis Shawky HolahPublished in: Journal of immunoassay & immunochemistry (2021)
Bladder carcinoma is the second most frequent cancer in Egyptian males. Leucine-rich and immunoglobulin-like domains (LRIGs) are usually dysregulated in various human tumors. The aim of this study is to explore the immunohistochemical expression of LRIG2 and LRIG3 in urothelial bladder carcinoma (UBC) and their relationship to patients clinicopathological data including survival. The study cohort included 79 UBC cases (14 non muscle invasive (NMI) and 65 muscle invasive (MI)). We assessed the associations of LRIG2 and LRIG3 expression with clinicopathological data, as well as progression-free and overall survival. Most of studied cases (>50%) express LRIG2 and LRIG3. Statistically significant association was observed between positivity for LRIG3 and muscle invasion (P = 0.001), high grade (P = 0.03), and female gender (P = 0.02). Moreover, positive LRIG2 staining was associated with early stage (T2) (P = 0.03), lymphovascular invasion (P = 0.004), and tendency to non-muscle invasive stage (P = 0.07). Grouping of cases according to positivity/negativity of both markers showed that cases with dual positivity for both proteins are associated with muscle invasion (P = 0.001) and paradoxically with prolonged overall survival (P = 0.037). We conclude that although the association of LRIG3 with MI and high-grade tumors, its expression is related to better survival. LRIG3 has the dominant role even if it coexists with LRIG2. The role of LRIG2 remains to be further investigated.
Keyphrases
- high grade
- early stage
- skeletal muscle
- poor prognosis
- end stage renal disease
- low grade
- mental health
- chronic kidney disease
- urinary tract
- endothelial cells
- newly diagnosed
- electronic health record
- peritoneal dialysis
- big data
- free survival
- young adults
- machine learning
- papillary thyroid
- lymph node metastasis
- mass spectrometry
- deep learning
- atomic force microscopy