Expression of Wnt signaling proteins LEF1, β-catenin, GSK3β, DVL1, and N-myc varies across retinoblastoma subtypes and pRb phosphorylation status

Retinoblastoma, a rare childhood eye cancer, has hereditary and non-hereditary forms. While TNM classification helps in prognosis, understanding molecular mechanisms is vital for the clinical behavior of retinoblastoma prediction. Our study aimed to analyze the expression levels of key Wnt pathway proteins, GSK3 beta, LEF1, beta-catenin, and DVL1, and associate them to non-phosphorylated active form (pRb) and the phosphorylated inactive form (ppRb) and N-myc expression, in retinoblastoma cells and healthy retinal cells, in order to elucidate their roles in retinoblastoma and identify potential targets that could help to improve diagnostic and therapy. Specimens from 22 retinoblastoma cases (unilateral, bilateral, and trilateral) were analyzed. Immunohistochemistry assessed proteins' expressions, followed by semi-quantitative analysis using the Immunoreactivity Score (IRS). Bayesian statistical methods were employed for data analysis. The study revealed various expression patterns of Wnt signaling proteins across different retinoblastoma types. The high expression levels were observed for LEF1 and DVL1. Inactive GSK3 beta and nuclear localization of beta-catenin indicated Wnt signaling activation. The levels of inactive ppRb were significantly higher in retinoblastoma compared to healthy retina, as well as the levels of inactive GSK3 beta. Positive correlations between DVL1 and N-myc, GSK3 beta Y216 and GSK3 beta S9 and non-P beta-catenin and LEF1 were established. Retinoblastomas without germline mutations (RB1+/+) exhibited high pRb, N-myc, and LEF1 levels, while those in genetically predisposed children (RB1+/-) showed lower expression of these proteins. Trilateral retinoblastomas demonstrated especially high N-myc and LEF1, but low pRb and ppRb levels. The findings highlight the meaningful role of the Wnt signaling pathway in retinoblastoma pathogenesis, providing insights into potential therapeutic targets. Understanding molecular features may pave the way for personalized treatments and improve outcomes for retinoblastoma patients.