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Diagnostic utility of immunohistochemistry in concordance with mRNA analysis of PRAME in the stratification of high-risk uveal melanoma patients.

Nikhil KumarMithalesh Kumar SinghLata SinghNeiwete LomiRachna MeelNeelam PushkerSeema SenRachna Meel
Published in: Human cell (2022)
Existing clinical indicators for metastatic risk classification and patient treatment of uveal melanoma (UM) in the Asian population are limited. Preferentially expressed antigen in melanoma (PRAME) has gained attention in the prognosis of cancers and considered as a potential biomarker in many tumors including UM. Therefore, this study investigated the expression of PRAME and its association with loss of nuclear BAP1 (nBAP1) as well as its correlation with clinicopathological parameters and patient outcome. Immunohistochemical expression of PRAME and BAP1 proteins were assessed in 66 prospective cases of UM. mRNA expression level was measured by quantitative real-time PCR. Kaplan-Meier curves and Cox proportional hazard models were used to analyze the correlation of protein expression with clinicopathological parameters, metastasis-free survival and overall survival. Nuclear PRAME (nPRAME) expression and loss of nBAP1 were observed in 24 and 62% cases, respectively. PRAME mRNA expression level was found to be upregulated in 64% (7/11) of metastatic patients. mRNA and immunoexpression of nPRAME were statistically significant with many clinicopathological high-risk factors. On univariate and multivariate analyses, high mitotic activity, extraocular invasion and presence of nPRAME expression were statistically significant (p < 0.05). On Kaplan-Meier survival analysis, patients expressing PRAME had significantly reduced metastasis-free survival (MFS) and overall survival (OS). MFS and OS were also reduced in patients expressing PRAME along with loss of nBAP1. Our data show that nPRAME expression, in combination with loss of nBAP1, could be a useful predictive biomarker in the therapeutic management of UM patients at high risk.
Keyphrases
  • end stage renal disease
  • chronic kidney disease
  • ejection fraction
  • poor prognosis
  • free survival
  • risk factors
  • squamous cell carcinoma
  • binding protein
  • high resolution
  • deep learning
  • big data
  • real time pcr