Aim: To confirm if p53 mutation could be a routine predictive marker for the prognosis of hepatocellular carcinoma (HCC) patients.
Methods: Two hundreds and forty-four formalin-fixed paraffin-embedded tumor samples of the patients with HCC receiving liver resection were detected for nuclear accumulation of p53. The percent of P53 immunoreactive tumor cells was scored as 0 to 3+ in P53 positive region (<10% -, 10-30% +, 31-50% ++, >50% +++). Proliferating cell nuclear antigen (PCNA) and some clinicopathological characteristics, including patients' sex, preoperative serum AFP level, tumor size, capsule, vascular invasion (both visual and microscopic), and Edmondson grade were also evaluated.
Results: In univariate COX harzard regression model analysis, tumor size, capsule status, vascular invasion, and p53 expression were independent factors that were closely related to the overall survival (OS) rates of HCC patients. The survival rates of patients with 3+ for P53 expression were much lower than those with 2+ or + for P53 expression. Only vascular invasion (P<0.05) and capsule (P<0.01) were closely related to the disease-free survival (DFS) of HCC patients. In multivariate analysis, p53 overexpression (RI 0.5456, P<0.01) was the most significant factor associated with the OS rates of patients after HCC resection, while tumor size (RI 0.5209, P<0.01), vascular invasion (RI 0.5271, P<0.01) and capsule (RI-0.8691, P<0.01) were also related to the OS. However, only tumor capsular status was an independent predictive factor (P<0.05) for the DFS. No significant prognostic value was found in PCNA-LI, Edmondson's grade, patients' sex and preoperative serum AFP level.
Conclusion: Accumulation of p53 expression, as well as tumor size, capsule and vascular invasion, could be valuable markers for predicting the prognosis of HCC patients after resection. The quantitative immunohistochemical scoring for P53 nuclear accumulation might be more valuable for predicting prognosis of patients after HCC resection than the common qualitative analysis.