PARKIN protein expression and its impact on the survival of patients with advanced colorectal cancer
Session type: Proffered paper
Colorectal cancer is the third most prevalent cancer and the fourth leading cause of cancer-related deaths worldwide. It features a well-known natural history with well described molecular, chromosome and epigenetic alterations. However, there is still a lack of accurate prognostic markers, as evidenced by the lower overall survival rate of patients with advanced cancer. Alterations in PARKIN (Parkin RBR E3 ubiquitin protein ligase [PARK2]) protein expression have been described in several diseases, including colorectal cancer, but its functional significance is still unknown. This study aimed to investigate the involvement of PARKIN expression in colorectal adenocarcinoma development and progression by evaluating the association between its expression, patients’ clinicopathological parameters and expression of known proteins involved in colorectal cancer.
Tissue microarrays consisting of the 73 tumor and 64 normal samples were generated to examine PARKIN expression and localization by immunohistochemistry.
A positive correlation of PARKIN and APC expression was observed in the superficial, intermediate, and profound regions of all cases (r = 0.37; P = 0.001). PARKIN expression was also significantly associated with tumors from males (P = 0.049), of the mucinous subtype (P = 0.028), and of advanced stage (III + IV, P = 0.041). In addition, increased PARKIN expression was observed in the invasive front tumor region (P = 0.013). Most importantly, a positive correlation was found between PARKIN expression and the overall survival of patients with advanced colorectal cancer (P = 0.019). Multivariate analysis showed that PARKIN expression is independent of any of the clinicopathological parameters evaluated in relation to patients survival.
These results suggest that PARKIN expression status can be used as an independent prognostic marker of survival in advanced colorectal cancer. PARKIN expression analysis can be used after surgery in combination with classic prognostic factors to improve the accuracy of survival prediction.