High expression of the transcriptional co-activator p300 predicts poor survival in resectable non-small cell lung cancers

X Hou, Y Li, R-Z Luo, J-H Fu, J-H He, L-J Zhang, H-X Yang
European Journal of Surgical Oncology 2012, 38 (6): 523-30

PURPOSE: To investigate the correlation between p300 (a transcriptional co-activator) expression and clinical/prognostic characteristics in surgically resected NSCLC patients for the purpose of identifying patients with increased risk of cancer recurrence and providing them with tailored therapy.

METHODS: One hundred and sixty-nine completely resected NSCLC patients were included in this study. Paraffin-embedded primary tumour tissues of patients were supplied to produce a tissue microarray, and immunohistochemistry was used for the evaluation of p300 expression. The clinical/prognostic significance of p300 expression was analysed for statistical significance. Survival was calculated by the Kaplan-Meier method, and the log-rank test was used to assess differences in survival between the groups. The prognostic impact of clinicopathologic variables and p300 expression was evaluated using a Cox proportional hazards model.

RESULTS: High expression of p300 was associated with poor disease-free survival (p = 0.027) and overall survival (p = 0.006) in NSCLC patients. Further analysis suggested that this difference in overall survival also existed in patients with T2 (p = 0.040), positive lymph nodes (p = 0.023), stage IIIA (p = 0.003), adenocarcinoma (p = 0.021), and a well-differentiated histological grade score (p = 0.011). The multivariate Cox regression analysis showed that low p300 expression is an independent marker of better disease-free survival (relative risk = 0.628, p = 0.047) and overall survival (relative risk = 0.545, p = 0.024) in operable NSCLC patients.

CONCLUSIONS: Low p300 expression is an independent prognostic marker of better survival in operable NSCLC patients. The combination of clinicopathological TNM staging classification with p300 expression may be useful in identifying patients with increased risk of cancer recurrence to provide them with tailored therapy.

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