Fluorodeoxyglucose positron emission tomography and chemotherapy-related tumor marker expression in non-small cell lung cancer

The chemotherapy resistance of non-small cell lung cancer (NSCLC) remains a clinic challenge and is closely associated with several biomarkers including epidermal growth factor receptor (EGFR) ( Drugs 72(Suppl 1):28–36, 012.), p53 ( Med Sci Monit 11(6):HY11–HY20, 2005.) and excision repair cross complementing gene 1 (ERCC1) ( J Thorac Oncol 8(5):582–586, 2013.). Fluorodeoxyglucose positron emission tomography (FDG–PET) is the best non-invasive surrogate for tumor biology with the maximal standardized uptake values (SUV_max) being the most important paradigm. However, there are limited data correlating FDG-PET with the chemotherapy resistant tumor markers. The purpose of this study was to determine the correlation of chemotherapy related tumor marker expression with FDG–PET SUV_max in NSCLC.

FDG–PET SUV_max was calculated in chemotherapy naïve patients with NSCLC (n = 62) and immunohistochemical analysis was performed for EGFR, p53 or ERCC1 on the intraoperative NSCLC tissues. Each tumor marker was assessed independently by two pathologists using common grading criteria. The SUV_max difference based on the histologic characteristics, gender, differentiation, grading and age as well as correlation analysis among these parameters were performed. Multiple stepwise regression analysis was further performed to determine the primary predictor for SUV_max and the receiver operating characteristics (ROC) curve analysis was performed to detect the optimized sensitivity and specificity for SUV_max in suggesting chemotherapy resistant tumor markers.

The significant tumor type (P = 0.045), differentiation (P = 0.021), p53 (P = 0.000) or ERCC1 (P = 0.033) positivity dependent differences of SUV_max values were observed. The tumor differentiation is significantly correlated with SUV_max (R = -0.327), tumor size (R = -0.286), grading (R = -0.499), gender (R = 0.286) as well as the expression levels for p53 (R = -0.605) and ERCC1 (R = -0.644). The expression level of p53 is significantly correlated with SUV_max (R = 0.508) and grading (R = 0.321). Furthermore, multiple stepwise regression analysis revealed that p53 expression was the primary predictor for SUV_max. When the cut-off value of SUV_max was set at 5.15 in the ROC curve analysis, the sensitivity and specificity of SUV_max in suggesting p53 positive NSCLC were 79.5% and 47.8%, respectively.

The current study suggests that SUV_max of primary tumor on FDG-PET might be a simple and good non-invasive method for predicting p53-related chemotherapy resistance in NSCLC when we set the cu-off value of SUVmax at 5.15.