Clinical usefulness of serum telomerase reverse transcriptase (hTERT) mRNA and epidermal growth factor receptor (EGFR) mRNA as a novel tumor marker for lung cancer

Abstract

Using a newly developed assay of telomerase reverse transcriptase (hTERT) mRNA in serum by real-time RT-PCR, we previously reported this assay to be superior to other tumor markers for hepatoma. In this study, we aimed to clarify its clinical significance as a biomarker for lung cancer. In 112 patients with lung tumor and 80 individuals without cancer, we measured serum hTERT mRNA and epidermal growth factor receptor (EGFR) mRNA levels, using a quantitative one-step real-time RT-PCR assay. We examined its sensitivity and specificity in lung cancer diagnosis, its clinical significance in comparison with other tumor markers, and its correlation with the clinical parameters using multivariate analyses and correlation relative tests. The copy number of serum hTERT mRNA was independently correlated with tumor size, tumor number, presence of metastasis and recurrence, and smoking (all P < 0.05). EGFR mRNA correlated with tumor number and clinical stage (both P < 0.05). The sensitivity and specificity in lung cancer diagnosis were 89.0% and 72.7% for hTERT mRNA, and 71.3% and 80.0% for EGFR mRNA, respectively. hTERT mRNA was superior to other tumor markers in lung cancer diagnosis. For both mRNAs, serum levels were significantly correlated with levels in lung cancer tissues (both P < 0.05). The copy number of hTERT mRNA significantly decreased after the surgical treatment. The data suggest that hTERT mRNA, especially when combined with EGFR mRNA, is a novel and excellent biomarker for pulmonary malignancies to diagnose and assess the clinical stage.

Figure 1

hTERT mRNA and EGFR mRNA expression. Quantitative assays for hTERT mRNA and (B) EGFR mRNA. In each, a strong linear relationship was demonstrated between copy number and PCR cycles using RNA controls for concentration. The dynamic ranges of real‐time PCR analysis for hTERT mRNA and EGFR mRNA were more than 5–10 copies in this assay and we were able to exclude the possibility of false negativity in serum samples from patients and controls. (C) ROC curve analysis of hTERT mRNA and EGFR mRNA expression. The curves shown were obtained by processing quantified raw data with SPSS 13.0 and the sensitivity and specificity values were calculated as the mean of confidence intervals of area under the curves. Each line has a cutoff point with the shortest distance to each curve from the upper‐left corner on the graph.

Figure 2

Immunohistochemistry of biomarker expression. Representative immunohistochemistry in cancerous portion and non‐cancerous portion of the lung in a patient with ADC with respective biomarker expression (original magnification ×200). Nuclear and cytoplasmic immunoreactivity were measured using the appropriate antibody to detect the expression of (a) hTERT, (b) EGFR, (c) CYFRA, and (d) CEA.

Figure 3

Correlation between hTERT and EGFR mRNA levels in serum and in lung cancer tissue. (A) hTERT mRNA levels in serum and in lung cancer tissue in 23 patients: P < 0.01 by paired t‐test; P = 0.021 by non‐parametric Spearman's test. (B) EGFR mRNA levels in serum and in lung cancer tissues in 9 patients: P < 0.01 by paired t‐test; P = 0.002 by non‐parametric Spearman's test. Only patients positive for mRNA in the tissue specimens were included in this analysis. Positive was defined as above the predictive cutoff values for the mRNA in the study population. The data were evaluated by a logarithm of quantification.

Figure 4

Quantification of hTERT and EGFR mRNA levels in serum before and after surgical treatment. (A) hTERT mRNA expression in 23 patients: P = 0.041 by paired t‐test; P = 0.038 by Wilcoxon test. (B) EGFR mRNA expression in nine patients: P = 0.065 by paired t‐test; P = 0.078 by Wilcoxon test. The data were evaluated by a logarithm of quantification.