Translational value of IDH1 and DNA methylation biomarkers in diagnosing lung cancers: a novel diagnostic panel of stage and histology-specificity

Background: Lung cancer is the leading cause of cancer-related death worldwide, and the timely and serial assessment of low-dose computed tomography (LDCT) in high-risk populations remains a challenge. Furthermore, testing a single biomarker for the diagnosis of lung cancers is of relatively low effectiveness. Thus, a stronger diagnostic combination of blood biomarkers is needed to improve the diagnosis of non-small cell lung cancer (NSCLC).

Methods: The blood levels of individual biomarkers [IDH1, DNA methylation of short stature homeobox 2 gene (SHOX2), and prostaglandin E receptor 4 gene (PTGER4)] were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. In total, 221 candidates were enrolled and randomly assigned into two groups for the training and validation of a diagnostic panel. Additionally, a subgroup analysis was performed in the whole cohort.

Results: A newly combined 3-marker diagnostic model for lung cancers was established and validated with area under the receiver operating characteristic (ROC) curve (AUC) values ranging from 0.835 to 0.905 in independent groups showing significantly stronger diagnostic value compared with a single tested biomarker. The sensitivity of the diagnostic model was as high as 86.1% and 80.0% in the training and validation sets, respectively. Although no apparent differences were found between the 3-marker and 2-marker models, the high clinical T-stage and histological type specificity of IDH1 and two other methylated DNA biomarkers were demonstrated in the subgroup analysis.

Conclusions: The combination of single biomarkers with high stage-specificity and histological type specificity (SHOX2 and PTGER4 DNA methylation and IDH1) showed better diagnostic performance in the detection of lung cancers compared with single marker assessment. A greater clinical utility of the panel may be developed by adding demographic/epidemiologic characteristics.