Risk stratification of gastrointestinal stromal tumors by Nanostring gene expression profiling

Purpose The risk assessment classification schemes for gastrointestinal stromal tumors (GIST) include tumor site, size, mitotic count and variably tumor rupture. Heterogeneity in high-risk GIST poses limitations for current classification schemes. This study aims to demonstrate the clinical utility of risk stratification by gene expression profiling (GEP) using Nanostring technology. Methods Fifty-six GIST cases were analyzed using a 231 gene expression panel. GEP results were correlated with clinical and pathological data. The prognostic performance was assessed in 34 patients with available survival data using ROC curves, Kaplan-Meier survival curves and compared with traditional risk assessment schemes. Volcano plot analysis identified seven genes with significantly higher expression (FDR < .0.05) in high-risk than in non-high-risk tumors, namely TYMS, CDC2, TOP2A, CCNA2, E2F1, PCNA, and BIRC5. Together, these transcripts exhibited significantly higher expression in high-risk tumors than in intermediate (P < 0.01), low (P < 0.001), and very low (P = 0.01) risk tumors. Receiver-operating characteristic curve analysis demonstrated area under the curve (AUC) to be 0.858 for the separation of high-risk and non-high-risk tumors. Kaplan-Meier survival analysis demonstrated improved risk stratification (log-rank test P < 0.001) compared to the current risk assessment classification (P = 0.231). Conclusion In addition to current clinical and histology-based risk classification for patients with GIST, gene expression may offer complementary prognostic information.

Automated summary

Gene expression profiling (GEP) can provide complementary risk stratification information for patients with gastrointestinal stromal tumors (GIST), in addition to clinical and histological data.