Application of liquid biopsy-based targeted capture sequencing analysis to improve the precision treatment of non-small cell lung cancer by tyrosine kinase inhibitors.

BACKGROUND: Targeted therapy of patients with non-small cell lung cancer (NSCLC) who harbour sensitising mutations by tyrosine kinase inhibitors (TKIs) has been found more effective than traditional chemotherapies. However, target genes status (eg, epidermal growth factor receptor (EGFR) TKIs sensitising and resistant mutations) need to be tested for choosing appropriate TKIs. This study is to investigate the performance of a liquid biopsy-based targeted capture sequencing assay on the molecular analysis of NSCLC. METHODS: Plasma samples from patients with NSCLC who showed resistance to the first/second-generation EGFR TKIs treatment were collected. The AVENIO ctDNA Expanded Kit is a 77 pan-cancer genes detection assay that was used for detecting EGFR TKIs resistance-associated gene mutations. Through comparison of the EGFR gene testing results from the Cobas EGFR Mutation Test v2, and UltraSEEK Lung Panel, the effectiveness of the targeted capture sequencing assay was verified. RESULTS: A total of 24 plasma cell-free DNA (cfDNA) samples were tested by the targeted capture sequencing assay. 33.3% (8/24) cfDNA samples were positive for EGFR exon 20 p.T790M which leads to EGFR dependent TKIs resistance. 8.3% (2/24) and 4.2% (1/24) samples were positive for mesenchymal-epithelial transition gene amplification and B-Raf proto-oncogene, serine/threonine kinase exon 15 p.V600E mutations which lead to EGFR independent TKIs resistance. The median value of the p.T790M variant allele fraction and variant copy numbers was 2% and 36.10 copies/mL plasma, respectively. The next-generation sequencing test showed higher than 90% concordance with either MassArray or qPCR-based methods for detecting either EGFR TKIs sensitising or resistance mutations. CONCLUSION: The targeted capture sequencing test can support comprehensive molecular analysis needed for TKIs treatment, which is promising to be clinically applied for the improved precision treatment of NSCLC.

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.