Comprehensive profiling and quantitation of oncogenic mutations in non small-cell lung carcinoma using single

Shirong Zhang1, Bing Xia1, Hong Jiang1

  • 1Department of Oncology, Hangzhou First People's Hospital, Nanjing Medical University, Zhejiang, Hangzhou 310006, China.

Oncotarget
|July 14, 2016
PubMed

Insights

This study analyzed 184 non-small cell lung cancer (NSCLC) patients, finding EGFR mutations most common. Personalized oncogenic mutation profiling can aid NSCLC treatment decisions.

Area of Science:

  • Oncology
  • Genetics
  • Molecular Biology

Background:

  • Activating and resistance mutations in tyrosine kinase domains of oncogenes are common in non-small cell lung cancer (NSCLC).
  • Understanding the spectrum and abundance of these mutations is crucial for targeted therapy and patient stratification.

Purpose of the Study:

  • To assess the frequency, type, and abundance of key oncogenic mutations (EGFR, KRAS, BRAF, TP53, ALK) in NSCLC.
  • To evaluate the performance of the Single Molecule Amplification and Re-sequencing Technology (SMART) assay for mutation detection.
  • To explore the clinical implications of personalized mutation profiling in NSCLC patient management.

Main Methods:

  • Analysis of tumour specimens from 184 early and late-stage NSCLC patients.
  • Utilized Single Molecule Amplification and Re-sequencing Technology (SMART) for comprehensive mutation profiling.
  • Benchmarked SMART assay sensitivity and specificity against the gold standard ARMS-PCR for EGFR mutation detection.

Main Results:

  • EGFR mutations were most prevalent (59.9%), followed by KRAS (16.9%), TP53 (12.7%), EML4-ALK fusions (6.3%), and BRAF (4.2%).
  • SMART assay demonstrated high sensitivity (≥0.1%) and specificity (98.7%) for EGFR mutations.
  • Tumour mutation profiles were heterogeneous, with monoclonal (51.6%) and polyclonal (12.6%) events observed; patterns were similar across early and advanced stages.

Conclusions:

  • Personalized profiling and quantitation of oncogenic mutations in NSCLC are feasible and informative.
  • This approach can enhance patient classification based on tumour characteristics.
  • Ancillary information from mutation profiling can significantly aid clinicians in treatment decision-making for NSCLC.

Related Concept Videos