Efficient ten-gene analysis of NSCLC tissue samples by next-generation sequencing.

Area of Science:

• Oncology
• Molecular Diagnostics
• Genomics

Background:

• Personalized medicine for lung cancer relies on accurate histological and molecular diagnosis.
• Current diagnostic methods like IHC, FISH, Sanger sequencing, and PCR are often costly and time-consuming.
• Next-generation sequencing (NGS) enables simultaneous multigene mutation analysis, potentially reducing costs and time.

Purpose of the Study:

• To evaluate a 10-gene, 32-mutation detection NGS panel for non-small cell lung cancer (NSCLC) diagnosis.
• To compare the sensitivity and efficiency of NGS with traditional methods for key lung cancer mutations.

Main Methods:

• A 10-gene, 32-mutation detection NGS panel was applied to 195 NSCLC samples.
• Epidermal Growth Factor Receptor (EGFR) and Anaplastic Lymphoma Kinase (ALK) results were verified using Sanger sequencing and Amplification-refractory Mutation System (ARMS) PCR.
• NGS performance was assessed for sensitivity in detecting low-abundance mutations and gene fusions.

Main Results:

• The NGS method showed higher sensitivity in detecting low-abundance mutations compared to Sanger sequencing and ARMS PCR.
• Potential limitations exist for detecting low-abundance or large-fragment gene fusions using genomic DNA.
• The NGS panel proved clinically applicable, efficient, and affordable for multigene mutation analysis in NSCLC.

Conclusions:

• A small NGS analysis panel is a viable, efficient, and cost-effective alternative to multiple traditional technologies for NSCLC diagnosis.
• NGS facilitates personalized treatment strategies by providing comprehensive molecular profiling.
• Further optimization may be needed to address limitations in detecting certain types of gene fusions.