Comparison of next generation sequencing, SNaPshot assay and real-time polymerase chain reaction for lung adenocarcinoma EGFR mutation assessment

Publication

Comparison of next generation sequencing, SNaPshot assay and real-time polymerase chain reaction for lung adenocarcinoma EGFR mutation assessment

Journal Paper/Review - May 23, 2016

Cernomaz Andrei-Tudor, Brutsche Martin, Zonda Radu, Peter Simona, Baty Florent, Marinca Mihai, Grigoriu Carmen, Pavel Ionut, Macovei Ina Iuliana, Grigoriu Bogdan- Dragos

Citation

Cernomaz A, Brutsche M, Zonda R, Peter S, Baty F, Marinca M, Grigoriu C, Pavel I, Macovei I, Grigoriu B. Comparison of next generation sequencing, SNaPshot assay and real-time polymerase chain reaction for lung adenocarcinoma EGFR mutation assessment. BMC Pulm Med 2016; 16:88.

Type

Journal Paper/Review (English)

Journal

BMC Pulm Med 2016; 16

Publication Date

May 23, 2016

Issn Electronic

1471-2466

Brief description/objective

BACKGROUND
The epidermal growth factor receptor (EGFR) mutation status assessment has become increasingly important given the significant impact of tyrosine kinase inhibitors in lung cancer management. Our aim was to compare real life operational characteristics for three EGFR mutation assays - two targeted approaches and a next generation sequencing (NGS) technique.

METHODS
EGFR mutation status was assessed for lung adenocarcinoma samples (formalin fixed- paraffin embedded samples) using qPCR, SNaPshot and NGS (Ion Torrent™) techniques.

RESULTS
A total of 15 high clinical significance mutations were identified by at least one technique from the total of 64 samples. All mutations were identified by the TaqMan qPCR technique while SNaPshot in conjunction with fragment analysis identified 11 EGFR mutations. The NGS approach followed by an automatic analysis using the default calling parameters identified 10 mutations from the SNaPshot/qPCR panel and other three insertions, five point mutations and 58 silent variants; manual data review identified all 15 high significance mutations.

CONCLUSIONS
Performance was similar for high tumor content samples but careful data analysis and post hoc variant calling filter alterations were necessary in order to obtain robust results from low tumor content samples by NGS. NGS is able to generate a comprehensive mutational profile albeit at a higher cost and workload. Result interpretation should take into account not only general run parameters such as mean read depth but also relative coverage and read distribution; currently there is an acute need to define firm recommendations/standards concerning NGS data interpretation and quality control.