Related Experiment Video
Updated: Jan 26, 2026

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
Published on: October 10, 2025
Targeted methods for molecular characterization of EGFR mutational profile in lung cancer Moroccan cohort
Houda Kaanane1, Hicham El Attar2, Amal Louahabi3
1Laboratory of Genetics and Molecular Pathology, Faculty of Medicine and Pharmacy of Casablanca, University Hassan II, Casablanca 20250, Morocco.
Abstract:
The study of EGFR gene mutational profile in NSCLC patients has a special clinical significance in the selection of patients for tyrosine-kinase inhibitors therapy. From 2017, the targeted therapy started to be accessible in public sector in Morocco, thus, the implementation of techniques for the molecular characterization of EGFR mutations in the laboratories became a necessity. The aim of this study was to present targeted methods "ADx-ARMS technology and the Idylla™ system" for the identification of EGFR mutational profile, methods that can be implemented in our clinical laboratories for routine analysis instead of outsourcing analysis to other countries. We conducted this study by processing 239 cases of NSCLC patients. Using the DNA extracted from the FFPE tissue, we evaluated somatic mutations in exons 18 to 21 of the tyrosine-kinase domain of EGFR gene by HRM-PCR combined to real time PCR "ADx-ARMS technology" and Idylla™ system. These sensitive methods showed that among the positive mutant cases, the distribution of mutations was as follows: 70% of patients having a deletion in exon 19, 15% in exon 21 (L858R), 7.5% in exon 20 and 7.5% in exon 18 (G719X). All of the positive EGFR mutations cases were adenocarcinoma and 42.1% of them were smokers. These results show the need to incorporate a quick and efficient method for the identification of EGFR mutation into routine practice in our laboratories, allowing more patients to benefit from targeted therapy.
Insights
Identifying EGFR mutations in non-small cell lung cancer (NSCLC) is crucial for targeted therapy. This study evaluated ADx-ARMS and Idylla™ systems for EGFR mutation profiling in Moroccan NSCLC patients, enabling routine molecular diagnostics.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- EGFR mutations are key biomarkers for targeted therapy in non-small cell lung cancer (NSCLC).
- Targeted therapy for NSCLC is available in Morocco, necessitating local EGFR mutation profiling.
- Outsourcing molecular diagnostics poses logistical and economic challenges.
Purpose of the Study:
- To evaluate ADx-ARMS and Idylla™ systems for identifying EGFR mutations in NSCLC.
- To establish efficient, routine molecular diagnostic methods for EGFR mutations in Moroccan clinical laboratories.
- To facilitate patient selection for tyrosine-kinase inhibitors (TKIs) therapy.
Main Methods:
- Analysis of 239 NSCLC patient cases using DNA from FFPE tissues.
- Employing HRM-PCR combined with real-time PCR (ADx-ARMS technology) for EGFR mutation detection.
- Utilizing the Idylla™ system for molecular characterization of EGFR mutations in exons 18-21.
Main Results:
- EGFR mutations were identified in a subset of NSCLC patients.
- The most frequent mutations were exon 19 deletions (70%), followed by exon 21 L858R (15%).
- Exon 20 and exon 18 mutations (G719X) each accounted for 7.5% of positive cases; all were adenocarcinomas, and 42.1% were smokers.
Conclusions:
- ADx-ARMS and Idylla™ are sensitive and efficient methods for EGFR mutation profiling.
- Implementing these methods in routine practice can improve NSCLC patient access to targeted therapies.
- Local molecular diagnostics are essential for personalized cancer treatment in Morocco.
Related Concept Videos
Mutations
Mutations
Chromosomal Alterations Are Large-Scale Mutations
While point mutations are changes in a single nucleotide in...
Targeted Cancer Therapies
There are several types of targeted therapies against...
Cancers Originate from Somatic Mutations in a Single Cell
Viral Mutations
Mutation, Gene Flow, and Genetic Drift

