Citation
Abstract
Lung cancer is one of the most common cancers and a leading cause of cancer-related mortality in Malaysia. This analysis aimed to evaluate the prevalence of actionable and common mutations, as well as co-mutations frequently occurring with EGFR variants in lung cancer. Mutational profiling of lung tumour samples was performed using next generation sequencing (NGS) panels at the Subang Jaya Medical Centre laboratory. A total of 469 lung tumour samples referred from several medical facilities in Malaysia were analysed and 84% were of the adenocarcinoma subtype. The three most frequent mutations found were EGFR (46.5%), TP53 (37.5%) and KRAS (14.3%). Actionable mutations with approved drug targets for lung cancer were detected in 63.5% of patient samples. Among patients with EGFR mutations, deletions in exon 19 were detected in 44.5% and p.L858R in 38.5% of samples. The most common co-mutations for samples with EGFR mutations were found in the TP53 gene (38.1%). A median turnaround time (TAT) of 3 working days was achievable with an automated NGS platform. NGS testing can provide valuable information on the mutational landscape and the prevalence of common or actionable mutations present in lung cancer patients. This real-world experience demonstrates the high percentage of actionable mutations detected and highlights the value of NGS testing in a clinical diagnostic setting.
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Official URL or Download Paper: https://www.mdpi.com/2673-5261/4/1/4
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Medicine and Health Science Institute of Bioscience |
DOI Number: | https://doi.org/10.3390/jmp4010004 |
Publisher: | Multidisciplinary Digital Publishing Institute |
Keywords: | Lung cancer; Next generation sequencing; EGFR; Actionable mutation |
Depositing User: | Ms. Nur Aina Ahmad Mustafa |
Date Deposited: | 10 Dec 2024 03:03 |
Last Modified: | 10 Dec 2024 03:03 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/jmp4010004 |
URI: | http://psasir.upm.edu.my/id/eprint/109443 |
Statistic Details: | View Download Statistic |
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