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Next generation sequencing in lung cancer: An initial experience from India
Pragya Gupta1, Kallol Saha1, Sushant Vinarkar1
1Department of Molecular Genetics, Tata Medical Center, Kolkata, West Bengal, India.
Current Problems in Cancer
|March 18, 2020
Summary
This study analyzed gene mutations in 154 lung adenocarcinoma patients using next-generation sequencing. TP53 and EGFR were the most common mutations, with EGFR alterations more frequent in females and non-smokers.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Non-small cell lung cancer (NSCLC) is a leading cause of cancer death worldwide.
- EGFR mutations are prevalent in East Asian NSCLC patients, influencing treatment strategies.
- Next-generation sequencing (NGS) enables comprehensive analysis of tumor mutational profiles.
Purpose of the Study:
- To conduct comprehensive mutational profiling of advanced lung adenocarcinoma patients in Eastern India.
- To identify common genetic alterations and their association with clinicopathologic features.
- To contribute to a larger dataset on lung cancer mutations from the region.
Main Methods:
- Analysis of clinicopathologic characteristics and mutational data from 154 lung adenocarcinoma cases.
- Utilized next-generation sequencing (Ion Ampliseq Cancer Hotspot panel v2) on the Ion torrent PGM platform.
- Data collected over a 42-month period (October 2014 to March 2018).
Main Results:
- 72.07% of cases (111/154) harbored at least one genetic alteration.
- TP53 mutations were most frequent (37.6%), followed by EGFR (32.4%), KRAS (18.18%), ERBB2 (3.2%), and BRAF (1.94%).
- EGFR mutations were more prevalent in females (43.3%) and non-smokers (52.08%) compared to males (26.7%) and smokers (16.1%).
Conclusions:
- This study presents comprehensive mutational profiling of a significant cohort of advanced lung adenocarcinoma patients from India.
- Identified key mutations including TP53, EGFR, KRAS, ERBB2, and BRAF.
- Highlights the association of EGFR mutations with specific demographic factors, valuable for targeted therapy selection.
