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Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing
Published on: October 10, 2025
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Targeting Infrequent Driver Alterations in Non-Small Cell Lung Cancer
Marie-Julie Nokin1, Chiara Ambrogio2, Ernest Nadal3
1University of Bordeaux, INSERM U1218, ACTION Laboratory, IECB, 33600 Pessac, France.
Trends in Cancer
|December 14, 2020
Summary
Targeted therapies for non-small cell lung cancer (NSCLC) show promise but often lead to acquired resistance. This review covers infrequent genomic alterations, treatment options, and resistance mechanisms in NSCLC.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Non-small cell lung cancer (NSCLC) treatment has advanced with targeted therapies for oncogenic driver mutations, establishing precision medicine.
- While effective, responses to targeted therapies are often temporary, with acquired resistance being a significant clinical challenge.
Purpose of the Study:
- To review the biology of infrequent genomic actionable alterations in NSCLC.
- To discuss current and emerging therapeutic strategies for NSCLC patients with uncommon drivers.
- To explore mechanisms of acquired drug resistance and future challenges in NSCLC targeted therapy.
Main Methods:
- Literature review of biological mechanisms.
- Analysis of current clinical trial data for targeted therapies.
- Discussion of emerging treatment options and resistance pathways.
Main Results:
- Infrequent genomic alterations represent a growing area of clinical research in NSCLC.
- Acquired resistance is a common limitation to the long-term efficacy of targeted therapies in NSCLC.
- Understanding resistance mechanisms is crucial for developing next-generation therapies.
Conclusions:
- Targeted therapies for NSCLC, particularly for uncommon drivers, require ongoing research into overcoming resistance.
- Future strategies must address the biology of rare alterations and the evolution of drug resistance.
- Precision medicine in NSCLC necessitates continuous innovation to improve patient outcomes.
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