Egfr Sequencing

EGFR sequencing is a molecular testing approach that reads the DNA sequence of the epidermal growth factor receptor (EGFR) gene to identify alterations relevant to cancer biology and treatment decisions. The method typically involves isolating tumor DNA, amplifying or preparing EGFR-containing regions, and determining their nucleotide order through sequencing, allowing variants such as activating mutations to be detected and characterized. In cancer research, these results help classify tumors, investigate signaling pathways that drive abnormal cell growth, and assess whether targeted EGFR inhibitors may be appropriate; repeated sequencing can also reveal genetic changes associated with treatment resistance and guide development of more effective therapies.

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Research

JoVE Journal - Cancer Research

Detection of Targetable Alterations in Non-small Cell Lung Cancer using Next-generation Sequencing

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2025

This protocol describes an automated, ISO15189-accredited next-generation sequencing workflow for detecting targetable genomic alterations in non-small cell lung cancer (NSCLC) formalin-fixed paraffin-embedded tissues.

Identification of EGFR and RAS Inhibitors using Caenorhabditis elegans

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Cited by 4 •

2020

The genetically tractable nematode Caenorhabditis elegans can be used as a simple and inexpensive model for drug discovery. Described here is a protocol to identify anticancer therapeutics that inhibit the downstream signaling of RAS and EGFR proteins.

Establishing Dual Resistance to EGFR-TKI and MET-TKI in Lung Adenocarcinoma Cells In Vitro with a 2-step Dose-escalation Procedure

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Cited by 4 •

2017

An in vitro method for establishing dual resistance to an EGFR-TKI and a MET-TKI in cancer cells is described. This method is useful for developing treatments for patients with EGFR-mutations, who exhibit disease progression despite EGFR-TKI treatment with MET-amplification. It can also be modified for inhibitors targeting other molecules.

Amplicon Sequencing using the Long-Read Sequencing Technologies

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2025

This protocol was optimized for targeted deep sequencing of 18 drug-resistance regions in Mycobacterium tuberculosis using a long-read sequencing platform, followed by analysis with a tuberculosis-specific bioinformatics pipeline designed for long-read data.

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

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Cited by 19 •

2020

This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.

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