Relationship Between Mutation Profile Detected by Next-generation Sequencing and Histopathological Parameters in Lung Squamous Cell Carcinoma

Lung Squamous cell carcinoma (LSCC) represents the second most common non-small cell lung cancer. Although studies identified adenocarcinoma-like driver mutations in LSCC using next-generation sequencing (NGS), the disease is challenging to treat due to the limited number of detectable mutations for targeted drug therapy. This study aimed to evaluate the mutation profiles of LSCC detected by NGS to assess the relationships between different driver mutations and clinicopathological parameters.

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Publication Details

Journal
Journal of Clinical and Translational Pathology
Published
2025-04-15
DOI
https://doi.org/10.14218/jctp.2025.00001
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
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article

Relationship Between Mutation Profile Detected by Next-generation Sequencing and Histopathological Parameters in Lung Squamous Cell Carcinoma

David Akin, Nesibe Kahraman Çetin, İbrahim Meteoğlu, Sinan Can Taşan et al.
Journal of Clinical and Translational Pathology
Cancer Genomics and Diagnostics
article

Relationship Between Mutation Profile Detected by Next-generation Sequencing and Histopathological Parameters in Lung Squamous Cell Carcinoma

David Akin, Nesibe Kahraman Çetin, İbrahim Meteoğlu, Sinan Can Taşan, İbrahim Halil Erdoğdu, Ezgi Özkıran
article en

Abstract

Lung Squamous cell carcinoma (LSCC) represents the second most common non-small cell lung cancer. Although studies identified adenocarcinoma-like driver mutations in LSCC using next-generation sequencing (NGS), the disease is challenging to treat due to the limited number of detectable mutations for targeted drug therapy. This study aimed to evaluate the mutation profiles of LSCC detected by NGS to assess the relationships between different driver mutations and clinicopathological parameters.

Journal of Clinical and Translational PathologyVol. 000(000)
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Openalex Percentile: Top 91%
Cancer Genomics and Diagnostics
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