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Diagnostic method of mass spectrometry for detecting lymph node metastasis of non‐small cell lung cancer

Authors :
Ryuichi Yoshimura
Wataru Shigeeda
Yuji Fujita
Tetsuo Kokaji
Hiroyuki Deguchi
Makoto Tomoyasu
Satoshi Kudo
Yuka Kaneko
Hironaga Kanno
Hidenobu Iwai
Tomohiko Mase
Hajime Saito
Source :
Thoracic Cancer, Vol 15, Iss 3, Pp 209-214 (2024)
Publication Year :
2024
Publisher :
Wiley, 2024.

Abstract

Abstract Background Histopathology by pathologists is essential in the diagnosis of non‐small cell lung cancer (NSCLC). However, auxiliary diagnostic procedures for malignant tumor have continued to evolve. Despite the poor prognosis of patients with NSCLC, the application of the latest procedures and technologies to the field of lung cancer has lagged. Mass spectrometry was used to detect trace amounts of peptides in human tissue with high accuracy. The aim of this study was to establish a method for diagnostic mass spectrometry to identify lymph node metastasis by detecting cytokeratin (CK)19, a useful biomarker in lung cancer. Methods We collected 81 lymph nodes with positive expression of CK19 in patients who underwent radical surgical resection in the Department of Thoracic Surgery at Iwate Medical University between May 2020 and December 2022. An X500R instrument was used for sample analysis. A positive result for lymph node metastasis as the detection at least two product ions (FGPGVAFR and ILGATIENSR) from CK19 was defined. Results Our study indicated a high diagnostic efficiency for mass spectrometry, with 87.5% sensitivity and 91.2% specificity. The mutual concordance of mass spectrometry methods and histopathological diagnosis was 90.1%. Conclusions Mass spectrometry offers high diagnostic accuracy and can be clinically applied to auxiliary diagnostic procedures for lymph node metastasis from NSCLC.

Details

Language :
English
ISSN :
17597714 and 17597706
Volume :
15
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Thoracic Cancer
Publication Type :
Academic Journal
Accession number :
edsdoj.3aad0295b49043249e06f85d2ab5c172
Document Type :
article
Full Text :
https://doi.org/10.1111/1759-7714.15179