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Author Spotlight: Enhancing Multicolor Fluorescence Localization in Lung Carcinoma Sample
Published on: November 21, 2023
Identification of immunohistochemical markers for distinguishing lung adenocarcinoma from squamous cell carcinoma
Cheng Zhan1, Li Yan1, Lin Wang1
11 Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China ; 2 Department of Radiation Oncology, Eye & ENT Hospital, Fudan University, Shanghai 200031, China ; 3 Department of Stomatology, Zhongshan Hospital, Fudan University, Shanghai 200032, China ; 4 Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Background:
Immunohistochemical staining has been widely used in distinguishing lung adenocarcinoma (LUAD) from lung squamous cell carcinoma (LUSC), which is of vital importance for the diagnosis and treatment of lung cancer. Due to the lack of a comprehensive analysis of different lung cancer subtypes, there may still be undiscovered markers with higher diagnostic accuracy.
Methods:
Herein first, we systematically analyzed high-throughput data obtained from The Cancer Genome Atlas (TCGA) database. Combining differently expressed gene screening and receiver operating characteristic (ROC) curve analysis, we attempted to identify the genes which might be suitable as immunohistochemical markers in distinguishing LUAD from LUSC. Then we detected the expression of six of these genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in lung cancer sections using immunohistochemical staining.
Results:
A number of genes were identified as candidate immunohistochemical markers with high sensitivity and specificity in distinguishing LUAD from LUSC. Then the staining results confirmed the potentials of the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) in distinguishing LUAD from LUSC, and their sensitivity and specificity were not less than many commonly used markers.
Conclusions:
The results revealed that the six genes (MLPH, TMC5, SFTA3, DSG3, DSC3 and CALML3) might be suitable markers in distinguishing LUAD from LUSC, and also validated the feasibility of our methods for identification of candidate markers from high-throughput data.
