Macrophages-based immune-related risk score model for relapse prediction in stage I–III non-small cell lung cancer assessed by multiplex immunofluorescence

Autor: Xiang-Rong, Wu, Hao-Xin, Peng, Miao, He, Ran, Zhong, Jun, Liu, Yao-Kai, Wen, Cai-Chen, Li, Jian-Fu, Li, Shan, Xiong, Tao, Yu, Hong-Bo, Zheng, Yan-Hui, Chen, Jian-Xing, He, Wen-Hua, Liang, Xiu-Yu, Cai
Rok vydání: 2022
Předmět:
Zdroj: Transl Lung Cancer Res
ISSN: 2226-4477
2218-6751
DOI: 10.21037/tlcr-21-916
Popis: BACKGROUND: Macrophages are critical players in regulating innate and adaptive immunity in the tumor microenvironment (TME). The prognostic value of macrophages and their heterogeneous phenotypes in non-small cell lung cancer (NSCLC) is still uncertain. METHODS: Surgically-resected samples of 681 NSCLC cases were stained by multiplex immunofluorescence to examine macrophage phenotypes as well as the expression levels of program death-ligand 1 (PD-L1) on them in both tumor nest and tumor stroma, including pan-macrophage (CD68+), M1 (CD68+CD163−), and M2 macrophages (CD68+CD163+). Various other immune cell markers, including CD4, CD8, CD20, CD38, CD66B, FOXP3, and CD133, were also evaluated. Machine learning algorithm by Random Forest (RF) model was utilized to screen the robust prognostic markers and construct the CD68-based immune-related risk score (IRRS) for predicting disease-free survival (DFS). RESULTS: The expression levels of CD68 were moderately correlated with the levels of PD-L1 (P
Databáze: OpenAIRE
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