肿瘤微环境
肺癌
生物
肿瘤科
比例危险模型
PDGFB公司
内科学
癌症
免疫疗法
癌症研究
医学
受体
血小板源性生长因子受体
生长因子
作者
Qingyu Sun,Yang Zhou,Lijuan Du,Mengke Zhang,Jiale Wang,Yuanyuan Ren,Fang Liu
出处
期刊:PubMed
[National Institutes of Health]
日期:2023-08-20
卷期号:45 (8): 684-699
被引量:3
标识
DOI:10.16288/j.yczz.23-077
摘要
Non-small cell lung cancer (NSCLC) is a highly morbid and fatal disease that exhibits individualized differences in prognosis and drug efficacy. Therefore, understanding the molecular mechanism of the occurrence and progression of lung cancer can improve early diagnosis, treatment and prognosis. Macrophages are a crucial component of the tumor microenvironment (TME) due to their high plasticity and heterogeneity. They play a multifaceted role in tumor initiation and progression. In order to elucidate the pathogenesis of tumor-associated macrophages (TAMs) related genes in NSCLC, transcriptomic sequencing, univariate COX regression, LASSO regression and multivariate COX regression analyses were conducted to identify the 11 genes that have the most significant association with prognosis. These genes include FCRLA, LDHA, LMOD3, MAP3K8, NT5E, PDGFB, S100P, SFXN1, TDRD1, TFAP2A and TUBB6. The risk score (RS) was computed, and all samples were split into high- and low-risk groups based on the median RS. The correlation of RS and 11 genes with macrophages was verified by the CIBERSORT deconvolution algorithm. These above results suggest that the risk score developed in this study can be utilized for predicting patients' prognosis and evaluating their immune infiltration status. This study can serve as a guide for subsequent tumor immunotherapy and gene targeting therapy.
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