A novel basement membrane-related gene signature for prognosis of lung adenocarcinomas

被引:28
|
作者
Zhang, Zhenxing [2 ]
Zhu, Haoran [3 ]
Wang, Xiaojun [1 ]
Lin, Shanan [1 ]
Ruan, Chenjin [1 ]
Wang, Qiang [1 ,4 ]
机构
[1] Taizhou Univ Hosp, Taizhou Cent Hosp, Dept Thorac Surg, Taizhou, Zhejiang Provin, Peoples R China
[2] Taizhou Univ Hosp, Taizhou Cent Hosp, Dept Thorac & Maxillofacial Surg B7X, Taizhou, Zhejiang Provin, Peoples R China
[3] Xi An Jiao Tong Univ, Hlth Sci Ctr, Xian, Shaanxi Provinc, Peoples R China
[4] Taizhou Univ Hosp, Taizhou Cent Hosp, Dept thorac Surg, 999 Donghai Ave, Taizhou 318000, Zhejiang Provin, Peoples R China
关键词
Lung adenocarcinoma; Basement membrane; Tumor microenvironment; Immune therapy; NELL2; T cell; CANCER; EXPRESSION; BIOLOGY; NELL2;
D O I
10.1016/j.compbiomed.2023.106597
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: Lung adenocarcinoma (LUAD) remains a global health concern with its poor prognosis and high mortality. Whether tumor cells invade through the basement membrane (BM) is the key factor to determine the prognosis of LUAD. This study aimed to identify the BM-related gene signatures to improve the overall prognosis of LUAD.Materials & methods: A series of bioinformatics analyses were conducted based on TCGA and GEO datasets. Unsupervised consistent cluster analysis was performed, and 500 LUAD patients were assigned to two different groups according to expressions of 222 BM-related genes. The differentially expressed genes (DEGs) between the two clusters were identified, and Lasso regression, ROC curve, univariate and multivariate Cox regression ana-lyses and enrichment analysis were conducted. Besides, ssGSEA, CIBERSORT and ESTIMATE algorithmwere were employed to understand the relationship between the tumor microenvironment (TME) and risk scores. Moreover, single cell clustering and trajectory analyses were performed to further understand the significance of BM-related genes. Finally, qRT-PCR was used to verify the prognosis model. Results: A total of 31 prognostic BM-related genes were determined for LUAD, and a novel 17-mRNA prognostic model named BMsocre was successfully established to predict the overall survival of LUAD patients. The high BMscore group indicated worse prognosis. Seventeen DEGs were enriched mainly in metabolism, ECM-receptor interaction and immune response. In addition, the high-risk group showed higher TMB and lower immune score. The low-risk group had a better immunotherapeutic response where immune escape was less likely. The BMscore model was verified in our patient cohort. Furthermore, NELL2 was mainly expressed in clusters of T cells, and was identified to play a critical role in T-cell differentiation. Conclusions: A novel BMscore model was successfully established and might be effective for providing guidance to LUAD therapy.
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页数:15
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