Analysis of Nucleoporin 107 Overexpression and Its Association with Prognosis and Immune Infiltration in Lung Adenocarcinoma by Bioinformatics Methods.

Abstract

Background:

Lung adenocarcinoma (LUAD) has high morbidity and mortality. Current studies indicate nucleoporin 107 (NUP107) is involved in the construction of nuclear pore complex, and NUP107 overexpression contributes to the growth and development in most types of cancers, but its effect in LUAD has not been elucidated.

Methods:

Differences in NUP107 expression were investigated using the Cancer Genome Atlas (TCGA) and multiple Gene Expression Omnibus (GEO) data sets. Enrichment analysis were implemented to probe the NUP107 function. The association of NUP107 with the degree of immune cell infiltration was investigated by the TIMER database, single-sample gene set enrichment analysis (ssGSEA), and ESTIMATE. The association of NUP107 expression with tumor mutation burden (TMB), TP53, and immune checkpoint was analyzed. Single-cell RNA sequencing data were used to detect NUP107 expression in different cell clusters. Finally, we performed real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) to prove the difference of NUP107 expression.

Results:

NUP107 was overexpressed in LUAD and mainly expressed in cancer stem cell (CSC). Overexpression of NUP107 in LUAD suggested a poorer prognosis. Functional enrichment analysis pointed out that NUP107 was mainly linked to the regulation of cell cycle. Both immune cell infiltration and TMB were found to be in connection with NUP107. Cases in the group with high NUP107 expression had poorer immune infiltration, but had higher expression of immune checkpoints, TMB, and proportion of TP53 mutations.

Conclusion:

NUP107 is a sensitive diagnostic and prognostic factor for LUAD and may be involved in tumor progression through its effects on cell cycle and immune infiltration.

• Authors: Zi-Hao Li, Jia-Yi Li, Yong-Jie Zhu, Lei Dai, Zuo-Tao Wu, Ju-Sen Nong, Ting Zhuo, Fu-Li Li, Ling-Yun He, Hong-Hua Liang, Feng-Ling Zang, Yong-Yong Wang, Ming-Wu Chen, Wei-Jia Huang, Jian-Bin Cao
• Journal: International journal of general medicine (Int J Gen Med) Vol. 16 Pg. 5449-5465 ( 2023) ISSN: 1178-7074 [Print] New Zealand
• PMID: 38021066 (Publication Type: Journal Article)
• Copyright: © 2023 Li et al.