Ncapg Is A Prognostic Biomarker of Immune Infiltration in Non-Small-Cell Lung Cancer

Abstract

Purpose: Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related deaths. The protein NCAPG plays a significant role in tumor development. Patients & methods: We set up a tissue microarray (containing 140 NSCLC and ten normal lung tissues) and performed immunohistochemistry to assess NCAPG expression in the tissues of 140 patients. The prognostic value of NCAPG in NSCLC was assessed using the univariate and multivariate Cox proportional hazards regression models and Kaplan–Meier plots. We analyzed the association between NCAPG and immune infiltration in NSCLC. Results: Multifactorial analysis and Kaplan–Meier plots revealed that upregulation of NCAPG expression was an independent factor in the prognosis of NSCLC. Data from CIBERSORT showed a negative correlation between NCAPG and the expression of memory CD4⁺ T cells, CD8⁺ T cells, dendritic cells, macrophages, mast cells and natural killer cells (p < 0.001). Gene set enrichment analysis revealed that cell cycle, adhesion and proliferation were significantly enriched in samples with a high NCAPG expression. Conclusion:NCAPG is a novel biomarker of prognosis and is associated with immune cell infiltration in the tumor microenvironment. Thus it may be a potential target in NSCLC treatment.

Keywords:

• immune infiltration
• NCAPG
• NSCLC
• prognostic biomarkers

Author contributions

This subject and manuscript were designed and written by Y Zhou and Y Fan. Y Zhou completed the experiment. M Lou analyzed data compilation. X Liu and M Yifeng were responsible for the literature search to improve the project, and revised the manuscript. T Jichun and Y Kai were responsible for administrative, technical or material support (building a database). All authors reviewed the manuscript and approved the manuscript for publication.

Acknowledgements

The authors acknowledge the TCGA, GEO, TIMER and CIBERSORT databases for free use.

Financial & competing interests disclosure

The following funds support this work: 333 Project of Jiangsu Province (grant no. BRA2020157); Six One Project, Research Projects of High-level Medical Personnel of Jiangsu Province (grant no. LGY2019025); High-level Talent Selection and Training Project of the 16th Batch of Six Talent Peak in Jiangsu Province (grant no. WSN-245); Medical Scientific Research Foundation of Jiangsu Commission of Health (grant no. H2018083); Jiangsu Provincial Medical Youth Talent (Jiangsu Health Scientific Education 2017 no. 3); 333 High-Level Talent Training Project (grant no. 2016, III-0719); High-Level Medical Talents Training Project (grant no. 2016CZBJ042). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that they have obtained appropriate institutional review board approval or have followed the principles outlined in the Declaration of Helsinki for all human or animal experimental investigations. In addition, for investigations involving human subjects, informed consent has been obtained from the participants involved. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research. All patients or their family members provided written informed consent.

Availability of data & materials

The authors obtained a tissue microarray (HlugC120PT01) from Superbiotek (Shanghai, China), which consisted of 140 non-small-cell lung cancer tissue samples and ten normal lung tissues. All patients had undergone lung cancer resection in 2005. We had access to complete clinical information from all patients (112 men and 28 women).

The data that support the findings of this study are openly available in The Cancer Genome Atlas data portal (https://tcga-data.nci.nih.gov/tcga/), Gene Expression Profiling Interactive Analysis (GEPIA) (http://gepia.cancer-pku.cn/index.html) and the Tumor Immune Estimation Resource (TIMER) database (https://cistrome.shinyapps.io/timer/). The rest of the data are available from the corresponding author on reasonable request.