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A novel neutrophil extracellular traps-related lncRNA signature predicts prognosis in patients with early-stage lung adenocarcinoma

Authors :
Huan Wang
Yueli Shi
Xia Xu
Shumin Xu
Yuting Shi
Weiyu Chen
Kai Wang
Source :
Annals of Medicine, Vol 55, Iss 2 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

AbstractBackground Neutrophil extracellular traps (NETs) could entrap tumour cells and promote their dissemination and metastasis. Further analysis of NETs-related molecules is expected to provide a new strategy for prognosis prediction and treatment of lung adenocarcinoma (LUAD) patients.Methods The model construction was established through co-expression analysis, Lasso Cox regression, univariate and multivariate COX regression, Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway. The potential drugs and analysed drug sensitivity were screened by pRRophetic packages.Results In this study, we constructed a 15 NETs-related long non-coding RNAs (lncRNAs) prognostic prediction model (AC091057.1, SPART-AS1, AC023796.2, AL031600.2, AC084781.1, AC032011.1, FAM66C, C026355.2, AL096870.2, AC092718.5, PELATON, AC008635.1, AL162632.3, AC087501.4 and AC123768.3) for patients with early-stage LUAD based on public databases and datasets. The signature is associated with immune cell functions, tumour mutation burden and treatment sensitivity in LUAD patients. Additionally, we found that FAM66C is highly expressed in lung cancer patients for the first time, which is associated with poor prognosis. FAM66C knockdown significantly inhibited the proliferation and migration ability of the tumour cells.Conclusions In conclusion, this model is a new and effective prognostic and efficacy predictive biomarker, FAM66C plays an oncogene role in the process of LUAD development. It may provide a new theoretical basis for the clinical diagnosis and treatment in LUAD patients in early stage.

Details

Language :
English
ISSN :
07853890 and 13652060
Volume :
55
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Annals of Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.568e5ed090124bf883daedf8c8510b08
Document Type :
article
Full Text :
https://doi.org/10.1080/07853890.2023.2279754