• Huan Wang, Yueli Shi, Xia Xu, Shumin Xu, Yuting Shi, Weiyu Chen, and Kai Wang.
• Department of Respiratory and Critical Care Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, China.
• Ann. Med. 2023 Jan 1; 55 (2): 22797542279754.

BackgroundNeutrophil 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.MethodsThe 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.ResultsIn 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.ConclusionsIn 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.

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