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Frontiers in Medical Science Research, 2022, 4(5); doi: 10.25236/FMSR.2022.040501.

Lung Adenocarcinoma Subtyping and Feature Identification Based on Multi-omics Data Analysis


Wenzong Lu, Hang Ma

Corresponding Author:
​Wenzong Lu

Department of Biomedical Engineering, College of Electronic and Information Engineering, Xi’an Technological University, Xi’an, Shaanxi Province, 710021, China.


Lung cancer is one of the cancers that seriously threaten human life, especially lung adenocarcinoma. Although various diagnostic and therapeutic methods continue to appear, the clinical outcomes are still gloomy. The gene coding and non-coding ribonucleic acid data of lung adenocarcinoma was analyzed by using the non-negative matrix factorization clustering, differential expression and survival analysis. Functional and pathway enrichment analysis was performed for each subtype. The computed tomography imaging features of lung adenocarcinoma were extracted and associated with weighted gene co-expression network analysis. All patients with lung adenocarcinoma could be significantly classified into three subtypes according to gene expression feature. The differential expressed genes were significantly enriched in biological processes including lung development, morphogenesis of an epithelium, receptor-mediated endocytosis for subtype 1, subtype 2, subtype 3, respectively. The number of special molecules is 340, 71, 109 for subtype 1, subtype 2, subtype 3, respectively. Some of them such as neuroendocrine convertase 1 for subtype 3, has_mir_10b for subtype 2, parathyroid hormone-related protein for subtype 1 and so on, were strongly associated with the integrate density feature in region of interest of computed tomography imaging. Subtypes of patients with lung adenocarcinoma could be accurately stratified by investigating the multi-omics data features, and several computed tomography imaging features are closely associated with the special molecules of each subtype, which is useful for selecting diagnosis and therapeutic methods.


Multi-omics; Lung cancer; Molecular subtype; Weighted gene co-expression network analysis

Cite This Paper

Wenzong Lu, Hang Ma. Lung Adenocarcinoma Subtyping and Feature Identification Based on Multi-omics Data Analysis. Frontiers in Medical Science Research (2022) Vol. 4, Issue 5: 1-9. https://doi.org/10.25236/FMSR.2022.040501.


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