Abstract
Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and regulators playing a potential role in LUAD progression have not been fully elucidated yet. Based on data from The Cancer Genome Atlas database, 2837 differentially expressed genes, 741 DE-regulators were screened by comparing cancer tissues with paracancerous tissues. Then, 651 hub driving genes were selected by the topological relation of the protein–protein interaction network. Also, the target genes of DE-regulators were identified. Moreover, a key gene set containing 65 genes was obtained from the hub driving genes and target genes intersection. Subsequently, 183 hub regulators were selected based on the analysis of node degree in the ceRNA network. Next, a comprehensive analysis of the subgroups and Wnt, mTOR, and MAPK signaling pathways was conducted to understand enrichment of the subgroups. Survival analysis and a receiver operating characteristic curve analysis were further used to screen for the key genes and regulators. Furthermore, we verified key molecules based on external database, LRRK2, PECAM1, EPAS1, LDB2, and HOXA11-AS showed good results. LRRK2 was further identified as promising biomarker associated with CNV alteration and various immune cells’ infiltration levels in LUAD. Overall, the present study provided a novel perspective and insight into hub driving genes and regulators in LUAD, suggesting that the identified signature could serve as an independent prognostic biomarker.
Highlights
In both sexes, lung cancer is one of the most common malignancies and the first leading cause of cancer-related death worldwide [1]
CircRNAs are regarded as a potential molecular marker that may serve in the diagnosis and treatment of the disease, as it License 4.0 (CC BY)
We focused on combining the protein–protein interaction (PPI) network and the subgroup analysis based on the competing endogenous RNA (ceRNA) network to explore the regulatory relationship between hub genes and regulators
Summary
Lung cancer is one of the most common malignancies and the first leading cause of cancer-related death worldwide [1]. Despite advances in cancer therapy, the 5-year survival rate of lung cancer is only 19% [2]. 70% of lung cancer patients have locally advanced or metastatic disease at the time of diagnosis, which leaves a small window for early detection or treatment [3]. It is necessary to identify molecular markers associated with patient survival that may contribute to the development of gene-targeted therapeutic approaches. LncRNAs are non-coding RNAs ranging in length from 200 nucleotides to 100 kb, which hold substantial promise as novel biomarkers and therapeutic targets for cancer [4]. CircRNAs are regarded as a potential molecular marker that may serve in the diagnosis and treatment of the disease, as it License 4.0 (CC BY)
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