ArticleInternational journal of molecular sciences2020
Identification of Key Genes Related to Lung Squamous Cell Carcinoma Using Bioinformatics Analysis.
Article in International journal of molecular sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed, 68 citations in OpenAlex.
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- First Report of Entrectinib as a Treatment Option for Pure Squamous Cell Carcinoma HarboringInternational journal of molecular sciences · 2025Article
- Analysis and exploration of regulatory mechanisms and potential prognostic biomarkers in squamous cell carcinoma of the lung by expression profiling.Translational cancer research · 2025Article
- Network pharmacology-based approach to research the effects and mechanisms ofFrontiers in medicine · 2025Article
- Identification of potential diagnostic targets and therapeutic strategies for anoikis-related biomarkers in lung squamous cell carcinoma using machine learning and computational virtual screening.Frontiers in pharmacology · 2025Article
- Identification and validation of a novel prognostic signature and key genes related to development of anaplastic thyroid carcinoma.Discover oncology · 2024Article
- A new method for network bioinformatics identifies novel drug targets for mucinous ovarian carcinoma.NAR genomics and bioinformatics · 2024Article
- Identification of a prognostic gene signature in patients with cisplatin resistant squamous cell lung cancer.Journal of thoracic disease · 2024Article
- Unveiling the Future of Oncology and Precision Medicine through Data Science.International journal of molecular sciences · 2024Article
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- Exploring potential key genes and pathways associatedwith hepatocellular carcinoma prognosis through bioinformatics analysis, followed by experimental validation.American journal of translational research · 2024Article
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- The application of Raman spectroscopy for the diagnosis and monitoring of lung tumors.Frontiers in bioengineering and biotechnology · 2024Review
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- Exploring tumor-normal cross-talk with TranNet: Role of the environment in tumor progression.PLoS computational biology · 2023Article
- Downregulation of microRNA‑494 inhibits cell proliferation in lung squamous cell carcinoma via the induction of PUMA‑α‑mediated apoptosis.Experimental and therapeutic medicine · 2023Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty-seven up-regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.