ArticleCancer biomarkers : section A of Disease markers2020
Transcriptome analysis reveals key signature genes involved in the oncogenesis of lung cancer.
Article in Cancer biomarkers : section A of Disease markers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker.Critical reviews in clinical laboratory sciences · 2024Pooled it
- Cyclovirobuxine D inhibits growth and progression of non‑small cell lung cancer cells by suppressing the KIF11‑CDC25C‑CDK1‑CyclinB1 GInternational journal of oncology · 2023Article
- A five-gene expression signature of centromeric proteins with prognostic value in lung adenocarcinoma.Translational cancer research · 2023Article
- Identification of cancer risk assessment signature in patients with chronic obstructive pulmonary disease and exploration of the potential key genes.Annals of medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer.
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