ArticleMedical principles and practice : international journal of the Kuwait University, Health Science Centre2023
Bioinformatics Analysis and Screening of Potential Target Genes Related to the Lung Cancer Prognosis.
Article in Medical principles and practice : international journal of the Kuwait University, Health Science Centre, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Identification of cellular senescence-associated genes for predicting the diagnosis, prognosis and immunotherapy response in lung adenocarcinoma via a 113-combination machine learning framework.Discover oncology · 2025Article
- Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.Scientific reports · 2025Article
- Research progress of kinesin family in neurological diseases.Frontiers in cellular neuroscience · 2025Review
- Multifaceted bioinformatic analysis of m6A-related ferroptosis and its link with gene signatures and tumour-infiltrating immune cells in gliomas.Journal of cellular and molecular medicine · 2024Article
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
Corrections and comments
- Retracted
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveSeveral genes have been validated as molecular targets for gene therapy in lung cancer. We screened target genes that affect survival of patients with lung cancer.
methodsData on gene expression in normal lung tissues/lung adenocarcinoma (LUAD) samples were acquired from Genotype-Tissue Expression (GTEx)/The Cancer Genome Atlas (TCGA) databases and merged to expand the sample size, followed by differential analysis of the merged expression data and acquisition of differentially expressed genes. Survival and simple Cox analyses were used to screen for genes affecting LUAD survival. Protein-protein interaction/multivariable Cox analyses were utilized, and a risk model was established. Candidate genes expression levels in cancer/paracancerous tissues of lung cancer patients, and BEAS-2B/A549/HCC95 cells were measured by RT-qPCR/Western blot. Survival analysis of candidate genes was conducted in LUAD samples collected from TCGA.
resultsAmong 947 genes differentially expressed in LUAD, 151 were correlated with patient survival, and 116 might act as risk factors for LUAD. The 7 identified candidate genes (TOP2A, TK1, KIF4A, ANLN, KIF2C, ASF1B, CCNB1) were high-risk genes playing possible roles in LUAD. These genes were differentially expressed in lung cancer and were associated with TNM stages (III - IV)/differentiation grade/lymph node metastasis/distant metastasis, which affected lung cancer patient survival.
conclusionP2A, TK1, KIF4A, ANLN, KIF2C, ASF1B and CCNB1 were highly-expressed in LUAD/lung squamous cell carcinoma (LUSC) and correlated with LUAD patient survival. This study contributes to better understanding of the prognostic regulation mechanism in LUAD and the screening of target genes for clinical treatment.
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Registered trials
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