ArticleOncology letters2024
Integrated analysis and validation reveal CYTH4 as a potential prognostic biomarker in acute myeloid leukemia.
Article in Oncology letters, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 4 citations in OpenAlex.
- Human biomarker navigator.iMeta · 2026Review
- CYTH4 Facilitates Renal Cell Carcinoma via Enhancing Proliferation and Likely Immune Evasion.Biomolecules · 2026Article
- MICA and CYTH4 as immunological biomarkers of intracranial aneurysm: a study integrating RNA sequencing, single-cell sequencing and Mendelian randomization.Functional & integrative genomics · 2026Article
- Cytohesin-4/ARF6 facilitates the progression of acute myeloid leukemia through activating PIK3R5/PI3K/AKT pathway.iScience · 2025Article
- Identification of Mitochondrial Unfolded Protein Response-Related Genes and Diagnostic Biomarkers in Atherosclerosis by Integrative Multidimensional Analysis and Experimental Validation.Journal of inflammation research · 2025Article
- Targeting guanine nucleotide exchange factors for novel cancer drug discovery.Expert opinion on drug discovery · 2024Review
- Targeting cytohesin-1 suppresses acute myeloid leukemia progression and overcomes resistance to ABT-199.Acta pharmacologica Sinica · 2024Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acute myeloid leukemia (AML) is a clonal hematological malignancy with high mortality rates. The identification of novel markers is urgent for AML. Cytohesins are a subfamily of guanine nucleotide exchange factors activating the ADP-ribosylation factor family GTPases. While the important roles of cytohesins have been reported in various cancers, their function in AML remains unclear. The present study aimed to explore the prognostic impact of cytohesin-4 (CYTH4) and the underlying molecular functions. RNA sequencing and AML clinical data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases to investigate gene expression and survival. Using the R software, differentially expressed genes were identified between the high- and the low-CYTH4 group. Functional enrichment analysis was conducted by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analyses. The CIBERSORTx tool was used to explore the proportions of different immune cell types. The molecular function of CYTH4 was also validated
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