Adenylate kinase 2 is a biomarker related to the prognosis of glioma and the immune microenvironment

Liu, Zhichen; Tang, Chunjiao; Xu, Teng; Mohamed, Zakaria Ahmed; Fan, Jingyi

doi:10.1002/jcla.24892

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…Gliomas with higher expression of AK2 had a worse prognosis. Experimental downregulation of AK2 in vitro in glioma tissue cultures reduced cell proliferation, migration, and colony formation [56].…”

Section: Uniprotmentioning

confidence: 93%

Characterization of vestibular schwannoma tissues using liquid chromatography‐tandem mass spectrometry analysis of specific peptide fragments separated by in‐sample tryptic protein digestion followed by mathematical analysis

Tesařová,

Boušková,

Cejnar

et al. 2023

J of Separation Science

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Vestibular schwannoma is the most common benign neoplasm of the cerebellopontine angle. Its first symptoms include hearing loss, tinnitus, and vestibular symptoms, followed by cerebellar and brainstem symptoms, along with palsy of the adjacent cranial nerves. However, the clinical picture has unpredictable dynamics and currently, there are no reliable predictors of tumor behavior. Hence, it is desirable to have a fast routine method for analysis of vestibular schwannoma tissues at the molecular level. The major objective of this study was to verify whether a technique using in‐sample specific protein digestion with trypsin would have the potential to provide a proteomic characterization of these pathological tissues. The achieved results showed that the use of this approach with subsequent liquid chromatography‐tandem mass spectrometry (LC‐MS/MS) analysis of released peptides allowed a fast identification of a considerable number of proteins in two differential parts of vestibular schwannoma tissue as well as in tissues of control healthy samples. Furthermore, mathematical analysis of MS data was able to discriminate between pathological vestibular schwannoma tissues and healthy tissues. Thus, in‐sample protein digestion combined with LC‐MS/MS separation and identification of released specific peptides followed by mathematical analysis appears to have the potential for routine characterization of vestibular schwannomas at the molecular level. Data are available via ProteomeXchange with identifier PXD045261.

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Section: Uniprotmentioning

confidence: 93%

Characterization of vestibular schwannoma tissues using liquid chromatography‐tandem mass spectrometry analysis of specific peptide fragments separated by in‐sample tryptic protein digestion followed by mathematical analysis

Tesařová,

Boušková,

Cejnar

et al. 2023

J of Separation Science

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“…AK2 encodes adenosine kinase 2, an enzyme that plays an important role in cells and is mainly involved in cellular energy metabolism and signal transduction. [17] At present, the direct link between AK2 and asthma has not been clarified. However, we can make some possible inferences.…”

Section: Disscussmentioning

confidence: 99%

Identification of biomarkers associated with pediatric asthma using machine learning algorithms: A review

Lin,

Wang,

et al. 2023

Medicine

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Pediatric asthma is a complex disease with a multifactorial etiology. The identification of biomarkers associated with pediatric asthma can provide insights into the pathogenesis of the disease and aid in the development of novel diagnostic and therapeutic strategies. This study aimed to identify potential biomarkers for pediatric asthma using Weighted Gene Co-expression Network Analysis (WGCNA) and machine learning algorithms. We obtained gene expression data from publicly available databases and performed WGCNA to identify gene co-expression modules associated with pediatric asthma. We then used machine learning algorithms, including random forest, lasso regression algorithm, and support vector machine-recursive feature elimination, to classify asthma cases and controls based on the identified gene modules. We also performed functional enrichment analyses to investigate the biological functions of the identified genes.We detected 24,544 genes exhibiting differential expression between controlled and uncontrolled genes from the GSE135192 dataset. In the combined WCGNA analysis, a total of 104 co-expression genes were screened, both controlled and uncontrolled. After screening, 11 hub genes were identified. They were AK2, PDK4, PER3, GZMH, NUMBL, NRL, SCO2, CREBZF, LARP1B, RXFP1, and VDAC3P1. The areas under their receiver operating characteristic curve were above 0.78. Our study identified potential biomarkers for pediatric asthma using WGCNA and machine learning algorithms. Our findings suggest that 11 hub genes could be used as novel diagnostic markers and treatment targets for pediatric asthma. These findings provide new insights into the pathogenesis of pediatric asthma and may aid in the development of novel diagnostic and therapeutic strategies.

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