Combined screening analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

Cao, Jingjie; Zhang, Ruiqiang; Zhang, Ye; Wang, Yijun

doi:10.21037/jgo-21-866

Cited by 4 publications

(2 citation statements)

References 41 publications

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“…This study emphasizes another possible pathway involved in KIF11 in HCC [ 43 ]. Lastly, Cao and coworkers found that KIF11 overexpression in HCC could also be related to epigenetic modifications, such as DNA methylation; in fact, among the genes exhibiting hypomethylation KIF11 is included, confirming once again the strong relationship between Eg5 expression and HCC and shedding light on another possible mechanism able to explain this correlation [ 42 ].…”

Section: Eg5 In Tumor Onset and Progressionmentioning

confidence: 94%

Eg5 and Diseases: From the Well‐Known Role in Cancer to the Less‐Known Activity in Noncancerous Pathological Conditions

Ricci,

Carradori,

Cataldi

et al. 2024

Biochemistry Research International

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Eg5 is a protein encoded by KIF11 gene and is primarily involved in correct mitotic cell division. It is also involved in nonmitotic processes such as polypeptide synthesis, protein transport, and angiogenesis. The scientific literature sheds light on the ubiquitous functions of KIF11 and its involvement in the onset and progression of different pathologies. This review focuses attention on two main points: (1) the correlation between Eg5 and cancer and (2) the involvement of Eg5 in noncancerous conditions. Regarding the first point, several tumors revealed an overexpression of this kinesin, thus pushing to look for new Eg5 inhibitors for clinical practice. In addition, the evaluation of Eg5 expression represents a crucial step, as its overexpression could predict a poor prognosis for cancer patients. Referring to the second point, in specific pathological conditions, the reduced activity of Eg5 can be one of the causes of pathological onset. This is the case of Alzheimer’s disease (AD), in which Aβ and Tau work as Eg5 inhibitors, or in acquired immune deficiency syndrome (AIDS), in which Tat‐mediated Eg5 determines the loss of CD4+ T‐lymphocytes. Reduced Eg5 activity, due to mutations of KIF11 gene, is also responsible for pathological conditions such as microcephaly with or without chorioretinopathy, lymphedema, or intellectual disability (MCLRI) and familial exudative vitreous retinopathy (FEVR). In conclusion, this review highlights the double impact that overexpression or loss of function of Eg5 could have in the onset and progression of different pathological situations. This emphasizes, on one hand, a possible role of Eg5 as a potential biomarker and new target in cancer and, on the other hand, the promotion of Eg5 expression/activity as a new therapeutic strategy in different noncancerous diseases.

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Section: Eg5 In Tumor Onset and Progressionmentioning

confidence: 94%

Eg5 and Diseases: From the Well‐Known Role in Cancer to the Less‐Known Activity in Noncancerous Pathological Conditions

Ricci,

Carradori,

Cataldi

et al. 2024

Biochemistry Research International

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show abstract

“…Top five items were selected. et al30 , 13 from Jiang et al31 , 20 from Zhang et al32 , 12 from Wu et al33 , 5 from Nguyen et al34 , 15 from Zhou et al35 , 6 from Yu et al36 , 10 from Kakar et al37 , 10 from Ji et al38 , 11 from Chen et al39 , 10 from Qiang et al40 , 10 from Wang et al41 , 10 from Zhang et al42 , 14 from Kim et al43 , 10 from Zhang et al44 , 14 from Sha et al45 , 10 from Chen et al46 , 4 from He et al47 , 10 from Zhang et al48 , 4 from Hu et al49 , 9 from Zhang et al50 , 15 from Li et al51 , 5 from Cao et al52 , 7 from Yang et al53 , 5 from Wang et al54 , 9 from Jiang et al55 , 16 from Li et al56 , 15 from Xing et al…”

mentioning

confidence: 99%

Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning

Hasan

Maniruzzaman

Shin

2023

Sci Rep

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Hepatocellular carcinoma (HCC) is the most common lethal malignancy of the liver worldwide. Thus, it is important to dig the key genes for uncovering the molecular mechanisms and to improve diagnostic and therapeutic options for HCC. This study aimed to encompass a set of statistical and machine learning computational approaches for identifying the key candidate genes for HCC. Three microarray datasets were used in this work, which were downloaded from the Gene Expression Omnibus Database. At first, normalization and differentially expressed genes (DEGs) identification were performed using limma for each dataset. Then, support vector machine (SVM) was implemented to determine the differentially expressed discriminative genes (DEDGs) from DEGs of each dataset and select overlapping DEDGs genes among identified three sets of DEDGs. Enrichment analysis was performed on common DEDGs using DAVID. A protein-protein interaction (PPI) network was constructed using STRING and the central hub genes were identified depending on the degree, maximum neighborhood component (MNC), maximal clique centrality (MCC), centralities of closeness, and betweenness criteria using CytoHubba. Simultaneously, significant modules were selected using MCODE scores and identified their associated genes from the PPI networks. Moreover, metadata were created by listing all hub genes from previous studies and identified significant meta-hub genes whose occurrence frequency was greater than 3 among previous studies. Finally, six key candidate genes (TOP2A, CDC20, ASPM, PRC1, NUSAP1, and UBE2C) were determined by intersecting shared genes among central hub genes, hub module genes, and significant meta-hub genes. Two independent test datasets (GSE76427 and TCGA-LIHC) were utilized to validate these key candidate genes using the area under the curve. Moreover, the prognostic potential of these six key candidate genes was also evaluated on the TCGA-LIHC cohort using survival analysis.

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The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

Zhao,

Li,

Feng

et al. 2024

Biomark Res

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As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

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Combined screening analysis of aberrantly methylated-differentially expressed genes and pathways in hepatocellular carcinoma

Cited by 4 publications

References 41 publications

Eg5 and Diseases: From the Well‐Known Role in Cancer to the Less‐Known Activity in Noncancerous Pathological Conditions

Eg5 and Diseases: From the Well‐Known Role in Cancer to the Less‐Known Activity in Noncancerous Pathological Conditions

Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

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