Targeting dual specificity protein kinase TTK attenuates tumorigenesis of glioblastoma

Wang, Jia; Xie, Yuchen; Bai, Xia; Wang, Ning; Deng, Zhong; Lian, Minxue; Yu, Shuo; Líu, Hao; Xie, Wei; Wang, Maode

doi:10.18632/oncotarget.23152

Cited by 42 publications

(57 citation statements)

References 28 publications

(35 reference statements)

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“…In glioma stem-like cells (GSCs), the MTFR2-dependent regulation of TTK was validated for a crucial role in maintaining GSCs in gliomas [44]. High expression of MCM2 in clinical samples was reported with CSC marker-positive breast cancer cells, and the MCM2-targeted therapeutic strategy, together with Hph-1-gp70 treatment to induce DNA damage, were regarded as a potential therapy for the eradication of stem-like cells from breast cancer tissue [45].…”

Section: Discussionmentioning

confidence: 99%

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Zhang

Tseng

Lien

et al. 2020

Genes

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Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

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Section: Discussionmentioning

confidence: 99%

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Zhang

Tseng

Lien

et al. 2020

Genes

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“…TTK has been identified as one of the promising candidates for vaccination in esophageal cancer patients with advanced stage disease 33,34 . Role of TTK in survival of cancer cells and cytotoxicity of its inhibitors has also been demonstrated in hepatocellular carcinoma 35 and glioblastoma 36 .…”

Section: Discussionmentioning

confidence: 95%

Integrated genomics and comprehensive validation reveal novel drivers of genomic evolution in esophageal adenocarcinoma

Kumar

Buon

Talluri

et al. 2020

Preprint

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Identification of genes driving genomic evolution can provide novel targets for cancer treatment and prevention. Here we show identification of a genomic instability gene signature, using an integrated genomics approach. Elevated expression of this signature correlated with poor survival in esophageal adenocarcinoma (EAC) as well as three other human cancers. Knockout and overexpression screens confirmed the relevance of this signature to genomic instability. Indepth evaluation of TTK (a kinase), TPX2 (spindle assembly factor) and RAD54B (recombination protein) further confirmed their role in genomic instability and tumor growth. Mutational signatures identified by whole genome sequencing and functional studies demonstrated that DNA damage and homologous recombination were common mechanisms of genomic instability induced by these genes. Consistently, a TTK inhibitor impaired EAC cell growth in vivo, and increased chemotherapy-induced cytotoxicity while inhibiting genomic instability in surviving cells. Thus inhibitors of TTK and other genes identified in this study have potential to inhibit/delay genomic evolution and tumor growth. Such inhibitors also have potential to increase chemotherapy-induced cytotoxicity while reducing its harmful genomic impact in EAC and possibly other cancers.

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“…e proteins encoded by genes BUB1, BUB1B, and TTK have the ability to phosphorylate serine and threonine residues in the substrates [14], while TTK can also phosphorylate tyrosine residues, acting on checkpoints during cell mitosis [15]. It has been found that numerous tumors, such as glioblastoma [16,17] and gastric adenocarcinoma [18], harbor expression changes in BUB1, BUB1B, and TTK as well as checkpoint dysfunction. Moreover, BUB1, BUB1B, and TTK were shown to be associated with malignant behaviors such as PCPG metastasis in TCGAbased studies [19,20].…”

Section: Discussionmentioning

confidence: 99%

Identification of Genes Associated with the Metastasis of Pheochromocytoma/Paraganglioma Based on Weighted Gene Coexpression Network Analysis

Ding

Zhang

et al. 2020

BioMed Research International

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Background. Pheochromocytoma/paraganglioma (PCPG) is a benign neuroendocrine neoplasm in most cases, but metastasis and other malignant behaviors can be observed in this tumor. The aim of this study was to identify genes associated with the metastasis of PCPG. Methods. The Cancer Genome Atlas (TCGA) expression profile data and clinical information were downloaded from the cbioportal, and the weighted gene coexpression network analysis (WGCNA) was conducted. The gene coexpression modules were extracted from the network through the WGCNA package of R software. We further extracted metastasis-related modules of PCPG. Enrichment analysis of Biological Process of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes was carried out for important modules, and survival analysis of hub genes in the modules was performed. Results. A total of 168 PCPG samples were included in this study. The weighted gene coexpression network was constructed with 5125 genes of the top 25% variance among the 20501 genes obtained from the database. We identified 11 coexpression modules, among which the salmon module was associated with the age of PCPG patients at diagnosis, metastasis, and malignancy of the tumors. Conclusion. WGCNA was performed to identify the gene coexpression modules and hub genes in the metastasis-related gene module of PCPG. The findings in this study provide a new clue for further study of the mechanisms underlying the PCPG metastasis.

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Targeting dual specificity protein kinase TTK attenuates tumorigenesis of glioblastoma

Cited by 42 publications

References 28 publications

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Integrated genomics and comprehensive validation reveal novel drivers of genomic evolution in esophageal adenocarcinoma

Identification of Genes Associated with the Metastasis of Pheochromocytoma/Paraganglioma Based on Weighted Gene Coexpression Network Analysis

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