Identification of KIF11 as a Novel Target in Meningioma

Jungwirth, Gerhard; Tao, Yu; Moustafa, Mahmoud; Rapp, Carmen; Warta, Rolf; Jungk, Christine; Sahm, Felix; Dettling, Steffen; Zweckberger, Klaus; Lamszus, Katrin; Senft, Christian; Loehr, Mario; Keßler, Almuth F.; Ketter, Ralf; Westphal, Manfred; Debus, J.; Deimling, Andreas von; Simon, Matthias; Unterberg, Andreas; Abdollahi, Amir; Herold‐Mende, Christel

doi:10.3390/cancers11040545

Cited by 35 publications

(35 citation statements)

References 86 publications

(103 reference statements)

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“…The prognosis of patients with high level KIF-2C was worse than others [15]. It was reported that down-regulation of KIF11 decreased the proliferation of meningioma cells [16]. Accordingly, KIF11 was supposed to be the novel therapeutic target of meningioma.…”

Section: Discussionmentioning

confidence: 99%

ZNF367-induced transcriptional activation of KIF15 accelerates the progression of breast cancer

Zeng¹,

Li²,

Zhai³

et al. 2020

Int. J. Biol. Sci.

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Breast cancer (BC) is one of the most common female cancers, and its incidence has been increasing in recent years. Although treatments are continuously improving, the prognosis of patients in the advanced stage is still unsatisfactory. Thus, an in-depth understanding of its molecular mechanisms is necessary for curing breast cancer. KIF15 is a tetrameric spindle motor which can regulate mitosis in cellular process and exert the crucial functions in several cancers. The purpose of our research was to investigate the functions of KIF15 in breast cancer. We tested the expression of KIF15 in breast cancer tissues and the survival rate of breast cancer patients with high or low level of KIF15 through TCGA data. What's more, western blot and immunohistochemistry assay were utilized to evaluate the protein level and mRNA level of KIF15 in breast cancer tissues. Then CCK-8, wound healing, transwell and flow cytometry experiments were adopted separately to test cell viability, migration, invasion and cell cycle distribution. We discovered that KIF15 was highly expressed in breast cancer tissues and high level KIF15 was associated with a low survival rate of breast cancer patients. Moreover, silence of KIF15 suppressed cell viability, migration, invasion and cell cycle distribution. Following, we discovered that ZNF367 was the upstream transcription factor of KIF15. In addition, silenced ZNF367 could also repress the growth of breast cancer cells. And rescue experiments indicated that overexpressed KIF15 could counteract the inhibition effect of silencing ZNF367 on the progression of breast cancer. Importantly, we discovered that KIF15 and ZNF367 were associated with the regulation of cell cycle. In short, ZNF367-activated KIF15 accelerated the progression of breast cancer by regulating cell cycle progress.

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Section: Discussionmentioning

confidence: 99%

ZNF367-induced transcriptional activation of KIF15 accelerates the progression of breast cancer

Zeng¹,

Li²,

Zhai³

et al. 2020

Int. J. Biol. Sci.

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“…In recent years new data concerning the molecular pathological background of meningiomas have been obtained. This not only facilitates the diagnosis of meningiomas but also offers the possibility to identify new prognostic and therapeutic targets [ 6 , 7 , 8 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

Occurrence of Fibrotic Tumor Vessels in Grade I Meningiomas Is Strongly Associated with Vessel Density, Expression of VEGF, PlGF, IGFBP-3 and Tumor Recurrence

Heß

Spille

Adeli

et al. 2020

Cancers

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Angiogenesis is a key feature during oncogenesis and remains a potential target of antiangiogenic therapy. While commonly described in high-grade lesions, vascularization and its correlation with prognosis in grade I meningiomas is largely unexplored. In the histological classification, not only the number but also the composition of blood vessels seems to be important. Therefore, tumor vessel density and fibrosis were correlated with clinical and imaging variables and prognosis in 295 patients with intracranial grade I meningioma. Expression of pro-angiogenic proteins within the meningiomas was investigated by proteome analyses and further validated by immunohistochemical staining. Fibrotic tumor vessels (FTV) were detected in 48% of all tumors and strongly correlated with vessel density, but not with the histopathological tumor subtype. Occurrence of FTV was correlated with a 2-fold increased risk of recurrence in both univariate and multivariate analyses. Explorative proteome analyses revealed upregulation of VEGF (vascular endothelial growth factor), PlGF (placental growth factor), and IGFBP-3 (insulin-like growth factor-binding protein-3) in tumors displaying FTV. Immunohistochemical analyses confirmed strong correlations between tumor vessel fibrosis and expression of VEGF, PlGF, and IGFBP-3. Presence of FTV was strongly associated with disruption of the arachnoid layer on preoperative MRI in univariate and multivariate analyses. In summary, the occurrence of fibrotic tumor vessels in grade I meningiomas is strongly associated with vessel density, disruption of the arachnoid layer, expression of VEGF, PlGF, IGFBP-3 and tumor recurrence.

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“…Seven members of KIF family (KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A and KIF23) were included in the 'lightgreen' module. KIF 11 and KIF23 are the well-studies KIF family members and considered as an oncogene, inhibition of which can cause arrest at mitosis exit in hepatocellular cell carcinoma, lung cancer, pleural mesothelioma, and glioma cancer, breast cancer, meningiomas [64][65][66][67][68][69]. A phase I clinical trial on the highly selective kinesin spindle protein inhibitor, ARRY-520, has been conducted on advanced AML patients [70].…”

Section: Discussionmentioning

confidence: 99%

The Landscape of Gene Co-Expression Modules Correlating with Prognostic Genetic Abnormalities in AML

Guo

Gao

et al. 2020

Preprint

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Background: The heterogenous cytogenetic and molecular variations were harbored by AML patients, some of which are related with AML pathogenesis and clinical outcomes. We aimed to uncover the intrinsic expression profiles correlating with prognostic genetic abnormalities by WGCNA.Methods: We downloaded the clinical and expression dataset from BeatAML, TCGA and GEO database. Using R (version 4.0.2) and ‘WGCNA’ package, the co-expression modules correlating with the ELN2017 prognostic markers were identified (R2 ≥ 0.4, p < 0.01). ORA detected the enriched pathways for the key co-expression modules. The patients in TCGA cohort were randomly assigned into the training set (50%) and testing set (50%). The LASSO penalized regression analysis was employed to build the prediction model, fitting OS to the expression level of hub genes by ‘glmnet’ package. Then the testing and 2 independent validation sets (GSE12417 and GSE37642) were used to validate the diagnostic utility and accuracy of the model. Results: A total of 37 gene co-expression modules and 973 hub genes were identified for the BeatAML cohort. We found that 3 modules were significantly correlated with genetic markers (the ‘lightyellow’ module for NPM1 mutation, the ‘saddlebrown’ module for RUNX1 mutation, the ‘lightgreen’ module for TP53 mutation). ORA revealed that the ‘lightyellow’ module was mainly enriched in DNA-binding transcription factor activity and activation of HOX genes. The ‘saddlebrown’ module was enriched in immune response process. And the ‘lightgreen’ module was predominantly enriched in mitosis cell cycle process. The LASSO- regression analysis identified 6 genes (NFKB2, NEK9, HOXA7, APRC5L, FAM30A and LOC105371592) with non-zero coefficients. The risk score generated from the 6-gene model, was associated with ELN2017 risk stratification, relapsed disease, and prior MDS history. The 5-year AUC for the model was 0.822 and 0.824 in the training and testing sets, respectively. Moreover, the diagnostic utility of the model was robust when it was employed in 2 validation sets (5-year AUC 0.743-0.79).Conclusions: We established the co-expression network signature correlated with the ELN2017 recommended prognostic genetic abnormalities in AML. The 6-gene prediction model for AML survival was developed and validated by multiple datasets.

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Identification of KIF11 as a Novel Target in Meningioma

Cited by 35 publications

References 86 publications

ZNF367-induced transcriptional activation of KIF15 accelerates the progression of breast cancer

ZNF367-induced transcriptional activation of KIF15 accelerates the progression of breast cancer

Occurrence of Fibrotic Tumor Vessels in Grade I Meningiomas Is Strongly Associated with Vessel Density, Expression of VEGF, PlGF, IGFBP-3 and Tumor Recurrence

The Landscape of Gene Co-Expression Modules Correlating with Prognostic Genetic Abnormalities in AML

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