Inhibition of casein kinase 2 prevents growth of human osteosarcoma

Takahashi, Kengo; Setoguchi, Takao; Tsuru, Arisa; Saitoh, Yoshinobu; Nagano, Satoshi; Ishidou, Yasuhiro; Maeda, Shingo; Furukawa, Tatsuhiko; Komiya, Setsuro

doi:10.3892/or.2016.5310

Cited by 18 publications

(21 citation statements)

References 43 publications

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“…Kinases catalyze the transfer of phosphate groups from high-energy, phosphate-donating molecules to specific substrates. Takahashi et al [27] used siRNA and the small molecule inhibitor CX-4945 to show that upregulation of casein kinase 2 (CK2) was important for the growth of human osteosarcoma cells. Zhu et al [28] reported that the checkpoint kinase inhibitor AZD7762 promoted apoptosis and mitotic catastrophe in osteosarcoma cells.…”

Section: Discussionmentioning

confidence: 99%

Co-expression network analysis identifies a gene signature as a predictive biomarker for energy metabolism in osteosarcoma

Zhu

Hou²,

et al. 2020

Cancer Cell Int

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Background: Osteosarcoma (OS) is a common malignant bone tumor originating in the interstitial tissues and occurring mostly in adolescents and young adults. Energy metabolism is a prerequisite for cancer cell growth, proliferation, invasion, and metastasis. However, the gene signatures associated with energy metabolism and their underlying molecular mechanisms that drive them are unknown. Methods: Energy metabolism-related genes were obtained from the TARGET database. We applied the "NFM" algorithm to classify putative signature gene into subtypes based on energy metabolism. Key genes related to progression were identified by weighted co-expression network analysis (WGCNA). Based on least absolute shrinkage and selection operator (LASSO) Cox proportional regression hazards model analyses, a gene signature for the predication of OS progression and prognosis was established. Robustness and estimation evaluations and comparison against other models were used to evaluate the prognostic performance of our model. Results: Two subtypes associated with energy metabolism was determined using the "NFM" algorithm, and significant modules related to energy metabolism were identified by WGCNA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) suggested that the genes in the significant modules were enriched in kinase, immune metabolism processes, and metabolism-related pathways. We constructed a seven-gene signature consisting of SLC18B1, RBMXL1, DOK3, HS3ST2, ATP6V0D1, CCAR1, and C1QTNF1 to be used for OS progression and prognosis. Upregulation of CCAR1, and C1QTNF1 was associated with augmented OS risk, whereas, increases in the expression SCL18B1, RBMXL1, DOK3, HS3ST2, and ATP6VOD1 was correlated with a diminished risk of OS. We confirmed that the seven-gene signature was robust, and was superior to the earlier models evaluated; therefore, it may be used for timely OS diagnosis, treatment, and prognosis. Conclusions: The seven-gene signature related to OS energy metabolism developed here could be used in the early diagnosis, treatment, and prognosis of OS.

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Section: Discussionmentioning

confidence: 99%

Co-expression network analysis identifies a gene signature as a predictive biomarker for energy metabolism in osteosarcoma

Zhu

Hou²,

et al. 2020

Cancer Cell Int

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“…Western blotting was performed as previously described (18). Cells were lysed using NP40 buffer, which contained 0.5% NP-40, 10 mM Tris-HCl (pH 7.4), 150 mM NaCl, 3 mM phenylmethylsulfonyl fluoride (Wako Pure Chemical Industries Co., Ltd., Kanagawa, Japan), 5 mg/ml aprotinin (Sigma-Aldrich; Merck KGaA), 2 mM sodium orthovanadate (Wako Pure Chemical Industries) and 5 mM EDTA.…”

Section: Methodsmentioning

confidence: 99%

Tranilast enhances the effect of anticancer agents in osteosarcoma

et al. 2019

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Tranilast [N-(3′,4′-dimethoxycinnamoyl)-anthranilic acid], initially developed as an antiallergic drug, also exhibits a growth inhibitory effect on various types of cancer. Osteosarcoma is treated mainly with high-dose methotrexate, doxorubicin, cisplatin and ifosfamide; however, 20–30 % of patients cannot be cured of metastatic disease. We investigated whether tranilast enhances the anticancer effects of chemotherapeutic drugs and analyzed its mechanism of action in osteosarcomas. Tranilast inhibited proliferation of HOS, 143B, U2OS and MG-63 osteosarcoma cells in a dose-dependent manner, as well as enhancing the effects of cisplatin and doxorubicin. The average combination index at effect levels for tranilast in combination with cisplatin was 0.57 in HOS, 0.4 in 143B, 0.39 in U2OS and 0.51 in MG-63 cells. Tranilast and cisplatin synergistically inhibited the viability of osteosarcoma cells. In flow cytometric analysis, although tranilast alone did not induce significant apoptosis, the combination of tranilast and cisplatin induced early and late apoptotic cell death. Expression of cleaved caspase-3, cleaved poly(ADP-ribose) polymerase and p-H2AX was enhanced by tranilast in combination with cisplatin. Tranilast alone increased expression of p21 and Bim protein in a dose-dependent manner. Cell cycle analysis using flow cytometry demonstrated that the combination of tranilast and cisplatin increased the number of cells in the G2/M phase. Compared with cisplatin alone, the combination increased levels of phospho-cyclin-dependent kinase 1 (Y15). In the 143B xenograft model, tumor growth was significantly inhibited by combined tranilast and cisplatin compared with the controls, whereas cisplatin alone did not significantly inhibit tumor growth. In conclusion, tranilast has a cytostatic effect on osteosarcoma cells and enhances the effect of anticancer drugs, especially cisplatin. Enhanced sensitivity to cisplatin was mediated by increased apoptosis through G2/M arrest. Since tranilast has been clinically approved and has few adverse effects, clinical trials of osteosarcoma chemotherapy in combination with tranilast are expected.

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“…Takahashi et al found overexpression of CK2α and CK2β protein in human osteosarcoma cell lines when compared to normal cells [127]. Furthermore, knockdown of either CK2α or CK2β with siRNA or incubation with CX-4945 led to prevention of osteosarcoma cell proliferation.…”

Section: Sarcomamentioning

confidence: 99%

Cancer-type dependent expression of CK2 transcripts.

Chua

Lee

Domı́nguez

2018

JCO

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A multitude of proteins are aberrantly expressed in cancer cells, including the oncogenic serine-threonine kinase CK2. In a previous report, we found increases in CK2 transcript expression that could explain the increased CK2 protein levels found in tumors from lung and bronchus, prostate, breast, colon and rectum, ovarian and pancreatic cancers. We also found that, contrary to the current notions about CK2, some CK2 transcripts were downregulated in several cancers. Here, we investigate all other cancers using Oncomine to determine whether they also display significant CK2 transcript dysregulation. As anticipated from our previous analysis, we found cancers with all CK2 transcripts upregulated (e.g. cervical), and cancers where there was a combination of upregulation and/or downregulation of the CK2 transcripts (e.g. sarcoma). Unexpectedly, we found some cancers with significant downregulation of all CK2 transcripts (e.g. testicular cancer). We also found that, in some cases, CK2 transcript levels were already dysregulated in benign lesions (e.g. Barrett's esophagus). We also found that CK2 transcript upregulation correlated with lower patient survival in most cases where data was significant. However, there were two cancer types, glioblastoma and renal cell carcinoma, where CK2 transcript upregulation correlated with higher survival. Overall, these data show that the expression levels of CK2 genes is highly variable in cancers and can lead to different patient outcomes.

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Inhibition of casein kinase 2 prevents growth of human osteosarcoma

Cited by 18 publications

References 43 publications

Co-expression network analysis identifies a gene signature as a predictive biomarker for energy metabolism in osteosarcoma

Co-expression network analysis identifies a gene signature as a predictive biomarker for energy metabolism in osteosarcoma

Tranilast enhances the effect of anticancer agents in osteosarcoma

Cancer-type dependent expression of CK2 transcripts.

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