The newly synthesized 2-arylnaphthyridin-4-one, CSC-3436, induces apoptosis of non-small cell lung cancer cells by inhibiting tubulin dynamics and activating CDK1

Chang, Ling; Yu, Yung Luen; Liu, Chin Yu; Cheng, Yung Yi; Chou, Ruey Hwang; Hsieh, Min Tsang; Lin, Hui Yi; Hung, Hsin Yi; Huang, Li Jiau; Wu, Yang Chang; Kuo, Sheng Chu

doi:10.1007/s00280-015-2765-0

Cited by 17 publications

(18 citation statements)

References 42 publications

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“…Eight proteins were significantly related to lung carcinogenesis—i.e., MEPCE, CDK1, PRKCA, COPS5, GSK3B, BRCA1, EP300, and PIN1 (Table 3) [3, 65–76]. Network analysis (Fig.…”

Section: Discussionmentioning

confidence: 99%

In silico identification of potential key regulatory factors in smoking-induced lung cancer

et al. 2017

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BackgroundLung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer. Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Identifying potential therapeutic targets is critical for the development of effective treatment strategies.MethodsWe used a systems biology approach to identify potential key regulatory factors in smoking-induced lung cancer. We first identified genes that were differentially expressed between smokers with normal lungs and those with cancerous lungs, then integrated these differentially expressed genes (DEGs) with data from a protein-protein interaction database to build a network model with functional modules for pathway analysis. We also carried out a gene set enrichment analysis of DEG lists using the Kinase Enrichment Analysis (KEA), Protein-Protein Interaction (PPI) hubs, and KEGG (Kyoto Encyclopedia of Genes and Genomes) databases.ResultsTwelve transcription factors were identified as having potential significance in lung cancer (CREB1, NUCKS1, HOXB4, MYCN, MYC, PHF8, TRIM28, WT1, CUX1, CRX, GABP, and TCF3); three of these (CRX, GABP, and TCF) have not been previously implicated in lung carcinogenesis. In addition, 11 kinases were found to be potentially related to lung cancer (MAPK1, IGF1R, RPS6KA1, ATR, MAPK14, MAPK3, MAPK4, MAPK8, PRKCZ, and INSR, and PRKAA1). However, PRKAA1 is reported here for the first time. MEPCE, CDK1, PRKCA, COPS5, GSK3B, BRCA1, EP300, and PIN1 were identified as potential hubs in lung cancer-associated signaling. In addition, we found 18 pathways that were potentially related to lung carcinogenesis, of which 12 (mitogen-activated protein kinase, gonadotropin-releasing hormone, Toll-like receptor, ErbB, and insulin signaling; purine and ether lipid metabolism; adherens junctions; regulation of autophagy; snare interactions in vesicular transport; and cell cycle) have been previously identified.ConclusionOur systems-based approach identified potential key molecules in lung carcinogenesis and provides a basis for investigations of tumor development as well as novel drug targets for lung cancer treatment.

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“…Eight proteins were significantly related to lung carcinogenesis—i.e., MEPCE, CDK1, PRKCA, COPS5, GSK3B, BRCA1, EP300, and PIN1 (Table 3) [3, 65–76]. Network analysis (Fig.…”

Section: Discussionmentioning

confidence: 99%

In silico identification of potential key regulatory factors in smoking-induced lung cancer

et al. 2017

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“…Microtubules are mainly used in the mitotic phase (M phase). As a result, any interference with the function of the microtubules will result in the M phase of the cell cycle being unable to proceed smoothly or promote cell G2/M phase arrest, resulting in cell death . Several benzo[ b ]furan compounds showed excellent activity as inhibitors of tubulin polymerization and were more potent than CA‐4 in this assay .…”

Section: Resultsmentioning

confidence: 99%

BF12, a Novel Benzofuran, Exhibits Antitumor Activity by Inhibiting Microtubules and the PI3K/Akt/mTOR Signaling Pathway in Human Cervical Cancer Cells

Gao

Feng

et al. 2020

Chemistry & Biodiversity

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BF12 [(2E)‐3‐[6‐Methoxy‐2‐(3,4,5‐trimethoxybenzoyl)‐1‐benzofuran‐5‐yl]prop‐2‐enoic acid], a novel derivative of combretastatin A‐4 (CA‐4), was previously found to inhibit tumor cell lines, with a particularly strong inhibitory effect on cervical cancer cells. In this study, we investigated the microtubule polymerization effects and apoptosis signaling mechanism of BF12. BF12 showed a potent efficiency against cervical cancer cells, SiHa and HeLa, with IC50 values of 1.10 and 1.06 μm, respectively. The cellular mechanism studies revealed that BF12 induced G2/M phase arrest and apoptosis in SiHa and HeLa cells, which were associated with alterations in the expression of the cell G2/M cycle checkpoint‐related proteins (cyclin B1 and cdc2) and alterations in the levels of apoptosis‐related proteins (P53, caspase‐3, Bcl‐2, and Bax) of these cells, respectively. Western blot analysis showed that BF12 inhibited the PI3 K/Akt/mTOR signaling pathway and induced apoptosis in human cervical cancer cells. BF12 was identified as a tubulin polymerization inhibitor, evidenced by the effective inhibition of tubulin polymerization and heavily disrupted microtubule networks in living SiHa and HeLa cells. By inhibiting the PI3 K/Akt/mTOR signaling pathway and inducing apoptosis in human cervical cancer cells, BF12 shows promise for use as a microtubule inhibitor.

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“…CDK1 gene is known to be a key regulator of the cell cycle pathway, and it is a potential therapeutic target for inhibitors in cancer treatment. CDK1 gene’s major role in development and cancer is supported by many experimental studies [ 40 – 43 ]. Genetic substitution of CDK1 gene has been shown to cause embryonic lethality [ 44 ], and its inhibition has been suggested as a potential therapy for MYC-dependent breast cancer [ 41 ].…”

Section: Resultsmentioning

confidence: 99%

Shortest path counting in probabilistic biological networks

Ren

Kahveci

2018

BMC Bioinformatics

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BackgroundBiological regulatory networks, representing the interactions between genes and their products, control almost every biological activity in the cell. Shortest path search is critical to apprehend the structure of these networks, and to detect their key components. Counting the number of shortest paths between pairs of genes in biological networks is a polynomial time problem. The fact that biological interactions are uncertain events however drastically complicates the problem, as it makes the topology of a given network uncertain.ResultsIn this paper, we develop a novel method to count the number of shortest paths between two nodes in probabilistic networks. Unlike earlier approaches, which uses the shortest path counting methods that are specifically designed for deterministic networks, our method builds a new mathematical model to express and compute the number of shortest paths. We prove the correctness of this model.ConclusionsWe compare our novel method to three existing shortest path counting methods on synthetic and real gene regulatory networks. Our experiments demonstrate that our method is scalable, and it outperforms the existing methods in accuracy. Application of our shortest path counting method to detect communities in probabilistic networks shows that our method successfully finds communities in probabilistic networks. Moreover, our experiments on cell cycle pathway among different cancer types exhibit that our method helps in uncovering key functional characteristics of biological networks.

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The newly synthesized 2-arylnaphthyridin-4-one, CSC-3436, induces apoptosis of non-small cell lung cancer cells by inhibiting tubulin dynamics and activating CDK1

Abstract: Our results reveal the cellular events in which CSC-3436 induces tumor cell death and demonstrate that CSC-3436 is a potential tubulin-disrupting agent for antitumor therapy against NSCLC.

Cited by 17 publications

References 42 publications

In silico identification of potential key regulatory factors in smoking-induced lung cancer

In silico identification of potential key regulatory factors in smoking-induced lung cancer

BF12, a Novel Benzofuran, Exhibits Antitumor Activity by Inhibiting Microtubules and the PI3K/Akt/mTOR Signaling Pathway in Human Cervical Cancer Cells

Shortest path counting in probabilistic biological networks

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