Synthesis of 2-alkoxy and 2-benzyloxy analogues of estradiol as anti-breast cancer agents through microtubule stabilization

Kumar, B. Sathish; Kumar, Amit; Singh, Jyotsna; Hasanain, Mohammad; Singh, Arjun; Fatima, Kaneez; Yadav, Dharmendra Kumar; Shukla, Vinay; Luqman, Suaib; Khan, Feroz; Chanda, Debabrata; Sarkar, Jayanta; Konwar, Rituraj; Dwivedi, Anila; Negi, Arvind S.

doi:10.1016/j.ejmech.2014.09.033

Cited by 64 publications

(14 citation statements)

References 36 publications

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“…The small molecular E2 is a type of human estrogen that exerts important effects on the reproductive and other related biological processes in both men and women 56 . It has significant anticancer activity against human breast cancer 57 . After implementing HSSMMA, we got the total ranking of miRNAs for E2.…”

Section: Resultsmentioning

confidence: 99%

In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm

Chen

Sun

et al. 2019

Molecular Therapy - Nucleic Acids

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Targeting microRNAs (miRNAs) with drug small molecules (SMs) is a new treatment method for many human complex diseases. Unsurprisingly, identification of potential miRNA-SM associations is helpful for pharmaceutical engineering and disease therapy in the field of medical research. In this paper, we developed a novel computational model of HeteSim-based inference for SM-miRNA Association prediction (HSSMMA) by implementing a path-based measurement method of HeteSim on a heterogeneous network combined with known miRNA-SM associations, integrated miRNA similarity, and integrated SM similarity. Through considering paths from an SM to a miRNA in the heterogeneous network, the model can capture the semantics information under each path and predict potential miRNA-SM associations based on all the considered paths. We performed global, miRNA-fixed local and SM-fixed local leave one out cross validation (LOOCV) as well as 5-fold cross validation based on the dataset of known miRNA-SM associations to evaluate the prediction performance of our approach. The results showed that HSSMMA gained the corresponding areas under the receiver operating characteristic (ROC) curve (AUCs) of 0.9913, 0.9902, 0.7989, and 0.9910 ± 0.0004 based on dataset 1 and AUCs of 0.7401, 0.8466, 0.6149, and 0.7451 ± 0.0054 based on dataset 2, respectively. In case studies, 2 of the top 10 and 13 of the top 50 predicted potential miRNA-SM associations were confirmed by published literature. We further implemented case studies to test whether HSSMMA was effective for new SMs without any known related miRNAs. The results from cross validation and case studies showed that HSSMMA could be a useful prediction tool for the identification of potential miRNA-SM associations.

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Section: Resultsmentioning

confidence: 99%

In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm

Chen

Sun

et al. 2019

Molecular Therapy - Nucleic Acids

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“…The small molecular 17β-Estradiol (E2) is the principal intracellular human estrogen that exerts important effects on the reproductive as well as many other organ systems in both men and women ( Simpson and Santen, 2015 ). The analogs of estradiol exhibit significant anticancer activity against human breast cancer cell lines ( Sathish Kumar et al, 2014 ). Estrogens have associations with cancer in target tissues, which is because they have a phenolic ring structure in common with the carcinogenic hydrocarbons ( Ryan, 1982 ).…”

Section: Resultsmentioning

confidence: 99%

Prediction of Potential Small Molecule-Associated MicroRNAs Using Graphlet Interaction

et al. 2018

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MicroRNAs (miRNAs) have been proved to be targeted by the small molecules recently, which made using small molecules to target miRNAs become a possible therapy for human diseases. Therefore, it is very meaningful to investigate the relationships between small molecules and miRNAs, which is still yet in the newly-developing stage. In this paper, we presented a prediction model of Graphlet Interaction based inference for Small Molecule-MiRNA Association prediction (GISMMA) by combining small molecule similarity network, miRNA similarity network and known small molecule-miRNA association network. This model described the complex relationship between two small molecules or between two miRNAs using graphlet interaction which consists of 28 isomers. The association score between a small molecule and a miRNA was calculated based on counting the numbers of graphlet interaction throughout the small molecule similarity network and the miRNA similarity network, respectively. Global and two types of local leave-one-out cross validation (LOOCV) as well as five-fold cross validation were implemented in two datasets to evaluate GISMMA. For Dataset 1, the AUCs are 0.9291 for global LOOCV, 0.9505, and 0.7702 for two local LOOCVs, 0.9263 ± 0.0026 for five-fold cross validation; for Dataset 2, the AUCs are 0.8203, 0.8640, 0.6591, and 0.8554 ± 0.0063, in turn. In case study for small molecules, 5-Fluorouracil, 17β-Estradiol and 5-Aza-2′-deoxycytidine, the numbers of top 50 miRNAs predicted by GISMMA and validated to be related to these three small molecules by experimental literatures are in turn 30, 29, and 25. Based on the results from cross validations and case studies, it is easy to realize the excellent performance of GISMMA.

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“…Lung, breast, colon, uterus and prostate are the main target organs that cancer can frequently occur 1,2 . Breast cancer is considered one of the most prevalent malignancies among the mentioned organs and is the second leading cause of cancer-related death in females worldwide [3][4][5][6] . Besides, chemotherapy is considered the most vital and conventional method for cancer treatment 7 .…”

Section: Introductionmentioning

confidence: 99%

Anti-proliferative and apoptotic effect of tetrahydrobenzo[h]quinoline on MCF-7 human breast cancer cell

Ghaffari¹,

Shanehbandi²,

Sarhadi³

et al. 2021

Pharm Sci

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Background: Quinoline and its derivatives display various biological activities based on versatility in designing a new drug class for medicinal applications. Hence, synthesizing innovative and varied derivatives of quinoline has gained considerable attention among chemists and biologists. This study evaluated the anti-proliferative and apoptotic effect of tetrahydrobenzo[h]quinoline on Michigan Cancer Foundation-7 (MCF-7) human breast cancer cells. Methods: The anti-proliferative effect of tetrahydrobenzo[h]quinoline was studied via MTT [3 0-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyl tetrazolium bromide] assays. A quantitative and qualitative study of apoptosis was carried out via flow cytometry and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL). Quantitative real-time PCR (qPCR) and immunoblotting analysis were employed to identify the expression level of genes and proteins involved in the apoptosis signaling pathway. Results: The synthesized compound reduced 50% of cell growth at concentrations of 10 and 7.5 µM during 24 and 48h, respectively, and induced apoptosis up to 30% in MCF-7 cancer cells. Regarding the gene expression level, Bcl-2 displayed considerable alleviation, whereas Bax expression increased significantly. Despite the remarkable increase in caspase 9 expression, there was no noticeable difference in the caspase 8 expression in treated cells compared to the control group. Western blotting data showed that the protein expression level of Bcl-2, pro-caspase 8, and 9 reduced. The protein content of Bax, cleaved-caspase 8, and 9 increased significantly, of which the protein level of cleaved-caspase 9 exhibited a tremendous rise in the treated group. Conclusion: The newly synthesized tetrahydrobenzo[h]quinoline can be a promising organic compound for cancer treatment if its anti-cancer effect investigates by other types of breast cancer cells. In vivo studies should be used to investigate the anti-cancer efficiency of this compound.

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Synthesis of 2-alkoxy and 2-benzyloxy analogues of estradiol as anti-breast cancer agents through microtubule stabilization

Cited by 64 publications

References 36 publications

In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm

In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm

Prediction of Potential Small Molecule-Associated MicroRNAs Using Graphlet Interaction

Anti-proliferative and apoptotic effect of tetrahydrobenzo[h]quinoline on MCF-7 human breast cancer cell

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