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      Piperine Increases Pentagamavunon-1 Anti-cancer Activity on 4T1 Breast Cancer Through Mitotic Catastrophe Mechanism and Senescence with Sharing Targeting on Mitotic Regulatory Proteins

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          Abstract

          Pentagamavunon-1 performs more potent anti-cancer effects than curcumin against various cancer cells, but it remains to be optimized. Piperine shows the activity as an enhancer of a therapeutic agent. This study expects to achieve higher effectiveness of PGV-1 on 4T1 breast cancer cells through co-treatment with piperine with exploring the effect of cytotoxicity, mitotic catastrophe, cellular senescence, and target proteins of PGV-1 and piperine on the regulation of mitosis in TNBC cells (4T1). The assays emphasize MTT assay, May Grünwald-Giemsa staining, SA-β-galactosidase assay, and bioinformatics analysis, respectively, to elicit the respected activities. The results revealed that PGV-1 performed a cytotoxic effect with an IC50 value of 9 µM while piperine showed a lower cytotoxic effect with an IC50 value of 800 µM on 4T1 cells 24 h treatment. However, the combination treatment of both showed a synergistic cytotoxic enhancement effect with an average CI value < 1. Furthermore, the combination of PGV-1 and piperine induced mitotic catastrophe and senescence better than the single treatment. Treatment of 1 µM of PGV-1 and 400 µM of piperine increased the percentage of senescent cells by 33%. Bioinformatics analysis revealed that PGV-1 and piperine target proteins play a role in mitotic regulation, namely CDK1, KIF11, AURKA, AURKB, and PLK1, to contribute to mitotic catastrophe. Therefore, piperine increases the effectiveness of PGV-1 to suppress 4T1 cells growth synergistically that may occur through mitotic catastrophe and senescence targeting on mitotic regulatory proteins.

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          UALCAN: A Portal for Facilitating Tumor Subgroup Gene Expression and Survival Analyses1

          Genomics data from The Cancer Genome Atlas (TCGA) project has led to the comprehensive molecular characterization of multiple cancer types. The large sample numbers in TCGA offer an excellent opportunity to address questions associated with tumo heterogeneity. Exploration of the data by cancer researchers and clinicians is imperative to unearth novel therapeutic/diagnostic biomarkers. Various computational tools have been developed to aid researchers in carrying out specific TCGA data analyses; however there is need for resources to facilitate the study of gene expression variations and survival associations across tumors. Here, we report UALCAN, an easy to use, interactive web-portal to perform to in-depth analyses of TCGA gene expression data. UALCAN uses TCGA level 3 RNA-seq and clinical data from 31 cancer types. The portal's user-friendly features allow to perform: 1) analyze relative expression of a query gene(s) across tumor and normal samples, as well as in various tumor sub-groups based on individual cancer stages, tumor grade, race, body weight or other clinicopathologic features, 2) estimate the effect of gene expression level and clinicopathologic features on patient survival; and 3) identify the top over- and under-expressed (up and down-regulated) genes in individual cancer types. This resource serves as a platform for in silico validation of target genes and for identifying tumor sub-group specific candidate biomarkers. Thus, UALCAN web-portal could be extremely helpful in accelerating cancer research. UALCAN is publicly available at http://ualcan.path.uab.edu.
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            SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules

            Abstract SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15–20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch).
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              Quantitative analysis of dose-effect relationships: the combined effects of multiple drugs or enzyme inhibitors

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                Author and article information

                Contributors
                Journal
                Iran J Pharm Res
                Iran J Pharm Res
                10.5812/ijpr
                Brieflands
                Iranian Journal of Pharmaceutical Research : IJPR
                Briefland
                1735-0328
                1726-6890
                04 February 2022
                December 2022
                : 21
                : 1
                : e123820
                Affiliations
                [1 ]Department of Biotechnology, Graduate School, Universitas Gadjah Mada, Yogyakarta, Indonesia
                [2 ]Cancer Chemoprevention Research Center, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia
                [3 ]Laboratory of Macromolecular Engineering, Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia
                Author notes
                [* ]Corresponding Author: Cancer Chemoprevention Research Center, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia. Email: edy_meiyanto@ 123456ugm.ac.id
                Author information
                https://orcid.org/0000-0001-8122-2649
                https://orcid.org/0000-0002-0886-6322
                Article
                10.5812/ijpr.123820
                9191230
                35765510
                81706ae4-7300-4732-814f-200efed8bd9f
                Copyright © 2022, Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

                History
                : 14 June 2021
                : 11 September 2021
                : 12 September 2021
                Categories
                Research Article

                pentagamavunon-1 (pgv-1),piperine,4t1 cells,tnbc,mitotic catastrophe,senescence,protein target

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