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      The Anticancer Effects of FDI-6, a FOXM1 Inhibitor, on Triple Negative Breast Cancer

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          Abstract

          Triple-negative breast cancer (TNBC) presents an important clinical challenge, as it does not respond to endocrine therapies or other available targeting agents. FOXM1, an oncogenic transcriptional factor, has reported to be upregulated and associated with poor clinical outcomes in TNBC patients. In this study, we investigated the anti-cancer effects of FDI-6, a FOXM1 inhibitor, as well as its molecular mechanisms, in TNBC cells. Two TNBC cell lines, MDA-MB-231 and HS578T, were used in this study. The anti-cancer activities of FDI-6 were evaluated using various 2D cell culture assays, including Sulforhodamine B (SRB), wound healing, and transwell invasion assays together with 3D spheroid assays, mimicking real tumour structural properties. After treatment with FDI-6, the TNBC cells displayed a significant inhibition in cell proliferation, migration, and invasion. Increased apoptosis was also observed in the treated cells. In addition, we found that FDI-6 lead to the downregulation of FOXM1 and its key oncogenic targets, including CyclinB1, Snail, and Slug. Interestingly, we also found that the FDI-6/Doxorubicin combination significantly enhanced the cytotoxicity and apoptotic properties, suggesting that FDI-6 might improve chemotherapy treatment efficacy and reduce unwanted side effects. Altogether, FDI-6 exhibited promising anti-tumour activities and could be developed as a newly effective treatment for TNBC.

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          NIH Image to ImageJ: 25 years of image analysis

          For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Breast cancer will be diagnosed in 12% of women in the United States over the course of their lifetimes and more than 250 000 new cases of breast cancer were diagnosed in the United States in 2017. This review focuses on current approaches and evolving strategies for local and systemic therapy of breast cancer.
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              Theoretical basis, experimental design, and computerized simulation of synergism and antagonism in drug combination studies.

              The median-effect equation derived from the mass-action law principle at equilibrium-steady state via mathematical induction and deduction for different reaction sequences and mechanisms and different types of inhibition has been shown to be the unified theory for the Michaelis-Menten equation, Hill equation, Henderson-Hasselbalch equation, and Scatchard equation. It is shown that dose and effect are interchangeable via defined parameters. This general equation for the single drug effect has been extended to the multiple drug effect equation for n drugs. These equations provide the theoretical basis for the combination index (CI)-isobologram equation that allows quantitative determination of drug interactions, where CI 1 indicate synergism, additive effect, and antagonism, respectively. Based on these algorithms, computer software has been developed to allow automated simulation of synergism and antagonism at all dose or effect levels. It displays the dose-effect curve, median-effect plot, combination index plot, isobologram, dose-reduction index plot, and polygonogram for in vitro or in vivo studies. This theoretical development, experimental design, and computerized data analysis have facilitated dose-effect analysis for single drug evaluation or carcinogen and radiation risk assessment, as well as for drug or other entity combinations in a vast field of disciplines of biomedical sciences. In this review, selected examples of applications are given, and step-by-step examples of experimental designs and real data analysis are also illustrated. The merging of the mass-action law principle with mathematical induction-deduction has been proven to be a unique and effective scientific method for general theory development. The median-effect principle and its mass-action law based computer software are gaining increased applications in biomedical sciences, from how to effectively evaluate a single compound or entity to how to beneficially use multiple drugs or modalities in combination therapies.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                22 June 2021
                July 2021
                : 22
                : 13
                : 6685
                Affiliations
                [1 ]Institute of Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand; k_ulhaka@ 123456outlook.co.th (K.U.); ploy_khunpitak@ 123456hotmail.com (T.K.)
                [2 ]Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand; kkanyana@ 123456gmail.com (K.K.); rassanee.b@ 123456gmail.com (R.B.)
                [3 ]National Nanotechnology Centre (NANOTEC), National Science and Technology Development Agency, Pathumthani 12120, Thailand; mattaka@ 123456nanotec.or.th
                [4 ]Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
                Author notes
                [* ]Correspondence: k.pasarat@ 123456gmail.com or pasarat.k@ 123456psu.ac.th ; Tel.: +66-74-451743
                Author information
                https://orcid.org/0000-0002-6765-0329
                https://orcid.org/0000-0003-3068-2412
                Article
                ijms-22-06685
                10.3390/ijms22136685
                8269391
                34206484
                9e133a54-6d66-41c9-9ab8-4af46ae33fe5
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 10 May 2021
                : 16 June 2021
                Categories
                Article

                Molecular biology
                triple negative breast cancer,foxm1,fdi-6,anti-cancer effects
                Molecular biology
                triple negative breast cancer, foxm1, fdi-6, anti-cancer effects

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