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      Dissecting multi drug resistance in head and neck cancer cells using multicellular tumor spheroids

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          Abstract

          One of the hallmarks of cancers is their ability to develop resistance against therapeutic agents. Therefore, developing effective in vitro strategies to identify drug resistance remains of paramount importance for successful treatment. One of the ways cancer cells achieve drug resistance is through the expression of efflux pumps that actively pump drugs out of the cells. To date, several studies have investigated the potential of using 3-dimensional (3D) multicellular tumor spheroids (MCSs) to assess drug resistance; however, a unified system that uses MCSs to differentiate between multi drug resistance (MDR) and non-MDR cells does not yet exist. In the present report we describe MCSs obtained from post-diagnosed, pre-treated patient-derived (PTPD) cell lines from head and neck squamous cancer cells (HNSCC) that often develop resistance to therapy. We employed an integrated approach combining response to clinical drugs and screening cytotoxicity, monitoring real-time drug uptake, and assessing transporter activity using flow cytometry in the presence and absence of their respective specific inhibitors. The report shows a comparative response to MDR, drug efflux capability and reactive oxygen species (ROS) activity to assess the resistance profile of PTPD MCSs and two-dimensional (2D) monolayer cultures of the same set of cell lines. We show that MCSs provide a robust and reliable in vitro model to evaluate clinical relevance. Our proposed strategy can also be clinically applicable for profiling drug resistance in cancers with unknown resistance profiles, which consequently can indicate benefit from downstream therapy.

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          Autophagy and multidrug resistance in cancer

          Multidrug resistance (MDR) occurs frequently after long-term chemotherapy, resulting in refractory cancer and tumor recurrence. Therefore, combatting MDR is an important issue. Autophagy, a self-degradative system, universally arises during the treatment of sensitive and MDR cancer. Autophagy can be a double-edged sword for MDR tumors: it participates in the development of MDR and protects cancer cells from chemotherapeutics but can also kill MDR cancer cells in which apoptosis pathways are inactive. Autophagy induced by anticancer drugs could also activate apoptosis signaling pathways in MDR cells, facilitating MDR reversal. Therefore, research on the regulation of autophagy to combat MDR is expanding and is becoming increasingly important. We summarize advanced studies of autophagy in MDR tumors, including the variable role of autophagy in MDR cancer cells.
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            Patient-derived models of acquired resistance can identify effective drug combinations for cancer.

            Targeted cancer therapies have produced substantial clinical responses, but most tumors develop resistance to these drugs. Here, we describe a pharmacogenomic platform that facilitates rapid discovery of drug combinations that can overcome resistance. We established cell culture models derived from biopsy samples of lung cancer patients whose disease had progressed while on treatment with epidermal growth factor receptor (EGFR) or anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors and then subjected these cells to genetic analyses and a pharmacological screen. Multiple effective drug combinations were identified. For example, the combination of ALK and MAPK kinase (MEK) inhibitors was active in an ALK-positive resistant tumor that had developed a MAP2K1 activating mutation, and the combination of EGFR and fibroblast growth factor receptor (FGFR) inhibitors was active in an EGFR mutant resistant cancer with a mutation in FGFR3. Combined ALK and SRC (pp60c-src) inhibition was effective in several ALK-driven patient-derived models, a result not predicted by genetic analysis alone. With further refinements, this strategy could help direct therapeutic choices for individual patients.
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              Multi-drug resistance in cancer chemotherapeutics: mechanisms and lab approaches.

              Multi-drug resistance (MDR) has become the largest obstacle to the success of cancer chemotherapies. The mechanisms of MDR and the approaches to test MDR have been discovered, yet not fully understood. This review covers the in vivo and in vitro approaches for the detection of MDR in the laboratory and the mechanisms of MDR in cancers. This study also envisages the future developments toward the clinical and therapeutic applications of MDR in cancer treatment. Future therapeutics for cancer treatment will likely combine the existing therapies with drugs originated from MDR mechanisms such as anti-cancer stem cell drugs, anti-miRNA drugs or anti-epigenetic drugs. The challenges for the clinical detection of MDR will be to find new biomarkers and to determine new evaluation systems before the drug resistance emerges. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
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                Author and article information

                Contributors
                Karin.roberg@liu.se
                hp401@cam.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 December 2019
                27 December 2019
                2019
                : 9
                : 20066
                Affiliations
                [1 ]ISNI 0000 0001 2162 9922, GRID grid.5640.7, Department of Clinical and Experimental Medicine (IKE), , Linköping University, ; Linköping, Sweden
                [2 ]Department of Otorhinolaryngology in Linköping, Anaesthetics, Operations and Specialty Surgery Center, Region Östergötland, Östergötland, Sweden
                [3 ]ISNI 0000 0004 1767 0991, GRID grid.444419.8, Department of Electrical Engineering, , National Institute of Technology Durgapur, ; Durgapur, India
                [4 ]ISNI 0000 0001 0930 2361, GRID grid.4514.4, Division of Molecular Medicine and Gene Therapy, , Lund University, ; Lund, Sweden
                [5 ]ISNI 0000 0001 2162 9922, GRID grid.5640.7, Department of Medical and Health Sciences (IMH), Division of Drug Research (LÄFO), , Linköping University, ; Linköping, Sweden
                [6 ]ISNI 0000000121885934, GRID grid.5335.0, Department of Chemical Engineering and Biotechnology, , University of Cambridge, ; Cambridge, UK
                Author information
                http://orcid.org/0000-0003-1208-9746
                http://orcid.org/0000-0002-6142-5489
                Article
                56273
                10.1038/s41598-019-56273-6
                6934860
                31882620
                53b26a2e-6887-4f27-a921-13218fe6c24c
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 15 September 2019
                : 4 December 2019
                Funding
                Funded by: MIIC PDF and MIIC seeding grant
                Funded by: The Swedish Cancer Society (2017/301), the County Council of Östergötland, and the Research Funds of Linköping University Hospital
                Categories
                Article
                Custom metadata
                © The Author(s) 2019

                Uncategorized
                cancer models
                Uncategorized
                cancer models

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