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      The impact of ABCB1 gene polymorphism and its expression on non-small-cell lung cancer development, progression and therapy – preliminary report

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          Abstract

          The ABCB1 gene belongs to ATP binding cassette (ABC) transporter genes that has been previously implicated in cancer progression and drug response. This study aimed to evaluate the association between the SNP 3435 and the expression of the ABCB1 gene in lung cancer patients in the Polish population in comparison to clinicopathological parameters and treatment. 150 RNA and 47 DNA samples were isolated from 49 lung cancer cases including both tissue samples and blood taken from the same patients at three time points: diagnosis, 100 days and one year after the surgical intervention. Qualitative and real-time PCR analysis of expression were done, also genotyping by PCR-RFLP. Mutant homozygous TT and allele T are present statistically significantly more frequently in the group of patients with lung cancer. There is no difference with expression level in lung cancer tissue and blood sample taken from the same patients before surgical treatment. On the basis of blood samples analysis it was observed that the expression level of ABCB1 mRNA was growing in time. Higher levels were marked after 100 days and one year after the surgical intervention. The complementary pharmacological treatment induced higher expression levels of ABCB1. The presented data suggest an important role of ABCB1 in lung cancer, the increasing level of ABCB1 mRNA which can be connected with induction of multidrug resistance mechanism is also significant, that observation must be confirmed in further analysis.

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          Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR

          Background Control genes, which are often referred to as housekeeping genes, are frequently used to normalise mRNA levels between different samples. However, the expression level of these genes may vary among tissues or cells and may change under certain circumstances. Thus, the selection of housekeeping genes is critical for gene expression studies. To address this issue, 7 candidate housekeeping genes including several commonly used ones were investigated in isolated human reticulocytes. For this, a simple ΔCt approach was employed by comparing relative expression of 'pairs of genes' within each sample. On this basis, stability of the candidate housekeeping genes was ranked according to repeatability of the gene expression differences among 31 samples. Results Initial screening of the expression pattern demonstrated that 1 of the 7 genes was expressed at very low levels in reticulocytes and was excluded from further analysis. The range of expression stability of the other 6 genes was (from most stable to least stable): GAPDH (glyceraldehyde 3-phosphate dehydrogenase), SDHA (succinate dehydrogenase), HPRT1 (hypoxanthine phosphoribosyl transferase 1), HBS1L (HBS1-like protein) and AHSP (alpha haemoglobin stabilising protein), followed by B2M (beta-2-microglobulin). Conclusion Using this simple approach, GAPDH was found to be the most suitable housekeeping gene for expression studies in reticulocytes while the commonly used B2M should be avoided.
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            Understanding survival analysis: Kaplan-Meier estimate

            Kaplan-Meier estimate is one of the best options to be used to measure the fraction of subjects living for a certain amount of time after treatment. In clinical trials or community trials, the effect of an intervention is assessed by measuring the number of subjects survived or saved after that intervention over a period of time. The time starting from a defined point to the occurrence of a given event, for example death is called as survival time and the analysis of group data as survival analysis. This can be affected by subjects under study that are uncooperative and refused to be remained in the study or when some of the subjects may not experience the event or death before the end of the study, although they would have experienced or died if observation continued, or we lose touch with them midway in the study. We label these situations as censored observations. The Kaplan-Meier estimate is the simplest way of computing the survival over time in spite of all these difficulties associated with subjects or situations. The survival curve can be created assuming various situations. It involves computing of probabilities of occurrence of event at a certain point of time and multiplying these successive probabilities by any earlier computed probabilities to get the final estimate. This can be calculated for two groups of subjects and also their statistical difference in the survivals. This can be used in Ayurveda research when they are comparing two drugs and looking for survival of subjects.
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              Multidrug resistance proteins: role of P-glycoprotein, MRP1, MRP2, and BCRP (ABCG2) in tissue defense.

              In tumor cell lines, multidrug resistance is often associated with an ATP-dependent decrease in cellular drug accumulation which is attributed to the overexpression of certain ATP-binding cassette (ABC) transporter proteins. ABC proteins that confer drug resistance include (but are not limited to) P-glycoprotein (gene symbol ABCB1), the multidrug resistance protein 1 (MRP1, gene symbol ABCC1), MRP2 (gene symbol ABCC2), and the breast cancer resistance protein (BCRP, gene symbol ABCG2). In addition to their role in drug resistance, there is substantial evidence that these efflux pumps have overlapping functions in tissue defense. Collectively, these proteins are capable of transporting a vast and chemically diverse array of toxicants including bulky lipophilic cationic, anionic, and neutrally charged drugs and toxins as well as conjugated organic anions that encompass dietary and environmental carcinogens, pesticides, metals, metalloids, and lipid peroxidation products. P-glycoprotein, MRP1, MRP2, and BCRP/ABCG2 are expressed in tissues important for absorption (e.g., lung and gut) and metabolism and elimination (liver and kidney). In addition, these transporters have an important role in maintaining the barrier function of sanctuary site tissues (e.g., blood-brain barrier, blood-cerebral spinal fluid barrier, blood-testis barrier and the maternal-fetal barrier or placenta). Thus, these ABC transporters are increasingly recognized for their ability to modulate the absorption, distribution, metabolism, excretion, and toxicity of xenobiotics. In this review, the role of these four ABC transporter proteins in protecting tissues from a variety of toxicants is discussed. Species variations in substrate specificity and tissue distribution of these transporters are also addressed since these properties have implications for in vivo models of toxicity used for drug discovery and development.
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                Author and article information

                Contributors
                ewa.balcerczak@umed.lodz.pl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 April 2020
                10 April 2020
                2020
                : 10
                : 6188
                Affiliations
                [1 ]ISNI 0000 0001 2165 3025, GRID grid.8267.b, Laboratory of Molecular Diagnostics and Pharmacogenomics, Department of Pharmaceutical Biochemistry and Molecular Diagnostics, Medical University of Lodz, ul. Muszynskiego 1, ; 90-151 Lodz, Poland
                [2 ]ISNI 0000 0001 2165 3025, GRID grid.8267.b, Department of Thoracic Surgery, Memorial Copernicus Hospital, Medical University of Lodz, ; Lodz, Poland
                Author information
                http://orcid.org/0000-0002-3565-7075
                http://orcid.org/0000-0002-9187-1199
                http://orcid.org/0000-0001-7478-7860
                http://orcid.org/0000-0003-2964-4793
                http://orcid.org/0000-0002-9524-6032
                http://orcid.org/0000-0001-9243-0275
                http://orcid.org/0000-0002-4899-2200
                http://orcid.org/0000-0002-8248-1041
                http://orcid.org/0000-0001-5257-2914
                Article
                63265
                10.1038/s41598-020-63265-4
                7148348
                32277145
                4daaf0f7-e082-4531-aca8-c4247fac4126
                © The Author(s) 2020

                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
                : 22 November 2019
                : 27 March 2020
                Categories
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                © The Author(s) 2020

                Uncategorized
                cancer,genetics,molecular biology,biomarkers,medical research,molecular medicine
                Uncategorized
                cancer, genetics, molecular biology, biomarkers, medical research, molecular medicine

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