110 research outputs found
ABCC10 (ATP-binding cassette, sub-family C (CFTR/MRP), member 10)
Review on ABCC10, with data on DNA/RNA, on the protein encoded and where the gene is implicated
Imatinib and Nilotinib Reverse Multidrug Resistance in Cancer Cells by Inhibiting the Efflux Activity of the MRP7 (ABCC10)
One of the major mechanisms that could produce resistance to antineoplastic drugs in cancer cells is the ATP binding cassette (ABC) transporters. The ABC transporters can significantly decrease the intracellular concentration of antineoplastic drugs by increasing their efflux, thereby lowering the cytotoxic activity of antineoplastic drugs. One of these transporters, the multiple resistant protein 7 (MRP7, ABCC10), has recently been shown to produce resistance to antineoplastic drugs by increasing the efflux of paclitaxel. In this study, we examined the effects of BCR-Abl tyrosine kinase inhibitors imatinib, nilotinib and dasatinib on the activity and expression of MRP7 in HEK293 cells transfected with MRP7, designated HEK-MRP7-2.We report for the first time that imatinib and nilotinib reversed MRP7-mediated multidrug resistance. Our MTT assay results indicated that MRP7 expression in HEK-MRP7-2 cells was not significantly altered by incubation with 5 microM of imatinib or nilotinib for up to 72 hours. In addition, imatinib and nilotinib (1-5 microM) produced a significant concentration-dependent reversal of MRP7-mediated multidrug resistance by enhancing the sensitivity of HEK-MRP7-2 cells to paclitaxel and vincristine. Imatinib and nilotinib, at 5 microM, significantly increased the accumulation of [(3)H]-paclitaxel in HEK-MRP7-2 cells. The incubation of the HEK-MRP7-2 cells with imatinib or nilotinib (5 microM) also significantly inhibited the efflux of paclitaxel.Imatinib and nilotinib reverse MRP7-mediated paclitaxel resistance, most likely due to their inhibition of the efflux of paclitaxel via MRP7. These findings suggest that imatinib or nilotinib, in combination with other antineoplastic drugs, may be useful in the treatment of certain resistant cancers
The establishment of two paclitaxel-resistant prostate cancer cell lines and the mechanisms of paclitaxel resistance with two cell lines
BACKGROUND Although paclitaxel is used for hormone-resistant prostate cancer, relapse definitely occurs later. Details of the molecular mechanism responsible for paclitaxel- resistance remain unclear. METHODS We established paclitaxel-resistant cells, DU145-TxR and PC-3-TxR from parent DU145 and PC-3. To characterize these cells, we examined cross-resistance to other anticancer drugs. Expression of several potential genes that had been related to drug-resistance was compared with parent cells by RT-PCR and Western blotting. Methylation analysis of multiple drug resistance (MDR1) promoter was carried out using bisulfite-modified DNA from cell lines. Knockdown experiments using small interfering RNA (siRNA) were also performed to confirm responsibility of drug-resistance. Finally, cDNA microarray was performed to quantify gene expression in PC-3 and PC-3-TxR cells. RESULTS The IC 50 for paclitaxel in DU145-TxR and PC-3-TxR was 34.0- and 43.4-fold higher than that in both parent cells, respectively. Both cells showed cross-resistance to some drugs, but not to VP-16 and cisplatin. Methylation analysis revealed that methylated CpG sites of MDR1 promoter in DU145 and PC-3 cells were demethylated in DU145-TxR cells, but not in PC-3-TxR cells. Knockdown of P-glycoprotein (P-gp), which was up-regulated in resistant cells, by MDR-1 siRNA restored paclitaxel sensitivity in DU145-TxR but not in PC-3-TxR, indicating that up-regulation of P-gp was not always main cause of paclitaxel-resistance. Microarray analysis identified 201 (1.34%) up-regulated genes and 218 (1.45%) out of screened genes in PC-3-TxR. CONCLUSIONS Our data will provide molecular mechanisms of paclitaxel-resistance and be useful for screening target genes to diagnose paclitaxel sensitivity. Prostate 67: 955–967, 2007. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56002/1/20581_ftp.pd
Wikipedia Information Flow Analysis Reveals the Scale-Free Architecture of the Semantic Space
In this paper we extract the topology of the semantic space in its encyclopedic acception, measuring the semantic flow between the different entries of the largest modern encyclopedia, Wikipedia, and thus creating a directed complex network of semantic flows. Notably at the percolation threshold the semantic space is characterised by scale-free behaviour at different levels of complexity and this relates the semantic space to a wide range of biological, social and linguistics phenomena. In particular we find that the cluster size distribution, representing the size of different semantic areas, is scale-free. Moreover the topology of the resulting semantic space is scale-free in the connectivity distribution and displays small-world properties. However its statistical properties do not allow a classical interpretation via a generative model based on a simple multiplicative process. After giving a detailed description and interpretation of the topological properties of the semantic space, we introduce a stochastic model of content-based network, based on a copy and mutation algorithm and on the Heaps' law, that is able to capture the main statistical properties of the analysed semantic space, including the Zipf's law for the word frequency distribution
ATP-binding cassette (ABC) transporters in normal and pathological lung
ATP-binding cassette (ABC) transporters are a family of transmembrane proteins that can transport a wide variety of substrates across biological membranes in an energy-dependent manner. Many ABC transporters such as P-glycoprotein (P-gp), multidrug resistance-associated protein 1 (MRP1) and breast cancer resistance protein (BCRP) are highly expressed in bronchial epithelium. This review aims to give new insights in the possible functions of ABC molecules in the lung in view of their expression in different cell types. Furthermore, their role in protection against noxious compounds, e.g. air pollutants and cigarette smoke components, will be discussed as well as the (mal)function in normal and pathological lung. Several pulmonary drugs are substrates for ABC transporters and therefore, the delivery of these drugs to the site of action may be highly dependent on the presence and activity of many ABC transporters in several cell types. Three ABC transporters are known to play an important role in lung functioning. Mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene can cause cystic fibrosis, and mutations in ABCA1 and ABCA3 are responsible for respectively Tangier disease and fatal surfactant deficiency. The role of altered function of ABC transporters in highly prevalent pulmonary diseases such as asthma or chronic obstructive pulmonary disease (COPD) have hardly been investigated so far. We especially focused on polymorphisms, knock-out mice models and in vitro results of pulmonary research. Insight in the function of ABC transporters in the lung may open new ways to facilitate treatment of lung diseases
Shared heritability and functional enrichment across six solid cancers
Correction: Nature Communications 10 (2019): art. 4386 DOI: 10.1038/s41467-019-12095-8Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r(g) = 0.57, p = 4.6 x 10(-8)), breast and ovarian cancer (r(g) = 0.24, p = 7 x 10(-5)), breast and lung cancer (r(g) = 0.18, p = 1.5 x 10(-6)) and breast and colorectal cancer (r(g) = 0.15, p = 1.1 x 10(-4)). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.Peer reviewe
Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types.
UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis. SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.The Breast Cancer Association Consortium (BCAC), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL), and the Ovarian Cancer Association Consortium (OCAC) that contributed breast, prostate, and ovarian cancer data analyzed in this study were in part funded by Cancer Research UK [C1287/A10118 and C1287/A12014 for BCAC; C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, and C16913/A6135 for PRACTICAL; and C490/A6187, C490/A10119, C490/A10124, C536/A13086, and C536/A6689 for OCAC]. Funding for the Collaborative Oncological Gene-environment Study (COGS) infrastructure came from: the European Community's Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), the US National Institutes of Health (CA128978) and the Post-Cancer GWAS Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (1U19 CA148537, 1U19 CA148065, and 1U19 CA148112), the US Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund [with donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07)]. Additional financial support for contributing studies is documented under Supplementary Financial Support.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/2159-8290.CD-15-122
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