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

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

Chemotherapy and signaling: How can targeted therapies supercharge cytotoxic agents?

In recent years, oncologists have begun to conclude that chemotherapy has reached a plateau of efficacy as a primary treatment modality, even if toxicity can be effectively controlled. Emerging specific inhibitors of signaling and metabolic pathways (i.e., targeted agents) contrast with traditional chemotherapy drugs in that the latter primarily interfere with the DNA biosynthesis and the cell replication machinery. In an attempt to improve on the efficacy, combination of targeted drugs with conventional chemotherapeutics has become a routine way of testing multiple new agents in early phase clinical trials. This review discusses the recent advances including integrative systematic biology and RNAi approaches to counteract the chemotherapy resistance and to buttress the selectivity, efficacy and personalization of anticancer drug therapy

Shared heritability and functional enrichment across six solid cancers

Abstract Quantifying 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 (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 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