Multidrug resistance protein 7 (MRP7, ABCC10) is a recently identified member of the ATP-binding cassette (ABC) transporter family, which adequately confers resistance to a diverse group of antineoplastic agents, including taxanes, vinca alkaloids and nucleoside analogs among others. Clinical studies indicate an increased MRP7 expression in non-small cell lung carcinomas (NSCLC) compared to a normal healthy lung tissue. Recent studies revealed increased paclitaxel sensitivity in the Mrp7(-/-) mouse model compared to their wild-type counterparts. This demonstrates that MRP7 is a key contributor in developing drug resistance. Recently our group reported that PD173074, a specific fibroblast growth factor receptor (FGFR) inhibitor, could significantly reverse P-glycoprotein-mediated MDR. However, whether PD173074 can interact with and inhibit other MRP members is unknown. In the present study, we investigated the ability of PD173074 to reverse MRP7-mediated MDR. We found that PD173074, at non-toxic concentration, could significantly increase the cellular sensitivity to MRP7 substrates. Mechanistic studies indicated that PD173074 (1 μmol/L) significantly increased the intracellular accumulation and in-turn decreased the efflux of paclitaxel by inhibiting the transport activity without altering expression levels of the MRP7 protein, thereby representing a promising therapeutic agent in the clinical treatment of chemoresistant cancer patients.

Bioinformatic approaches have complemented experimental efforts to inventorize plant miRNA targets. We carried out global computational analysis of rice (Oryza sativa) transcriptome to generate a comprehensive list of putative miRNA targets. Our predictions (684 unique transcripts) showed that rice miRNAs mediate regulation of diverse functions including transcription (41%), catalysis (28%), binding (18%), and transporter activity (11%). Among the predicted targets, 61.7% hits were in coding regions and nearly 72% targets had a solitary miRNA hit. The study predicted more than 70 novel targets of 34 miRNAs putatively regulating functions like stress-response, catalysis, and binding. It was observed that more than half (55%) of the targets were conserved between O. sativa indica and O. sativa japonica. Members of 31 miRNA families were found to possess conserved targets between rice and at least one of other grass family members. About 44% of the unique targets were common between two dissimilar miRNA prediction algorithms. Such an extent of cross-species conservation and algorithmic consensus confers confidence in the list of rice miRNA targets predicted in this study.
Algorithms ; Arabidopsis ; genetics ; metabolism ; Conserved Sequence ; Databases, Nucleic Acid ; Gene Expression Profiling ; statistics & numerical data ; Genomics ; statistics & numerical data ; MicroRNAs ; genetics ; metabolism ; Models, Genetic ; Oryza ; classification ; genetics ; metabolism ; Poaceae ; classification ; genetics ; metabolism ; RNA, Plant ; genetics ; metabolism ; Species Specificity

Bioinformatic approaches have complemented experimental efforts to inventorize plant miRNA targets. We carried out global computational analysis of rice (Oryza sativa) transcriptome to generate a comprehensive list of putative miRNA targets. Our predictions (684 unique transcripts) showed that rice miRNAs mediate regu- lation of diverse functions including transcription (41%), catalysis (28%), binding (18%), and transporter activity (11%). Among the predicted targets, 61.7% hits were in coding regions and nearly 72% targets had a solitary miRNA hit. The study predicted more than 70 novel targets of 34 miRNAs putatively regulating functions like stress-response, catalysis, and binding. It was observed that more than half (55%) of the targets were conserved between O. sativa indica and O. aativa japonica. Members of 31 miRNA families were found to possess conserved targets between rice and at least one of other grass family members. About 44% of the unique targets were common between two dissimilar miRNA prediction al- gorithms. Such an extent of cross-species conservation and algorithmic consensus confers confidence in the list of rice miRNA targets predicted in this study.