Medication-Assisted Treatment of Opiate Dependence Is Gaining Favor.

Medication-assisted treatment of opiate dependence is gaining favor.

Cleve Clin J Med. 2013 Jun; 80(6): 345-9
Jerry JM, Collins GB

People addicted to opiates are more likely to avoid returning to these drugs if they participate in a program that includes taking maintenance doses of methadone or buprenorphine than with an abstinence program. Although medical opinion has long been divided on the issue of abstinence vs medication-assisted treatment, the latter seems to be gaining respect as an evidence-based approach. HubMed – drug

The Genetic Architecture of Methotrexate Toxicity is Similar in Drosophila melanogaster and Humans.

G3 (Bethesda). 2013 Jun 3;
Kislukhin G, King EG, Walters KN, Macdonald SJ, Long AD

The severity of the toxic side effects of chemotherapy varies among patients and much of this variation is likely genetically based. Here, we use the model system Drosophila melanogaster to genetically dissect toxicity of methotrexate (MTX), a drug used primarily to treat childhood acute lymphoblastic leukemia and rheumatoid arthritis. We utilize the Drosophila Synthetic Population Resource (DSPR), a panel of recombinant inbred lines derived from a multiparent advanced intercross, and quantify MTX toxicity as a reduction in female fecundity. We identify three QTL affecting MTX toxicity; two co-localize with the fly orthologs of human genes believed to mediate MTX toxicity, and one is a novel MTX toxicity gene with a human ortholog. A fourth suggestive QTL spans a centromere. Local single marker association scans of candidate gene exons fail to implicate amino acid variants as the causative SNPs, and we therefore hypothesize the causative variation is regulatory. In addition, the effects at our mapped QTL do not conform to a simple biallelic pattern, suggesting multiple causative factors underlie the QTL mapping results. Consistent with this observation, no single SNP located in or near a candidate gene can explain the QTL mapping signal. Overall, our results validate D. melanogaster as a model for uncovering the genetic basis of chemotoxicity and suggest the genetic basis of MTX toxicity is due to a handful of genes each harboring multiple segregating regulatory factors. HubMed – drug

Next-generation sequencing of paired tyrosine kinase inhibitor-sensitive and -resistant EGFR mutant lung cancer cell lines identifies spectrum of DNA changes associated with drug resistance.

Genome Res. 2013 Jun 3;
Jia P, Jin H, Meador CB, Xia J, Ohashi K, Liu L, Pirazzoli V, Dahlman KB, Politi K, Michor F, Zhao Z, Pao W

Somatic mutations in genes encoding kinases are associated with increased sensitivity of some solid tumors to kinase inhibitors, but patients with metastatic cancer eventually develop disease progression. A common method used to model acquired resistance involves culturing parental drug-sensitive cells with increasing concentrations of drug until cells emerge that are resistant. In EGFR mutant lung cancer, this modeling has reliably identified clinically relevant EGFR tyrosine kinase inhibitor (TKI) resistance mechanisms such as the second-site mutation, EGFR T790M, amplification of the gene encoding an alternative kinase, MET, and epithelial-mesenchymal transition (EMT). The full spectrum of DNA changes associated with EGFR TKI acquired resistance remains unknown. Here, we used next-generation sequencing and bioinformatics analysis to characterize mutational changes associated with 4 populations of EGFR mutant drug-sensitive cell lines and 5 matched drug-resistant cell lines. Comparing resistant cells with their parental counterparts, we identified 16-89 coding SNVs/indels that were acquired and 1-27 that were lost; few SNVs/indels were shared across resistant lines. Comparison of two related parental lines revealed no unique coding SNVs/indels, suggesting that the changes in the resistant lines were due to drug selection. When analyzing whole genome sequencing data from one isogenic pair, we found that there was a higher frequency of SNVs in ‘constant late’ replication timing zones as compared to ‘constant early’ replication timing zones (chi-squared p-value < 10-5) and an enrichment of SNV frequencies in genomic regions harboring lamina-associated domains compared to the remainder of the nucleus (chi-squared p-value < 10-5). Surprisingly, we observed a higher burden of CNV changes across all resistant lines, and the one line that had an EMT phenotype displayed significantly higher levels of CNV changes than the other lines with acquired resistance. These results demonstrate a framework for studying the evolution of drug-related genetic variants over time and provide the first genome-wide spectrum of mutations associated with the development of cellular drug resistance in an oncogene-addicted cancer. Collectively, the data suggest that CNV changes may play a larger role than previously appreciated in the acquisition of drug resistance and highlight that resistance may be heterogeneous in the context of different tumor cell backgrounds. HubMed – drug

Establishing a High-Throughput and Automated Cancer Cell Proliferation Panel for Oncology Lead Optimization.

J Biomol Screen. 2013 Jun 3;
Lei M, Ribeiro H, Kolodin G, Gill J, Wang YS, Maloney D, Fan Y, Li S, Myer L, Beluch M, Zhang L, Schweizer L

Tumor cell proliferation assays are widely used for oncology drug discovery, including target validation, lead compound identification, and optimization, as well as determination of compound off-target activities. Taking advantage of robotic systems to maintain cell culture and perform cell proliferation assays would greatly increase productivity and efficiency. Here we describe the establishment of automated systems for high-throughput cell proliferation assays in a panel of 13 human tumor cell lines. These cell lines were selected from various types of human tumors containing a broad range of well-characterized mutations in multiple cellular signaling pathways. Standard procedures for cell culture and assay performance were developed and optimized in each cell line. Moreover, in-house developed software (i.e., Toolset, Curvemaster, and Biobars) was applied to analyze the data and generate data reports. Using tool compounds, we have shown that results obtained through this panel exhibit high reproducibility over a long period. Furthermore, we have demonstrated that this panel can be used to identify sensitive and insensitive cell lines for specific cancer targets, to drive cellular structure-activity relationships, and to profile compound off-target activities. All those efforts are important for cancer drug discovery lead optimization. HubMed – drug