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AZD6244 and MK2206 are targeted small-molecule drugs that inhibit MEK and AKT respectively. The efficacy of this combination in lung cancer is unknown. Our previous work showed the importance of activated AKT in mediating resistance of non-small cell lung cancer (NSCLC) to AZD6244. Thus we hypothesized that dual inhibition of both downstream MEK and AKT pathways would induce synergistic antitumor activity. In this study, we evaluated the efficacy of AZD6244 and MK2206 individually on a large panel of lung cancer cell lines. Then, we treated 28 human lung cancer cell lines with a combination of AZD6244 and MK2206 at clinically applicable drug molar ratios. The AZD6244-MK2206 combination therapy resulted in a synergistic effect on inhibition of lung cancer cell growth compared to the results of single drug treatment alone. MK2206 enhanced AZD6244-induced Bim overexpression and apoptosis in A549 and H157 cells. When we tested the combination of AZD6244 and MK2206 at ratios of 8∶1, 4∶1, 2∶1, and 1∶8, we found that the synergistic effect of the combination therapy was ratio-dependent. At ratios of 8∶1, 4∶1, and 2∶1, the drug combination consistently demonstrated synergy, whereas decreasing the ratio to 1∶8 resulted in a loss of synergy and produced an additive or antagonistic effect in most cell lines. Furthermore, the AZD6244-MK2206 combination therapy showed synergy in the suppression of A549 and H157 xenograft tumor growth and increased mean animal survival time. The AZD6244-MK2206 combination therapy resulted in effective inhibition of both p-ERK and p-AKT expression in tumor tissue. In addition, a significant increase of apoptosis was detected in tumor tissue from mice treated with AZD6244-MK2206 compared with that from the single agent treated mice. Our study suggests that the combination of AZD6244 and MK2206 has a significant synergistic effect on tumor growth in vitro and in vivo and leads to increased survival rates in mice bearing highly aggressive human lung tumors.

Background Evaluation of cancer biomarkers from blood could significantly enable biomarker assessment by providing a relatively non-invasive source of representative tumor material. Circulating Tumor Cells (CTCs) isolated from blood of metastatic cancer patients hold significant promise in this regard. Methodology/Principal Findings Using spiked tumor-cells we evaluated CTC capture on different CTC technology platforms, including CellSearch® and two biochip platforms, and used the isolated CTCs to develop and optimize assays for molecular characterization of CTCs. We report similar performance for the various platforms tested in capturing CTCs, and find that capture efficiency is dependent on the level of EpCAM expression. We demonstrate that captured CTCs are amenable to biomarker analyses such as HER2 status, qRT-PCR for breast cancer subtype markers, KRAS mutation detection, and EGFR staining by immunofluorescence (IF). We quantify cell surface expression of EGFR in metastatic lung cancer patient samples. In addition, we determined HER2 status by IF and FISH in CTCs from metastatic breast cancer patients. In the majority of patients (89%) we found concordance with HER2 status from patient tumor tissue, though in a subset of patients (11%), HER2 status in CTCs differed from that observed in the primary tumor. Surprisingly, we found CTC counts to be higher in ER+ patients in comparison to HER2+ and triple negative patients, which could be explained by low EpCAM expression and a more mesenchymal phenotype of tumors belonging to the basal-like molecular subtype of breast cancer. Conclusions/Significance Our data suggests that molecular characterization from captured CTCs is possible and can potentially provide real-time information on biomarker status. In this regard, CTCs hold significant promise as a source of tumor material to facilitate clinical biomarker evaluation. However, limitations exist from a purely EpCAM based capture system and addition of antibodies to mesenchymal markers could further improve CTC capture efficiency to enable routine biomarker analysis from CTCs.

Therapies consisting of a combination of agents are an attractive proposition, especially in the context of diseases such as cancer, which can manifest with a variety of tumor types in a single case. However uncovering usable drug combinations is expensive both financially and temporally. By employing computational methods to identify candidate combinations with a greater likelihood of success we can avoid these problems, even when the amount of data is prohibitively large. HITTING SET is a combinatorial problem that has useful application across many fields, however as it is NP-complete it is traditionally considered hard to solve exactly. We introduce a more general version of the problem (α,β,d)-HITTING SET, which allows more precise control over how and what the hitting set targets. Employing the framework of Parameterized Complexity we show that despite being NP-complete, the ((α,β,d)-HITTING SET problem is fixed-parameter tractable with a kernel of size O(αdkd) when we parameterize by the size k of the hitting set and the maximum number a of the minimum number of hits, and taking the maximum degree d of the target sets as a constant. We demonstrate the application of this problem to multiple drug selection for cancer therapy, showing the flexibility of the problem in tailoring such drug sets. The fixed-parameter tractability result indicates that for low values of the parameters the problem can be solved quickly using exact methods. We also demonstrate that the problem is indeed practical, with computation times on the order of 5 seconds, as compared to previous Hitting Set applications using the same dataset which exhibited times on the order of 1 day, even with relatively relaxed notions for what constitutes a low value for the parameters. Furthermore the existence of a kernelization for ((α,β,d)-HITTING SET indicates that the problem is readily scalable to large datasets. © 2010 Mellor et al.

Background Carbonic anhydrase IX (CAIX) is a membrane spanning protein involved in the enzymatic regulation of tumor acid-base balance. CAIX has been shown to be elevated in a number of hypoxic tumor types. The purpose of this study was to determine the efficiency of intact and IgG fragments of cG250 to target CAIX in vivo in a hypoxic tumor model. Methodology/Principal Findings Conventional biodistribution studies were performed with 111In-DO3A-cG250, 111In-DO3A-F(ab')2-cG250 and 111In-DO3A-Fab-cG250. Additional ex vivo analysis of the tumor was performed with markers for tumor hypoxia, blood perfusion and endogenous CAIX expression. All four data sets were digitally correlated to determine the optimal agent for determining hypoxia in a HT29 colon cancer xenograft. The HT29 human colorectal tumor xenografts show strong CAIX expression in hypoxic areas of poor blood perfusion. The intact IgG had an initial high focal uptake at the periphery of these hypoxic regions and penetration into the areas of highest CAIX expression over the 7-day study period. The lower molecular weight antibody fragments had a faster uptake into areas of high CAIX expression, but had a much lower absolute uptake at the optimal imaging times. Conclusions/Significance For the clinical detection of hypoxia induced CAIX using cG250 antibody based agents, imaging with the intact IgG at 7 days post injection would allow for the most sensitive and accurate detection of CAIX.

International audience; BACKGROUND: Angiogenesis is the target of several agents in the treatment of malignancies, including renal cell carcinoma (RCC). There is a real need for surrogate biomarkers that can predict selection of patients who may benefit from antiangiogenic therapies, prediction of disease outcome and which may improve the knowledge regarding mechanism of action of these treatments. Tyrosine kinase inhibitors (TKI) have proven efficacy in metastatic RCC (mRCC). However, the molecular mechanisms underlying the clinical response to these drugs remain unclear. METHODOLOGY/PRINCIPAL FINDINGS: The present study aimed to identify molecular biomarkers associated with the response to sunitinib, a Tyrosine kinase inhibitor. To evaluate this relationship, primary tumors from 23 metastatic RCC patients treated by sunitinib were analyzed for a panel of 16 biomarkers involved in tumor pathways targeted by sunitinib, using real-time quantitative reverse-transcriptase PCR. Nine of the 23 patients (39%) responded to sunitinib. Among transcripts analyzed, only the levels of vascular endothelial growth factor (VEGF) soluble isoforms (VEGF(121) and VEGF(165)) were associated with the response to sunitinib (P = 0.04 for both). Furthermore, the ratio of VEGF soluble isoforms (VEGF(121)/VEGF(165)) was significantly associated with prognosis (P = 0.02). CONCLUSIONS: This preliminary study provides a promising tool that might help in the management of metastatic RCC, and could be extended to other tumors treated by TKI.

Recent advances in structural bioinformatics have enabled the prediction of protein-drug off-targets based on their ligand binding sites. Concurrent developments in systems biology allow for prediction of the functional effects of system perturbations using large-scale network models. Integration of these two capabilities provides a framework for evaluating metabolic drug response phenotypes in silico. This combined approach was applied to investigate the hypertensive side effect of the cholesteryl ester transfer protein inhibitor torcetrapib in the context of human renal function. A metabolic kidney model was generated in which to simulate drug treatment. Causal drug off-targets were predicted that have previously been observed to impact renal function in gene-deficient patients and may play a role in the adverse side effects observed in clinical trials. Genetic risk factors for drug treatment were also predicted that correspond to both characterized and unknown renal metabolic disorders as well as cryptic genetic deficiencies that are not expected to exhibit a renal disorder phenotype except under drug treatment. This study represents a novel integration of structural and systems biology and a first step towards computational systems medicine. The methodology introduced herein has important implications for drug development and personalized medicine., Author Summary Pharmaceutical science is only beginning to scratch the surface on the exact mechanisms of drug action that lead to a drug's breadth of patient responses, both intended and side effects. Decades of clinical trials, molecular studies, and more recent computational analysis have sought to characterize the interactions between a drug and the cell's molecular machinery. We have devised an integrated computational approach to assess how a drug may affect a particular system, in our study the metabolism of the human kidney, and its capacity for filtration of the contents of the blood. We applied this approach to retrospectively investigate potential causal drug targets leading to increased blood pressure in participants of clinical trials for the drug torcetrapib in an effort to display how our approach could be directly useful in the drug development process. Our results suggest specific metabolic enzymes that may be directly responsible for the side effect. The drug screening framework we have developed could be used to link adverse side effects to particular drug targets, discover new uses for old drugs, identify biomarkers for metabolic disease and drug response, and suggest genetic or dietary risk factors to help guide personalized patient care.

Variants resistant to compounds specifically targeting HCV are observed in clinical trials. A multi-variant viral dynamic model was developed to quantify the evolution and in vivo fitness of variants in subjects dosed with monotherapy of an HCV protease inhibitor, telaprevir. Variant fitness was estimated using a model in which variants were selected by competition for shared limited replication space. Fitness was represented in the absence of telaprevir by different variant production rate constants and in the presence of telaprevir by additional antiviral blockage by telaprevir. Model parameters, including rate constants for viral production, clearance, and effective telaprevir concentration, were estimated from 1) plasma HCV RNA levels of subjects before, during, and after dosing, 2) post-dosing prevalence of plasma variants from subjects, and 3) sensitivity of variants to telaprevir in the HCV replicon. The model provided a good fit to plasma HCV RNA levels observed both during and after telaprevir dosing, as well as to variant prevalence observed after telaprevir dosing. After an initial sharp decline in HCV RNA levels during dosing with telaprevir, HCV RNA levels increased in some subjects. The model predicted this increase to be caused by pre-existing variants with sufficient fitness to expand once available replication space increased due to rapid clearance of wild-type (WT) virus. The average replicative fitness estimates in the absence of telaprevir ranged from 1% to 68% of WT fitness. Compared to the relative fitness method, the in vivo estimates from the viral dynamic model corresponded more closely to in vitro replicon data, as well as to qualitative behaviors observed in both on-dosing and long-term post-dosing clinical data. The modeling fitness estimates were robust in sensitivity analyses in which the restoration dynamics of replication space and assumptions of HCV mutation rates were varied., Author Summary Hepatitis C virus (HCV) infects an estimated 170 million people worldwide. Current treatment for HCV is 48 weeks of peginterferon and ribavirin of which patient response has large variability. Recently, specifically targeted antiviral therapies for HCV (STAT-C) are under clinical development and have shown potentials to improve response. Within a patient, HCV exists as quasispecies consisting of multiple variants. Models of HCV dynamics in response to peginterferon and ribavirin treatment have been proposed elsewhere, with HCV quasispecies assumed to respond homogenously to treatment. However, some of the HCV variants possess different degrees of sensitivity to a STAT-C compound, and therefore, selections and competitions among variants have been observed in patients treated with STAT-C. We have developed a viral dynamic model that quantifies the evolution of multiple variants in patients dosed in monotherapy with telaprevir, a compound specifically designed to inhibit HCV NS3.4A protease. Our novel modeling approach integrated data from both in vitro and in patients, both during and after dosing with telaprevir. Our model quantified the antiviral response to telaprevir and the in vivo fitness of variants. The model provides a useful framework for the designs of STAT-C during clinical development and for understanding the consequences of failure to STAT-C.

Background: Statins effectively lower total and plasma LDL-cholesterol, but the magnitude of decrease varies among individuals. To identify single nucleotide polymorphisms (SNPs) contributing to this variation, we performed a combined analysis of genome-wide association (GWA) results from three trials of statin efficacy. Methods and Principal Findings: Bayesian and standard frequentist association analyses were performed on untreated and statin-mediated changes in LDL-cholesterol, total cholesterol, HDL-cholesterol, and triglyceride on a total of 3932 subjects using data from three studies: Cholesterol and Pharmacogenetics (40 mg/day simvastatin, 6 weeks), Pravastatin/ Inflammation CRP Evaluation (40 mg/day pravastatin, 24 weeks), and Treating to New Targets (10 mg/day atorvastatin, 8 weeks). Genotype imputation was used to maximize genomic coverage and to combine information across studies. Phenotypes were normalized within each study to account for systematic differences among studies, and fixed-effects combined analysis of the combined sample were performed to detect consistent effects across studies. Two SNP associations were assessed as having posterior probability greater than 50%, indicating that they were more likely than not to be genuinely associated with statin-mediated lipid response. SNP rs8014194, located within the CLMN gene on chromosome 14, was strongly associated with statin-mediated change in total cholesterol with an 84% probability by Bayesian analysis, and a p-value exceeding conventional levels of genome-wide significance by frequentist analysis (P=1.8610 28 ). This SNP was less significantly associated with change in LDL-cholesterol (posterior probability=0.16, P=4.0610 26 ). Bayesian analysis also assigned a 51% probability that rs4420638, located in APOC1 and near APOE, was associated with change in LDL-cholesterol. Conclusions and Significance: Using combined GWA analysis from three clinical trials involving nearly 4,000 individuals treated with simvastatin, pravastatin, or atorvastatin, we have identified SNPs that may be associated with variation in the magnitude of statin-mediated reduction in total and LDL-cholesterol, including one in the CLMN gene for which statistical evidence for association exceeds conventional levels of genome-wide significance. Trial Registration: PRINCE and TNT are not registered. CAP is registered at Clinicaltrials.gov NCT00451828

Background In a cross-sectional study we studied the fasting serum DPP-4 enzymatic activity (sDPP-4) and the insulin resistance index (HOMA2-IR) in gliptin naive patients with type 2 diabetes and in non-alcoholic fatty liver disease (NAFLD) and in healthy controls (CNTRL). Methods and Findings sDPP-4 was measured by kinetic assay in 39 NAFLD (F/M:19/20, mean age: 47.42 yrs) and 82 type 2 diabetes (F/M:48/34, 62.8 yrs) patients and 26 (F/M:14/12, 35.3 yrs) controls. Definition of T2D group as patients with type 2 diabetes but without clinically obvious liver disease created non-overlapping study groups. Diagnosis of NAFLD was based on ultrasonography and the exclusion of other etiololgy. Patients in T2D and NAFLD groups were similarly obese. 75 g CH OGTT in 39 NAFLD patients: 24-NGT, 4-IGT or IFG (“prediabetes”), 11-type 2 diabetes. HOMA2-IR: CNTRL: 1.44; T2D-group: 2.62 (p = 0.046 vs CNTRL, parametric tests); NAFLD(NGTonly): 3.23 (p = 0.0013 vs CNTRL); NAFLD(IFG/IGT/type 2 diabetes): 3.82 (p

BACKGROUND: While it is accepted that a majority of invasive breast cancer progresses from a ductal carcinoma in situ (DCIS) precursor stage, very little is known about the factors that promote survival of DCIS neoplastic cells within the hypoxic, nutrient deprived intraductal microenvironment. METHODOLOGY AND PRINCIPAL FINDINGS: We examined the hypothesis that fresh human DCIS lesions contain pre-existing carcinoma precursor cells. We characterized these cells by full genome molecular cytogenetics (Illumina HumanCytoSNP profile), and signal pathway profiling (Reverse Phase Protein Microarray, 59 endpoints), and demonstrated that autophagy is required for survival and anchorage independent growth of the cytogenetically abnormal tumorigenic DCIS cells. Ex vivo organoid culture of fresh human DCIS lesions, without enzymatic treatment or sorting, induced the emergence of neoplastic epithelial cells exhibiting the following characteristics: a) spontaneous generation of hundreds of spheroids and duct-like 3-D structures in culture within 2-4 weeks; b) tumorigenicity in NOD/SCID mice; c) cytogenetically abnormal (copy number loss or gain in chromosomes including 1, 5, 6, 8, 13, 17) compared to the normal karyotype of the non-neoplastic cells in the source patient's breast tissue; d) in vitro migration and invasion of autologous breast stroma; and e) up-regulation of signal pathways linked to, and components of, cellular autophagy. Multiple autophagy markers were present in the patient's original DCIS lesion and the mouse xenograft. We tested whether autophagy was necessary for survival of cytogenetically abnormal DCIS cells. The lysosomotropic inhibitor (chloroquine phosphate) of autophagy completely suppressed the generation of DCIS spheroids/3-D structures, suppressed ex vivo invasion of autologous stroma, induced apoptosis, suppressed autophagy associated proteins including Atg5, AKT/PI3 Kinase and mTOR, eliminated cytogenetically abnormal spheroid forming cells from the organ culture, and abrogated xenograft tumor formation. CONCLUSIONS: Cytogenetically abnormal spheroid forming, tumorigenic, and invasive neoplastic epithelial cells pre-exist in human DCIS and require cellular autophagy for survival.

Despite the successful introduction of potent anti-cancer therapeutics, most of these drugs lead to only modest tumor-shrinkage or transient responses, followed by re-growth of tumors. Combining different compounds has resulted in enhanced tumor control and prolonged survival. However, methods querying the efficacy of such combinations have been hampered by limited scalability, analytical resolution, statistical feasibility, or a combination thereof. We have developed a theoretical framework modeling cellular viability as a stochastic lifetime process to determine synergistic compound combinations from high-throughput cellular screens. We apply our method to data derived from chemical perturbations of 65 cancer cell lines with two inhibitors. Our analysis revealed synergy for the combination of both compounds in subsets of cell lines. By contrast, in cell lines in which inhibition of one of both targets was sufficient to induce cell death, no synergy was detected, compatible with the topology of the oncogenically activated signaling network. In summary, we provide a tool for the measurement of synergy strength for combination perturbation experiments that might help define pathway topologies and direct clinical trials.

Contains fulltext : 87600.pdf (Publisher’s version ) (Open Access) HIV protease inhibitors must penetrate into cells to exert their action. Differences in the intracellular pharmacokinetics of these drugs may explain why some patients fail on therapy or suffer from drug toxicity. Yet, there is no information available on the intracellular levels of HIV protease inhibitors in HIV infected children, which is in part due to the large amount of sample that is normally required to measure the intracellular concentrations of these drugs. Therefore, we developed an ultra-fast and sensitive assay to measure the intracellular concentrations of HIV protease inhibitors in small amounts of peripheral blood mononuclear cells (PBMCs), and determined the intracellular concentrations of lopinavir and ritonavir in HIV infected children. An assay based on matrix-assisted laser desorption/ionization (MALDI)-triple quadrupole mass spectrometry was developed to determine the concentrations of HIV protease inhibitors in 10 microL plasma and 1x10(6) PBMCs. Precisions and accuracies were within the values set by the FDA for bioanalytical method validation. Lopinavir and ritonavir did not accumulate in PBMCs of HIV infected children. In addition, the intracellular concentrations of lopinavir and ritonavir correlated poorly to the plasma concentrations of these drugs. MALDI-triple quadrupole mass spectrometry is a new tool for ultra-fast and sensitive determination of drug concentrations which can be used, for example, to assess the intracellular pharmacokinetics of HIV protease inhibitors in HIV infected children.

Background Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. Methodology/Principal Findings In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic), and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as ‘brain group’ and ‘non-brain group’; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. Conclusions/Significance The methodology employed here may be used to facilitate disease-specific biomarker discovery.

Cancer patients show large individual variation in their response to chemotherapeutic agents. Gemcitabine (dFdC) and AraC, two cytidine analogues, have shown significant activity against a variety of tumors. We previously used expression data from a lymphoblastoid cell line-based model system to identify genes that might be important for the two drug cytotoxicity. In the present study, we used that same model system to perform a genome-wide association (GWA) study to test the hypothesis that common genetic variation might influence both gene expression and response to the two drugs. Specifically, genome-wide single nucleotide polymorphisms (SNPs) and mRNA expression data were obtained using the Illumina 550K(R) HumanHap550 SNP Chip and Affymetrix U133 Plus 2.0 GeneChip, respectively, for 174 ethnically-defined "Human Variation Panel" lymphoblastoid cell lines. Gemcitabine and AraC cytotoxicity assays were performed to obtain IC(50) values for the cell lines. We then performed GWA studies with SNPs, gene expression and IC(50) of these two drugs. This approach identified SNPs that were associated with gemcitabine or AraC IC(50) values and with the expression regulation for 29 genes or 30 genes, respectively. One SNP in IQGAP2 (rs3797418) was significantly associated with variation in both the expression of multiple genes and gemcitabine and AraC IC(50). A second SNP in TGM3 (rs6082527) was also significantly associated with multiple gene expression and gemcitabine IC50. To confirm the association results, we performed siRNA knock down of selected genes with expression that was associated with rs3797418 and rs6082527 in tumor cell and the knock down altered gemcitabine or AraC sensitivity, confirming our association study results. These results suggest that the application of GWA approaches using cell-based model systems, when combined with complementary functional validation, can provide insights into mechanisms responsible for variation in cytidine analogue response.

Membrane transporters play crucial roles in the cellular uptake and efflux of an array of small molecules including nutrients, environmental toxins, and many clinically used drugs. We hypothesized that common genetic variation in the proximal promoter regions of transporter genes contribute to observed variation in drug response. A total of 579 polymorphisms were identified in the proximal promoters (-250 to +50 bp) and flanking 5' sequence of 107 transporters in the ATP Binding Cassette (ABC) and Solute Carrier (SLC) superfamilies in 272 DNA samples from ethnically diverse populations. Many transporter promoters contained multiple common polymorphisms. Using a sliding window analysis, we observed that, on average, nucleotide diversity (pi) was lowest at approximately 300 bp upstream of the transcription start site, suggesting that this region may harbor important functional elements. The proximal promoters of transporters that were highly expressed in the liver had greater nucleotide diversity than those that were highly expressed in the kidney consistent with greater negative selective pressure on the promoters of kidney transporters. Twenty-one promoters were evaluated for activity using reporter assays. Greater nucleotide diversity was observed in promoters with strong activity compared to promoters with weak activity, suggesting that weak promoters are under more negative selective pressure than promoters with high activity. Collectively, these results suggest that the proximal promoter region of membrane transporters is rich in variation and that variants in these regions may play a role in interindividual variation in drug disposition and response.

Background: Von Willebrand factor (VWF) is critical for the in vivo survival of factor VIII (FVIII). Since FVIII half-life correlates with VWF-antigen pre-infusion levels, we hypothesized that VWF levels are useful to predict FVIII half-life. Methodology: Standardized half-life studies and analysis of pre-infusion VWF and VWF-propeptide levels were performed in a cohort of 38 patients with severe haemophilia A (FVIII

BACKGROUND: Studies of the genetic basis of drug response could help clarify mechanisms of drug action/metabolism, and facilitate development of genotype-based predictive tests of efficacy or toxicity (pharmacogenetics). OBJECTIVES: We conducted a systematic review and field synopsis of pharmacogenetic studies to quantify the scope and quality of available evidence in this field in order to inform future research. DATA SOURCES: Original research articles were identified in Medline, reference lists from 24 meta-analyses/systematic reviews/review articles and U.S. Food and Drug Administration website of approved pharmacogenetic tests. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, AND INTERVENTION CRITERIA: We included any study in which either intended or adverse response to drug therapy was examined in relation to genetic variation in the germline or cancer cells in humans. STUDY APPRAISAL AND SYNTHESIS METHODS: Study characteristics and data reported in abstracts were recorded. We further analysed full text from a random 10% subset of articles spanning the different subclasses of study. RESULTS: From 102,264 Medline hits and 1,641 articles from other sources, we identified 1,668 primary research articles (1987 to 2007, inclusive). A high proportion of remaining articles were reviews/commentaries (ratio of reviews to primary research approximately 25 ratio 1). The majority of studies (81.8%) were set in Europe and North America focussing on cancer, cardiovascular disease and neurology/psychiatry. There was predominantly a candidate gene approach using common alleles, which despite small sample sizes (median 93 [IQR 40-222]) with no trend to an increase over time, generated a high proportion (74.5%) of nominally significant (por=4 studies, only 31 meta-analyses were identified. The majority (69.4%) of end-points were continuous and likely surrogate rather than hard (binary) clinical end-points. CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS: The high expectation but limited translation of pharmacogenetic research thus far may be explained by the preponderance of reviews over primary research, small sample sizes, a mainly candidate gene approach, surrogate markers, an excess of nominally positive to truly positive associations and paucity of meta-analyses. Recommendations based on these findings should inform future study design to help realise the goal of personalised medicines. SYSTEMATIC REVIEW REGISTRATION NUMBER: Not Registered.

Background KRAS mutations occur in 35–45% of metastatic colorectal cancers (mCRC) and preclude responsiveness to EGFR-targeted therapy with cetuximab or panitumumab. However, less than 20% patients displaying wild-type KRAS tumors achieve objective response. Alterations in other effectors downstream of the EGFR, such as BRAF, and deregulation of the PIK3CA/PTEN pathway have independently been found to give rise to resistance. We present a comprehensive analysis of KRAS, BRAF, PIK3CA mutations, and PTEN expression in mCRC patients treated with cetuximab or panitumumab, with the aim of clarifying the relative contribution of these molecular alterations to resistance. Methodology/Principal Findings We retrospectively analyzed objective tumor response, progression-free (PFS) and overall survival (OS) together with the mutational status of KRAS, BRAF, PIK3CA and expression of PTEN in 132 tumors from cetuximab or panitumumab treated mCRC patients. Among the 106 non-responsive patients, 74 (70%) had tumors with at least one molecular alteration in the four markers. The probability of response was 51% (22/43) among patients with no alterations, 4% (2/47) among patients with 1 alteration, and 0% (0/24) for patients with ≥2 alterations (p

Background Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. Methods and Findings We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. Conclusion We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study.

Multiple drug class combinations are often prescribed for the treatment of schizophrenia, although antipsychotic monotherapy reflects FDA labeling and scientific justification for combinations is highly variable. This study was performed to gain current data regarding drug treatment of schizophrenia as practiced in the community and to assess the frequencies of off-label drug class combinations. 200 DSM IV-diagnosed schizophrenic patients recruited from community treatment sources participated in this cross-sectional study of community based schizophrenic patients. Drug class categories include First and Second Generation Antipsychotic drugs (FGA and SGA, respectively), mood stabilizers, antidepressants and anti-anxiety drugs. 25.5% of patients received antipsychotic monotherapy; 70% of patients received an antipsychotic and another drug class. A total of 42.5% of patients received more than one antipsychotic drug. The most common drug class combination was antipsychotic and a mood stabilizer. Stepwise linear discriminant function analysis identified the diagnosis of schizoaffective schizophrenia, history of having physically hurt someone and high scores on the General Portion of the PANSS rating scale predicted the combined use of an antipsychotic drug and a mood stabilizer. "Real world" pharmacotherapy of schizophrenia has developed its own established practice that is predominantly off-label and may have outstripped current data support. The economic implications for public sector payers are substantial as well as for the revenue of the pharmaceutical industry, whose promotion of off-label drug use is an increasingly problematic. These data are consistent with the recognition of the therapeutic limitations of both first and second generation antipsychotic drugs.

Endothelial inflammation with chemokine involvement contributes to acute coronary syndromes (ACS). We tested the hypothesis that variation in the chemokine gene CXCL5, which encodes epithelial neutrophil-activating peptide (ENA-78), is associated with ACS prognosis. We also investigated whether statin use, a potent modulator of inflammation, modifies CXCL5's association with outcomes and characterized the in vitro effect of atorvastatin on endothelial ENA-78 production. Using a prospective cohort of ACS patients (n = 704) the association of the CXCL5 -156 G>C polymorphism (rs352046) with 3-year all-cause mortality was estimated with hazard ratios (HR). Models were stratified by genotype and race. To characterize the influence of statins on this association, a statin*genotype interaction was tested. To validate ENA-78 as a statin target in inflammation typical of ACS, endothelial cells (HUVECs) were treated with IL-1beta and atorvastatin with subsequent quantification of CXCL5 expression and ENA-78 protein concentrations. C/C genotype was associated with a 2.7-fold increase in 3-year all-cause mortality compared to G/G+G/C (95%CI 1.19-5.87; p = 0.017). Statins significantly reduced mortality in G/G individuals only (58% relative risk reduction; p = 0.0009). In HUVECs, atorvastatin dose-dependently decreased IL-1beta-stimulated ENA-78 concentrations (p

Background Dysregulated PI3K/Akt signaling occurs commonly in breast cancers and is due to HER2 amplification, PI3K mutation or PTEN inactivation. The objective of this study was to determine the role of Akt activation in breast cancer as a function of mechanism of activation and whether inhibition of Akt signaling is a feasible approach to therapy. Methodology/Principal Findings A selective allosteric inhibitor of Akt kinase was used to interrogate a panel of breast cancer cell lines characterized for genetic lesions that activate PI3K/Akt signaling: HER2 amplification or PI3K or PTEN mutations in order to determine the biochemical and biologic consequences of inhibition of this pathway. A variety of molecular techniques and tissue culture and in vivo xenograft models revealed that tumors with mutational activation of Akt signaling were selectively dependent on the pathway. In sensitive cells, pathway inhibition resulted in D-cyclin loss, G1 arrest and induction of apoptosis, whereas cells without pathway activation were unaffected. Most importantly, the drug effectively inhibited Akt kinase and its downstream effectors in vivo and caused complete suppression of the growth of breast cancer xenografts with PI3K mutation or HER2 amplification, including models of the latter selected for resistance to Herceptin. Furthermore, chronic administration of the drug was well-tolerated, causing only transient hyperglycemia without gross toxicity to the host despite the pleiotropic normal functions of Akt. Conclusions/Significance These data demonstrate that breast cancers with PI3K mutation or HER2 amplification are selectively dependent on Akt signaling, and that effective inhibition of Akt in tumors is feasible and effective in vivo. These findings suggest that direct inhibition of Akt may represent a therapeutic strategy for breast and other cancers that are addicted to the pathway including tumors with resistant to Herceptin.

Cancers have been revealed to be extremely heterogenous in terms of the frequency and types of mutations present in cells from different malignant tumors. Thus, it is likely that uniform clinical treatment is not optimal for all patients, and that the development of individualized therapeutic regimens may be beneficial. We describe the generation of multiple, unique small peptides nine to thirty-four amino acids in length which, when labeled with the radioisotope (32)P, bind with vastly differing efficiencies to cell lines derived from different colon adenocarcinomas. In addition, the most effective of these peptides permanently transfers the (32)P radioisotope to colorectal cancer cellular proteins within two hours at a rate that is more than 150 times higher than in cell lines derived from other cancers or from the normal tissues tested. Currently, the only two FDA-approved radioimmunotherapeutic agents in use both employ antibodies directed against the B cell marker CD20 for the treatment of non-Hodgkin's lymphoma. By using the method described herein, large numbers of different (32)P-labeled peptides can be readily produced and assayed against a broad spectrum of cancer types. This report proposes the development and use of (32)P-labeled peptides as potential individualized peptide-binding therapies for the treatment of colon adenocarcinoma patients.

Background Though recent advancement in proteomics has provided a novel perspective on several distinct pathogenetic mechanisms leading to preterm birth (inflammation, bleeding), the etiology of most preterm births still remains elusive. We conducted a multidimensional proteomic analysis of the amniotic fluid to identify pathways related to preterm birth in the absence of inflammation or bleeding. Methodology/Principal Findings A proteomic fingerprint was generated from fresh amniotic fluid using surface-enhanced laser desorbtion ionization time of flight (SELDI-TOF) mass spectrometry in a total of 286 consecutive samples retrieved from women who presented with signs or symptoms of preterm labor or preterm premature rupture of the membranes. Inflammation and/or bleeding proteomic patterns were detected in 32% (92/286) of the SELDI tracings. In the remaining tracings, a hierarchical algorithm was applied based on descriptors quantifying similarity/dissimilarity among proteomic fingerprints. This allowed identification of a novel profile (Q-profile) based on the presence of 5 SELDI peaks in the 10–12.5 kDa mass area. Women displaying the Q-profile (mean±SD, gestational age: 25±4 weeks, n = 40) were more likely to deliver preterm despite expectant management in the context of intact membranes and normal amniotic fluid clinical results. Utilizing identification-centered proteomics techniques (fluorescence two-dimensional differential gel electrophoresis, robotic tryptic digestion and mass spectrometry) coupled with Protein ANalysis THrough Evolutionary Relationships (PANTHER) ontological classifications, we determined that in amniotic fluids with Q-profile the differentially expressed proteins are primarily involved in non-inflammatory biological processes such as protein metabolism, signal transduction and transport. Conclusion/Significance Proteomic profiling of amniotic fluid coupled with non-hierarchical bioinformatics algorithms identified a subgroup of patients at risk for preterm birth in the absence of intra-amniotic inflammation or bleeding, suggesting a novel pathogenetic pathway leading to preterm birth. The altered proteins may offer opportunities for therapeutical intervention and future drug development to prevent prematurity.

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution., Comment: 36 pages, 10 figures, revised version

Background: Multiple sclerosis (MS) is a heterogeneous disease. In order to understand the partial responsiveness to IFNs in Relapsing Remitting MS (RRMS) we studied the pharmacological effects of IFNs therapy. Methodology: Large scale gene expression profiling was performed on peripheral blood of 16 RRMS patients at baseline and one month after the start of IFNs therapy. Differential gene expression was analyzed by Significance Analysis of Microarrays. Subsequent expression analyses on specific genes were performed after three and six months of treatment. Peripheral blood mononuclear cells (PBMC) were isolated and stimulated in vitro with IFNs. Genes of interest were measured and validated by quantitative realtime PCR. An independent group of 30 RRMS patients was used for validation. Principal Findings: Pharmacogenomics revealed a marked variation in the pharmacological response to IFNs between patients. A total of 126 genes were upregulated in a subset of patients whereas in other patients these genes were downregulated or unchanged after one month of IFNs therapy. Most interestingly, we observed that the extent of the pharmacological response correlates negatively with the baseline expression of a specific set of 15 IFN response genes (R= 20.7208; p=0.0016). The negative correlation was maintained after three (R= 20.7363; p=0.0027) and six (R= 20.8154; p=0.0004) months of treatment, as determined by gene expression levels of the most significant correlating gene. Similar results were obtained in an independent group of patients (n=30; R= 20.4719; p=0.0085). Moreover, the ex vivo results could be confirmed by in vitro stimulation of purified PBMCs at baseline with IFNs indicating that differential responsiveness to IFNs is an intrinsic feature of peripheral blood cells at baseline. Conclusion: These data imply that the expression levels of IFN response genes in the peripheral blood of MS patients prior to treatment could serve a role as biomarker for the differential clinical response to IFNs. Citation: van Baarsen LGM, Vosslamber S, Tijssen M, Baggen JMC, van der Voort LF, et al. (2008) Pharmacogenomics of Interferon-s Therapy in Multiple Sclerosis

Poor angiogenesis is a major road block for tissue repair. The regeneration of virtually all tissues is limited by angiogenesis, given the diffusion of nutrients, oxygen, and waste products is limited to a few hundred micrometers. We postulated that co-transplantation of hematopoietic and mesenchymal stem/progenitor cells improves angiogenesis of tissue repair and hence the outcome of regeneration. In this study, we tested this hypothesis by using bone as a model whose regeneration is impaired unless it is vascularized. Hematopoietic stem/progenitor cells (HSCs) and mesenchymal stem/progenitor cells (MSCs) were isolated from each of three healthy human bone marrow samples and reconstituted in a porous scaffold. MSCs were seeded in micropores of 3D calcium phosphate (CP) scaffolds, followed by infusion of gel-suspended CD34(+) hematopoietic cells. Co-transplantation of CD34(+) HSCs and CD34(-) MSCs in microporous CP scaffolds subcutaneously in the dorsum of immunocompromised mice yielded vascularized tissue. The average vascular number of co-transplanted CD34(+) and MSC scaffolds was substantially greater than MSC transplantation alone. Human osteocalcin was expressed in the micropores of CP scaffolds and was significantly increased upon co-transplantation of MSCs and CD34(+) cells. Human nuclear staining revealed the engraftment of transplanted human cells in vascular endothelium upon co-transplantation of MSCs and CD34(+) cells. Based on additional in vitro results of endothelial differentiation of CD34(+) cells by vascular endothelial growth factor (VEGF), we adsorbed VEGF with co-transplanted CD34(+) and MSCs in the microporous CP scaffolds in vivo, and discovered that vascular number and diameter further increased, likely owing to the promotion of endothelial differentiation of CD34(+) cells by VEGF. Together, co-transplantation of hematopoietic and mesenchymal stem/progenitor cells may improve the regeneration of vascular dependent tissues such as bone, adipose, muscle and dermal grafts, and may have implications in the regeneration of internal organs.

Background SCN5A encodes the alpha-subunit (Na(v)1.5) of the principle Na(+) channel in the human heart. Genetic lesions in SCN5A can cause congenital long QT syndrome (LQTS) variant 3 (LQT-3) in adults by disrupting inactivation of the Na(v)1.5 channel. Pharmacological targeting of mutation-altered Na(+) channels has proven promising in developing a gene-specific therapeutic strategy to manage specifically this LQTS variant. SCN5A mutations that cause similar channel dysfunction may also contribute to sudden infant death syndrome (SIDS) and other arrhythmias in newborns, but the prevalence, impact, and therapeutic management of SCN5A mutations may be distinct in infants compared with adults. Methods and results Here, in a multidisciplinary approach, we report a de novo SCN5A mutation (F1473C) discovered in a newborn presenting with extreme QT prolongation and differential responses to the Na(+) channel blockers flecainide and mexiletine. Our goal was to determine the Na(+) channel phenotype caused by this severe mutation and to determine whether distinct effects of different Na(+) channel blockers on mutant channel activity provide a mechanistic understanding of the distinct therapeutic responsiveness of the mutation carrier. Sequence analysis of the proband revealed the novel missense SCN5A mutation (F1473C) and a common variant in KCNH2 (K897T). Patch clamp analysis of HEK 293 cells transiently transfected with wild-type or mutant Na(+) channels revealed significant changes in channel biophysics, all contributing to the proband's phenotype as predicted by in silico modeling. Furthermore, subtle differences in drug action were detected in correcting mutant channel activity that, together with both the known genetic background and age of the patient, contribute to the distinct therapeutic responses observed clinically. Significance The results of our study provide further evidence of the grave vulnerability of newborns to Na(+) channel defects and suggest that both genetic background and age are particularly important in developing a mutation-specific therapeutic personalized approach to manage disorders in the young.

Many higher plants contain novel metabolites with antimicrobial, antifungal and antiviral properties. However, in the developed world almost all clinically used chemotherapeutics have been produced by in vitro chemical synthesis. Exceptions, like taxol and vincristine, were structurally complex metabolites that were difficult to synthesize in vitro. Many non-natural, synthetic drugs cause severe side effects that were not acceptable except as treatments of last resort for terminal diseases such as cancer. The metabolites discovered in medicinal plants may avoid the side effect of synthetic drugs, because they must accumulate within living cells. The aim here was to test an aqueous extract from the young developing leaves of willow (Salix safsaf, Salicaceae) trees for activity against human carcinoma cells in vivo and in vitro. In vivo Ehrlich Ascites Carcinoma Cells (EACC) were injected into the intraperitoneal cavity of mice. The willow extract was fed via stomach tube. The (EACC) derived tumor growth was reduced by the willow extract and death was delayed (for 35 days). In vitro the willow extract could kill the majority (75%–80%) of abnormal cells among primary cells harvested from seven patients with acute lymphoblastic leukemia (ALL) and 13 with AML (acute myeloid leukemia). DNA fragmentation patterns within treated cells inferred targeted cell death by apoptosis had occurred. The metabolites within the willow extract may act as tumor inhibitors that promote apoptosis, cause DNA damage, and affect cell membranes and/or denature proteins.

Background: Histone deacetylase inhibitors (HDACis) are promising anticancer drugs; however, the molecular mechanisms leading to HDACi-induced cell death have not been well understood and no clear mechanism of resistance has been elucidated to explain limited efficacy of HDACis in clinical trials. Methods and Findings: Here, we show that protein levels of checkpoint kinase 1 (Chk1), which has a major role in G2 cell cycle checkpoint regulation, was markedly reduced at the protein and transcriptional levels in lung cancer cells treated with pan-and selective HDACis LBH589, scriptaid, valproic acid, apicidin, and MS-275. In HDACi treated cells Chk1 function was impaired as determined by decreased inhibitory phosphorylation of cdc25c and its downstream target cdc2 and increased expression of cdc25A and phosphorylated histone H3, a marker of mitotic entry. In time course experiments, Chk1 downregulation occurred after HDACi treatment, preceding apoptosis. Ectopic expression of Chk1 overcame HDACiinduced cell death, and pretreating cells with the cdc2 inhibitor purvalanol A blocked entry into mitosis and prevented cell death by HDACis. Finally, pharmacological inhibition of Chk1 showed strong synergistic effect with LBH589 in lung cancer cells. Conclusions: These results define a pathway through which Chk1 inhibition can mediate HDACi-induced mitotic entry and cell death and suggest that Chk1 could be an early pharmacodynamic marker to assess HDACi efficacy in clinical samples.

David Mangelsdorf and colleagues show that nuclear receptor expression is strongly associated with clinical outcomes of lung cancer patients, and this expression profile is a potential prognostic signature for lung cancer patient survival time, particularly for individuals with early stage disease., Background The identification of prognostic tumor biomarkers that also would have potential as therapeutic targets, particularly in patients with early stage disease, has been a long sought-after goal in the management and treatment of lung cancer. The nuclear receptor (NR) superfamily, which is composed of 48 transcription factors that govern complex physiologic and pathophysiologic processes, could represent a unique subset of these biomarkers. In fact, many members of this family are the targets of already identified selective receptor modulators, providing a direct link between individual tumor NR quantitation and selection of therapy. The goal of this study, which begins this overall strategy, was to investigate the association between mRNA expression of the NR superfamily and the clinical outcome for patients with lung cancer, and to test whether a tumor NR gene signature provided useful information (over available clinical data) for patients with lung cancer. Methods and Findings Using quantitative real-time PCR to study NR expression in 30 microdissected non-small-cell lung cancers (NSCLCs) and their pair-matched normal lung epithelium, we found great variability in NR expression among patients' tumor and non-involved lung epithelium, found a strong association between NR expression and clinical outcome, and identified an NR gene signature from both normal and tumor tissues that predicted patient survival time and disease recurrence. The NR signature derived from the initial 30 NSCLC samples was validated in two independent microarray datasets derived from 442 and 117 resected lung adenocarcinomas. The NR gene signature was also validated in 130 squamous cell carcinomas. The prognostic signature in tumors could be distilled to expression of two NRs, short heterodimer partner and progesterone receptor, as single gene predictors of NSCLC patient survival time, including for patients with stage I disease. Of equal interest, the studies of microdissected histologically normal epithelium and matched tumors identified expression in normal (but not tumor) epithelium of NGFIB3 and mineralocorticoid receptor as single gene predictors of good prognosis. Conclusions NR expression is strongly associated with clinical outcomes for patients with lung cancer, and this expression profile provides a unique prognostic signature for lung cancer patient survival time, particularly for those with early stage disease. This study highlights the potential use of NRs as a rational set of therapeutically tractable genes as theragnostic biomarkers, and specifically identifies short heterodimer partner and progesterone receptor in tumors, and NGFIB3 and MR in non-neoplastic lung epithelium, for future detailed translational study in lung cancer. Please see later in the article for the Editors' Summary, Editors' Summary Background Lung cancer, the most common cause of cancer-related death, kills 1.3 million people annually. Most lung cancers are “non-small-cell lung cancers” (NSCLCs), and most are caused by smoking. Exposure to chemicals in smoke causes changes in the genes of the cells lining the lungs that allow the cells to grow uncontrollably and to move around the body. How NSCLC is treated and responds to treatment depends on its “stage.” Stage I tumors, which are small and confined to the lung, are removed surgically, although chemotherapy is also sometimes given. Stage II tumors have spread to nearby lymph nodes and are treated with surgery and chemotherapy, as are some stage III tumors. However, because cancer cells in stage III tumors can be present throughout the chest, surgery is not always possible. For such cases, and for stage IV NSCLC, where the tumor has spread around the body, patients are treated with chemotherapy alone. About 70% of patients with stage I and II NSCLC but only 2% of patients with stage IV NSCLC survive for five years after diagnosis; more than 50% of patients have stage IV NSCLC at diagnosis. Why Was This Study Done? Patient responses to treatment vary considerably. Oncologists (doctors who treat cancer) would like to know which patients have a good prognosis (are likely to do well) to help them individualize their treatment. Consequently, the search is on for “prognostic tumor biomarkers,” molecules made by cancer cells that can be used to predict likely clinical outcomes. Such biomarkers, which may also be potential therapeutic targets, can be identified by analyzing the overall pattern of gene expression in a panel of tumors using a technique called microarray analysis and looking for associations between the expression of sets of genes and clinical outcomes. In this study, the researchers take a more directed approach to identifying prognostic biomarkers by investigating the association between the expression of the genes encoding nuclear receptors (NRs) and clinical outcome in patients with lung cancer. The NR superfamily contains 48 transcription factors (proteins that control the expression of other genes) that respond to several hormones and to diet-derived fats. NRs control many biological processes and are targets for several successful drugs, including some used to treat cancer. What Did the Researchers Do and Find? The researchers analyzed the expression of NR mRNAs using “quantitative real-time PCR” in 30 microdissected NSCLCs and in matched normal lung tissue samples (mRNA is the blueprint for protein production). They then used an approach called standard classification and regression tree analysis to build a prognostic model for NSCLC based on the expression data. This model predicted both survival time and disease recurrence among the patients from whom the tumors had been taken. The researchers validated their prognostic model in two large independent lung adenocarcinoma microarray datasets and in a squamous cell carcinoma dataset (adenocarcinomas and squamous cell carcinomas are two major NSCLC subtypes). Finally, they explored the roles of specific NRs in the prediction model. This analysis revealed that the ability of the NR signature in tumors to predict outcomes was mainly due to the expression of two NRs—the short heterodimer partner (SHP) and the progesterone receptor (PR). Expression of either gene could be used as a single gene predictor of the survival time of patients, including those with stage I disease. Similarly, the expression of either nerve growth factor induced gene B3 (NGFIB3) or mineralocorticoid receptor (MR) in normal tissue was a single gene predictor of a good prognosis. What Do These Findings Mean? These findings indicate that the expression of NR mRNA is strongly associated with clinical outcomes in patients with NSCLC. Furthermore, they identify a prognostic NR expression signature that provides information on the survival time of patients, including those with early stage disease. The signature needs to be confirmed in more patients before it can be used clinically, and researchers would like to establish whether changes in mRNA expression are reflected in changes in protein expression if NRs are to be targeted therapeutically. Nevertheless, these findings highlight the potential use of NRs as prognostic tumor biomarkers. Furthermore, they identify SHP and PR in tumors and two NRs in normal lung tissue as molecules that might provide new targets for the treatment of lung cancer and new insights into the early diagnosis, pathogenesis, and chemoprevention of lung cancer. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000378. The Nuclear Receptor Signaling Atlas (NURSA) is consortium of scientists sponsored by the US National Institutes of Health that provides scientific reagents, datasets, and educational material on nuclear receptors and their co-regulators to the scientific community through a Web-based portal The Cancer Prevention and Research Institute of Texas (CPRIT) provides information and resources to anyone interested in the prevention and treatment of lung and other cancers The US National Cancer Institute provides detailed information for patients and professionals about all aspects of lung cancer, including information on non-small-cell carcinoma and on tumor markers (in English and Spanish) Cancer Research UK also provides information about lung cancer and information on how cancer starts MedlinePlus has links to other resources about lung cancer (in English and Spanish) Wikipedia has a page on nuclear receptors (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)

Background: Flavopiridol is a cyclin-dependent kinase inhibitor in phase II clinical development for treatment of various forms of cancer. When administered with a pharmacokinetically (PK)-directed dosing schedule, flavopiridol exhibited striking activity in patients with refractory chronic lymphocytic leukemia. This study aimed to evaluate pharmacogenetic factors associated with inter-individual variability in pharmacokinetics and outcomes associated with flavopiridol therapy. Methodology/Principal Findings: Thirty-five patients who received single-agent flavopiridol via the PK-directed schedule were genotyped for 189 polymorphisms in genes encoding 56 drug metabolizing enzymes and transporters. Genotypes were evaluated in univariate and multivariate analyses as covariates in a population PK model. Transport of flavopiridol and its glucuronide metabolite was evaluated in uptake assays in HEK-293 and MDCK-II cells transiently transfected with SLCO1B1. Polymorphisms in ABCC2, ABCG2, UGT1A1, UGT1A9, and SLCO1B1 were found to significantly correlate with flavopiridol PK in univariate analysis. Transport assay results indicated both flavopiridol and flavopiridol-glucuronide are substrates of the SLCO1B1/OATP1B1 transporter. Covariates incorporated into the final population PK model included bilirubin, SLCO1B1 rs11045819 and ABCC2 rs8187710. Associations were also observed between genotype and response. To validate these findings, a second set of data with 51 patients was evaluated, and overall trends for associations between PK and PGx were found to be consistent. Conclusions/Significance: Polymorphisms in transport genes were found to be associated with flavopiridol disposition and outcomes. Observed clinical associations with SLCO1B1 were functionally validated indicating for the first time its relevance as a transporter of flavopiridol and its glucuronide metabolite. A second 51-patient dataset indicated similar trends between genotype in the SLCO1B1 and other candidate genes, thus providing support for these findings. Further study in larger patient populations will be necessary to fully characterize and validate the clinical impact of polymorphisms in SLCO1B1 and other transporter and metabolizing enzyme genes on outcomes from flavopiridol therapy.

AZD6244 (ARRY-142886) is an inhibitor of MEK1/2 and can inhibit cell proliferation or induce apoptosis in a cell-type dependent manner. The precise molecular mechanism of AZD6244-induced apoptosis is not clear. To investigate mechanisms of AZD6244 induced apoptosis in human lung cancer, we determined the molecular changes of two subgroups of human lung cancer cell lines that are either sensitive or resistant to AZD6244 treatment. We found that AZD6244 elicited a large increase of Bim proteins and a smaller increase of PUMA and NOXA proteins, and induced cell death in sensitive lung cancer cell lines, but had no effect on other Bcl-2 related proteins in those cell lines. Knockdown of Bim by siRNA greatly increased the IC(50) and reduced apoptosis for AZD6244 treated cells. We also found that levels of endogenous p-Thr32-FOXO3a and p-Ser253-FOXO3a were lower in AZD6244-sensitive cells than in AZD6244-resistant cells. In the sensitive cells, AZD6244 induced FOXO3a nuclear translocation required for Bim activation. Moreover, the silencing of FOXO3a by siRNA abrogated AZD6244-induced cell apoptosis. In addition, we found that transfection of constitutively active AKT up-regulated p-Thr32-FOXO3a and p-Ser253-FOXO3a expression and inhibited AZD6244-induced Bim expression in sensitive cells. These results show that Bim plays an important role in AZD6244-induced apoptosis in lung cancer cells and that the PI3K/AKT/FOXO3a pathway is involved in Bim regulation and susceptibility of lung cancer cells to AZD6244. These results have implications in the development of strategies to overcome resistance to MEK inhibitors.

Background The beta2-adrenergic receptor (beta2AR) is expressed on numerous cell-types including airway smooth muscle cells and cardiomyocytes. Drugs (agonists or antagonists) acting at these receptors for treatment of asthma, chronic obstructive pulmonary disease, and heart failure show substantial interindividual variability in response. The ADRB2 gene is polymorphic in noncoding and coding regions, but virtually all ADRB2 association studies have utilized the two common nonsynonymous coding SNPs, often reaching discrepant conclusions. Methodology/principal findings We constructed the 8 common ADRB2 haplotypes derived from 26 polymorphisms in the promoter, 5'UTR, coding, and 3'UTR of the intronless ADRB2 gene. These were cloned into an expression construct lacking a vector-based promoter, so that beta2AR expression was driven by its promoter, and steady state expression could be modified by polymorphisms throughout ADRB2 within a haplotype. "Whole-gene" transfections were performed with COS-7 cells and revealed 4 haplotypes with increased cell surface beta2AR protein expression compared to the others. Agonist-promoted downregulation of beta2AR protein expression was also haplotype-dependent, and was found to be increased for 2 haplotypes. A phylogenetic tree of the haplotypes was derived and annotated by cellular phenotypes, revealing a pattern potentially driven by expression. Conclusions/significance Thus for obstructive lung disease, the initial bronchodilator response from intermittent administration of beta-agonist may be influenced by certain beta2AR haplotypes (expression phenotypes), while other haplotypes may influence tachyphylaxis during the response to chronic therapy (downregulation phenotypes). An ideal clinical outcome of high expression and less downregulation was found for two haplotypes. Haplotypes may also affect heart failure antagonist therapy, where beta2AR increase inotropy and are anti-apoptotic. The haplotype-specific expression and regulation phenotypes found in this transfection-based system suggest that the density of genetic information in the form of these haplotypes, or haplotype-clusters with similar phenotypes can potentially provide greater discrimination of phenotype in human disease and pharmacogenomic association studies.

Background Although multicompartment systems made of single unilamellar vesicles offer the potential to outperform single compartment systems widely used in analytic, synthetic, and medical applications, their use has remained marginal to date. On the one hand, this can be attributed to the binary character of the majority of the current tethering protocols that impedes the implementation of real multicomponent or multifunctional systems. On the other hand, the few tethering protocols theoretically providing multicompartment systems composed of several distinct vesicle populations suffer from the readjustment of the vesicle formation procedure as well as from the loss of specificity of the linking mechanism over time. Methodology/Principal Findings In previous studies, we presented implementations of multicompartment systems and resolved the readjustment of the vesicle formation procedure as well as the loss of specificity by using linkers consisting of biotinylated DNA single strands that were anchored to phospholipid-grafted biotinylated PEG tethers via streptavidin as a connector. The systematic analysis presented herein provides evidences for the incorporation of phospholipid-grafted biotinylated PEG tethers to the vesicle membrane during vesicle formation, providing specific anchoring sites for the streptavidin loading of the vesicle membrane. Furthermore, DNA-mediated vesicle-vesicle self-assembly was found to be sequence-dependent and to depend on the presence of monovalent salts. Conclusions/Significance This study provides a solid basis for the implementation of multi-vesicle assemblies that may affect at least three distinct domains. (i) Analysis. Starting with a minimal system, the complexity of a bottom-up system is increased gradually facilitating the understanding of the components and their interaction. (ii) Synthesis. Consecutive reactions may be implemented in networks of vesicles that outperform current single compartment bioreactors in versatility and productivity. (iii) Personalized medicine. Transport and targeting of long-lived, pharmacologically inert prodrugs and their conversion to short-lived, active drug molecules directly at the site of action may be accomplished if multi-vesicle assemblies of predefined architecture are used.

We report the first genome-wide association study (GWAS) whose sample size (1,053 Swedish subjects) is sufficiently powered to detect genome-wide significance (p, Author Summary Recently, geneticists have begun assaying hundreds of thousands of genetic markers covering the entire human genome to systematically search for and identify genes that cause disease. We have extended this “genome-wide association study” (GWAS) method by assaying ∼326,000 markers in 1,053 Swedish patients in order to identify genes that alter response to the anticoagulant drug warfarin. Warfarin is widely prescribed to reduce blood clotting in order to protect high-risk patients from stroke, thrombosis, and heart attack. But patients vary widely (20-fold) in the warfarin dose needed for proper blood thinning, which means that initial doses in some patients are too high (risking severe bleeding) or too low (risking serious illness). Our GWAS detected two genes (VKORC1, CYP2C9) already known to cause ∼40% of the variability in warfarin dose and discovered a new gene (CYP4F2) contributing 1%–2% of the variability. Since our GWAS searched the entire genome, additional genes having a major influence on warfarin dose might not exist or be found in the near-term. Hence, clinical trials assessing patient benefit from individualized dose forecasting based on a patient's genetic makeup at VKORC1, CYP2C9 and possibly CYP4F2 could provide state-of-the-art clinical benchmarks for warfarin use during the foreseeable future.

BACKGROUND: Cancer patients carrying mutations in the dihydropyrimidine dehydrogenase gene (DPYD) have a high risk to experience severe drug-adverse effects following chemotherapy with fluoropyrimidine drugs such as 5-fluorouracil (5-FU) or capecitabine. The pretreatment detection of this impairment of pyrimidine catabolism could prevent serious, potentially lethal side effects. As known deleterious mutations explain only a limited proportion of the drug-adverse events, we systematically searched for additional DPYD variations associated with enhanced drug toxicity. METHODOLOGY/PRINCIPAL FINDINGS: We performed a whole gene approach covering the entire coding region and compared DPYD genotype frequencies between cancer patients with good (n = 89) and with poor (n = 39) tolerance of a fluoropyrimidine-based chemotherapy regimen. Applying logistic regression analysis and sliding window approaches we identified the strongest association with fluoropyrimidine-related grade III and IV toxicity for the non-synonymous polymorphism c.496A>G (p.Met166Val). We then confirmed our initial results using an independent sample of 53 individuals suffering from drug-adverse-effects. The combined odds ratio calculated for 92 toxicity cases was 4.42 [95% CI 2.12-9.23]; p (trend)G with toxicity was particularly present in patients with gastroesophageal and breast cancer, but did not reach significance in patients with colorectal malignancies. CONCLUSION: Our results show compelling evidence that, at least in distinct tumor types, a common DPYD polymorphism strongly contributes to the occurrence of fluoropyrimidine-related drug adverse effects. Carriers of this variant could benefit from individual dose adjustment of the fluoropyrimidine drug or alternate therapies.

BackgroundGeneric antiretroviral therapy is the mainstay of HIV treatment in resource-limited settings, yet there is little evidence confirming the bioequivalence of generic and brand name formulations. We compared the steady-state pharmacokinetics of lamivudine, stavudine and nevirapine in HIV-infected subjects who were receiving a generic formulation (Triomune) or the corresponding brand formulations (Epivir, Zerit, and Viramune).Methodology/principal findingsAn open-label, randomized, crossover study was carried out in 18 HIV-infected Ugandan subjects stabilized on Triomune-40. Subjects received lamivudine (150 mg), stavudine (40 mg), and nevirapine (200 mg) in either the generic or brand formulation twice a day for 30 days, before switching to the other formulation. At the end of each treatment period, blood samples were collected over 12 h for pharmacokinetic analysis. The main outcome measures were the mean AUC(0-12h) and C(max). Bioequivalence was defined as a geometric mean ratio between the generic and brand name within the 90% confidence interval of 0.8-1.25. The geometric mean ratios and the 90% confidence intervals were: stavudine C(max), 1.3 (0.99-1.71) and AUC(0-12h), 1.1 (0.87-1.38); lamivudine C(max), 0.8 (0.63-0.98) and AUC(0-12h), 0.8 (0.65-0.99); and nevirapine C(max), 1.1 (0.95-1.23) and AUC(0-12h), 1.1 (0.95-1.31). The generic formulation was not statistically bioequivalent to the brand formulations during steady state, although exposures were comparable. A mixed random effects model identified about 50% intersubject variability in the pharmacokinetic parameters.Conclusions/significant findingsThese findings provide support for the use of Triomune in resource-limited settings, although identification of the sources of intersubject variability in these populations is critical.

A prominent feature of Parkinson's disease (PD) is the loss of dopamine in the striatum, and many therapeutic interventions for the disease are aimed at restoring dopamine signaling. Dopamine signaling includes the synthesis, storage, release, and recycling of dopamine in the presynaptic terminal and activation of pre- and post-synaptic receptors and various downstream signaling cascades. As an aid that might facilitate our understanding of dopamine dynamics in the pathogenesis and treatment in PD, we have begun to merge currently available information and expert knowledge regarding presynaptic dopamine homeostasis into a computational model, following the guidelines of biochemical systems theory. After subjecting our model to mathematical diagnosis and analysis, we made direct comparisons between model predictions and experimental observations and found that the model exhibited a high degree of predictive capacity with respect to genetic and pharmacological changes in gene expression or function. Our results suggest potential approaches to restoring the dopamine imbalance and the associated generation of oxidative stress. While the proposed model of dopamine metabolism is preliminary, future extensions and refinements may eventually serve as an in silico platform for prescreening potential therapeutics, identifying immediate side effects, screening for biomarkers, and assessing the impact of risk factors of the disease.

Background Effective therapy for HIV-infected individuals remains an unmet medical need. Promising clinical trials with dendritic cell (DC)-based immunotherapy consisting of autologous DC loaded with autologous virus have been reported, however, these approaches depend on large numbers of HIV virions to generate sufficient doses for even limited treatment regimens. Methodology/Principal Findings The present study describes a novel approach for RT-PCR amplification of HIV antigens. Previously, RT-PCR amplification of autologous viral sequences has been confounded by the high mutation rate of the virus which results in unreliable primer-template binding. To resolve this problem we developed a multiplex RT-PCR strategy that allows reliable strain-independent amplification of highly polymorphic target antigens from any patient and requires neither viral sequence data nor custom-designed PCR primers for each individual. We demonstrate the application of our RT-PCR process to amplify translationally-competent RNA encoding regions of Gag, Vpr, Rev and Nef. The products amplified using this method represent a complex mixture of autologous antigens encoded by viral quasispecies. We further demonstrate that DCs electroporated with in vitro-transcribed HIV RNAs are capable of stimulating poly-antigen-specific CD8+ T cell responses in vitro. Conclusion/Significance This study describes a strategy to overcome patient to patient viral diversity enabling strain-independent RT-PCR amplification of RNAs encoding sequence divergent quasispecies of Gag, Vpr, Rev and Nef from small volumes of infectious plasma. The approach allows creation of a completely autologous therapy that does not require advance knowledge of the HIV genomic sequences, does not have yield limitations and has no intact virus in the final product. The simultaneous use of autologous viral antigens and DCs may provoke broad patient-specific immune responses that could potentially induce effective control of viral loads in the absence of conventional antiretroviral drug therapy.