Parametric Model of Combination Therapy for Non-Hodgkin Lymphoma.
Parametric model of combination therapy for non-hodgkin lymphoma.
Filed under: Drug and Alcohol Rehabilitation
PLoS One. 2012; 7(12): e51736
Weiss RF, Miller MG, Cronin JF, Hensley HH, Joshi ID, Smith MR
The development and clinical testing of drug combinations for the treatment of Non-Hodgkin Lymphoma (NHL) and other cancers has recently shown great promise. However, determining the optimum combination and its associated dosages for maximum efficacy and minimum side effects is still a challenge. This paper describes a parametric analysis of the dynamics of malignant B-cells and the effects of an anti-sense oligonucleotide targeted to BCL-2 (as-bcl-2), anti-CD-20 (rituximab) and their combination, for a SCID mouse human lymphoma xenograft model of NHL. Our parametric model is straightforward. Several mechanisms of malignant B-cell birth and death in the nodal micro-environment are simulated. Cell death is accelerated by hypoxia and starvation induced by tumor scale, by modification of anti-apoptosis with as-bcl-2, and by direct kill effects of rituximab (cell kill by cytotoxic immune cells is not included, due to the absence of an immune system in the corresponding experiments). We show that the cell population dynamics in the control animals are primarily determined by K*, the ratio of rate constants for malignant cell death, K(d), and cell birth, K(b). Tumor growth with independent treatments is reproduced by the model, and is used to predict their effect when administered in combination. Malignant cell lifetimes are derived to provide a quantitative comparison of the efficacy of these treatments. Future experimental and clinical applications of the model are discussed.
HubMed – drug
Residual expression of reprogramming factors affects the transcriptional program and epigenetic signatures of induced pluripotent stem cells.
Filed under: Drug and Alcohol Rehabilitation
PLoS One. 2012; 7(12): e51711
Sommer CA, Christodoulou C, Gianotti-Sommer A, Shen SS, Sailaja BS, Hezroni H, Spira A, Meshorer E, Kotton DN, Mostoslavsky G
Delivery of the transcription factors Oct4, Klf4, Sox2 and c-Myc via integrating viral vectors has been widely employed to generate induced pluripotent stem cell (iPSC) lines from both normal and disease-specific somatic tissues, providing an invaluable resource for medical research and drug development. Residual reprogramming transgene expression from integrated viruses nevertheless alters the biological properties of iPSCs and has been associated with a reduced developmental competence both in vivo and in vitro. We performed transcriptional profiling of mouse iPSC lines before and after excision of a polycistronic lentiviral reprogramming vector to systematically define the overall impact of persistent transgene expression on the molecular features of iPSCs. We demonstrate that residual expression of the Yamanaka factors prevents iPSCs from acquiring the transcriptional program exhibited by embryonic stem cells (ESCs) and that the expression profiles of iPSCs generated with and without c-Myc are indistinguishable. After vector excision, we find 36% of iPSC clones show normal methylation of the Gtl2 region, an imprinted locus that marks ESC-equivalent iPSC lines. Furthermore, we show that the reprogramming factor Klf4 binds to the promoter region of Gtl2. Regardless of Gtl2 methylation status, we find similar endodermal and hepatocyte differentiation potential comparing syngeneic Gtl2(ON) vs Gtl2(OFF) iPSC clones. Our findings provide new insights into the reprogramming process and emphasize the importance of generating iPSCs free of any residual transgene expression.
HubMed – drug
Prophylactic Valproic Acid Treatment Prevents Schizophrenia-Related Behaviour in Disc1-L100P Mutant Mice.
Filed under: Drug and Alcohol Rehabilitation
PLoS One. 2012; 7(12): e51562
Lipina TV, Haque FN, McGirr A, Boutros PC, Berger T, Mak TW, Roder JC, Wong AH
Schizophrenia is a neurodevelopmental disorder with onset early in adulthood. Disrupted-In-Schizophrenia-1 (DISC1) is a susceptibility gene for schizophrenia and other psychiatric disorders. Disc1-L100P mutant mice show behaviors relevant to schizophrenia at 12 weeks, but not at 8 weeks of age, and may be useful for investigating the onset of schizophrenia in early adulthood.We investigated whether early valproic acid treatment would prevent behavioral, cellular and gene expression abnormalities in Disc1-L100P mutants.Valproic acid prevented hyperactivity and deficits in prepulse inhibition and latent inhibition in Disc1-L100P mice. Genome-wide transcription profiling identified Lcn2 (lipocalin2) transcripts as being elevated by the Disc1 mutation and corrected by valproate. Disc1-L100P mice also had increased glial cell numbers in the subventricular zone, which was normalized by valproate. Genetic deletion of Lcn2 normalized glial cell numbers and behavior in Disc1-L100P mutants.Pharmacological treatments are a feasible way of preventing abnormal behaviour in a genetic model of schizophrenia. Lcn2 is a potential novel drug target for early intervention in schizophrenia.
HubMed – drug
Medication adherence in the general population.
Filed under: Drug and Alcohol Rehabilitation
PLoS One. 2012; 7(12): e50537
Glombiewski JA, Nestoriuc Y, Rief W, Glaesmer H, Braehler E
Adherence to medication is low in specific populations who need chronic medication. However, adherence to medication is also of interest in a more general fashion, independent of specific populations or side effects of particular drugs. If clinicians and researchers expect patients to show close to full adherence, it is relevant to know how likely the achievement of this goal is. Population based rates can provide an estimate of efforts needed to achieve near complete adherence in patient populations. The objective of the study was to collect normative data for medication nonadherence in the general population.We assessed 2,512 persons (a representative sample of German population). Adherence was measured by Rief Adherence Index. We also assessed current medication intake and side effects. We found that at least 33% of Germans repeatedly fail to follow their doctor’s recommendations regarding pharmacological treatments and only 25% of Germans describe themselves as fully adherent. Nonadherence to medication occurs more often in younger patients with higher socioeconomic status taking short-term medications than in older patients with chronic conditions. Experience with medication side effects was the most prominent predictor of nonadherence.The major strengths of our study are a representative sample and a novel approach to assess adherence. Nonadherece seems to be commonplace in the general population. Therefore adherence cannot be expected per se but needs special efforts on behalf of prescribers and public health initiatives. Nonadherence to medication should not only be considered as a drug-specific behaviour problem, but as a behaviour pattern that is independent of the prescribed medication.
HubMed – drug
Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology.
Filed under: Drug and Alcohol Rehabilitation
PLoS One. 2012; 7(12): e48238
Lee CM, Mudaliar MA, Haggart DR, Wolf CR, Miele G, Vass JK, Higham DJ, Crowther D
Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data. In particular, we perform the first study that involves more than two datasets. We discuss the algorithmic issues required to convert the approach into a practical computational tool and apply the technique to new gene expression data quantifying the molecular changes in four tissue types due to different dosages of an experimental panPPAR agonist in mouse. This study is of interest in toxicology because, whilst PPARs form potential therapeutic targets for diabetes, it is known that they can induce serious side-effects. Our results show that the practical simultaneous non-negative matrix factorization developed here can add value to the data analysis. In particular, we find that factorizing the data as a single object allows us to distinguish between the four tissue types, but does not correctly reproduce the known dosage level groups. Applying our new approach, which treats the four tissue types as providing distinct, but related, datasets, we find that the dosage level groups are respected. The new algorithm then provides separate gene list orderings that can be studied for each tissue type, and compared with the ordering arising from the single factorization. We find that many of our conclusions can be corroborated with known biological behaviour, and others offer new insights into the toxicological effects. Overall, the algorithm shows promise for early detection of toxicity in the drug discovery process.
HubMed – drug
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