scholarly journals Translational aspects of genetic factors in the prediction of drug response variability: a case study of warfarin pharmacogenomics in a multi-ethnic cohort from Asia

2011 ◽  
Vol 12 (4) ◽  
pp. 312-318 ◽  
Author(s):  
S L Chan ◽  
C Suo ◽  
S C Lee ◽  
B C Goh ◽  
K S Chia ◽  
...  
Keyword(s):  
Drug Response ◽  
Genetic Factors ◽  
Response Variability

scholarly journals A unifying framework disentangles genetic, epigenetic, and stochastic sources of drug-response variability in an in vitro model of tumor heterogeneity

2020 ◽  
Author(s):  
Corey E. Hayford ◽  
Darren R. Tyson ◽  
C. Jack Robbins ◽  
Peter L. Frick ◽  
Vito Quaranta ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Line ◽  
Tumor Heterogeneity ◽  
Drug Response ◽  
Genetic Factors ◽  
Theoretical Framework ◽  
Response Variability ◽  
Genetic Differences ◽  
Tumor Relapse ◽  
Stochastic Sources

ABSTRACTTumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability of targeted therapy response is observed. Additional genetic mutations can only partially explain this variability, leading to consideration of non-genetic factors, such as “stem-like” and “mesenchymal” phenotypic states, as critical contributors to tumor relapse and resistance. Here, we show that both genetic and non-genetic factors contribute to targeted drug-response variability in an experimental tumor heterogeneity model based on multiple versions and clonal sublines of PC9, the archetypal EGFR-mutant non-small cell lung cancer cell line. We observe significant drug-response variability across PC9 cell line versions, among sublines, and within sublines. To disentangle genetic, epigenetic, and stochastic components underlying this variability, we adopt a theoretical framework whereby distinct genetic states give rise to multiple epigenetic “basins of attraction”, across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Using mutational impact analysis, single-cell differential gene expression, and semantic similarity of gene ontology terms to connect genomics and transcriptomics, we establish a baseline of genetic differences explaining drug-response variability across PC9 cell line versions. In contrast, with the same approach, we conclude that in all but one of the clonal sublines, drug-response variability is due to epigenetic rather than genetic differences. Finally, using a clonal drug-response assay and stochastic simulations, we attribute drug-response variability within sublines to intracellular stochastic fluctuations and confirm that one subline likely contains a genetic resistance mutation that emerged in the absence of selective pressures. We propose that a theoretical framework deconvolving the complex interplay among genetic, epigenetic, and stochastic sources of intratumoral heterogeneity will lead to novel therapeutic strategies to combat tumor relapse and resistance.

scholarly journals A case study of temporal lobe development in familial schizophrenia

1996 ◽  
Vol 26 (1) ◽  
pp. 191-195 ◽  
Author(s):  
W. G. Honer ◽  
A. S. Bassett ◽  
P. Falkai ◽  
T. G. Beach ◽  
J. S. Lapointe
Keyword(s):  
Temporal Lobe ◽  
Neuronal Migration ◽  
Developmental Disorders ◽  
Genetic Factors ◽  
Cortical Atrophy ◽  
Potential Candidate ◽  
Linkage Studies ◽  
Temporal Lobes ◽  
Neurodevelopmental Abnormalities

SynopsisCase studies of patients with familial schizophrenia may help to define the pathophysiology of this illness and indicate potential candidate genes for genetic linkage studies. In this regard, the clinical, radiological and pathological assessments of a 39-year-old affected man from a pedigree with familial schizophrenia are presented. Brain imaging with CT indicated moderate cortical atrophy, particularly of the temporal lobes. Neuropathological examination revealed granular ependymitis, indicating possible past ventricular pathology. Granular ependymitis was reported to occur in genetic developmental disorders with neuronal migration abnormalities. In the present case, heterotopic clusters of neurons were visualized in the entorhinal cortex, suggesting that temporal lobe development was not entirely normal. This case study suggests that genetic factors could be investigated further as one possible aetiology of certain neurodevelopmental abnormalities observed in schizophrenia.

scholarly journals Effect of Apatyakara Ghrita Followed by Koshtha Shuddhi with Haritakyadi Churna in the Management of Ksheena Shukra w.s.r. to Oligozoospermia: A Case Study

AYUSHDHARA ◽  
2021 ◽  
pp. 3377-3383
Author(s):  
Devesh Jaiman ◽  
HML Meena ◽  
Bharat Kumar Padhar ◽  
Harish Bhakuni
Keyword(s):  
Male Infertility ◽  
Genetic Factors ◽  
Semen Quality ◽  
Sperm Count ◽  
Common Finding ◽  
Testicular Dysfunction ◽  
Seminal Parameters ◽  
Associated Symptoms

Oligozoospermia is a condition where sperm count is below 15 million/ml and a common finding which is related to male infertility. Some of the known responsible factors for male infertility are poor semen quality, genetic factors, testicular dysfunction and endocrine inter relationship etc. According to Ayurvedic classics, Oligozoospermia can be correlated with Ksheena Shukra which is due to increased Vata and Pitta Dosha being more prevalent in Madhyama Vayas. According to WHO, in India, the overall prevalence of primary infertility ranges between 3.9% and 16.8%.  Methods: In this study, a male patient aged 40 years was presented with a desire to get a child and other associated symptoms were Daurbalya (weakness), Mukha Shosha (dryness of the mouth), Sadana (loss of rigidity), Shrama (post act exhaustion), Alpachestata (early ejaculation), Maithune Ashakti (problematic or not satisfactory coitus), Rati Anabhimukhata (loss of sexual desire) etc. The patient was managed with Apatyakara Ghrita followed by Koshtha Shuddhi with Haritakyadi Churna. For the assessment of the effect of therapies on sexual parameters, the scoring pattern prepared by Mehra & Singh, 1995 and Seminal Parameters has been adopted. Results and Conclusion: Apatyakara Ghrita is found effective to increase sperm count from 12 million/ ml to 45 million/ml and motility from 20% to 75% and no adverse effect of the adopted management was seen during treatment and even after the 2 months of follow-up.

Anti-VEGF Treatment and Response in Age-related Macular Degeneration: Disease’s Susceptibility, Pharmacogenetics and Pharmacokinetics

2020 ◽  
Vol 27 (4) ◽  
pp. 549-569 ◽  
Author(s):  
Olalla Maroñas ◽  
Laura García-Quintanilla ◽  
Andrea Luaces-Rodríguez ◽  
Anxo Fernández-Ferreiro ◽  
Ana Latorre-Pellicer ◽  
...  
Keyword(s):  
Macular Degeneration ◽  
Drug Response ◽  
Genetic Factors ◽  
Point Of View ◽  
Age Related Macular Degeneration ◽  
Risk Scores ◽  
Future Directions ◽  
Current Review ◽  
Age Related ◽  
Therapeutic Landscape

: The current review is focussing different factors that contribute and directly correlate to the onset and progression of Age-related Macular Degeneration (AMD). In particular, the susceptibility to AMD due to genetic and non-genetic factors and the establishment of risk scores, based on the analysis of different genes to measure the risk of developing the disease. A correlation with the actual therapeutic landscape to treat AMD patients from the point of view of pharmacokinetics and pharmacogenetics is also exposed. Treatments commonly used, as well as different regimes of administration, will be especially important in trying to classify individuals as “responders” and “non-responders”. Analysis of different genes correlated with drug response and also the emerging field of microRNAs (miRNAs) as possible biomarkers for early AMD detection and response will be also reviewed. : This article aims to provide the reader a review of different publications correlated with AMD from the molecular and kinetic point of view as well as its commonly used treatments, major pitfalls and future directions that, to our knowledge, could be interesting to assess and follow in order to develop a personalized medicine model for AMD.

Pharmacogenomic Discovery Approaches: Will the Real Genes Please Stand Up?

2005 ◽  
Vol 23 (29) ◽  
pp. 7342-7349 ◽  
Author(s):  
Richard A. Walgren ◽  
Melissa A. Meucci ◽  
Howard L. McLeod
Keyword(s):  
Candidate Gene ◽  
Drug Response ◽  
Genetic Factors ◽  
Growth Factor Receptor ◽  
Clinical Tests ◽  
Activating Mutations ◽  
Genome Wide ◽  
Epidermal Growth ◽  
The Right ◽  
Efficacy Prediction

Genetic inheritance plays a significant role in the interindividual variability of drug response. The field of pharmacogenomics seeks to identify genetic factors that influence drug response, including both those that are inherited and those that arise within tumors, and use this information to improve drug therapy. Candidate gene approaches have led to clinical tests for toxicity avoidance (eg, TPMT, UGT1A1) and efficacy prediction (eg, epidermal growth factor receptor–activating mutations). However, the “right” genes are not known for most anticancer drugs. Strategies for uncovering pharmacogenomic associations vary widely from monogenic candidate gene approaches to polygenic genome-wide approaches. This review will place in context clinically relevant pharmacogenomic discovery approaches, including the relative strengths and weaknesses and the challenges inherent with achieving the goal of individualized therapy.

scholarly journals CASE STUDY ON IFOSMADIDE-INDUCED CYSTITIS

2020 ◽  
pp. 1-2 ◽  
Author(s):  
SRINIVAS PASULA ◽  
SYEDA ZAINEB HUMAIRA HUSSAINI ◽  
NAGARAJU GV
Keyword(s):  
Adverse Drug Reaction ◽  
Drug Reaction ◽  
Male Patient ◽  
Tissue Damage ◽  
Drug Response ◽  
Hodgkin's Lymphoma ◽  
Normal Dose ◽  
Laboratory Investigations ◽  
Probable Type

 Adverse drug response elaborates, is response to the drug which is caused to an organ or tissue damage for normal dose in the patients for the prophylaxis, 22 years male patient was hospitalized with complaints of relapsed Hodgkin’s lymphoma (HL) using post-Adriamycin, Bleomycin, Binblastine, and Dacarbazine regimen. The patient had treated HL with ICE regimen, after 24 hours of treatment with prescribed the ICE regimen, The patient was observed with following symptoms like vomiting, painful burning micturition and laboratory investigations reported. Abnormal then we suggested Mesna 3 days for prophylactic course then symptoms were not found and patient was discharged. We conducted Adverse drug reaction (ADR) assessment was resulted as probable type and we can probably prevent this type of ADR.

scholarly journals Distinct Effects of Inflammation on Cytochrome P450 Regulation and Drug Metabolism: Lessons from Experimental Models and a Potential Role for Pharmacogenetics

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1509
Author(s):  
Laura M. de Jong ◽  
Wim Jiskoot ◽  
Jesse J. Swen ◽  
Martijn L. Manson
Keyword(s):  
Cytochrome P450 ◽  
Drug Metabolism ◽  
Drug Response ◽  
Genetic Factors ◽  
Potential Role ◽  
In Vitro Models ◽  
Experimental Models ◽  
Individual Variability ◽  
The Individual

Personalized medicine strives to optimize drug treatment for the individual patient by taking into account both genetic and non-genetic factors for drug response. Inflammation is one of the non-genetic factors that has been shown to greatly affect the metabolism of drugs—primarily through inhibition of cytochrome P450 (CYP450) drug-metabolizing enzymes—and hence contribute to the mismatch between the genotype predicted drug response and the actual phenotype, a phenomenon called phenoconversion. This review focuses on inflammation-induced drug metabolism alterations. In particular, we discuss the evidence assembled through human in-vitro models on the effect of inflammatory mediators on clinically relevant CYP450 isoform levels and their metabolizing capacity. We also present an overview of the current understanding of the mechanistic pathways via which inflammation in hepatocytes may modulate hepatic functions that are critical for drug metabolism. Furthermore, since large inter-individual variability in response to inflammation is observed in human in-vitro models and clinical studies, we evaluate the potential role of pharmacogenetic variability in the inflammatory signaling cascade and how this can modulate the outcome of inflammation on drug metabolism and response.

scholarly journals Whole genome sequencing identifies putative associations between genomic polymorphisms and clinical response to the antiepileptic drug levetiracetam

2019 ◽  
Author(s):  
DV Vavoulis ◽  
AT Pagnamenta ◽  
SJL Knight ◽  
MM Pentony ◽  
M Armstrong ◽  
...  
Keyword(s):  
Antiepileptic Drug ◽  
Whole Genome Sequencing ◽  
Clinical Response ◽  
Genome Sequencing ◽  
Drug Response ◽  
Low Frequency ◽  
Response Variability ◽  
Whole Genome ◽  
Extreme Response ◽  
Synaptic Neurotransmission

ABSTRACTIn the context of pharmacogenomics, whole genome sequencing provides a powerful approach for identifying correlations between response variability to specific drugs and genomic polymorphisms in a population, in an unbiased manner. In this study, we employed whole genome sequencing of DNA samples from patients showing extreme response (n=72) and non-response (n=27) to the antiepileptic drug levetiracetam, in order to identify genomic variants that underlie response to the drug. Although no common SNP (MAF>5%) crossed the conventional genome-wide significance threshold of 5×10−8, we found common polymorphisms in genes SPNS3, HDC, MDGA2, NSG1 and RASGEF1C, which collectively predict clinical response to levetiracetam in our cohort with ∼91% predictive accuracy (∼94% positive predictive value, ∼85% negative predictive value). Among these genes, HDC, NSG1, MDGA2 and RASGEF1C are potentially implicated in synaptic neurotransmission, while SPNS3 is an atypical solute carrier transporter homologous to SV2A, the known molecular target of levetiracetam. Furthermore, we performed gene- and pathway-based statistical analysis on sets of rare and low-frequency variants (MAF<5%) and we identified associations between genes or pathways and response to levetiracetam. Our findings include a) the genes PRKCB and DLG2, which are involved in glutamatergic neurotransmission, a known target of anticonvulsants, including levetiracetam; b) the genes FILIP1 and SEMA6D, which are involved in axon guidance and modelling of neural connections; and c) pathways with a role in synaptic neurotransmission, such as WNT5A-dependent internalization of FZD4 and disinhibition of SNARE formation. Targeted analysis of genes involved in neurotransmitter release and transport further supports the possibility of association between drug response and genes NSG1 and DLG2. In summary, our approach to utilise whole genome sequencing on subjects with extreme response phenotypes is a feasible route to generate plausible hypotheses for investigating the genetic factors underlying drug response variability in cases of pharmaco-resistant epilepsy.AUTHOR SUMMARYLevetiracetam (LEV) is a prominent antiepileptic drug prescribed for the treatment of both focal and generalised epilepsy. The molecular mechanism mediating its action is not well understood, but it involves the modulation of synaptic neurotransmition through binding to the synaptic vesicle glycoprotein SV2A. Identifying genomic polymorphisms that predict response to the drug is important, because it can help clinicians prescribe the most appropriate treatment in a patient-specific manner. In this study, we employed whole genome sequencing (WGS) of DNA samples from extreme responders or non-responders to LEV and we identified a small group of common variants, which successfully predict response to the drug in our cohort. These variants are mostly located in genes implicated in synaptic function. Furthermore, we identified significant associations between clinical response to LEV and low-frequency variants in genes and pathways involved in excitatory neurotransmission or in the moulding of neural networks in the brain. Our approach to utilise WGS on subjects with extreme response phenotypes is a feasible route to generate plausible hypotheses on the genomic basis of pharmaco-resistant epilepsy. We expect that the rapidly decreasing cost of WGS will allow conducting similar studies on a larger scale in the near future.

scholarly journals An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability

PLoS Biology ◽  
2021 ◽  
Vol 19 (6) ◽  
pp. e3000797
Author(s):  
Corey E. Hayford ◽  
Darren R. Tyson ◽  
C. Jack Robbins ◽  
Peter L. Frick ◽  
Vito Quaranta ◽  
...  
Keyword(s):  
Cell Line ◽  
Tumor Heterogeneity ◽  
Drug Response ◽  
Acquired Resistance ◽  
Genetic Alterations ◽  
Response Variability ◽  
Stochastic Simulations ◽  
Nsclc Cell Line ◽  
Cell Fate Decisions ◽  
Egfr Inhibition

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability in response to targeted therapies is well known. The existence of additional genomic alterations among tumor cells can only partially explain this variability. As such, nongenetic factors are increasingly seen as critical contributors to tumor relapse and acquired resistance in cancer. Here, we show that both genetic and nongenetic factors contribute to targeted drug response variability in an experimental model of tumor heterogeneity. We observe significant variability to epidermal growth factor receptor (EGFR) inhibition among and within multiple versions and clonal sublines of PC9, a commonly used EGFR mutant nonsmall cell lung cancer (NSCLC) cell line. We resolve genetic, epigenetic, and stochastic components of this variability using a theoretical framework in which distinct genetic states give rise to multiple epigenetic “basins of attraction,” across which cells can transition driven by stochastic noise. Using mutational impact analysis, single-cell differential gene expression, and correlations among Gene Ontology (GO) terms to connect genomics to transcriptomics, we establish a baseline for genetic differences driving drug response variability among PC9 cell line versions. Applying the same approach to clonal sublines, we conclude that drug response variability in all but one of the sublines is due to epigenetic differences; in the other, it is due to genetic alterations. Finally, using a clonal drug response assay together with stochastic simulations, we attribute subclonal drug response variability within sublines to stochastic cell fate decisions and confirm that one subline likely contains genetic resistance mutations that emerged in the absence of drug treatment.

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