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Objective: To analyze the local functional activity and connectivity features of the brain associated with drug response inpatients newly diagnosed with epilepsy (NDE) who are naïve to anti-seizure medication (ASM). Methods: Recruited patients, underwent functional magnetic resonance imaging at baseline, and were assigned to the well-controlled (WC, n = 28) or uncontrolled (UC, n = 11) groups based on their response to ASM. Healthy participants were included in the control group (HC, n = 29). The amplitudes of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) were used to measure local functional activity, and voxel-wise degree centrality (DC) and seed-based functional connectivity (FC) were used to evaluate the connecting intensity of the brain areas. Results: Compared to the HC and WC groups, the UC group had higher ALFF values in the left posterior central gyrus (PoCG.L) and left inferior temporal gyrus (ITG.L) and higher DC in the bilateral PoCG (Gaussian random field correction, voxel-level P < 0.001, and cluster-level P < 0.05). Both PoCG and ITG.L in the UC group showed stronger FC with multiple brain regions, mainly located in the occipital and temporal lobes, compared to the HC or WC group, while the WC group showed decreased or similar FC compared to the HC group. Interpretation: Excessive enhancement of brain functional activity or connecting intensity in ASM-naïve patients with NDE may be associated with a higher risk of poor drug response. [ABSTRACT FROM AUTHOR]

Neonatal intensive care unit (NICU), particularly in treating developmental and epileptic encephalopathy (DEE) and metabolic epilepsy (ME), requires a deep understanding of their complex etiologies and treatment responses. After excluding treatable cases such as infectious or autoimmune encephalitis, our focus shifted to a more challenging subgroup of 59 patients for in-depth genetic analysis using exome sequencing (ES). The ES analysis identified 40 genetic abnormalities, significantly including de novo variants. Notably, we found structural variation as duplications in regions 2q24.3, including SCN1A and SCN2A were observed in 7 cases. These genetic variants, impacting ion channels, glucose transport, transcription regulation, and kinases, play a crucial role in determining medication efficacy. More than one-third (34.2%) of patients with DEE had an unfavorable response to anti-seizure medications (ASMs) in the chronic phase. However, since the ketogenic supplementary diet showed a positive effect, more than three-quarters (80%) of these drug-resistant patients improved during a 3-month follow-up. In contrast, the ME had a lower adverse reaction rate of 9.1% (2/22) to specialized medications, yet there were 5 fatalities and 10 cases with unidentified genetic etiologies. This study suggests the potential of categorizing drug-resistant variants and that a ketogenic diet could be beneficial in managing DEE and ME. It also opens new perspectives on the mechanisms of the ketogenic diet on the discovered genetic variants. [ABSTRACT FROM AUTHOR]

Drug responses heterogeneity is often highlighted to justify the need for precision medicine. However, due to the highly complex nature of cell phenotypes in many diseases, one of key challenges is how to obtain the high content features in a cellular population. Here we present a single-cell vibrational phenomics approach, integrating synchrotron infrared microspectroscopy and multivariate calculation, for quantitatively evaluating the cellular responses to drug perturbation with single cell resolution. In a human hepatocellular carcinoma HepG2 cell model, the phenotypic changes induced by two types of drugs, taxol (TAX) and protopanaxadiol (PPD), were analyzed and revealed the response heterogeneity in drug concentration and chemical components. These findings not only provide a label-free strategy for determining the drug response at the single cell level, but also demonstrate the great potential of vibrational phenomics as a drug discovery platform. [ABSTRACT FROM AUTHOR]

Recent researches reported that neurotrophins can promote glioma growth/invasion but the relevant model for predicting patients' survival in Lower-Grade Gliomas (LGGs) lacked. In this study, we adopted univariate Cox analysis, LASSO regression, and multivariate Cox analysis to determine a signature including five neurotrophin-related genes (NTGs), CLIC1, SULF2, TGIF1, TTF2, and WEE1. Two-sample Mendelian Randomization (MR) further explored whether these prognostic-related genes were genetic variants that increase the risk of glioma. A total of 1306 patients have been included in this study, and the results obtained from the training set can be verified by four independent validation sets. The low-risk subgroup had longer overall survival in five datasets, and its AUC values all reached above 0.7. The risk groups divided by the NTGs signature exhibited a distinct difference in targeted therapies from the copy-number variation, somatic mutation, LGG's surrounding microenvironment, and drug response. MR corroborated that TGIF1 was a potential causal target for increasing the risk of glioma. Our study identified a five-NTGs signature that presented an excellent survival prediction and potential biological function, providing new insight for the selection of LGGs therapy. [ABSTRACT FROM AUTHOR]

Abstract Mass spectrometry has revolutionized cell signaling research by vastly simplifying the analysis of many thousands of phosphorylation sites in the human proteome. Defining the cellular response to perturbations is crucial for further illuminating the functionality of the phosphoproteome. Here we describe µPhos (‘microPhos’), an accessible phosphoproteomics platform that permits phosphopeptide enrichment from 96-well cell culture and small tissue amounts in 90% selectivity, and excellent quantitative reproducibility. Employing highly sensitive trapped ion mobility mass spectrometry, we quantify ~17,000 Class I phosphosites in a human cancer cell line using 20 µg starting material, and confidently localize ~6200 phosphosites from 1 µg. This depth covers key signaling pathways, rendering sample-limited applications and perturbation experiments with hundreds of samples viable. We employ µPhos to study drug- and time-dependent response signatures in a leukemia cell line, and by quantifying 30,000 Class I phosphosites in the mouse brain we reveal distinct spatial kinase activities in subregions of the hippocampal formation.

Considering the key role of myeloid cell differentiation—related genes in the tumor microenvironment (TME), we aimed to build a prognostic risk model using these genes for Lung adenocarcinoma (LUAD). The mRNA gene expression profiles of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were downloaded as the training and validation sets. Then, "edgeR" R package was applied to screen out the differentially expressed genes (DEGs) and univariate cox regression, backward stepwise selection analyses were performed to construct a prognostic model for LUAD. ESTIMATE, TIMER, XCELL, CIBERSORT abs, QUANTISEQ, MCPCOUNTER, EPIC, and CIBERSORT algorithms were conducted to access the association of risk levels with the stromal and immune cell infiltration levels in LUAD. Six genes (F2RL1, PRKDC, TNFSF11, INHA, PLA2G3 and TUBB1) were utilized to construct the prognostic model. The risk model showed excellent prognostic performance for LUAD in both TCGA and GEO datasets. Also, compared to the low-risk patients, the high-risk patients had higher expression of immune checkpoint molecules and showed a lower IC50 value to the chemotherapy agents. Our findings provided a myeloid cell differentiation—related gene signature that could effectively predict prognosis and guide treatment strategies for LUAD patients. [ABSTRACT FROM AUTHOR]

Background: Recent research reported that mononuclear phagocyte system (MPS) can contribute to immune defense but the classification of head and neck squamous cell carcinoma (HNSCC) patients based on MPS-related multi-omics features using machine learning lacked. Methods: In this study, we obtain marker genes for MPS through differential analysis at the single-cell level and utilize "similarity network fusion" and "MoCluster" algorithms to cluster patients' multi-omics features. Subsequently, based on the corresponding clinical information, we investigate the prognosis, drugs, immunotherapy, and biological differences between the subtypes. A total of 848 patients have been included in this study, and the results obtained from the training set can be verified by two independent validation sets using "the nearest template prediction". Results: We identified two subtypes of HNSCC based on MPS-related multi-omics features, with CS2 exhibiting better predictive prognosis and drug response. CS2 represented better xenobiotic metabolism and higher levels of T and B cell infiltration, while the biological functions of CS1 were mainly enriched in coagulation function, extracellular matrix, and the JAK-STAT signaling pathway. Furthermore, we established a novel and stable classifier called "getMPsub" to classify HNSCC patients, demonstrating good consistency in the same training set. External validation sets classified by "getMPsub" also illustrated similar differences between the two subtypes. Conclusions: Our study identified two HNSCC subtypes by machine learning and explored their biological difference. Notably, we constructed a robust classifier that presented an excellent classifying prediction, providing new insight into the precision medicine of HNSCC. [ABSTRACT FROM AUTHOR]

Objective: Due to the pivotal role cancer-associated fibroblasts (CAFs) play in tumor progression, our study aimed to develop a signature of CAFs-related gene (CRG) to predict the survival outcomes and treatment response of bladder cancer (BLCA). Methods: The transcriptome data and relevant clinical information about BLCA were collected from publicly available databases, including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Weighted gene co-expression network analysis was utilized to uncover CAFs-associated hub genes, and subsequently, a risk model for survival prognosis was constructed using LASSO-Cox regression. The immune microenvironment, immune infiltration, immunotherapy response, and drug sensitivity were explored using ESTIMATE, CIBERSORT, TIDE, and oncoPredict algorithms. To verify the expression of the CRGs, additional analyses were performed using online databases (HPA, CCLE, TIMER, cBioPortal, and TISCH). Results: Our study developed a CRG signature and constructed a prognostic model. Significant differences in overall survival were observed between the two risk stratifications. The risk score increased with the infiltration of CAFs and tumor staging progression, while closely correlating with immune checkpoint expression and infiltration of CD8 T cells, follicular helper T cells, regulatory T cells, activated dendritic cells, M0 macrophages, M2 macrophages, and resting mast cells. Furthermore, a higher proportion of patients in the low-risk stratification exhibited responsiveness to immunotherapy, and significant variances in sensitivity to multiple chemotherapy medications were observed between the two risk stratifications. Conclusion: The construction of the risk model based on the CRG signature offers new avenues for the prognosis evaluation and development of personalized treatment strategies for BLCA. [ABSTRACT FROM AUTHOR]

The exact molecular mechanism underlying the heterogeneous drug response against breast carcinoma remains to be fully understood. It is urgently required to identify key genes that are intricately associated with varied clinical response of standard anti-cancer drugs, clinically used to treat breast cancer patients. In the present study, the utility of transcriptomic data of breast cancer patients in discerning the clinical drug response using machine learning-based approaches were evaluated. Here, a computational framework has been developed which can be used to identify key genes that can be linked with clinical drug response and progression of cancer, offering an immense opportunity to predict potential prognostic biomarkers and therapeutic targets. The framework concerned utilizes DeSeq2, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape, and machine learning techniques to find these crucial genes. Total RNA extraction and qRT-PCR were performed to quantify relative expression of few hub genes selected from the networks. In our study, we have experimentally checked the expression of few key hub genes like APOA2, DLX5, APOC3, CAMK2B, and PAK6 that were predicted to play an immense role in breast cancer tumorigenesis and progression in response to anti-cancer drug Paclitaxel. However, further experimental validations will be required to get mechanistic insights of these genes in regulating the drug response and cancer progression which will likely to play pivotal role in cancer treatment and precision oncology. [ABSTRACT FROM AUTHOR]

Drugs pharmacology is defined by pharmacokinetics and pharmacodynamics and both of them are affected by genetic variability. Genetic variability varies from population to population, and sometimes even within the population, it exists. Single nucleotide polymorphisms (SNPs) are one of the major genetic variability factors which are found to be associated with the pharmacokinetics and pharmacodynamics process of a drug and are responsible for variable drug response and clinical phenotypes. Studies of SNPs can help to perform genome-wide association studies for their association with pharmacological and clinical events, at the same time; their information can direct genome-wide association studies for their use as biomarkers. With the aim to mine and characterize Indian populated SNPs of pharmacological and clinical importance. Two hundred six candidate SNPs belonging to 43 genes were retrieved from Indian Genome Variation Database. The distribution pattern of considered SNPs was observed against all five world super-populations (AFR, AMR, EAS, EUR, and SAS). Further, their annotation was done through SNP-nexus by considering Human genome reference builds - hg38, pharmacological and clinical information was supplemented by PharmGKB and ClinVar database. At last, to find out the association between SNPs linkage disequilibrium was observed in terms of r2. Overall, the study reported 53 pharmaco-clinical active SNPs and found 24 SNP-pairs as potential markers, and recommended their clinical and experimental validation. [ABSTRACT FROM AUTHOR]

The majority of the biomarkers were associated with the diagnosis of epilepsy and few of them can be applied to predict the response to antiseizure medications (ASMs). In this study, we identified 26 significantly up-regulated genes and 32 down-regulated genes by comparing the gene expression profiles of patients with epilepsy that responded to valproate with those without applying any ASM. The results of gene set enrichment analysis indicated that the ferroptosis pathway was significantly impacted (p = 0.0087) in patients who responded to valproate. Interestingly, the gene NCOA4 in this pathway exhibited significantly different expression levels between the two groups, indicating that NCOA4 could serve as a potential biomarker to better understand the mechanism of valproate resistance. In addition, six up-regulated genes SF3A2, HMGN2, PABPN1, SSBP3, EFTUD2, and CREB3L2 as well as six down-regulated genes ZFP36L1, ACRC, SUB1, CALM2, TLK1, and STX2 also showed significantly different expression patterns between the two groups. Moreover, based on the gene expression profiles of the patients with the treatment of valproate, carbamazepine, and phenytoin, we proposed a strategy for predicting the response to the ASMs by using the Connectivity Map scoring method. Our findings could be helpful for better understanding the mechanisms of drug resistance of ASMs and improving the clinical treatment of epilepsy. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 caused by the coronavirus (SARS-CoV-2) prompted number of computational and laboratory efforts to discover molecules against the virus entry or replication. Simultaneously, due to the availability of clinical information, drug-repurposing efforts led to the discovery of 2-deoxy-d-glucose (2-DG) for treating COVID-19 infection. 2-DG critically accumulates in the infected cells to prevent energy production and viral replication. As there is no clarity on the impact of genetic variations on the efficacy and adverse effects of 2-DG in treating COVID-19 using in silico approaches, we attempted to extract the genes associated with the 2-DG pathway using the Comparative Toxicogenomics Database. The interaction between selected genes was assessed using ClueGO, to identify the susceptible gene loci for SARS-CoV infections. Further, SNPs that were residing in the distinct genomic regions were retrieved from the Ensembl genome browser and characterized. A total of 80 SNPs were retrieved using diverse bioinformatics resources after assessing their (a) detrimental influence on the protein stability using Swiss-model, (b) miRNA regulation employing miRNASNP3, PolymiRTS, MirSNP databases, (c) binding of transcription factors by SNP2TFBS, SNPInspector, and (d) enhancers regulation using EnhancerDB and HaploReg reported A2M rs201769751, PARP1 rs193238922 destabilizes protein, six polymorphisms of XIAP effecting microRNA binding sites, EGFR rs712829 generates 15 TFBS, BECN1 rs60221525, CASP9 rs4645980, SLC2A2 rs5393 impairs 14 TFBS, STK11 rs3795063 altered 19 regulatory motifs. These data may provide the relationship between genetic variations and drug effects of 2-DG which may further assist in assigning the right individuals to benefit from the treatment. [ABSTRACT FROM AUTHOR]

A unique specimen of argyria is preserved in the Morgagni Museum of Pathological Anatomy at the University of Padua (Italy). It is a stuffed head belonging to a man who decided to cure his syphilis by himself with the so-called infernal stone (silver nitrate) every day for years, thus developing argyria in the second half of the nineteenth century. Paleopathological and historical studies were performed on the specimen to confirm the diagnosis of argyria. Furthermore, a morphological investigation of the specimen was conducted with histological and ultrastructural investigations, including environmental scanning electron microscopy and electron dispersive x‐ray spectroscopy, recording high presence of silver in the dermis and epidermis and also other chemical elements correlated to the "infernal stone." A comparison with actual cases may also lead to a common feature: a potential dependence on the perceived benefits brought by silver compound that may sustain a further prolonged intake. [ABSTRACT FROM AUTHOR]

Background: Ginseng, a traditional herbal medicine, has been used for thousands of years to treat various diseases including metabolic syndrome (MS). However, the underlying mechanism(s) of such beneficial actions of ginseng against MS is poorly understood. Emerging evidence indicates a close association of the host gut microbiota with MS. The present study was conducted to examine, whether the beneficial effects of Korean red ginseng (KRG) against MS could be influenced by gut microbial population and whether gut microbial profile could be considered a valuable biomarker for targeted treatment strategy for MS in compliance with the predictive, preventive, and personalized medicine (PPPM / 3PM). Methods: This clinical study was a randomized, double-blind, placebo-controlled trial evaluating the effects of KRG treatment for 8 weeks on patients with MS. The anthropometric parameters, vital signs, metabolic biomarkers, and gut microbial composition through 16S rRNA gene sequencing were assessed at the baseline and endpoint. The impact of KRG was also evaluated after categorizing the subjects into responders and non-responders, as well as enterotypes 1 and 2 based on their gut microbial profile at the baseline. Results: Fifty out of 60 subjects who meet the MS criteria completed the trial without showing adverse reactions. The KRG treatment caused a significant decrease in systolic blood pressure (SBP). Microbial analysis revealed a decrease in Firmicutes, Proteobacteria, and an increase in Bacteroidetes in response to KRG. In patient stratification analysis, the responders showing marked improvement in the serum levels of lipid metabolic biomarkers TC and LDL due to the KRG treatment exhibited higher population of both the family Lachnospiraceae and order Clostridiales compared to the non-responders. The homeostasis model assessment-insulin resistance (HOMA-IR) and insulin level were decreased in enterotype 1 (Bacteroides-abundant group) and increased in enterotype 2 (prevotella-abundant group) following the KRG treatment. Conclusion: In this study, the effects of KRG on the glucose metabolism in MS patients were influenced by the relative abundances of gut microbial population and differed according to the individual enterotype. Therefore, the analysis of enterotype categories is considered to be helpful in predicting the effectiveness of KRG on glucose homeostasis of MS patients individually. This will further help to decide on the appropriate treatment strategy for MS, in compliance with the perspective of PPPM. [ABSTRACT FROM AUTHOR]

Alveolar rhabdomyosarcoma (aRMS) is a histological subtype of RMS, which is the most common pediatric and adolescent soft-tissue sarcoma, accounting for 3–4% of all pediatric malignancies. Patient-derived cells are essential tools for understanding the molecular mechanisms of poor prognosis and developing novel anti-cancer drugs. However, only a limited number of well-characterized cell lines for rhabdomyosarcoma from public cell banks is available. Therefore, we aimed to establish a novel cell line of aRMS from the tumor tissue of a patient with aRMS. The cell line was established from surgically resected tumor tissue from a 4-year-old male patient diagnosed with stage III, T2bN1M0 aRMS and was named as NCC-aRMS1-C1. The cells were maintained for more than 3 months under tissue culture conditions and passaged more than 20 times. We confirmed the presence of identical fusion gene such as PAX7-FOXO1 in both the original tumor and NCC-aRMS1-C1. The cells exhibited spheroid formation and invasion. We found that docetaxel, vincristine, ifosfamide, dacarbazine, and romidepsin showed remarkable growth-suppressive effects on the NCC-aRMS1-C1 cells. In conclusion, the NCC-aRMS1-C1 cell line exhibited characteristics that may correspond to the lymph node metastasis in aRMS and mirror its less aggressive features. Thus, it may be useful for innovative seeds for novel therapeutic strategies. [ABSTRACT FROM AUTHOR]

Forkhead box O4 (FOXO4) is a member of the FOXO family that regulates a number of genes involved in metabolism, cell cycle, apoptosis, and cellular homeostasis via transcriptional activity. It also mediates cell responses to oxidative stress and treatment with antitumor agents. The expression of FOXO4 is repressed by microRNAs in multiple cancer cells, while FOXO4 function is regulated by post-translational modifications and interaction with other proteins. The deregulation of FOXO4 is closely linked to the progression of several types of cancer, senescence, and other diseases. In this review, we present recent findings on the regulation of FOXO4 in physiological and pathological conditions and provide an overview of the complex role of FOXO4 in disease development and response to therapy. [ABSTRACT FROM AUTHOR]

A major hurdle faced by most schizophrenia patients is the poor efficacy of current antipsychotic medications. This stems from a poor understanding of the underlying pathophysiology and the lack of biomarkers for the prediction of a positive medication response. By employing state-of-the-art proteomic analysis of blood plasma from 58 patients who were either drug-naive or drug-free at the time of sample collection, we identified potential biomarkers that were predictive of a positive response after 6 weeks of treatment with antipsychotics. Complement and coagulation cascades were the most over-represented biological pathways among these proteins, consistent with the importance of these processes in schizophrenia. Although preliminary, these findings are novel and may drive future efforts in the development of predictive tests for medication efficacy and thereby have a positive influence on disease outcome. [ABSTRACT FROM AUTHOR]

Objectives: In this review, we focus on the application of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9), as a powerful genome editing system, in the identification of resistance mechanisms and in overcoming drug resistance in the most frequent solid tumors. Data acquisition: Data were collected by conducting systematic searching of scientific English literature using specific keywords such as "cancer", "CRISPR" and related combinations. Results: The review findings revealed the importance of CRISPR/Cas9 system in understanding drug resistance mechanisms and identification of resistance-related genes such as PBRM1, SLFN11 and ATPE1 in different cancers. We also provided an overview of genes, including RSF1, CDK5, and SGOL1, whose disruption can synergize with the currently available drugs such as paclitaxel and sorafenib. Conclusion: The data suggest CRISPR/Cas9 system as a useful tool in elucidating the molecular basis of drug resistance and improving clinical outcomes. [ABSTRACT FROM AUTHOR]

Abstract Most molecular cancer therapies act on protein targets but data on the proteome status of patients and cellular models for proteome‐guided pre‐clinical drug sensitivity studies are only beginning to emerge. Here, we profiled the proteomes of 65 colorectal cancer (CRC) cell lines to a depth of > 10,000 proteins using mass spectrometry. Integration with proteomes of 90 CRC patients and matched transcriptomics data defined integrated CRC subtypes, highlighting cell lines representative of each tumour subtype. Modelling the responses of 52 CRC cell lines to 577 drugs as a function of proteome profiles enabled predicting drug sensitivity for cell lines and patients. Among many novel associations, MERTK was identified as a predictive marker for resistance towards MEK1/2 inhibitors and immunohistochemistry of 1,074 CRC tumours confirmed MERTK as a prognostic survival marker. We provide the proteomic and pharmacological data as a resource to the community to, for example, facilitate the design of innovative prospective clinical trials.

Purpose: In order to monitor the drug responses of three-dimensional mammary tumor spheroids and to elucidate the role of inter- and intra-spheroid heterogeneity in determining drug sensitivity in the spheroids, an integrated image analysis framework was developed for morphometric and metabolic characterization of the three-dimensional tumor spheroids.Procedure: Three-dimensional spheroid cultures of primary mammary tumor epithelial cells isolated from freshly excised tumors from a transgenic mouse model of adenocarcinoma (MMTV-PyMT) were imaged by using vital dyes and mitochondrial membrane potential markers. Custom-developed java and python program codes facilitated image processing, numerical computation, and graphical analysis of large datasets generated from the experiments. A panel of cancer drugs (rapamycin, BEZ235, MK2206, and flavopiridol) was tested to determine the degree of drug sensitivity as well as heterogeneity in drug response.Results: A new quantitative metric (growth/toxicity) was developed based on morphometric parameters that were found to track the growth and apoptotic cell populations. Further, this study identified two parameters, namely, skew and kurtosis-which report the spatial heterogeneity in mitochondrial metabolism within the spheroids. The results of this study show that three-dimensional tumor spheroids selectively respond to cancer drugs depending on the specific metabolic pathways (AKT inhibition pathway in the present study), and there exists significant heterogeneity in the untreated tumor spheroids. Drug sensitivity of the spheroids was found to be associated with significant alterations in mitochondrial heterogeneity within the spheroids.Conclusions: In conclusion, the quantitative imaging of morphometric and metabolic analysis in large image datasets can serve as an excellent tool box for characterizing tumor heterogeneity in three-dimensional tumor spheroids and potentially, in intact tumors as well. [ABSTRACT FROM AUTHOR]

Objectives: In this review, we focus on the application of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9), as a powerful genome editing system, in the identification of resistance mechanisms and in overcoming drug resistance in the most frequent solid tumors. Data acquisition: Data were collected by conducting systematic searching of scientific English literature using specific keywords such as "cancer", "CRISPR" and related combinations. Results: The review findings revealed the importance of CRISPR/Cas9 system in understanding drug resistance mechanisms and identification of resistance-related genes such as PBRM1, SLFN11 and ATPE1 in different cancers. We also provided an overview of genes, including RSF1, CDK5, and SGOL1, whose disruption can synergize with the currently available drugs such as paclitaxel and sorafenib. Conclusion: The data suggest CRISPR/Cas9 system as a useful tool in elucidating the molecular basis of drug resistance and improving clinical outcomes. [ABSTRACT FROM AUTHOR]

Clear cell sarcoma (CCS) is an aggressive mesenchymal malignancy characterized by the unique chimeric EWS-ATF1 fusion gene. Patient-derived cancer models are essential tools for the understanding of tumorigenesis and the development of anti-cancer drugs; however, only a limited number of CCS cell lines exist. The objective of this study was to establish patient-derived CCS models. We established patient-derived CCS models from a 43-yr-old female patient. We prepared the patient-derived xenografts (PDXs) from tumor tissues obtained through biopsy or surgery and isolated stable cell lines from PDXs and the original tumor tissue. The presence of gene fusions was examined by RT-PCR, and Sanger sequencing. The established cell lines were characterized by short tandem repeat, viability, colony and spheroid formation, and invasion analyses. Differences in gene enrichment between the primary tumor and cell lines were examined by mass spectrometry and KEGG pathway analysis. The cell lines were maintained for more than 80 passages, and had tumorigenic characteristics such as colony and spheroid formation and invasion. Mass spectrometric proteome analysis demonstrated that the cell lines were enriched for similar but distinct molecular pathways, compared to those in the xenografts and original tumor tissue. Next, tyrosine kinase inhibitors were screened for their suppressive effects on viability. We found that ponatinib, vandetanib, and doxorubicin suppressed the growth of cell lines, and had equivalent IC values. Further in-depth investigation and understanding of drug-sensitivity mechanisms will be important for the clinical applications of our cell lines. [ABSTRACT FROM AUTHOR]

Abstract Epithelial‐mesenchymal transition (EMT) is a reversible and dynamic process hypothesized to be co‐opted by carcinoma during invasion and metastasis. Yet, there is still no quantitative measure to assess the interplay between EMT and cancer progression. Here, we derived a method for universal EMT scoring from cancer‐specific transcriptomic EMT signatures of ovarian, breast, bladder, lung, colorectal and gastric cancers. We show that EMT scoring exhibits good correlation with previously published, cancer‐specific EMT signatures. This universal and quantitative EMT scoring was used to establish an EMT spectrum across various cancers, with good correlation noted between cell lines and tumours. We show correlations between EMT and poorer disease‐free survival in ovarian and colorectal, but not breast, carcinomas, despite previous notions. Importantly, we found distinct responses between epithelial‐ and mesenchymal‐like ovarian cancers to therapeutic regimes administered with or without paclitaxel in vivo and demonstrated that mesenchymal‐like tumours do not always show resistance to chemotherapy. EMT scoring is thus a promising, versatile tool for the objective and systematic investigation of EMT roles and dynamics in cancer progression, treatment response and survival.

The proneness of diseases and susceptibility towards drugs vary from person to person. At present, there is a strong demand for the personalization of drugs. The genetic signature behind proneness of the disease has been studied through a comprehensive 'octopodial approach'. All the genetic variants included in the approach have been introduced. The breast cancer associated with BRCA1 mutation has been taken as the illustrative example to introduce all these factors. The genetic variants associated with the drug action of tamoxifen have been fully illustrated in the manuscript . The design of a new personalized anti-breast cancer drug has been explained in the third phase. For the design of new personalized drugs, a metabolite of anti-cancer drug chlorambucil has been taken as the template. The design of drug has been made with respect to the protein 1T15 of BRCA1 gene corresponding to the genetic signature of rs28897696. [ABSTRACT FROM AUTHOR]

Drug therapy for non-small cell lung cancer consists mainly of platinum-based chemotherapy regimens. However, toxicity, drug resistance, and high risk of death have been seen in the clinic, which means there is a need for optimizing the use of medications. Platinum resistance could be mediated by a series of DNA repair pathways, and therefore, these pathways should be taken into account for optimizing drug using. The goal of pharmacogenomics is to elucidate genetic factors, such as DNA repair genes, which might underlie drug efficacy and effectiveness, and to improve therapeutic effects or guide personalized therapy as well. Here, we reviewed the current knowledge of pharmacogenomic data on DNA repair systems and examined whether they could be further translated into the clinic with evidence-based perspectives. [ABSTRACT FROM AUTHOR]

To refer to metabolomics as a new field is injustice to ancient doctors who used ants to diagnose the patients of diabetes having glycosuria. Measuring the levels of molecules in biological fluids believing them to be the representatives of biochemical pathways of carbohydrates, fats, proteins, nucleic acids or xenobiotic metabolism and deciphering meaningful data from it is what can be called as metabolomics, just as high glucose in urine suggests diabetes mellitus. Genomics, epigenetics, proteomics, transcriptomics finally converge to metabolomics, which are the signatures of mechanisms of bodily processes which is why understanding this science can have many applications. Just as a heap of stones does not make a house, having data of metabolite levels does not make it a science. Analyzing this data would help us in constructing biochemical pathways and their interactions. Analyzing the changes caused by a drug in the metabolite levels would help us in deriving the mechanisms by which the drug acts. Comparing metabolite levels in diseased with non-diseased, good-responders with poor-responders to a particular drug can help in identifying new markers of a disease or response to a drug respectively. Also, metabolite levels of an endogenous substrate can tell us the status of a person's metabolizing enzymes and help in drug dose titration. Generating hypothesis by identifying the new molecular markers and testing their utility in clinics seems to be the most promising approach in future. This review narrates the modes of quantifying and identifying metabolome, its proposed applications in diagnosis, monitoring and understanding the diseases and drug responses. We also intend to identify hindrances in using metabolomics in clinical studies or experiments. [ABSTRACT FROM AUTHOR]

TNF-blocking agents, non-biological disease-modifying anti-rheumatic drugs (nbDMARDs) and non-steroidal anti-inflammatory drugs (NSAIDs) are commonly prescribed treatments in psoriatic arthritis. A large proportion of patients do not respond to these medications, although unfortunately clinically useful biomarkers that predict future response are currently lacking. Several candidate gene polymorphisms have been associated with responses to biologic therapies and nbDMARDs; however, replication and validation of these variants in large prospective psoriatic arthritis cohorts are required before translating these to clinical practice. In this review, we discuss the advances made in pharmacogenetics of treatment response in psoriatic arthritis to date, with focus on biologic therapies approved for use, nbDMARDs and NSAIDs, as well as outline emerging methodologies to obtain data that will help inform a future precision medicine approach in this condition. [ABSTRACT FROM AUTHOR]

The MDR1 gene encodes for P-glycoprotein (P-gp), which is an efflux transporter at the cell membrane. The P-gp has wide substrate specificity for multiple medications including the lipid lowering drug, atorvastatin. In this study, we investigated the possible association between three common MDR1 gene polymorphisms (G2677T, C3435T, and C1236T), and the lipid lowering effect of atorvastatin among Jordanians. Lipid and lipoproteins were measured in blood samples collected from patients (n = 201) at baseline and during atorvastatin treatment. MDR1 polymorphisms were genotyped using polymerase chain reaction-restriction fragment length polymorphism. Both the TT genotype of G2677T and the TT genotype of the C3435T polymorphisms were associated with lower levels of low-density lipoproteins after atorvastatin treatment. However, the effects of atorvastatin on the levels of total cholesterol, triglycerides, and high-density lipoprotein, were not correlated with any of the genotypes in both polymorphisms. Finally, the C1236T polymorphism was not associated with the lipid lowering effect of atorvastatin. In conclusion, the MDR1 gene polymorphisms G2677T, and C3435T, but not C1236T were associated with the lipid lowering effect of atorvastatin among Jordanians. [ABSTRACT FROM AUTHOR]

Circulating tumor cells (CTC) are of high importance, since they are potential metastatic precursors and are readily available for prognostic analysis and treatment testing. In this review, we demonstrate the great power that green fluorescent protein (GFP) labeling and orthotopic mouse models of cancer confer to the study of CTCs for isolation and characterization, including metastatic testing in mice and the chick embryo as well as drug response testing in vitro. We also describe a facile method to label patient CTCs ex vivo using a telomerase-expressing GFP-containing adenovirus that will allow the CTC studies described in this review to be translated clinically. [ABSTRACT FROM AUTHOR]

Selection of personalized chemotherapy regimen for individual patients has significant potential to improve chemotherapy efficacy and to reduce the deleterious effects of ineffective chemotherapy drugs. In this study, a rapid and high-throughput in vitro drug response assay was developed using a combination of microwell array and molecular imaging. The microwell array provided high-throughput analysis of drug response, which was quantified based on the reduction in intracellular uptake (2-[ N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino]-2-deoxy- d-glucose) (2-NBDG). Using this synergistic approach, the drug response measurement was completed within 4 h, and only a couple thousand cells were needed for quantification. The broader application of this microwell molecular imaging approach was demonstrated by evaluating the drug response of two cancer cell lines, cervical (HeLa) and bladder (5637) cancer cells, to two distinct classes of chemotherapy drugs (cisplatin and paclitaxel). This approach did not require an extended cell culturing period, and the quantification of cellular drug response was 4-16 times faster compared with other cell-microarray drug response studies. Moreover, this molecular imaging approach had comparable sensitivity to traditional cell viability assays, i.e., the MTT assay and propidium iodide labeling of cellular nuclei;and similar throughput results as flow cytometry using only 1,000-2,000 cells. Given the simplicity and robustness of this microwell molecular imaging approach, it is anticipated that the assay can be adapted to quantify drug responses in a wide range of cancer cells and drugs and translated to clinical settings for a rapid in vitro drug response using clinically isolated samples. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

The glutathione S-transferases (GSTs) are phase II xenobiotic metabolizing enzymes known to be involved in the detoxification of carcinogens and anticancer drugs. Individual genetic variation linked to inherited polymorphisms of GSTT1 and GSTM1 leading to a complete loss of enzyme activity could expose subjects to develop cancer or to induce drug resistance. Indeed, despite the impressive results obtained with the imatinib, some patients with chronic myeloid leukemia (CML) fail to achieve the expected results or develop resistance. The present study aimed to examine the impact of GSTT1 and GSTM1 polymorphisms on the response to imatinib in patients with CML. Multiplex polymerase chain reaction was used to detect the genotypes of GSTT1 and GSTM1 in 60 CML patients. We found that side effects were more frequent in patients carrying GSTT1 null when compared to GSTT1 present carriers (31 vs. 16.6 %; χ = 6.2; p = 0.013). The loss of hematologic response was statistically greater in patients carrying the combined genotype GSTT1 present/ GSTM1 present (26.3 %) when compared to GSTT1 null/ GSTM1 present (12.8 %), GSTT1 present/ GSTM1 null (8.3 %) and GSTT1 null/ GSTM1 null (0 %), ( χ = 18.85; p < 0.001). The complete cytogenetic response was higher in patients harboring the GSTT1 null/ GSTM1 null (75 %) compared with GSTT1 null/ GSTM1 present (55.6 %), GSTT1 present/ GSTM1 null (50 %) and GSTT1 present/ GSTM1 present (47.8). On the other hand, the frequency of none cytogenetic responders was more common in patients carrying GSTT1 present/ GSTM1 present (34.8 %) when compared to other genotype combinations ( χ = 20.99; p = 0.05). Moreover, the GSTT1 present/ GSTM1 present appeared to be associated with a final dose of 600 or 800 mg of imatinib, but not significantly. Based on these findings, we find that the interaction between GSTT1 and GSTM1 seems to influence treatment outcome in patients with CML. Therefore, further investigations are required to confirm these results, for better genotype-phenotype correlation. [ABSTRACT FROM AUTHOR]

In the spite of the impressive results achieved with imatinib in chronic myeloid leukemia (CML) patients, differences in patient's response are observed, which may be explained by interindividual genetic variability. It is known that cytochrome P450 enzymes play a major role in the metabolism of imatinib. The present study aimed to understand the functional impact of CYP2B6 15631G>T polymorphism on the response of imatinib in CML patients and its relation to CML susceptibility. We have genotyped CYP2B6 G15631T in 48 CML patients and 64 controls by PCR-RFLP. CYP2B6 15631G>T was not found to be a risk factor for CML (OR 95 % CI, 1.12, 0.6-2, p > 0.05). Hematologic response loss was higher in patients with 15631GG/TT genotype when compared with 15631GT (36.8 vs. 13.8 %; X = 3.542, p = 0.063). Complete cytogenetic response was higher in 15631GG/GT genotype groups when compared with 15631TT ( X = 3.298, p = 0.024). Primary cytogenetic resistance was higher in patients carrying 15631GG/TT genotype when compared with 15631GT carriers (52.6 vs. 17.2 %; X = 6.692, p = 0.010). Furthermore, side effects were more common for patients carrying 15631GG genotypes when compared with GT/TT carriers (36 vs. 13.8 %; X = 8.3, p = 0.004). In light of our results, identification of 15631G>T polymorphism in CML patients might be helpful to predict therapeutic response to imatinib. [ABSTRACT FROM AUTHOR]

Notwithstanding the availability of disease-modifying treatments including interferon-β, glatiramer acetate, and natalizumab, a considerable proportion of multiple sclerosis (MS) patients experience continued progression of disease, clinical relapses, disease activity on MRI, and adverse effects. Application of gene expression, proteomic or genomic approaches is universally accepted as a suitable strategy toward the identification of biomarkers with predictive value for beneficial/poor clinical response to therapy and treatment risks. This review focuses on recent progress in research on the pharmacogenomics of disease-modifying therapies for MS. Although MS drug response biomarkers are not yet routinely implemented in the clinic, the diversity of reported, promising molecular markers is rapidly increasing. Even though most of these markers await further validation, given time, this research is likely to empower neurologists with an enhanced armamentarium to facilitate rational decisions on therapy and patient management. [ABSTRACT FROM AUTHOR]

The role of a functional polymorphism in the transcriptional control region of serotonin transporter gene (5-HTTLPR, SERTPR) has been studied intensively in major depression and in the response to selective serotonin inhibitors (SSRIs) in major depression. The findings have been contradictory, although majority of the studies indicate that the short allele is associated with poor response to SSRIs in major depression. In the present study, we evaluated the association of 5-HTTLPR with treatment response to SSRI medication in Finnish Caucasian MDD patients. A secondary purpose was to study the possible association of this particular polymorphism with major depressive disorder. The aim of the study was to replicate the previous findings in this area. Primary outcomes of the treatment were remission, defined by an exit score of seven or less, and response, defined by a reduction of at least 50% on the MADRS. We had also a control population of 375 healthy blood donors, as a secondary objective was to evaluate the possible association of this particular polymorphism with major depressive disorder. Twenty-nine of the 85 (34.1%) patients reached the remission and 58.8% achieved the predefined response criteria. The l/l genotype of 5-HTTLPR was presented in 51.7% of those patients who achieved remission vs. 25.0% in the non-remitters ( P = 0.03). The result remained statistically significant after adjusting for age, gender, medication and MADRS points at the study entry. However, the small sample size limits the reliability of this result. [ABSTRACT FROM AUTHOR]

Our knowledge of the pharmacogenetics of warfarin and clopidogrel continues to expand as we learn more about the individual genetic variations that contribute to the drugs' efficacy and toxicity. We aim to review the recent developments in the field and discuss the clinical implications for the treatment of ischemic stroke patients. Despite recent advances, there is still insufficient data to suggest that routine genetic testing improves outcomes in patients treated with warfarin or clopidogrel for prevention of stroke. [ABSTRACT FROM AUTHOR]

Major Depressive Disorder (MDD) and antidepressant therapy response are largely based on behavioral criteria, which are known to correlate at best modestly with biological measures. Therefore, it is not surprising that the search for peripheral biological markers (biomarkers) being assessed in distant biological systems such as body fluids has not yet resulted in clinically convincing measures for MDD diagnostics or treatment evaluation. Imaging genetics studies, however, have been successful in the search for intermediate imaging phenotypes of MDD and treatment response that are directly related to the neurobiological underpinnings of MDD, but are not suitable for a broad clinical use today. Hence, we argue that intermediate phenotypes derived from imaging genetics studies should be utilized as substitutes of behaviorally assessed psychiatric diagnoses or therapy response in the search for easily accessible peripheral biomarkers. This article will further cover the current state of peripheral and neural biomarker research. [ABSTRACT FROM AUTHOR]

Development of effective and durable breast cancer treatment strategies requires a mechanistic understanding of the influence of the microenvironment on response. Previous work has shown that cellular signaling pathways and cell morphology are dramatically influenced by three-dimensional (3D) cultures as opposed to traditional two-dimensional (2D) monolayers. Here, we compared 2D and 3D culture models to determine the impact of 3D architecture and extracellular matrix (ECM) on HER2 signaling and on the response of HER2-amplified breast cancer cell lines to the HER2-targeting agents Trastuzumab, Pertuzumab and Lapatinib. We show that the response of the HER2-amplified AU565, SKBR3 and HCC1569 cells to these anti-HER2 agents was highly dependent on whether the cells were cultured in 2D monolayer or 3D laminin-rich ECM gels. Inhibition of β1 integrin, a major cell–ECM receptor subunit, significantly increased the sensitivity of the HER2-amplified breast cancer cell lines to the humanized monoclonal antibodies Trastuzumab and Pertuzumab when grown in a 3D environment. Finally, in the absence of inhibitors, 3D cultures had substantial impact on HER2 downstream signaling and induced a switch between PI3K-AKT- and RAS-MAPK-pathway activation in all cell lines studied, including cells lacking HER2 amplification and overexpression. Our data provide direct evidence that breast cancer cells are able to rapidly adapt to different environments and signaling cues by activating alternative pathways that regulate proliferation and cell survival, events that may play a significant role in the acquisition of resistance to targeted therapies. [ABSTRACT FROM AUTHOR]

The CAN-NCIC-MA22 phase I/II clinical trial evaluated women with locally advanced or inflammatory breast cancer treated with epirubicin and docetaxel at 2 or 3 weekly intervals in sequential cohorts. The relationship between various biomarkers and treatment response was assessed. Breast biopsy cores were obtained from 50 patients pre-, mid-, and post-treatment. Immunohistochemical staining was performed to determine baseline levels of estrogen receptor (ER), progesterone receptor (PR), Her2/Neu protein (HER2), and topoisomerase II (Topo 2), expressed as percent positive stain. Tumor RNA integrity (RIN) and tumor cellularity were measured pre-, mid- and post-treatment by capillary electrophoresis and light microscopy after hematoxylin/eosin staining, respectively. Associations between 1) maximum RIN and 2) tumor cellularity at the three time points with baseline levels of ER, PR, Her2, and topo II were assessed using Spearman and Pearson correlation coefficients. Associations between RIN and tumor cellularity with chemotherapy dose level or pathologic response were assessed using one-way ANOVA. In this study, we observed that low mid-treatment maximum RIN (but not tumor cellularity) was associated with high chemotherapy drug dose level ( P = 0.05) and eventual pathologic complete response (pCR) ( P = 0.01). Post-treatment, low maximum RIN was found to be associated with low tumor cellularity ( P = 0.004), and low tumor cellularity with pCR ( P = 0.01). Post-treatment tumor cellularity was lowest in patients with tumors having high baseline PR levels ( P = 0.05). The association of mid-treatment RIN with drug dose level and with pCR suggests that tumor RIN may represent an important new biomarker for measuring response to chemotherapy in breast cancer patients. [ABSTRACT FROM AUTHOR]

Pituitary tumor transforming gene 1 (PTTG1), a transforming gene highly expressed in several cancers, is a mammalian securin protein regulating both G1/S and G2/M phases. Using protein array screening, we showed PTTG1 interacting with Aurora kinase A (Aurora-A), and confirmed the interaction using co-immunoprecipitation, His-tagged pull-down assays and intracellular immunofluorescence colocalization. PTTG1 transfection into HCT116 cells prevented Aurora-A T288 autophosphorylation, inhibited phosphorylation of the histone H3 Aurora-A substrate and resulted in abnormally condensed chromatin. PTTG1-null cell proliferation was more sensitive to Aurora-A knock down and to Aurora kinase Inhibitor III treatment. The results indicate that PTTG1 and Aurora-A interact to regulate cellular responses to anti-neoplastic drugs. PTTG1 knockdown is therefore a potential approach to improve the efficacy of tumor Aurora kinase inhibitors.Oncogene (2008) 27, 6385–6395; doi:10.1038/onc.2008.234; published online 28 July 2008 [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine if magnetic resonance imaging (MRI) could quantify a difference in clitoral response following administration of a vasoactive medication, in 12 women with female sexual arousal disorder (FSAD). Subjects were entered into a double-blind, randomized two-way crossover study of sildenafil 50 mg vs placebo administered 1 h prior to genital MRI. Each subject underwent two MR studies, performed while subjects viewed alternating segments of nonerotic and erotic video. MR images were analyzed for change in clitoral volume during each session. The mean change in clitoral volume for the entire group was higher in the sildenafil MRI session (1282 mm3) compared with placebo (849 mm3) but did not reach statistical significance (P=0.064). Comparison using analysis of variance between the two sessions for each individual subject revealed a significant increase in clitoral volume following sildenafil compared with placebo in 6 of 12 subjects, no significant change in either imaging session in three subjects and in three subjects, there was a robust clitoral response in both MR sessions. In conclusion, MR measurements of clitoral volume can provide an objective measure of engorgement change following a vasoactive medication in women with FSAD.International Journal of Impotence Research (2008) 20, 105–110; doi:10.1038/sj.ijir.3901625; published online 6 December 2007 [ABSTRACT FROM AUTHOR]

There is limited information describing species related pharmacogenetic differences in animals. Despite the lack of genetic information in veterinary medicine, breed specific responses to endogenous and exogenous substances have been reported across many species. This finding underscores the importance of obtaining insight into the genotypic and phenotypic variation present across breeds. This article provides a summary of the literature pertaining to canine breed differences in physiology, drug response, drug pharmacokinetics, and metabolic idiosyncrasies. The existing knowledge of pedigrees and the known phenotypes and genotypes of dogs provides important information for determining mode of inheritance, penetration, and other major characteristics of heritable traits. Understanding these breed differences will improve canine population predictions (for canine drug products) and may be of value when extrapolating toxicology data from dogs to humans. [ABSTRACT FROM AUTHOR]

The study was designed to determine whether impaired antiplatelet response to clopidogrel but not to aspirin may be responsible for loss of pleiotropic effects of the drug. Study included 34 consecutive patients with STEMI undergoing primary percutaneous coronary intervention (PCI) with stent implantation treated with aspirin (loading dose 300 mg followed by 75 mg/day) and clopidogrel (loading dose 600 mg followed by 75 mg/day). On the basis of Platelet Function Analyzer (PFA)-100 test which measured closure times (CT) in test with collagen/epinephrine (CEPI-CT) or collagen/adenosine diphosphate (CADP-CT) patients were stratified after 7 days from admission as full aspirin or clopidogrel responders (CEPI-CT or CADP-CT = 300 sec., respectively) and non-full aspirin or clopidogrel responders (CEPI-CT or CADP-CT < 300 sec., respectively). High sensitivity C-reactive protein (hs-CRP) was measured at baseline and after 7 days of treatment. All patients received comparable statin treatment. Median and interquartile ranges (IQR) of hs-CRP increased significantly from 2.5 mg/L (0.4–44.8) at baseline to 8.05 mg/L (1.4–33.9) at day 7 ( P = .002) in non-full clopidogrel responders subgroup and only slightly in the full clopidogrel responders subgroup (2.45 mg/L, IQR 0.4–48.3 vs. 4.2 mg/L, IQR 1.9–17.5) ( P = .3) remaining within reference intervals. On the contrary median and IQR of hs-CRP increased significantly in both non-full aspirin responders (2.4 mg/L, IQR 1.3–3.3 vs. 5.8 mg/L, IQR 3.2–14.8, P = .01) and full aspirin responders (2.9 mg/L, IQR 2.0–3.7 vs. 5.6 mg/L, IQR 4.3–12.9, P = .04). Impaired antiplatelet response to clopidogrel but not to aspirin may contribute to smaller anti-inflammatory response in patients with ST-elevation myocardial infarction. [ABSTRACT FROM AUTHOR]

The product of the ABCB1 gene, P-glycoprotein (PGP), is a transmembrane active efflux pump for a variety of drugs. It is a putative mechanism of multidrug resistance in a range of diseases. It is postulated that ABCB1 polymorphisms contribute to variability in PGP function, and that therefore multidrug resistance is, at least in part, genetically determined. However, studies of ABCB1 genotype or haplotype and PGP expression, activity or drug response have produced inconsistent results. This critical review of ABCB1 genotype and PGP function, including mRNA expression, PGP–substrate drug pharmacokinetics and drug response, highlights methodological limitations of existing studies, including inadequate power, potential confounding by co-morbidity and co-medication, multiple testing, poor definition of disease phenotype and outcomes, and analysis of multiple drugs that might not be PGP substrates. We have produced recommendations for future research that will aid clarification of the association between ABCB1 genotypes and factors related to PGP activity.The Pharmacogenomics Journal (2007) 7, 154–179. doi:10.1038/sj.tpj.6500413; published online 12 September 2006 [ABSTRACT FROM AUTHOR]

For many psychiatric conditions it is speculated that, rather than being single disease entities, they are a set of several disorders sharing clinical features but having (partly) different underlying causes. The possibility of measuring genetic variation on a large scale has given researchers new hope of identifying these disease subtypes that may differ with respect to prognosis, course, and response to treatment. However, although a considerable number of articles have been published suggesting that we may even be on the verge of making genotype-based diagnoses, the reality is that we do not have a good answer to even the most basic question of how measured genes could best be used to refine diagnostic categories. In this article, we show that for common psychiatric disorders, it may not be possible to simply look for similar genetic profiles in groups of patients. Instead, we propose a model assuming that genotypes affect phenotypes through more or less coherent etiological systems or pathogenic processes and argue that these etiological systems may provide a more fruitful basis for defining disease subtypes. Several examples from the literature that support the face validity of different aspects of our model are given. Finally, we argue that, given our limited knowledge of disease etiology, the use of discovery-oriented techniques requiring extensive data collection and (artificial) intelligent computer searches may be imperative, and discuss the prospect of model-based diagnosis to classify etiologically different disease subtypes. [ABSTRACT FROM AUTHOR]

Cocaine addiction is a major health and social problem for which there are presently no effective pharmacotherapies. Many of the most promising medications target dopamine based on the large literature that supports its role in addiction. Recent studies show that genetic factors are also important. Rodent models and gene knock-out technology have helped elucidate the involvement of specific genes in the function of the dopamine reward system and intracellular cascades that lead to neuronal changes in this system. Human epidemiological, linkage, and association studies have identified allelic variants (polymorphisms) that give rise to altered metabolism of dopamine and its functional consequences. Individuals with these polymorphisms respond differently to psychostimulants and possibly to pharmacotherapies. Here we review the literature on genetic variations that affect dopamine neurotransmission, responses to psychostimulants and potential treatments for cocaine addiction. Behavioral responses to psychostimulants in animals with different or modified genetics in dopamine signaling are discussed. We also review polymorphisms in humans that affect dopaminergic neurotransmission and alter the subjective effects of psychostimulants. Pharmacotherapies may have increased efficacy when targeted to individuals possessing specific genetic polymophisms in dopamine’s metabolic and intracellular messenger systems. [ABSTRACT FROM AUTHOR]

At the blood–brain barrier (BBB) many cellular and dynamic mechanisms influence the cerebral drug metabolism and the drug response. In this review, we focus mainly on the role P-glycoprotein (P-gp) plays at the BBB. This protein is a 170-kDa ATP-dependent drug transport protein, located in the apical membrane of endothelial cells. Utilizing ATP hydrolysis as an energy source, it exports molecules which attempt to pass through the cell membrane from the outside to the inside, protecting cells from toxins and a wide range of substances. We briefly summarize some of the currently available in vivo and in vitro methods to investigate P-gp and its substrates. Hitherto, no chemical characteristic has been discovered that clearly distinguishes substrates from non-substrates of P-gp. We discuss some examples of substrates stressing the diversity of drugs and endogenous substances that relate to P-gp either as a substrate, an inhibitor, an inducer or as a combination of the above. Finally, we discuss genetic polymorphisms of the genes encoding for P-gp and their effects on drug response. [ABSTRACT FROM AUTHOR]