Bioactivated Glucoraphanin Modulates Genes Involved in Necroptosis on Motor-Neuron-like Nsc-34: A Transcriptomic Study.

Research on bioactive compounds has grown recently due to their health benefits and limited adverse effects, particularly in reducing the risk of chronic diseases, including neurodegenerative conditions. According to these observations, this study investigates the activity of sulforaphane (RS-GRA) on an in vitro model of differentiated NSC-34 cells. We performed a transcriptomic analysis at various time points (24 h, 48 h, and 72 h) and RS-GRA concentrations (1 µM, 5 µM, and 10 µM) to identify molecular pathways influenced by this compound and the effects of dosage and prolonged exposure. We found 39 differentially expressed genes consistently up- or downregulated across all conditions. Notably, Nfe2l2, Slc1a5, Slc7a11, Slc6a9, Slc6a5, Sod1, and Sod2 genes were consistently upregulated, while Ripk1, Glul, Ripk3, and Mlkl genes were downregulated. Pathway perturbation analysis showed that the overall dysregulation of these genes results in a significant increase in redox pathway activity (adjusted p-value 1.11 × 10-3) and a significant inhibition of the necroptosis pathway (adjusted p-value 4.64 × 10-3). These findings suggest RS-GRA's potential as an adjuvant in neurodegenerative disease treatment, as both increased redox activity and necroptosis inhibition may be beneficial in this context. Furthermore, our data suggest two possible administration strategies, namely an acute approach with higher dosages and a chronic approach with lower dosages.

Genetic underpinnings of YMRS and MADRS scores variations in a bipolar sample.

Bipolar disorder (BPD) affects approximately 2% of the global population. Its clinical course is highly variable and current treatments are not always effective for all patients. Genetic factors play a significant role in BPD and its treatment, although the genetic background appear to be highly heterogeneous. Polygenic risk scores (PRS) are a powerful tool for risk assessment, yet using all genomic data may introduce confounding factors. Focusing on specific genetic clusters PRS (gcPRS) may mitigate this issue. This study aims to assess a neural network model's efficacy in predicting response to treatment (RtT) in BPD individuals using PRS calculated from specific gcPRS and other variables. 1538 individuals from STEP-BD (age 41.39 ± 12.66, 59.17% female) were analyzed. gcPRS were calculated from a Genome-wide association study (GWAS) with clinical covariates and a molecular pathway analysis (MPA) based on drugs interaction networks. A neural network was trained using gcPRS and clinical variables to predict RtT. Ten biological networks were identified through MPA, with gcPRS derived from risk variants within corresponding gene groups. However, the model did not show significant accuracy in predicting RtT in BPD individuals. RtT in BPD is influenced by multiple factors. This study attempted a comprehensive approach integrating clinical and biological data to predict RtT. However, the model did not achieve significant accuracy, possibly due to limitations such as sample size, disorder complexity, and population heterogeneity. This data highlights the challenge of developing personalized treatments for BPD and the necessity for further research in this area.

In Silico Analysis Highlights Potential Predictive Indicators Associated with Secondary Progressive Multiple Sclerosis.

Multiple sclerosis (MS) is a complex inflammatory disease affecting the central nervous system. Most commonly, it begins with recurrent symptoms followed by partial or complete recovery, known as relapsing-remitting MS (RRMS). Over time, many RRMS patients progress to secondary progressive MS (SPMS), marked by gradual symptom deterioration. The factors triggering this transition remain unknown, lacking predictive biomarkers. This study aims to identify blood biomarkers specific to SPMS. We analyzed six datasets of SPMS and RRMS patients' blood and brain tissues, and compared the differential expressed genes (DEGs) obtained to highlight DEGs reflecting alterations occurring in both brain and blood tissues and the potential biological processes involved. We observed a total of 38 DEGs up-regulated in both blood and brain tissues, and their interaction network was evaluated through network analysis. Among the aforementioned DEGs, 21 may be directly involved with SPMS transition. Further, we highlighted three biological processes, including the calcineurin-NFAT pathway, related to this transition. The investigated DEGs may serve as a promising means to monitor the transition from RRMS to SPMS, which is still elusive. Given that they can also be sourced from blood samples, this approach could offer a relatively rapid and convenient method for monitoring MS and facilitating expedited assessments.

Network Analysis Performed on Transcriptomes of Parkinson's Disease Patients Reveals Dysfunction in Protein Translation.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra region of the brain. The hallmark pathological feature of PD is the accumulation of misfolded proteins, leading to the formation of intracellular aggregates known as Lewy bodies. Recent data evidenced how disruptions in protein synthesis, folding, and degradation are events commonly observed in PD and may provide information on the molecular background behind its etiopathogenesis. In the present study, we used a publicly available transcriptomic microarray dataset of peripheral blood of PD patients and healthy controls (GSE6613) to investigate the potential dysregulation of elements involved in proteostasis-related processes at the transcriptomic level. Our bioinformatics analysis revealed 375 differentially expressed genes (DEGs), of which 281 were down-regulated and 94 were up-regulated. Network analysis performed on the observed DEGs highlighted a cluster of 36 elements mainly involved in the protein synthesis processes. Different enriched ontologies were related to translation initiation and regulation, ribosome structure, and ribosome components nuclear export. Overall, this data consistently points to a generalized impairment of the translational machinery and proteostasis. Dysregulation of these mechanics has been associated with PD pathogenesis. Understanding the precise regulation of such processes may shed light on the molecular mechanisms of PD and provide potential data for early diagnosis.

Body weight changes and bipolar disorder: a molecular pathway analysis.

BACKGROUND: There is evidence suggesting a link between weight-related disorders and bipolar disorder (BD). The pathophysiology of the association includes psychological, social and psychotropic treatment-related variables, together with psychiatric comorbidity. Weight changes during BD may influence compliance to the treatment, quality of life and prognosis, and can modulate risk of death associated with, for example, diabetes or cardiovascular disorders. METHODS: The STEP-BD sample is analyzed through a hypothesis-free molecular pathway analysis in order to detect the molecular pathways that distinguish individuals who experience weight change during BD treatment from those who do not. A total of 618 individuals were available for the analysis, mean age = 41.19 ± 12.58, females = 351 (56.8%). Socioeconomic variables and treatment-related variables were included as clinical covariates. A cluster analysis in the genetic dataset provided the genetic covariate input to the study to avoid stratification factors. RESULT: After applying the quality analysis that is typical for this kind of investigation, no Genome Wide Association Study significant finding was retrieved. Six molecular pathways were found to be significantly associated with weight change during the first 3 months of treatment after correction for multiple testing. Of those, CDC42 (R-HSA-9013148) participates in insulin synthesis and secretion and contributes to the pathogenesis of insulin resistance and Rac Family Small GTPase 1 (R-HSA-9013149) is involved in metabolic regulation of pancreatic islet ß-cells and in diabetes pathophysiology. DISCUSSION: Pathways that are central in energy homeostasis may play a role to separate individuals with BD that will experience weight changes during treatment from those who will not. If confirmed, such finding can be instrumental in the identification of the correct preventive strategies and most correct treatment to increase compliance and efficacy in the treatment of BD.

Metabolizing status of CYP2C19 in response and side effects to medications for depression: Results from a naturalistic study.

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Polymorphisms in cytochrome P450 genes (CYP450) were demonstrated to play a significant role in antidepressant response and side effects, but their effect in real-world clinical practice is poorly known. We determined the metabolic status of CYP2C19 based on the combination of *1, *2, *3 and *17 alleles extracted from genome-wide data in 1239 patients with MDD, pharmacologically treated in a naturalistic setting. Symptom improvement and side effects were assessed using the Montgomery and Åsberg Depression Rating Scale and the Udvalg for Kliniske Undersøgelse scale, respectively. We tested if symptom improvement, response and side effects were associated with CYP2C19 metabolic status adjusting for potential confounders. We considered patients treated with drugs for depression having CYP2C19 genotyping recommended by guidelines (T1 Drugs); secondarily, with all psychotropic drugs having CYP2C19 as relevant metabolic path (T2 Drugs). In the group treated with T1 drugs (n = 540), poor metabolizers (PMs) showed higher response and higher symptom improvement compared to normal metabolizers (p = 0.023 and p = 0.009, respectively), but also higher risk of autonomic and neurological side effects (p = 0.022 and p = 0.022 respectively). In patients treated with T2 drugs (n = 801), similar results were found. No associations between metabolizer status and other types of side effects were found (psychic and other side effects). Our study suggests potential advantages of CYP2C19 pharmacogenetic testing to guide treatment prescription, that may not be limited to the drugs currently recommended by guidelines.

Suicide Related Phenotypes in a Bipolar Sample: Genetic Underpinnings.

Suicide in Bipolar Disorder (BD) is a relevant clinical concern. Genetics may shape the individual risk for suicide behavior in BD, together with known clinical factors. The lack of consistent replication in BD may be associated with its multigenetic component. In the present contribution we analyzed a sample of BD individuals (from STEP-BD database) to identify the genetic variants potentially associated with three different suicide-related phenotypes: (1) a feeling that the life was not worth living; (2) fantasies about committing a violent suicide; (3) previous attempted suicide. The sample under analysis included 1115 BD individuals. None of the SNPs reached genome-wide significance. However, a trend of association was evidenced for rs2767403, an intron variant of AOPEP gene, in association with phenotype #1 (p = 5.977 × 10-6). The molecular pathway analysis showed a significant enrichment in all the investigated phenotypes on pathways related to post synaptic signaling, neurotransmission and neurodevelopment. Further, NOTCH signaling or the γ-aminobutyric acid (GABA)-ergic signaling were found to be associated with specific suicide-related phenotypes. The present investigation contributes to the hypothesis that the genetic architecture of suicide behaviors in BD is related to alteration of entire pathways rather than single genes. In particular, our molecular pathway analysis points on some specific molecular events that could be the focus of further research in this field.

CNVs inform the biological network of Autism spectrum disorder.

Autism spectrum disorder (ASD) is a heterogeneous condition linked to an anomalous neurodevelopment. Although the underlying causes of ASD are not well described, literature data strongly suggests a genetic component, with a complex inheritance pattern. It has recently been observed that CNVs (copy number variation) may play an important role in ASD manifestation and partially explain the complex heritability of this tract. Another factor That adds another level of complexity to ASD is its potential genetic heterogeneity. In this paper, we hypothesize that the different patterns of alteration within individuals with ASD may converge towards the same function. We genotyped a sample of 107 individuals through aCGH analysis for CNVs that were related (by localization) to approximately 1400 genes. The genes were tested for functional interactions and clustered in functional groups. We highlighted a functional genetic cluster of 256 genes potentially related to ASD. These altered genes may contribute to the same function, alterations of which increase the risk of ASD. After testing our functional cluster for biological functions, processes related to oxidative stress, immune system and energy metabolism are the pathways potentially involved with the biological alterations underlying ASD.

The biological pathways of Alzheimer disease: a review.

Alzheimer disease is a progressive neurodegenerative disorder, mainly affecting older people, which severely impairs patients' quality of life. In the recent years, the number of affected individuals has seen a rapid increase. It is estimated that up to 107 million subjects will be affected by 2050 worldwide. Research in this area has revealed a lot about the biological and environmental underpinnings of Alzheimer, especially its correlation with ß-Amyloid and Tau related mechanics; however, the precise molecular events and biological pathways behind the disease are yet to be discovered. In this review, we focus our attention on the biological mechanics that may lie behind Alzheimer development. In particular, we briefly describe the genetic elements and discuss about specific biological processes potentially associated with the disease.

Molecular Pathways within Autism Spectrum Disorder Endophenotypes.

Autism spectrum disorder (ASD) is a condition that includes a number of neurodevelopmental mental disorders. Recent genetic/genomic investigations have reported an increased prevalence of copy number variations (CNVs) in individuals with autism. Despite the extensive evidence of a genetic component, the genes involved are not known and the background is heterogeneous among subjects. As such, it is highly likely that multiple events (molecular cascades) are implicated in the development of autism. The aim of this work was to shed some light on the biological background behind this condition. We hypothesized that the heterogeneous alterations found within different individuals may converge into one or more specific biological functions (pathways) linked to the heterogeneous phenotypes commonly observed in subjects with ASD. We analyzed a sample of 107 individuals for CNV alterations and checked the genes located within the altered loci (1366). Then, we characterized the subjects for distinct phenotypes. After creating subsamples based on symptoms, the CNVs related to each specific symptom were used to create distinct networks associated with each phenotype (18 in total in the sample under analysis). These networks were independently clustered and enriched to identify potential common pathways involved in autism and variably combined with the clinical phenotype. The first 10 pathways of the analysis are discussed.

Possible Modulatory Role of ARC Gene Variants in Mood Disorders.

OBJECTIVE: The genetic background of mood disorders is gradually emerging through the use of large multicenter samples but a detailed phenotyping is complementary in elucidating the role of modulating variants. METHODS: In the present paper we focused on the possible modulatory effects of ARC gene variants on two independent mood disorder samples of European (n = 246 bipolar disorder) and Korean (n = 132 bipolar disorder; n = 242 major depressive disorder [MDD]) ancestry. RESULTS: No result survived Bonferroni correction, however we evidenced promising trend toward possible association between ARC gene variants and mood disorder phenotypes. In particular, we evidenced weak correlations of ARC single nucleotide polymorphisms with depressive symptoms severity (evaluated through Hamilton depression rating scale scores) in the MDD Korean (rs7465272) and European (rs11167152) samples. Additionally rs10110456 was found to be related to Family History, while rs7465272 was related to suicide risk in the Korean sample. Finally, rs7465272 was associated with body mass index in the European sample. CONCLUSION: Overall, ARC gene variants may have a partial role in modulatory effect on treatment efficacy or phenotypes of mood disorders. Further studies, on larger samples may provide a better understanding on the role of ARC gene variants in the symptom severity and treatment outcomes in patients with mood disorders.

Research Domain Criteria (RDoC): A Perspective to Probe the Biological Background behind Treatment Efficacy in Depression.

BACKGROUND: Major Depressive Disorder(MDD) and its frequent partial response to antidepressants are a major health concern and therefore an important focus of research. Despite the efforts, MDD pathogenesis and the mechanisms of antidepressant action are only partially understood. In the last few years, the need of rethinking the classification of depressive disorders and psychiatric disorders, in general, has been suggested, in order to provide a nosology that reflects more closely the biological background associated with disease pathogenesis and its role/significance in treatment. The classification proposed by the National Institute of Mental Health (NIMH), namely the research domain criteria (RDoC), may represent a key framework to guide research in this direction. METHODS: A literature search was performed on PubMed and Google Scholar databases in order to retrieve data regarding Antidepressants effects on specific RDoC constructs. Further, the targets of drugs of interest were identified through the Drug bank database, and their possible function within RDoC constructs was discussed. DISCUSSION: In this review, we summarize and discuss the significance of the results of pre-clinical and clinical studies investigating specific RDoC paradigms relevant to depressive phenotypes and antidepressant effects. CONCLUSION: The RDoC framework may facilitate a more specific use of antidepressants based on the individual's spectrum of symptoms and the development of new compounds that target specific depressive symptoms.

ZNF804A Gene Variants Have a Cross-diagnostic Influence on Psychosis and Treatment Improvement in Mood Disorders.

OBJECTIVE: Genetic variations in the gene encoding zinc finger protein 804A gene (ZNF804A) have been associated with major depression and bipolar disorder. In this work we focused on the potential influence of ZNF804A variations on the risk of developing specific sub-phenotypes as well as the individual response to available treatments. METHODS: We used two samples of different ethnic origin: a Korean sample, composed by 242 patients diagnosed with major depression and 132 patients diagnosed with bipolar disorder and 326 healthy controls; an Italian sample composed 151 major depression subjects, 189 bipolar disorder subjects and 38 outpatients diagnosed for a primary anxiety disorder. RESULTS: Our analyses reported an association of rs1344706 with psychotic phenotype in the cross-diagnostic pooled sample (geno p = 4.15 × 10-4, allelic p = 1.06 × 10-4). In the cross-diagnosis Italian sample but not in the Korean one, rs7597593 was involved with depressive symptoms improvement after treatment (geno p = 0.025, allelic p = 0.007). CONCLUSION: The present study evidenced the role of ZNF804A alterations in symptoms improvement after treatment. Both manic and depressive symptoms seem to be modulated by ZNF804A, though the latter was observed in the bipolar pooled sample only. The role of this factor is likely related to synaptic development and maintenance; however, further analyses will be needed to better understand the molecular mechanics involved with ZNF804A.

Genetic variants associated with psychotic symptoms across psychiatric disorders.

BACKGROUND: Recent evidence suggests that psychiatric symptoms share a common genetic liability across diagnostic categories. The present study investigated the effects of variants within previously identified relevant genes on specific symptom clusters, independently from the diagnosis. METHODS: 1550 subjects affected by Schizophrenia (SCZ), Major Depressive Disorder or Bipolar Disorder were included. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Hamilton Depression Rating Scale (HDRS). Principal component analysis and a further clinical refinement were used to define symptom clusters. Clusters scores were tested for association with 46 genetic variants within nine genes previously linked to one or more major psychiatric disorders by large genome wide association studies (ANK3, CACNA1C, CACNB2, FKBP5, FZD3, GRM7, ITIH3, SYNE1, TCF4). Exploratory analyses were performed in each disorder separately to further elucidate the SNPs effects. RESULTS: five PANSS clusters (Negative; Impulsiveness; Cognitive; Psychotic; Depressive) and four HDRS clusters (Core Depressive; Somatic; Psychotic-like; Insomnia) were identified. CACNA1C rs11615998 was associated with HDRS Psychotic cluster in the whole sample. In the SCZ sample, CACNA1C rs11062296 was associated with PANSS Impulsiveness cluster and CACNA1C rs2238062 was associated with PANSS negative cluster. DISCUSSION: CACNA1C rs11615998 was associated with psychotic symptoms (C-allele carriers have decreased psychotic-risk) independently from the diagnosis, in line with the evidence of a cross disorder effect of many risk variants. This gene was previously associated with SCZ and cross-disorder liability to psychiatric disorders. Our findings confirmed that deep phenotyping is pivotal to clarify the role of genetic variants on symptoms patterns.

Correction to: Psychiatric disorders and SLC6A4 gene variants: possible effects on alcohol dependence and alzheimer's disease.

The following authors have double affiliations: Stefania Boccia, Marco Di Nicola and they should read.

Psychiatric disorders and SLC6A4 gene variants: possible effects on alcohol dependence and alzheimer's disease.

Serotoninergic system is one of the most important neurotransmission systems investigated in the field of psychiatry. Extensive evidence reveals how alterations of this system, and especially of the SLC6A4 gene, may be associated with psychiatric disorders. In this study we aimed to evaluate the pleiotropic nature of SLC6A4 alterations and their association with the overall risk of brain diseases rather than disorder-specific. SLC6A4 variants, namely 5HTTLPR, STin2, rs2066713, rs25531, rs4251417, rs6354 and rs7224199 were investigated in 4 independent cohorts of subjects with specific psychiatric disorders, including Alcohol dependence disorder (ALC), Alzheimer disease (ALZ), Schizophrenia (SCZ) and Bipolar disorder (BPD). Other variables (biochemical parameters and Psychiatric scales scores) were also tested for association. SLC6A4 polymorphisms are not associated with the risk of developing major psychiatric disorders (SCZ and BPD); however some signals were detected in ALC (HTTLPR pd = 9.25 × 10-03, pr = 7.24 × 10-03; rs2066713 pd = 6.35 × 10-08; rs25531 pd = 2.95 × 10-02; rs4251417 pd = 2.46 × 10-03), and ALZ (rs6354 pr = 1.22 × 10-02; rs7224199 pd = 1.00 × 10-08, pr = 2.65 × 10-02) cohorts. Some associations were also observed on exploratory analyses. Our findings did not reveal any major influence on SCZ and BPD development; On the other hand, some alteration of the SLC6A4 sequence were associated with an increased risk of ALC and ALZ disorders, suggesting common pathways. The results of this study should be carefully interpreted since it suffers of some inherent limitations (e.g. cohort size, slight ethnic heterogeneity). Further analyses may provide better detail on the molecular processes behind SLC6A4 alterations.

Genes Involved in Neurodevelopment, Neuroplasticity and Major Depression: No Association for CACNA1C, CHRNA7 and MAPK1.

OBJECTIVE: Genetics factors are likely to play a role in the risk, clinical presentation and treatment outcome in major depressive disorder (MDD). In this study, we investigated the role of three candidate genes for MDD; calcium voltage- gated channel subunit alpha1 C ( CACNA1C ), cholinergic receptor nicotinic alpha 7 subunit ( CHRNA7 ), and mitogen- activated protein kinase 1 ( MAPK1 ). METHODS: Two-hundred forty-two MDD patients and 326 healthy controls of Korean ancestry served as samples for the analyses. Thirty-nine single nucleotide polymorphisms (SNPs) within CACNA1C , CHRNA7 , and MAPK1 genes were genotyped and subsequently tested for association with MDD (primary analysis) and other clinical features (symptoms' severity, age of onset, history of suicide attempt, treatment outcome) (secondary analyses). Single SNPs, haplotypes and epistatic analyses were performed. RESULTS: Single SNPs were not associated with disease risk and clinical features. However, a combination of alleles (haplotype) within MAPK1 was found associated with MDD-status. Secondary analyses detected a possible involvement of CACNA1C haplotype in resistance to antidepressant treatment. CONCLUSION: These data suggest a role for MAPK1 and CACNA1C in MDD risk and treatment resistance, respectively. However, since many limitations characterize the analysis, the results must be considered with great caution and verified.

Alzheimer's Disease and Neurotransmission Gene Variants: Focus on Their Effects on Psychiatric Comorbidities and Inflammatory Parameters.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder accounting for 60-70% of dementia cases. Genetic origin accounts for 49-79% of disease risk. This paper aims to investigate the association of 17 polymorphisms within 7 genes involved in neurotransmission (COMT, HTR2A, PPP3CC, RORA, SIGMAR1, SIRT1, and SORBS3) and AD. METHODS: A Greek and an Italian sample were investigated, for a total of 156 AD subjects and 301 healthy controls. Exploratory analyses on psychosis and depression comorbidities were performed, as well as on other available clinical and serological parameters. RESULTS: AD was associated with rs4680 within the COMT gene in the total sample. Trends of association were found in the 2 subsamples. Some nominal associations were found for the depressive phenotype. rs10997871 and rs10997875 within SIRT1 were nominally associated with depression in the total sample and in the Greek subsample. rs174696 within COMT was associated with depression comorbidity in the Italian subsample. DISCUSSION: Our data support the role of COMT, and particularly of rs4680, in the pathogenesis of AD. Furthermore, the SIRT1 gene seems to modulate depressive symptomatology in the AD population.

FKBP5 Gene Variants May Modulate Depressive Features in Bipolar Disorder.

BACKGROUND: Previous evidence suggested the possible association of FK506 binding protein 5 (FKBP5) gene variants in bipolar disorder (BPD). OBJECTIVE: Given the need of refinement of the findings obtained in large but poorly phenotyped samples, this study investigated the possible role of variants within FKBP5 in a small but deeply phenotyped BPD sample. METHODS: A sample (N = 131) of bipolar patients were investigated with 10 polymorphisms within the FKBP5 gene. A control sample (N = 65) was also used for the analyses. Treatment response and remission of symptoms were evaluated using of the Hamilton Depression Rating Scale (HDRS), Hamilton Anxiety Rating Scale (HARS), and Young Mania Rating Scale (YMRS). The same analyses were also performed on the depressive subsample of BPD (D.BPD). RESULTS: rs3800373 was associated with disorder risk in the depressive BPD subsample with the G allele being more frequent in subjects with a D.BPD phenotype. This was the only association that survived statistical correction. CONCLUSIONS: rs3800373 FKBP5 may increase the risk of developing predominantly depressed BPD, probably through the creation of an enhancer consensus sequence in the 3'UTR of the gene, thus potentially increasing its expression. This finding seems to be partially supported by literature data, which evidenced increased levels of FKBP5 in psychiatric subjects.

Pharmacogenetic and pharmacogenomic discovery strategies.

Genetic/genomic profiling at a single-patient level is expected to provide critical information for determining inter-individual drug toxicity and potential efficacy in cancer therapy. A better definition of cancer subtypes at a molecular level, may correspondingly complement such pharmacogenetic and pharmacogenomic approaches, for more effective personalized treatments. Current pharmacogenetic/pharmacogenomic strategies are largely based on the identification of known polymorphisms, thus limiting the discovery of novel or rarer genetic variants. Recent improvements in cost and throughput of next generation sequencing (NGS) are now making whole-genome profiling a plausible alternative for clinical procedures. Beyond classical pharmacogenetic/pharmacogenomic traits for drug metabolism, NGS screening programs of cancer genomes may lead to the identification of novel cancer-driving mutations. These may not only constitute novel therapeutic targets, but also effector determinants for metabolic pathways linked to drug metabolism. An additional advantage is that cancer NGS profiling is now leading to discovering targetable mutations, e.g., in glioblastomas and pancreatic cancers, which were originally discovered in other tumor types, thus allowing for effective repurposing of active drugs already on the market.