Pharmacogenomic Biomarkers Research Articles

Pharmacogenomic and Pharmacometabolomic Biomarkers of the Efficacy and Safety of Antidepressants: Focus on Selective Serotonin Reuptake Inhibitors

Pharmacogenomic and Pharmacometabolomic Biomarkers of the Efficacy and Safety of Antidepressants: Focus on Selective Serotonin Reuptake Inhibitors

Pharmacogenomic augmented machine learning in electronic health record alerts: A health system-wide usability survey of clinicians.

Pharmacogenomic (PGx) biomarkers integrated using machine learning can be embedded within the electronic health record (EHR) to provide clinicians with individualized predictions of drug treatment outcomes. Currently, however, drug alerts in the EHR are largely generic (not patient-specific) and contribute to increased clinician stress and burnout. Improving the usability of PGx alerts is an urgent need. Therefore, this work aimed to identify principles for optimal PGx alert design through a health-system-wide, mixed-methods study. Clinicians representing multiple practices and care settings (N = 1062) in urban, rural, and underserved regions were invited to complete an electronic survey comparing the usability of three drug alerts for citalopram, as a case study. Alert 1 contained a generic warning of pharmacogenomic effects on citalopram metabolism. Alerts 2 and 3 provided patient-specific predictions of citalopram efficacy with varying depth of information. Primary outcomes included the System's Usability Scale score (0-100 points) of each alert, the perceived impact of each alert on stress and decision-making, and clinicians' suggestions for alert improvement. Secondary outcomes included the assessment of alert preference by clinician age, practice type, and geographic setting. Qualitative information was captured to provide context to quantitative information. The final cohort comprised 305 geographically and clinically diverse clinicians. A simplified, individualized alert (Alert 2) was perceived as beneficial for decision-making and stress compared with a more detailed version (Alert 3) and the generic alert (Alert 1) regardless of age, practice type, or geographic setting. Findings emphasize the need for clinician-guided design of PGx alerts in the era of digital medicine.

Pharmacogenomics: Importance in Exploration of Target Molecule, Drug Resistance and Mechanism in Cancer Chemotherapy

Background: The field of pharmacogenomics investigates the ways in which genes impact the body's reaction to drugs. Through the integration of genetics and medical knowledge, it is possible to develop individualised and efficient therapies that are based on genetic profiles. Specifically, this evaluation focuses on three aspects: Finding molecular targets and gaining a grasp of their structures is the first step. 2. Using pharmacogenomics to lessen the harmful effects of drugs 1. 3. Predicting pharmacological mechanisms based on genetic variances. Methods: A systematic review examining pharmacogenomics' role in cancer chemotherapy, focusing on target molecules, drug resistance, and mechanism, was conducted using PRISMA-compliant databases. The review included English-published journals from 2000-2023, aiming to reduce bias and ensure all relevant research is found, chosen, and critically assessed. Results: The results show that over the past 20 years, cytotoxic medications and personalized treatments have significantly improved cancer treatment strategies. Targeted drugs, small molecule drugs, and pharmacogenomic biomarkers offer targeted treatment for carcinoma tissues. Conclusion: Understanding genetic profiles and drug resistance is crucial for effective cancer treatment. Combination therapies have advanced treatment for advanced or metastatic cancers.

Pharmacogenomic biomarkers in coronary artery disease: a narrative review.

Coronary artery disease (CAD) has a high mortality rate. Despite various therapeutic targets, non-responsiveness to drugs remains a prevalent issue. Pharmacogenomics assesses the way an individual's genetic attributes affect their likely response to drug therapy. Single-nucleotide polymorphisms play a crucial role in determining these outcomes. This review offers an overview of single-nucleotide polymorphisms investigated in clinical studies and their associations with drug response/nonresponse in the treatment of CAD. A total of 104 studies of whole sets of chromosomes and several genes were explored. A total of161 polymorphisms exhibited associations with drug response/nonresponse in CAD across diverse ethnic populations. This pool can serve as a pharmacogenomic biomarker for predicting response to drug therapy in patients with CAD.

Pharmacogenomic biomarker information on drug labels of the Spanish Agency of Medicines and Sanitary products: evaluation and comparison with other regulatory agencies.

This work aimed to analyse the pharmacogenetic information in the Spanish Drug Regulatory Agency (AEMPS) Summary of Products Characteristics (SmPC), evaluating the presence of pharmacogenetic biomarkers, as well as the associated recommendations. A total of 55.4% of the 1891 drug labels reviewed included information on pharmacogenetic biomarker(s). Pharmacogenomic information appears most frequently in the "antineoplastic and immunomodulating agents", "nervous system", and "cardiovascular system" Anatomical Therapeutic Chemical groups. A total of 509 different pharmacogenetic biomarkers were found, of which CYP450 enzymes accounted for almost 34% of the total drug-biomarker associations evaluated. A total of 3679 drug-biomarker pairs were identified, 102 of which were at the 1A level (PharmGKB® classification system), and 33.33% of these drug-pharmacogenetic biomarker pairs were assigned to "actionable PGx", 12.75% to "informative PGx", 4.9% to "testing recommended", and 4.9% to "testing required". The rate of coincidence in the assigned PGx level of recommendation between the AEMPS and regulatory agencies included in the PharmGKB® Drug Label Annotations database (i.e., the FDA, EMA, SWISS Medic, PMDA, and HCSC) ranged from 45% to 65%, being 'actionable level' the most frequent. On the other hand, discrepancies between agencies did not exceed 35%. This study highlights the presence of relevant pharmacogenetic information on Spanish drug labels, which would help avoid interactions, toxicity, or lack of treatment efficacy.

Pharmacogenomic and pharmacometabolomic biomarkers of the efficacy and safety of antidepressants: focus on selective serotonin reuptake inhibitors

The efficacy and safety of psychopharmacotherapy with antidepressants is of great medical importance. The search for clinical and biological predictors for choosing the optimal psychopharmacotherapy with antidepressants is actively underway all over the world. Research is mainly devoted to searching for associations of polymorphic gene variants with the efficacy and safety of therapy. However, information about a patient's genetic polymorphism is often insufficient to predict the efficacy and safety of a drug. Modern research on the personalization of pharmacotherapy should include, in addition to genetic, phenotypic biomarkers. This is important because genotyping, for example, cannot accurately predict the actual metabolic activity of an isoenzyme. To personalize therapy, a combination of methods is required to obtain the most complete profile of the efficacy and safety of the drug. Successful treatment of depression remains a challenge, and inter-individual differences in response to antidepressants are common. About half of patients with depressive disorders do not respond to the first attempt at antidepressant therapy. Serious side-effects of antidepressant pharmacotherapy and discontinuation of treatment due to their intolerance are associated with ineffective therapy. This review presents the results of the latest studies of «omics» biomarkers of the efficacy and safety of antidepressants.

Influence of IL-β, IL-1RN, and TNF-α variants on the risk of acetylsalicylic acid-induced upper gastrointestinal bleeding: a case-control study.

Forgerini et al. investigated the role of seven genetic variants in the risk of upper gastrointestinal bleeding as an adverse drug reaction. In 289 participants (50 cases and 189 controls), the presence of seven variants in the IL-1β, IL-1RN, and TNF-α genes was not associated with susceptibility to acetylsalicylic acid-induced upper gastrointestinal bleeding. The use of acetylsalicylic acid, even in low doses, may be associated with the onset of upper gastrointestinal bleeding as an idiosyncratic response. Considering the role of the genetic background in inter-individual responses to pharmacotherapy, we aimed to investigate the role of seven variants in the TNF-α, IL-β, and IL-1RN genes in association with the risk of upper gastrointestinal bleeding in users of low-dose acetylsalicylic acid for the prevention of cardiovascular events. A case-control study was conducted in a Brazilian hospital complex. The Case Group comprised patients diagnosed with upper gastrointestinal bleeding who were administered a low dose of acetylsalicylic acid (n=50). Two Control Groups were recruited: 1) low-dose acetylsalicylic acid users without gastrointestinal complaints and under the supervision of a cardiologist (n=50) and 2) healthy controls (n=189). Sociodemographic, clinical, pharmacotherapeutic, and lifestyle data were recorded through face-to-face interviews. Genomic DNA from all participants was genotyped for rs16944 and rs1143634 (IL-β gene), rs4251961 (IL-1RN gene), and rs1799964, rs1799724, rs361525, and rs1800629 (TNF-α gene). No significant difference was noted in the genotypic frequencies of TNF-α, IL-β, and IL-1RN variants between the Case and Control Groups of low-dose acetylsalicylic acid users (p>0.05). The frequency of rs1800629 genotypes (TNF-α gene) differed significantly between the Case Group and healthy controls (p=0.003). None of the evaluated variants were associated with a risk of upper gastrointestinal bleeding. This study aimed to explore pharmacogenomics biomarkers in low-dose acetylsalicylic acid users. Our data suggest that the presence of IL-1β, IL-1RN, and TNF-α variants was not associated with an increased risk of upper gastrointestinal bleeding.

Antihypertensives associated adverse events: a review of mechanisms and pharmacogenomic biomarkers available evidence in multi-ethnic populations.

Hypertension remains a significant health burden worldwide, re-emphasizing the outstanding need for more effective and safer antihypertensive therapeutic approaches. Genetic variation contributes significantly to interindividual variability in treatment response and adverse events, suggesting pharmacogenomics as a major approach to optimize such therapy. This review examines the molecular mechanisms underlying antihypertensives-associated adverse events and surveys existing research on pharmacogenomic biomarkers associated with these events. The current literature revealed limited conclusive evidence supporting the use of genetic variants as reliable indicators of antihypertensive adverse events. However, several noteworthy associations have emerged, such as 1) the role of ACE variants in increasing the risk of multiple adverse events, 2) the bradykinin pathway's involvement in cough induced by ACE inhibitors, and 3) the impact of CYP2D6 variants on metoprolol-induced bradycardia. Nonetheless, challenges persist in identifying biomarkers for adverse events across different antihypertensive classes, sometimes due to the rarity of certain events, such as ACE inhibitors-induced angioedema. We also highlight the main limitations of previous studies that warrant attention, including using a targeted gene approach with a limited number of tested variants, small sample sizes, and design issues such as overlooking doses or the time between starting treatment and the onset of adverse events. Addressing these challenges requires collaborative efforts and the integration of technological advancements, such as next-generation sequencing, which can significantly enhance research outcomes and provide the needed evidence. Furthermore, the potential combination of genomic biomarker identification and machine learning is a promising approach for tailoring antihypertensive therapy to individual patients, thereby mitigating the risk of developing adverse events. In conclusion, a deeper understanding of the mechanisms and the pharmacogenomics of adverse events in antihypertensive therapy will likely pave the way for more personalized treatment strategies to improve patient outcomes.

Risk-conferring HLA variants in an epilepsy cohort: benefits of multifaceted use of whole genome sequencing in clinical practice

BackgroundWhole genome sequencing is increasingly used in healthcare, particularly for diagnostics. However, its clinically multifaceted potential for individually customised diagnostic and therapeutic care remains largely unexploited. We used existing whole...

CVM-1118 (foslinanib), a 2-phenyl-4-quinolone derivative, promotes apoptosis and inhibits vasculogenic mimicry via targeting TRAP1.

CVM-1118 (foslinanib) is a phosphoric ester compound selected from 2-phenyl-4-quinolone derivatives. The NCI 60 cancer panel screening showed CVM-1125, the major active metabolite of CVM-1118, to exhibit growth inhibitory and cytotoxic effects at nanomolar range. CVM-1118 possesses multiple bioactivities, including inducing cellular apoptosis, cell cycle arrest at G2/M, as well as inhibiting vasculogenic mimicry (VM) formation. The TNF receptor associated protein 1 (TRAP1) was identified as the binding target of CVM-1125 using nematic protein organization technique (NPOT) interactome analysis. Further studies demonstrated CVM-1125 reduced the protein level of TRAP1 and impeded its downstream signaling by reduction of cellular succinate levels and destabilization of HIF-1α. The pharmacogenomic biomarkers associated with CVM-1118 were also examined by Whole Genome CRISPR Knock-Out Screening. Two hits (STK11 and NF2) were confirmed with higher sensitivity to the drug in cell knock-down experiments. Biological assays indicate that the mechanism of action of CVM-1118 is via targeting TRAP1 to induce mitochondrial apoptosis, suppress tumor cell growth, and inhibit vasculogenic mimicry formation. Most importantly, the loss-of-function mutations of STK11 and NF2 are potential biomarkers of CVM-1118 which can be applied in the selection of cancer patients for CVM-1118 treatment. CVM-1118 is currently in its Phase 2a clinical development.

The Prevalence and Features of Medications With Actionable Pharmacogenomic Biomarkers Prescribed to Kidney Transplant Recipients

Genetic variants are associated with pharmacokinetic and pharmacodynamic changes, leading to variability in drug effects and safety profiles in the clinical response. The role of genetic variants in kidney transplant recipients (KTRs) has not been extensively studied. Here, we explored the potential of incorporating pharmacogenomic (PGx) gene biomarkers into prescription practices for KTRs. This study analyzed 490 KTRs participating in the Taiwan Precision Medicine Initiative program and used medications with actionable PGx biomarkers. The analysis included prescriptions issued between January 2000 and December 2021 with 206 CPIC-recommended level A or B gene-drug pairs, encompassing 363 single or combination drug products. All KTRs had the potential to receive at least one prescription that could be adjusted based on their genetic profiles after the day of surgery. The top 5 medications prescribed within the first 3 months after transplantation were mycophenolic acid, tacrolimus, pantoprazole, labetalol, and tramadol. These findings highlight the significant potential of PGx-guided prescriptions for KTRs. Additionally, some drug-gene pairs, such as tramadol/CYP2D6, pantoprazole/CYP2C19, and atorvastatin/SLCO1B1, were considered high-quality evidence by the Clinical Pharmacogenetics Implementation Consortium and were included in the Food and Drug Administration's drug labels, indicating that they have the potential for clinical application. Overall, this study demonstrated the potential of incorporating PGx gene biomarkers into prescribing practices for KTRs, which could improve personalized pharmacotherapy for these patients.

CDX-301 prevents radiation-induced dysregulation of miRNA expression and biogenesis

Risks of radiation exposure necessitate the development ofradioprophylactic drugs. We have reported the efficacy of CDX-301, a recombinantly developed human protein form of Fms-related tyrosine kinase 3 ligand (Flt3L), as a radioprophylactic and radiomitigatory agent. Here, we performed global microRNA profiling to further understand the mechanism of action of CDX-301. We find that CDX-301 administration 24h prior to total body irradiation prevents radiation-induced dysregulation of microRNA biogenesis and expression in murine serum and spleen samples in a time- and tissue-dependent manner. Further analysis shows that activation of the HOTAIR regulatory pathway has a prominent function in radiation-induced injury responses, which is inhibited by pre-treatment with CDX-301. Moreover, CDX-301 attenuates radiation-induced dysregulation of several cellular functions such as inflammatory and immune responses. In corroboration, we also find that pre-treatment with CDX-301 restores the expression of bone marrow aplasia markers and inflammatory cytokines and growth factors, as well as the expression of genes associated with MAP kinase and TGF-β pathways that are altered by radiation. Our findings provide new insights into CDX-301-mediated molecular and cellular mechanisms and point to a possible novel radioprotective drug for the prevention of irradiation-induced injury and hematopoietic acute radiation syndrome.

Pharmacogenetic Biomarkers and Personalized Medicine: Upcoming Concept in Pharmacotherapy

Pharmacogenomics is the study of an individual's response to drugs as a result of their genetic makeup. Pharmacogenomics has been merged with pharmacology and genomics to produce safe and effective drugs that are customized to the unique genetic profile of each individual. Drug prescribing focused on pharmacogenomics opens up a modern avenue for developing and prescribing safe and efficient drugs to specific patients. Patients that are prescribed medications that are more appropriate to them based on their physiology and lifestyle characteristics are referred to as obtaining personalized medicine. The medicinal use of molecularly targeted agents, which are commonly used for customized therapies, could aid in disease detection in a small number of patients. To assess the advantage of selected patients with genomic changes to a given treatment, clinical trial research designs for different diagnostics and therapeutics must aim for rate-limiting steps. Precision medicine techniques are used to classify specific patients' genetic flaws in the hopes of identifying new disease-prevention treatments. Precision medicine, on the other hand, is more precise in clinical practice, with an emphasis on identifying new therapeutic targets, recent advances in molecular testing trials, and a variety of advanced approaches are available for collecting biological samples in clinical practice to conduct genomic processing. Pharmacogenomics biomarkers use customized drugs to anticipate the incidence of diseases in the future. Individual precision medicine can overcome the limitations of traditional medicine in terms of disease prevention.

Pharmacogenomic biomarkers as source of evidence of the effectiveness and safety of antidepressant therapy

ObjectiveThe main goal of this work was to identify, describe, characterize, and classify the scientific evidence regarding the use of pharmacogenomic biomarkers in antidepressant treatment.MethodsThe work was developed in two phases: i) a search for pharmacogenomic biomarkers in summaries of antidepressant drugs with marketing authorization in Portugal; and ii) a systematic literature review based on the data obtained in the first phase, with the main objective of finding international literature that could describe and characterize previously reported biomarkers and identify other relevant biomarkers. Finally, the levels of evidence and recommendation grades were classified.ResultsAmong the 26 drugs with marketing authorization in Portugal, only 16 had pharmacogenomic information. The most widely studied pharmacogenomic biomarker was CYP2D6. These results were mostly supported by the systematic literature review, which yielded 103 papers, 63 of which were ultimately included in the review. The systematic literature review also revealed the existence of other relevant biomarkers. Most of the included studies show a good level of evidence, which guarantees reliability and good recommendation grades. For the database (built during phase i), the results were informative but resulted in no specific recommendations.ConclusionsMost pharmacogenomic variants are not studied or acknowledged by genetic tests, and more scientific research is needed to confirm their usefulness. Therefore, only a small number of variants are considered when prescribing antidepressant drugs. In addition, genotyping of patients is not common in clinical practice.

MiRNAs as potential diagnostic biomarkers and pharmacogenomic indicators in psychiatric disorders.

The heterogeneity of psychiatric disorders and the lack of reliable biomarkers for prediction and treatments follow-up pose difficulties towards recognition and understanding of the molecular basis of psychiatric diseases. However, several studies based on NGS approaches have shown that miRNAs could regulate gene expression during onset and disease progression and could serve as potential diagnostic and pharmacogenomics biomarkers during treatment. We provide herein a detailed overview of circulating miRNAs and their expression profiles as biomarkers in schizophrenia, bipolar disorder and major depressive disorder and their role in response to specific treatments. Bioinformatics analysis of miR-34a, miR-106, miR-134 and miR-132, which are common among SZ, BD and MDD patients, showed brain enrichment and involvement in the modulation of critical signaling pathways, which are often deregulated in psychiatric disorders. We propose that specific miRNAs support accurate diagnosis and effective precision treatment of psychiatric disorders.

Toward Individualized Prediction of Response to Methotrexate in Early Rheumatoid Arthritis: A Pharmacogenomics-Driven Machine Learning Approach.

To test the ability of machine learning (ML) approaches with clinical and genomic biomarkers to predict methotrexate treatment response in patients with early rheumatoid arthritis (RA). Demographic, clinical, and genomic data from 643 patients of European ancestry with early RA (mean age 54 years; 70% female) subdivided into a training (n = 336) and validation cohort (n = 307) were used. The genomic data comprised 160 single-nucleotide polymorphisms (SNPs) previously associated with RA or methotrexate metabolism. Response to methotrexate monotherapy was defined as good or moderate by the European Alliance of Associations for Rheumatology (EULAR) response criteria at the 3-month follow-up. Supervised ML methods were trained with 5 repeats and 10-fold cross-validation using the training cohort. Prediction performance was validated in the independent validation cohort. Supervised ML methods combining age, sex, smoking, rheumatoid factor, baseline Disease Activity Score in 28 joints (DAS28) scores and 160 SNPs predicted EULAR response at 3 months with the area under the receiver operating curve of 0.84 (P = 0.05) in the training cohort and achieved a prediction accuracy of 76% (P = 0.05) in the validation cohort (sensitivity 72%, specificity 77%). Intergenic SNPs rs12446816, rs13385025, rs113798271, and ATIC (rs2372536) had variable importance above 60.0 and along with baseline DAS28 scores were among the top predictors of methotrexate response. Pharmacogenomic biomarkers combined with baseline DAS28 scores can be useful in predicting response to methotrexate in patients with early RA. Applying ML to predict treatment response holds promise for guiding effective RA treatment choices, including timely escalation of RA therapies.

Applying Pharmacogenomic Guidelines to Combat Medical Care.

Pharmacogenomics is a pillar of personalized medicine that has the potential to deliver optimized treatment in many medical settings. Military medicine in the deployed setting is unique and therefore warrants separate assessment pertaining to its potential capabilities and impact. Pharmacogenomics for United States Active Duty Service Members medical care in the deployed setting has not, to our knowledge, been previously reviewed. We present potential applications of pharmacogenomics to forward medical care through two comprehensive references for deployed medical care, the Tactical Combat Casualty Care Guidelines (TCCC) and Emergency War Surgery (EWS) fifth edition. All drugs within the deployment manuals, TCCC guidelines and EWS book, were identified and the list was cross-referenced to the Clinical Pharmacogenetics Implementation Consortium guidelines and genes-drugs interactions list as well as the Food and Drug Administration Table of Pharmacogenomics Biomarkers in Drug Labeling. Ten pharmacologic categories were identified, consisting of 15 drugs, along with the classes, aminogylcosides, beta-blockers, and volatile anesthetics. Drugs and pharmacogenomics liabilities were tabulated. Eight specific drugs or classes are expounded upon given the belief of the authors of their potential for impacting future treatment on the battlefield in the setting of prolonged field care. This review outlines several genes with liabilities in the prolonged field care setting and areas that may produce improved care with further study.

Molecular Genetic Techniques in Biomarker Analysis Relevant for Drugs Centrally Approved in Europe.

On the basis of scientific evidence, information on the option, recommendation or requirement to test for pharmacogenetic or pharmacogenomic biomarkers is incorporated in the Summary of Product Characteristics of an increasing number of drugs in Europe. A screening of the Genetic Testing Registry (GTR) showed that a variety of molecular genetic testing methods is currently offered worldwide in testing services with regard to according drugs and biomarkers. Thereby, among the methodology indicated in the screened GTR category ‘Molecular Genetics’, next-generation sequencing is applied for identification of the largest proportion of evaluated biomarkers that are relevant for therapeutic management of centrally approved drugs in Europe. However, sufficient information on regulatory clearances, clinical utility, analytical and clinical validity of applied methods is rarely provided.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40291-021-00567-x.

Tools in Pharmacogenomics Biomarker Identification for Cancer Patients.

The understanding of the biological differences which underlie the inter-individual variability in drug response improved the efficacy of cancer therapy in the era of precision medicine. In fact molecularly targeted drugs and immunotherapy represent a revolution in cancer treatment. The identification of genetic predictive and/or prognostic biomarkers linked to drug pharmacokinetics (PK) and pharmacodynamics (PD) is allowed by the development of high-throughput omics tools for detecting and understanding biological differences among individuals, in order to improve drug efficacy and minimize risk of toxicity. Personalized medicine in cancer treatment reduces costs of the healthcare system. Unfortunately, pharmacogenomics biomarkers discovery is influenced by complexity, need of high-quality evidence, and a validation process for regulatory purposes. This chapter is focused on the critic analysis of presently available pharmacogenomics tools for discovering or testing genetic polymorphic variants in drug metabolizing enzyme to be introduced in clinical practice for the prospective stratification of cancer patients.

Identification and Characterization of Key Differentially Expressed Genes Associated With Metronomic Dosing of Topotecan in Human Prostate Cancer.

Repetitive, low-dose (metronomic; METRO) drug administration of some anticancer agents can overcome drug resistance and increase drug efficacy in many cancers, but the mechanisms are not understood fully. Previously, we showed that METRO dosing of topotecan (TOPO) is more effective than conventional (CONV) dosing in aggressive human prostate cancer (PCa) cell lines and in mouse tumor xenograft models. To gain mechanistic insights into METRO-TOPO activity, in this study we determined the effect of METRO- and CONV-TOPO treatment in a panel of human PCa cell lines representing castration-sensitive/resistant, androgen receptor (+/−), and those of different ethnicity on cell growth and gene expression. Differentially expressed genes (DEGs) were identified for METRO-TOPO therapy and compared to a PCa patient cohort and The Cancer Genome Atlas (TCGA) database. The top five DEGs were SERPINB5, CDKN1A, TNF, FOS, and ANGPT1. Ingenuity Pathway Analysis predicted several upstream regulators and identified top molecular networks associated with METRO dosing, including tumor suppression, anti-proliferation, angiogenesis, invasion, metastasis, and inflammation. Further, the top DEGs were associated with increase survival of PCa patients (TCGA database), as well as ethnic differences in gene expression patterns in patients and cell lines representing African Americans (AA) and European Americans (EA). Thus, we have identified candidate pharmacogenomic biomarkers and novel pathways associated with METRO-TOPO therapy that will serve as a foundation for further investigation and validation of METRO-TOPO as a novel treatment option for prostate cancers.