Epigenetics in Drug Response

Lenvatinib in hepatocellular carcinoma: Resistance mechanisms and strategies for improved efficacy

Hepatocellular carcinoma (HCC), one of the most prevalent and destructive causes of cancer-related deaths worldwide, approximately 70% of patients with HCC exhibit advanced disease at diagnosis, limiting the potential for radical treatment. For such patients, lenvatinib, a long-awaited alternative to sorafenib for first-line targeted therapy, has become a key treatment. Unfortunately, despite some progress, the prognosis for advanced HCC remains poor because of drug resistance development. However, the molecular mechanisms underlying lenvatinib resistance and ways to relief drug resistance in HCC are largely unknown and lack of systematic summary; thus, this review not only aims to explore factors contributing to lenvatinib resistance in HCC, but more importantly, summary potential methods to conquer or mitigate the resistance. The results suggest that abnormal activation of pathways, drug transport, epigenetics, tumour microenvironment, cancer stem cells, regulated cell death, epithelial-mesenchymal transition, and other mechanisms are involved in the development of lenvatinib resistance in HCC and subsequent HCC progression. To improve the therapeutic outcomes of lenvatinib, inhibiting acquired resistance, combined therapies, and nano-delivery carriers may be possible approaches.

The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy

Pharmacotherapy for neuropsychiatric disorders, such as anxiety and depression, has been characterized by significant inter-individual variability in drug response and the development of side effects. Pharmacogenetics, as a key part of personalized medicine, aims to optimize therapy according to a patient's individual genetic signature by targeting genetic variations involved in pharmacokinetic or pharmacodynamic processes. Pharmacokinetic variability refers to variations in a drug's absorption, distribution, metabolism, and elimination, whereas pharmacodynamic variability results from variable interactions of an active drug with its target molecules. Pharmacogenetic research on depression and anxiety has focused on genetic polymorphisms affecting metabolizing cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes, P-glycoprotein ATP-binding cassette (ABC) transporters, and monoamine and γ-aminobutyric acid (GABA) metabolic enzymes, transporters, and receptors. Recent pharmacogenetic studies have revealed that more efficient and safer treatments with antidepressants and anxiolytics could be achieved through genotype-guided decisions. However, because pharmacogenetics cannot explain all observed heritable variations in drug response, an emerging field of pharmacoepigenetics investigates how epigenetic mechanisms, which modify gene expression without altering the genetic code, might influence individual responses to drugs. By understanding the epi(genetic) variability of a patient's response to pharmacotherapy, clinicians could select more effective drugs while minimizing the likelihood of adverse reactions and therefore improve the quality of treatment.

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Machine Learning and Pharmacogenomics at the Time of Precision Psychiatry

Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML) techniques and related algorithms play a central role as diagnostic, prognostic, and decision-making tools in this field. Another promising area becoming part of everyday clinical practice is personalized therapy and pharmacogenomics. Applying ML to pharmacogenomics opens new frontiers to tailored therapeutical strategies to help clinicians choose drugs with the best response and fewer side effects, operating with genetic information and combining it with the clinical profile. This systematic review aims to draw up the state-of-the-art ML applied to pharmacogenomics in psychiatry. Our research yielded fourteen papers; most were published in the last three years. The sample comprises 9,180 patients diagnosed with mood disorders, psychoses, or autism spectrum disorders. Prediction of drug response and prediction of side effects are the most frequently considered domains with the supervised ML technique, which first requires training and then testing. The random forest is the most used algorithm; it comprises several decision trees, reduces the training set's overfitting, and makes precise predictions. ML proved effective and reliable, especially when genetic and biodemographic information were integrated into the algorithm. Even though ML and pharmacogenomics are not part of everyday clinical practice yet, they will gain a unique role in the next future in improving personalized treatments in psychiatry.

Epigenetics in drug disposition & drug therapy: symposium report of the 24th North American meeting of the International Society for the Study of Xenobiotics (ISSX)

The 24th North American International Society for the Study of Xenobiotics (ISSX) meeting, held virtually from September 13 to 17, 2021, embraced the theme of "Broadening Our Horizons." This reinforces a key mission of ISSX: striving to share innovative science related to drug discovery and development. Session speakers and the ISSX New Investigators Group, which supports the scientific and professional development of student and early career ISSX members, elected to highlight the scientific content presented during the captivating session titled, "Epigenetics in Drug Disposition & Drug Therapy." The impact genetic variation has on drug response is well established; however, this session underscored the importance of investigating the role of epigenetics in drug disposition and drug discovery. Session speakers, Drs. Ning, McClay, and Lazarus, detailed mechanisms by which epigenetic players including long non-coding RNA (lncRNAs), microRNA (miRNAs), DNA methylation, and histone acetylation can alter the expression of genes involved in pharmacokinetics, pharmacodynamics, and toxicity. Dr. Ning detailed current knowledge about miRNAs and lncRNAs and the mechanisms by which they can affect the expression of drug metabolizing enzymes (DMEs) and nuclear receptors. Dr. Lazarus discussed the potential role of miRNAs on UDP-glucuronosyltransferase (UGT) expression and activity. Dr. McClay provided evidence that aging alters methylation and acetylation of DMEs in the liver, affecting gene expression and activity. These topics, compiled by the symposium organizers, presenters, and the ISSX New Investigators Group, are herein discussed, along with exciting future perspectives for epigenetics in drug disposition and drug discovery research.

Pharmacogenetics of Bronchodilator Response: Future Directions

PURPOSE OF REVIEW

Several genome-wide association studies (GWASs) of bronchodilator response (BDR) to albuterol have been published over the past decade. This review describes current knowledge gaps, including pharmacogenetic studies of albuterol response in minority populations, effect modification of pharmacogenetic associations by age, and relevance of BDR phenotype characterization to pharmacogenetic findings. New approaches, such as leveraging additional "omics" data to focus pharmacogenetic interrogation, as well as developing polygenic risk scores in asthma treatment responses, are also discussed.

RECENT FINDINGS

Recent pharmacogenetic studies of albuterol response in minority populations have identified genetic polymorphisms in loci (DNAH5, NFKB1, PLCB1, ADAMTS3, COX18, and PRKG1), that are associated with BDR. Additional studies are needed to replicate these findings. Modification of the pharmacogenetic associations for SPATS2L and ASB3 polymorphisms by age has also been published. Evidence from metabolomic and epigenomic studies of BDR may point to new pharmacogenetic targets. Lastly, a polygenic risk score for response to albuterol has been developed but requires validation in additional cohorts. In order to expand our knowledge of pharmacogenetics of BDR, additional studies in minority populations are needed. Consideration of effect modification by age and leverage of other "omics" data beyond genomics may also help uncover novel pharmacogenetic loci for use in precision medicine for asthma treatment.

Shifting Gears in Precision Oncology-Challenges and Opportunities of Integrative Data Analysis

For decades, research relating to modification of host immunity towards antitumor response activation has been ongoing, with the breakthrough discovery of immune-checkpoint blockers. Several biomarkers with potential predictive value have been reported in recent studies for these novel therapies. However, with the plethora of therapeutic options existing for a given cancer entity, modern oncology is now being confronted with multifactorial interpretation to devise “the best therapy” for the individual patient. Into the bargain come the multiverse guidelines for established and emerging diagnostic biomarkers, as well as the complex interplay between cancer cells and tumor microenvironment, provoking immense challenges in the therapy decision-making process. Through this review, we present various molecular diagnostic modalities and techniques, such as genomics, immunohistochemistry and quantitative image analysis, which have the potential of becoming powerful tools in the development of an optimal treatment regime when analogized with patient characteristics. We will summarize the underlying complexities of these methods and shed light upon the necessary considerations and requirements for data integration. It is our hope to provide compelling evidence to emphasize on the need for inclusion of integrative data analysis in modern cancer therapy, and thereupon paving a path towards precision medicine and better patient outcomes.

Coding SNPs in hsa-miR-1343-3p and hsa-miR-6783-3p target sites of CYP2C19 modulates clopidogrel response in individuals with cardiovascular diseases

AIMS

To investigate the impact of microRNA target SNPs (mirSNPs) and their interaction with miRNAs on important drug-metabolizing enzymes, transporters and target genes for prediction of clopidogrel drug response in cardiovascular disease individuals.

MAIN METHODS

A prospective cross-sectional study was conducted on 292 individuals undergoing clopidogrel drug therapy. All the enrolled participants were administered 300 mg loading dose followed by 75 mg dose of maintenance therapy. Platelet aggregations were measured before administration of the loading dose and 2 h post fifth day dose of clopidogrel maintenance therapy. Clopidogrel carboxylic acid metabolite from plasma and urine were analyzed post maintenance therapy using the RP-HPLC method. Genotyping of mirSNP's shortlisted through in silico analysis was performed by tetra ARMS PCR and validated by Sanger DNA sequencing. The levels of selected miRNAs were estimated by the TaqMan-PCR assay. Functional validation of mirSNPs was performed in HepG2 cells after transfecting with the selected gene and miRNA mimics. Protein expressions were analyzed by western blot.

KEY FINDINGS

23% of enrolled individuals showed resistance to clopidogrel therapy. Out of 13 mirSNP's analyzed, CYP2C19 rs4244285 was associated with clopidogrel drug resistance and clopidogrel carboxylic acid metabolite in urine and plasma. hsa-miR-1343-3p and hsa-miR-6783-3p levels were significantly high in individuals with CYP2C19 rs4244285 mutant genotype and these miRNAs down-regulated the protein expression of CYP2C19.

SIGNIFICANCE

We demonstrated the role of coding mirSNP (rs4244285) in the regulation of the CYP2C19 gene through miRNAs and its implications to clopidogrel drug response prediction in the Indian population.

Clinical and genetic predictors of diabetes drug's response

Diabetes is a major health problem worldwide. Glycemic control is the main goal in the management of type 2 diabetes. While many anti-diabetic drugs and guidelines are available, almost half of diabetic patients do not reach their treatment goal and develop complications. The glucose-lowering response to anti-diabetic drug differs significantly between individuals. Relatively little is known about the factors that might underlie this response. The identification of predictors of response to anti-diabetic drugs is essential for treatment personalization. Unfortunately, the evidence on predictors of drugs response in type 2 diabetes is scarce. Only a few trials were designed for specific groups of patients (e.g. patients with renal impairment or older patients), while subgroup analyses of larger trials are frequently unreported. Physicians need help in picking the drug which provides the maximal benefit, with minimal side effects, in the right dose, for a specific patient, using an omics-based approach besides the phenotypic characteristics.

Multicentric Case-Control Study on Azathioprine Dose and Pharmacokinetics in Early-onset Pediatric Inflammatory Bowel Disease

BACKGROUND

Early-onset inflammatory bowel disease (IBD) is generally aggressive, with a high probability of complications and need of surgery. Despite the introduction of highly effective biological drugs, treatment with azathioprine continues to be important even for early-onset IBD; however, in these patients azathioprine response seems to be reduced. This study evaluated azathioprine doses, metabolite concentrations, and their associations with patients' age in children with IBD treated at 6 tertiary pediatric referral centers.

METHODS

Azathioprine doses, metabolites, and clinical effects were assessed after at least 3 months of therapy in 17 early-onset (age < 6 yr, cases) and 51 nonearly-onset (aged > 12 and <18 yrs, controls) patients with IBD. Azathioprine dose was titrated on therapeutic efficacy (response and adverse effects). Azathioprine metabolites and thiopurine methyltransferase activity were determined by high-performance liquid chromatography with ultra violet-vis detection (HPLC-UV) methods.

RESULTS

Frequency of patients in remission was similar among early-onset and control groups, respectively (82% and 84%, P value = 0.72). Early-onset patients required higher doses of azathioprine (median 2.7 versus 2.0 mg·kg·d, P value = 1.1 × 10). Different doses resulted in comparable azathioprine active thioguanine nucleotide metabolite concentrations (median 263 versus 366 pmol/8 × 10 erythrocytes, P value = 0.41) and methylmercaptopurine nucleotide concentrations (median 1455 versus 1532 pmol/8 × 10 erythrocytes, P value = 0.60). Lower ratios between thioguanine nucleotide metabolites and azathioprine doses were found in early-onset patients (median 98 versus 184 pmol/8 × 10 erythrocytes·mg·kg·d, P value = 0.017). Interestingly, early-onset patients presented also higher thiopurine methyltransferase activity (median 476 versus 350 nmol methylmercaptopurine/mg hemoglobin/h, P-value = 0.046).

CONCLUSIONS

This study demonstrated that patients with early-onset IBD present increased inactivating azathioprine metabolism, likely because of elevated activity of the enzyme thiopurine methyltransferase.

Clinical Pharmacology & Therapeutics: Past, Present, and Future

Clinical Pharmacology & Therapeutics (CPT), the definitive and timely source for advances in human therapeutics, transcends the drug discovery, development, regulation, and utilization continuum to catalyze, evolve, and disseminate discipline-transformative knowledge. Prioritized themes and multidisciplinary content drive the science and practice of clinical pharmacology, offering a trusted point of reference. An authoritative herald across global communities, CPT is a timeless information vehicle at the vanguard of discovery, translation, and application ushering therapeutic innovation into modern healthcare.

Impact of Membrane Drug Transporters on Resistance to Small-Molecule Tyrosine Kinase Inhibitors

Small-molecule inhibitors of tyrosine kinases (TKIs) are the mainstay of treatment for many malignancies and represent novel treatment options for other diseases such as idiopathic pulmonary fibrosis. Twenty-five TKIs are currently FDA-approved and >130 are being evaluated in clinical trials. Increasing evidence suggests that drug exposure of TKIs may significantly contribute to drug resistance, independently from somatic variation of TKI target genes. Membrane transport proteins may limit the amount of TKI reaching the target cells. This review highlights current knowledge on the basic and clinical pharmacology of membrane transporters involved in TKI disposition and their contribution to drug efficacy and adverse drug effects. In addition to non-genetic and epigenetic factors, genetic variants, particularly rare ones, in transporter genes are promising novel factors to explain interindividual variability in the response to TKI therapy.