Pharmacogenomics of breast cancer: highlighting CYP2D6 and tamoxifen

Developing an innovative 3D printing platform for production of personalised medicines in a hospital for the OPERA clinical trial

Breast cancer is the most frequently diagnosed cancer in women worldwide, and non-adherence to adjuvant hormonotherapy can negatively impact cancer recurrence and relapse. Non-adherence is associated with side effects of hormonotherapy. Pharmacological strategies to mitigate the side effects include coadministration of antidepressants, however patients remain non-adherent. The aim of this work was to develop medicines containing both hormonotherapy, tamoxifen (20 mg), along with anti-depressants, either venlafaxine (37.5 or 75 mg) or duloxetine (30 or 60 mg), to assess the acceptability and efficacy of this personalised approach for mitigating tamoxifen side effects in a clinical trial. A major criterion for the developed medicines was the production rate, specified at minimum 200 dosage units per hour to produce more than 40,000 units required for the clinical trial. A novel capsule filling approach enabled by the pharmaceutical 3D printer M3DIMAKER 2 was developed for this purpose. Firstly, semi-solid extrusion 3D printing enabled the filling of tamoxifen pharma-ink prepared according to French compounding regulation, followed by filling of commercial venlafaxine or duloxetine pellets enabled by the development of an innovative pellet dispensing printhead. The medicines were successfully developed and produced in the clinical pharmacy department of the cancer hospital Gustave Roussy, located in Paris, France. The developed medicines satisfied quality and production rate requirements and were stable for storage up to one year to cover the duration of the trial. This work demonstrates the feasibility of developing and producing combined tamoxifen medicines in a hospital setting through a pharmaceutical 3D printer to enable a clinical trial with a high medicines production rate requirement.

Hallmarks of cancer resistance

This review explores the hallmarks of cancer resistance, including drug efflux mediated by ATP-binding cassette (ABC) transporters, metabolic reprogramming characterized by the Warburg effect, and the dynamic interplay between cancer cells and mitochondria. The role of cancer stem cells (CSCs) in treatment resistance and the regulatory influence of non-coding RNAs, such as long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), are studied. The chapter emphasizes future directions, encompassing advancements in immunotherapy, strategies to counter adaptive resistance, integration of artificial intelligence for predictive modeling, and the identification of biomarkers for personalized treatment. The comprehensive exploration of these hallmarks provides a foundation for innovative therapeutic approaches, aiming to navigate the complex landscape of cancer resistance and enhance patient outcomes.

Predictive modeling of adverse drug reactions to tamoxifen therapy for breast cancer on base of pharmacogenomic testing

OBJECTIVES

The present study investigated the analysis of adverse drug reactions (ADRs) to tamoxifen (TAM) in breast cancer patients in relation to the carriage of genetic polymorphisms of genes encoding enzymes of CYP system and transporters of P-glycoprotein (Pg) and predictive models based on it.

METHODS

A total of 120 women with breast cancer taking adjuvant TAM were examined for the gene polymorphisms such as CYP2D6*4, CYP3A5*3, CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*3 and ABCB1 (C3435T). Allelic variants were determined using the real-time polymerase chain reaction method. The research material was double sampling of buccal epithelium. Medical history data and extracts from case histories were used as sources of medical information, on the basis of which questionnaires specially created by us were filled out.

RESULTS

An associative analysis showed association with the development of ADRs to TAM indicating their clinical significance from different genetic polymorphisms of CYP2D6, CYP3A5, CYP2C9 and ABCB1. The complex associative analysis performed using mathematical modeling made it possible to build predictive risk models for the development of ADRs such as hot flashes, dyspepsia, bone pain, and asthenia.

CONCLUSIONS

Models that include both genetic and non-genetic determinants of ADRs of TAM may further improve the prediction of individual response to TAM.

Tamoxifen induces ferroptosis in MCF-7 organoid

BACKGROUND

Breast cancer is the most common female malignant tumor type globally. The occurrence and development of breast cancer involve ferroptosis, which is closely related to its treatment. The development of breast cancer organoids facilitates the analysis of breast cancer molecular background and tumor biological behavior, including clinical pathological characteristics, drug response, or drug resistance relationship, and promotes the advancement of precision treatment for breast cancer. The three-dimensional (3D) cell culture of breast cancer MCF-7 organoid is more similar to the in vivo environment and thus obtains more realistic results than 2D cell culture. Our study examined the new mechanism of tamoxifen in treating breast cancer through breast cancer MCF-7 organoids.

METHODS

We used 3D cells to culture breast cancer MCF-7 organoid, as well as tamoxifen-treated MCF-7 and tamoxifen-resistant MCF-7 (MCF-7 TAMR) cells. We used transcriptome sequencing. We detected GPX4 and SLC7A11 protein levels using Western blotting and the content of ATP, glutathione, and ferrous ions using the Cell Counting Lite 3D Kit. We assessed cell viability using the Cell Counting Kit-8 (CCK-8) assay.

RESULTS

Tamoxifen significantly inhibited the growth of MCF-7 organoids and significantly induced ferroptosis in MCF-7 organoids. The ferroptosis inhibitor reversed the significant tamoxifen-induced MCF-7 organoid inhibition activity. Moreover, the ferroptosis activator enhanced the tamoxifen-induced MCF-7 TAMR cell activity inhibition.

CONCLUSION

Our study revealed that ferroptosis plays an important role in tamoxifen-induced MCF-7 organoid cell death and provides a new research idea for precise treatment of breast cancer through an organoid model.

Hypoxia inducible factor-1α (HIF-1α) in breast cancer: The crosstalk with oncogenic and onco-suppressor factors in regulation of cancer hallmarks

Low oxygen level at tumor microenvironment leads to a condition, known as hypoxia that is implicated in cancer progression. Upon hypoxia, HIF-1α undergoes activation and due to its oncogenic function and interaction with other molecular pathways, promotes tumor progression. The HIF-1α role in regulating breast cancer progression is described, Overall, HIF-1α has upregulation in breast tumor and due to its tumor-promoting function, its upregulation is in favor of breast tumor progression. HIF-1α overexpression prevents apoptosis in breast tumor and it promotes cell cycle progression. Silencing HIF-1α triggers cycle arrest and decreases growth. Migration of breast tumor enhances by HIF-1α signaling and it mainly induces EMT in providing metastasis. HIF-1α upregulation stimulates drug resistance and radio-resistance in breast tumor. Furthermore, HIF-1α signaling induces immune evasion of breast cancer. Berberine and pharmacological intervention suppress HIF-1α signaling in breast tumor and regulation of HIF-1α by non-coding RNAs occurs. Furthermore, HIF-1α is a biomarker in clinic.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Early increase in tamoxifen dose in CYP2D6 poor metaboliser breast cancer patients and survival: A propensity score matching analysis

PURPOSE

Tamoxifen is a drug used for hormone receptor-positive breast cancers, primarily metabolised by the CYP2D6 enzyme into active metabolites such as endoxifen. CYP2D6 displays varying degrees of activity depending on its genotype. This study aims to analyse the effect of an early increase in tamoxifen dose in poor metabolisers (PM) on survival.

METHODS

We enrolled 220 patients diagnosed with breast cancer who were treated with tamoxifen. CYP2D6 polymorphisms were determined, and the phenotype was estimated according to the Clinical Pharmacogenetics Implementation Consortium. Disease-free survival (DFS) and overall survival (OS) were analysed considering the entire patient group, and a subgroup of 110 patients selected by Propensity Score Matching (PSM). All women were treated with 20 mg/day of tamoxifen for 5 years, except PM, who initially received 20 mg/day for 4 months, followed by 40 mg/day for 4 months and 60 mg/day for 4 months before returning to the standard dose of 20 mg/day until completing 5 years of treatment.

RESULTS

The analysis of the influence of CYP2D6 polymorphisms in the complete group and in the PSM subgroup revealed no significant differences for DFS or OS. Furthermore, DFS and OS were analysed in relation to various covariates such as age, histological grade, nodal status, tumour size, HER-2, Ki-67, chemotherapy, and radiotherapy. Only age, histological grade, nodal status, and chemotherapy treatment demonstrated statistical significance.

CONCLUSION

An early increase in tamoxifen dose in PM patients is not associated with survival differences among CYP2D6 phenotypes.

Non-Coding RNAs Modulating Estrogen Signaling and Response to Endocrine Therapy in Breast Cancer

The largest part of human DNA is transcribed into RNA that does not code for proteins. These non-coding RNAs (ncRNAs) are key regulators of protein-coding gene expression and have been shown to play important roles in health, disease and therapy response. Today, endocrine therapy of ERα-positive breast cancer (BC) is a successful treatment approach, but resistance to this therapy is a major clinical problem. Therefore, a deeper understanding of resistance mechanisms is important to overcome this resistance. An increasing amount of evidence demonstrate that ncRNAs affect the response to endocrine therapy. Thus, ncRNAs are considered versatile biomarkers to predict or monitor therapy response. In this review article, we intend to give a summary and update on the effects of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) on estrogen signaling in BC cells, this pathway being the target of endocrine therapy, and their role in therapy resistance. For this purpose, we reviewed articles on these topics listed in the PubMed database. Finally, we provide an assessment regarding the clinical use of these ncRNA types, particularly their circulating forms, as predictive BC biomarkers and their potential role as therapy targets to overcome endocrine resistance.

Breast cancer pharmacogenetics: a systematic review

Breast cancer was declared the most prevalent type of cancer in 2020. Among other factors, treatment response can be affected by genetic polymorphisms - which is the focus of pharmacogenetics - and ethnicity is also a contributing factor in this context. Relevant genes in disease treatment pathways were selected to evaluate treatment response from the pharmacogenetic perspective; polymorphism frequencies and ethnic and continental representation across the available literature were also assessed through a systematic review. The identified associations and gaps have been described in this study with the purpose that, in the future, treatments can be personalized and thus be more effective, safer, and accessible to all.

Comparison of Anticancer Drug Toxicities: Paradigm Shift in Adverse Effect Profile

The inception of cancer treatment with chemotherapeutics began in the 1940s with nitrogen mustards that were initially employed as weapons in World War II. Since then, treatment options for different malignancies have evolved over the period of last seventy years. Until the late 1990s, all the chemotherapeutic agents were small molecule chemicals with a highly nonspecific and severe toxicity spectrum. With the landmark approval of rituximab in 1997, a new horizon has opened up for numerous therapeutic antibodies in solid and hematological cancers. Although this transition to large molecules improved the survival and quality of life of cancer patients, this has also coincided with the change in adverse effect patterns. Typically, the anticancer agents are fraught with multifarious adverse effects that negatively impact different organs of cancer patients, which ultimately aggravate their sufferings. In contrast to the small molecules, anticancer antibodies are more targeted toward cancer signaling pathways and exhibit fewer side effects than traditional small molecule chemotherapy treatments. Nevertheless, the interference with the immune system triggers serious inflammation- and infection-related adverse effects. The differences in drug disposition and interaction with human basal pathways contribute to this paradigm shift in adverse effect profile. It is critical that healthcare team members gain a thorough insight of the adverse effect differences between the agents discovered during the last twenty-five years and before. In this review, we summarized the general mechanisms and adverse effects of small and large molecule anticancer drugs that would further our understanding on the toxicity patterns of chemotherapeutic regimens.

Antiproliferative activity of Tamoxifen, Vitamin D3 and their concomitant treatment

Breast cancer stands out as the most common cancer type among women throughout the world. Especially for the estrogen receptor alpha (ER α +) positive breast cancer cells Tamoxifen has been widely used as an anti-cancer agent. Tamoxifen's mechanism of action is through ER. It binds to the receptor and leads to a conformational change which eventually prevents cancer cells proliferation and survival. In our current study, we aimed to investigate the combination of Tamoxifen with Vitamin D₃ to test whether this combination will enhance the anti-cancer effect of Tamoxifen on breast cancer cells in vitro. Vitamin D₃ has sterol structure and this property enables it to act similar to hormones. Vitamin D Receptor (VDR) has been commonly found in different types of cancer cells including but not limited to breast and prostate cancer cells. Through this receptor Vitamin D₃ acts as an anti-proliferative agent. We examined the proliferation rate, apoptosis and necrosis levels as well as cell cycle progression in MCF-7 breast cancer cell line in the presence of Vitamin D₃ and Tamoxifen to compare the changes with the Tamoxifen treated group. Our results suggest that Tamoxifen was a more potent anti-cancer agent than Vitamin D₃ or its combination with Vitamin D₃ based on cell cycle arrest, apoptosis and cell proliferation levels. This effect in the apoptosis rate and cell cycle stage of the MCF-7 cells were in line with the changes in gene expression profile of P53, BAX and BCL-2. Our results suggest that Tamoxifen by itself is adequate enough and more potent than Vitamin D₃ or its combination with Vitamin D₃ as anti-cancer agent for the breast cancer cells in vitro.

A Systematic Review of Artificial Intelligence Techniques in Cancer Prediction and Diagnosis

Artificial intelligence has aided in the advancement of healthcare research. The availability of open-source healthcare statistics has prompted researchers to create applications that aid cancer detection and prognosis. Deep learning and machine learning models provide a reliable, rapid, and effective solution to deal with such challenging diseases in these circumstances. PRISMA guidelines had been used to select the articles published on the web of science, EBSCO, and EMBASE between 2009 and 2021. In this study, we performed an efficient search and included the research articles that employed AI-based learning approaches for cancer prediction. A total of 185 papers are considered impactful for cancer prediction using conventional machine and deep learning-based classifications. In addition, the survey also deliberated the work done by the different researchers and highlighted the limitations of the existing literature, and performed the comparison using various parameters such as prediction rate, accuracy, sensitivity, specificity, dice score, detection rate, area undercover, precision, recall, and F1-score. Five investigations have been designed, and solutions to those were explored. Although multiple techniques recommended in the literature have achieved great prediction results, still cancer mortality has not been reduced. Thus, more extensive research to deal with the challenges in the area of cancer prediction is required.

Downregulation of RPS14 inhibits the proliferation and metastasis of estrogen receptor-positive breast cancer cells

OBJECTIVE

Ribosomal protein S14 (RPS14) is a component of the 40S ribosomal subunit and is considered to be indispensable for ribosomal biogenesis. Previously, we found that RPS14 was significantly downregulated in estrogen receptor-positive (ER+) breast cancer cells following treatment with 4-hydroxytamoxifen (4-OH-TAM). However, its role in breast cancer remains poorly understood. In the present study, we sought to demonstrate, for the first time, that RPS14 is highly expressed in ER+ breast cancer tissues and its downregulation can significantly inhibit the proliferation, cycle, and metastasis of ER+ breast cancer cells, as well as induce cell apoptosis.

METHODS

Quantitative RT-PCR and western blotting were used to determine the expression of target genes. Herein, lentivirus-mediated small hairpin RNA (shRNA) targeting RPS14 was designed to determine the impact of RPS14 knockdown on ER+ breast cancer cells. Further, bioinformatics analysis was used to reveal the significance of differentially expressed genes in RPS14 knockdown breast cancer cells.

RESULTS

RPS14 was highly expressed in ER+ breast cancer tissues compared to ER- tissues. The downregulation of RPS14 in two ER+ breast cancer cell lines suppressed cell proliferation, cell cycle and metastasis, and induced apoptosis. Based on bioinformatics analysis, the expression level of several significant genes, such as ASNS, Ret, and S100A4, was altered in breast cancer cells after RPS14 downregulation. Furthermore, the BAG2 and interferon signaling pathways were identified to be significantly activated.

CONCLUSIONS

The downregulation of RPS14 in ER+ breast cancer cells can inhibit their proliferation and metastasis.

Parkinson's disease and cancer: a systematic review and meta-analysis of over 17 million participants

OBJECTIVE

To systematically review and qualitatively evaluate epidemiological evidence on associations between Parkinson's disease (PD) and cancer via meta-analysis.

DATA SOURCES

MEDLINE via PubMed, Web of Science and EMBASE, until March 2021.

STUDY SELECTION

Included were publications that (1) were original epidemiological studies on PD and cancer; (2) reported risk estimates; (3) were in English. Exclusion criteria included: (1) review/comments; (2) biological studies; (3) case report/autopsy studies; (4) irrelevant exposure/outcome; (5) treated cases; (6) no measure of risk estimates; (7) no confidence intervals/exact p values and (8) duplicates.

DATA EXTRACTION AND SYNTHESIS

PRISMA and MOOSE guidelines were followed in data extraction. Two-step screening was performed by two authors blinded to each other. A random-effects model was used to calculate pooled relative risk (RR).

MAIN OUTCOMES AND MEASURES

We included publications that assessed the risk of PD in individuals with vs without cancer and the risk of cancer in individuals with vs without PD.

RESULTS

A total of 63 studies and 17 994 584 participants were included. Meta-analysis generated a pooled RR of 0.82 (n=33; 95% CI 0.76 to 0.88; p<0.001) for association between PD and total cancer, 0.76 (n=21; 95% CI 0.67 to 0.85; p<0.001) for PD and smoking-related cancer and 0.92 (n=19; 95% CI 0.84 to 0.99; p=0.03) for non-smoking-related cancer. PD was associated with an increased risk of melanoma (n=29; pooled RR=1.75; 95% CI 1.43 to 2.14; p<0.001) but not for other skin cancers (n=17; pooled RR=0.90; 95% CI 0.60 to 1.34; p=0.60).

CONCLUSIONS

PD and total cancer were inversely associated. This inverse association persisted for both smoking-related and non-smoking-related cancers. PD was positively associated with melanoma. These results provide evidence for further investigations for possible mechanistic associations between PD and cancer.

PROSPERO REGISTRATION NUMBER

CRD42020162103.

Interactions between cardiology and oncology drugs in precision cardio-oncology

Recent advances in treatment have transformed the management of cancer. Despite these advances, cardiovascular disease remains a leading cause of death in cancer survivors. Cardio-oncology has recently evolved as a subspecialty to prevent, diagnose, and manage cardiovascular side effects of antineoplastic therapy. An emphasis on optimal management of comorbidities and close attention to drug interactions are important in cardio-oncologic care. With interdisciplinary collaboration among oncologists, cardiologists, and pharmacists, there is potential to prevent and reduce drug-related toxicities of treatments. The cytochrome P450 (CYP450) family of enzymes and the P-glycoprotein (P-g) transporter play a crucial role in drug metabolism and drug resistance. Here we discuss the role of CYP450 and P-g in drug interactions in the field of cardio-oncology, provide an overview of the cardiotoxicity of a spectrum of cancer agents, highlight the role of precision medicine, and encourage a multidisciplinary treatment approach for patients with cancer.

Association of single nucleotide polymorphisms of cytochrome P450 enzymes with experience of vasomotor, vaginal and musculoskeletal symptoms among breast cancer patients: a systematic review

Background

Adjuvant endocrine therapies are known to induce undesirable adverse effects such as vasomotor, vaginal and musculoskeletal symptoms among breast cancer patients. Drugs used in these therapies are often metabolised by cytochrome P450 (CYP) enzymes, in which their metabolising activities can be modified by single nucleotide polymorphisms (SNP) in CYP genes and CYP genotypes. This review aims to explore whether SNPs or genotypes of CYP are associated with the occurrence, frequency and severity of vasomotor, vaginal and musculoskeletal symptoms in breast cancer patients on adjuvant endocrine therapies.

Methods

A literature review was conducted using five electronic databases, resulting in the inclusion of 14 eligible studies, and their findings were presented narratively. Selected items from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist were used for critical appraisal of the reporting quality of the included studies.

Results

Most of the included studies showed that SNPs or genotypes of CYP that modify its metabolising activity have no effect on the occurrence, frequency or severity of vasomotor symptoms, including hot flashes. One study showed no correlation of these genetic variations in CYP with musculoskeletal symptoms, and no data were available on the association between such genetic variations and vaginal symptoms.

Conclusions

Overall, genetic variations in CYP have no effect on the experience of hot flashes among breast cancer patients. We recommend exploration of the link between the active metabolites of chemotherapeutic drugs and the molecules shown to affect the occurrence or severity of hot flashes, and the establishment of the relationship between such genetic variations and patients’ experience of musculoskeletal and vaginal symptoms. Subgroup analyses based on patients’ duration of adjuvant endocrine therapies in such studies are recommended.

Intratumoural Cytochrome P450 Expression in Breast Cancer: Impact on Standard of Care Treatment and New Efforts to Develop Tumour-Selective Therapies

Despite significant advances in treatment strategies over the past decade, selective treatment of breast cancer with limited side-effects still remains a great challenge. The cytochrome P450 (CYP) family of enzymes contribute to cancer cell proliferation, cell signaling and drug metabolism with implications for treatment outcomes. A clearer understanding of CYP expression is important in the pathogenesis of breast cancer as several isoforms play critical roles in metabolising steroid hormones and xenobiotics that contribute to the genesis of breast cancer. The purpose of this review is to provide an update on how the presence of CYPs impacts on standard of care (SoC) drugs used to treat breast cancer as well as discuss opportunities to exploit CYP expression for therapeutic intervention. Finally, we provide our thoughts on future work in CYP research with the aim of supporting ongoing efforts to develop drugs with improved therapeutic index for patient benefit.

Recent advances in the personalized treatment of estrogen receptor-positive breast cancer with tamoxifen: a focus on pharmacogenomics

Introduction: Tamoxifen is still an important drug in hormone-dependent breast cancer therapy. Personalization of its clinical use beyond hormone receptor positivity could improve the substantial variability of the treatment response.Areas covered: The overview of the current evidence for the treatment personalization using therapeutic drug monitoring, or using genetic biomarkers including CYP2D6 is provided. Although many studies focused on the PK aspects or the impact of CYP2D6 variability the translation into clinical routine is not clearly defined due to the inconsistent clinical outcome data.Expert opinion: We believe that at least the main candidate factors, i.e. CYP2D6 polymorphism, CYP2D6 inhibition, endoxifen serum levels may become important predictors of clinical relevance for tamoxifen treatment personalization in the future. To achieve this aim, however, further research should take into consideration more precise characterization of the disease, epigenetic factors and also utilize an appropriately powered multifactorial approach instead of a single gene evaluating studies.

Increasing engagement in pharmacology and pharmacogenetics education using games and online resources: The PharmacoloGenius mobile app

Mobile applications represent useful instruments to convey information and engage the users even during traveling, thanks to the wide diffusion of smartphones, tablets, smartwatches, and similar devices. As such, they have high potential as learning tools that can act complementary to traditional teaching approaches. In the field of pharmacology, mobile applications are increasingly being used to improve adherence of patients or to help them report suspect adverse drug reactions. However, they have been scarcely applied to pharmacology education. In this article, we present PharmacoloGenius, a free Android mobile application integrating resources useful for students as well as healthcare professionals or researchers to expand knowledge on pharmacological topics. We gave particular emphasis to pharmacogenetics, as it is a fundamental tool to achieve personalized treatment. The application offers original games such as pharmacological trivia based on textbooks or special "journal club" trivia based on research articles conveying the state of the art on specific topics. Additionally, the app offers a curated list of online resources to study pharmacology and pharmacogenetics (e.g., free online courses, videos, and databases) as well as updated news on conferences, grants, and opportunities for pharmacologists. In conclusion, PharmacoloGenius aims to be a useful instrument for people interested in expanding their knowledge on pharmacology in an engaging way.

A Review of the Important Role of CYP2D6 in Pharmacogenomics

Cytochrome P450 2D6 (CYP2D6) is a critical pharmacogene involved in the metabolism of ~20% of commonly used drugs across a broad spectrum of medical disciplines including psychiatry, pain management, oncology and cardiology. Nevertheless, CYP2D6 is highly polymorphic with single-nucleotide polymorphisms, small insertions/deletions and larger structural variants including multiplications, deletions, tandem arrangements, and hybridisations with non-functional CYP2D7 pseudogenes. The frequency of these variants differs across populations, and they significantly influence the drug-metabolising enzymatic function of CYP2D6. Importantly, altered CYP2D6 function has been associated with both adverse drug reactions and reduced drug efficacy, and there is growing recognition of the clinical and economic burdens associated with suboptimal drug utilisation. To date, pharmacogenomic clinical guidelines for at least 48 CYP2D6-substrate drugs have been developed by prominent pharmacogenomics societies, which contain therapeutic recommendations based on CYP2D6-predicted categories of metaboliser phenotype. Novel algorithms to interpret CYP2D6 function from sequencing data that consider structural variants, and machine learning approaches to characterise the functional impact of novel variants, are being developed. However, CYP2D6 genotyping is yet to be implemented broadly into clinical practice, and so further effort and initiatives are required to overcome the implementation challenges and deliver the potential benefits to the bedside.

Involvement of cytochrome P450 enzymes in inflammation and cancer: a review

Cytochrome P450 (CYP) enzymes are responsible for the biotransformation of drugs, xenobiotics, and endogenous substances. This enzymatic activity can be modulated by intrinsic and extrinsic factors, modifying the organism's response to medications. Among the factors that are responsible for enzyme inhibition or induction is the release of proinflammatory cytokines, such as interleukin-1 (IL-1), IL-6, tumor necrosis factor α (TNF-α), and interferon-γ (IFN-γ), from macrophages, lymphocytes, and neutrophils. These cells are also present in the tumor microenvironment, participating in the development of cancer, a disease that is characterized by cellular mutations that favor cell survival and proliferation. Mutations also occur in CYP enzymes, resulting in enzymatic polymorphisms and modulation of their activity. Therefore, the inhibition or induction of CYP enzymes by proinflammatory cytokines in the tumor microenvironment can promote carcinogenesis and affect chemotherapy, resulting in adverse effects, toxicity, or therapeutic failure. This review discusses the relevance of CYPs in hepatocarcinoma, breast cancer, lung cancer, and chemotherapy by reviewing in vitro, in vivo, and clinical studies. We also discuss the importance of elucidating the relationships between inflammation, CYPs, and cancer to predict drug interactions and therapeutic efficacy.