Front Oncol. 2021 Jul 1;11:694526. doi: 10.3389/fonc.2021.694526. eCollection 2021.

ABSTRACT

Amino acid (AA) metabolism plays an important role in many cellular processes including energy production, immune function, and purine and pyrimidine synthesis. Cancer cells therefore require increased AA uptake and undergo metabolic reprogramming to satisfy the energy demand associated with their rapid proliferation. Like many other cancers, myeloid leukemias are vulnerable to specific therapeutic strategies targeting metabolic dependencies. Herein, our review provides a comprehensive overview and TCGA data analysis of biosynthetic enzymes required for non-essential AA synthesis and their dysregulation in myeloid leukemias. Furthermore, we discuss the role of the general control nonderepressible 2 (GCN2) and-mammalian target of rapamycin (mTOR) pathways of AA sensing on metabolic vulnerability and drug resistance.

PMID:34277440 | PMC:PMC8281237 | DOI:10.3389/fonc.2021.694526

Therap Adv Gastroenterol. 2021 Jul 3;14:17562848211024464. doi: 10.1177/17562848211024464. eCollection 2021.

ABSTRACT

BACKGROUND: 5-fluorouracil (5-FU) and mitomycin-C (MMC) with radiotherapy (RT) remain an established treatment for patients with anal cancer (AC). Genetic mutations in two major metabolizing enzymes for 5-FU; dihydropyrimidine dehydrogenase (DPYD and thymidylate synthetase (TYMS), have been associated with clinical response and toxicity. However, their place in the treatment of AC remains undetermined.

METHODS: We retrospectively reviewed 21 patients with AC, including T2-4, N0-1, M0 or T1-4, N2-3, and M0 treated between 2012 and 2018. All patients were treated with 5-FU 1,000 mg/m2/day via continuous intravenous (IV) infusion 1-4 and 29-32, MMC 10 mg/m2 IV bolus days 1 and 29 plus RT. Patients who developed ⩾3 grade toxicities were tested for the DPYD and TYMS genes. Treatment was either modified with reduced doses or changed to MMC 10 mg/m2 day 1 and 29 with cisplatin 25 mg/m2/week plus RT. Toxicities and responses were collected.

RESULTS: Six out of 21 patients who developed ⩾3 grade toxicities including pancytopenia, neutropenia, thrombocytopenia, mucositis, nausea, rash, and nephritis were found to have genetic mutations: TYMS 2RG/3RC (n = 2), 3RG/3RC (n = 1), 2R/2R (n = 2), TYMS 3'UTR del/Ins (n = 2), and DPYD c.2864A > T heterozygous (n = 1). Two patients received 5-FU at a 50% reduced dose on days 29-32; one patient refused to receive 5-FU (continued with MMC and RT); one patient received only radiation therapy due to persistent pancytopenia despite the use of growth factors; two patients received an alternative regimen consisting of MMC 10 mg/m2 on day 29 with cisplatin (CDDP) 25 mg/m2/week plus RT; and two patients received cisplatin/MMC with RT from the beginning as they were prospectively detected to have TYMS abnormalities prior to dosing the chemotherapy. These patients tolerated treatment very well with only grade 2 toxicities. All the patients (4/4) on cisplatin/MMC achieved clinical complete response (cCR), while four patients (4/15) on 5-FU/MMC reached cCR at the first assessment. Radiological response showed complete response at the end of 24 weeks assessment.

CONCLUSIONS: Molecular testing for DPYD and TYMS genes can allow us to identify patients who are most likely to respond or face severe toxicity to 5-FU in a potentially curable cancer. Combining radiation with CDDP with MMC in patients with AC is feasible. A prospective study based on pharmacogenetic testing comparing MMC/cisplatin with MMC/5-FU is indicated in patients with AC.

PMID:34276810 | PMC:PMC8255561 | DOI:10.1177/17562848211024464

Front Pharmacol. 2021 Jul 1;12:700454. doi: 10.3389/fphar.2021.700454. eCollection 2021.

ABSTRACT

Sentrin specific-protease 1 (SENP1) is a protein involved in deSUMOylation that is almost overexpressed in cancer. SENP1 has a determinative role in the activation of transcription programs in the innate immune responses and the development B of and C lymphocytes. We found, SENP1 possibly plays a critical role in immune infiltration and acts as an expression marker in PAAD, ESCA, and THYM. CD4+ T cells, CD8+ T cells, and macrophages were more key-related immune cells, indicating that SENP1 might be introduced as a potential target for cancer immunotherapy. We further showed that dysregulation of SENP1 is powerfully associated with decreased patient survival and clinical stage. Total SENP1 protein also increases in cancer. SENP1 is also controlled by transcription factors (TFs) CREB1, KDM5A, REST, and YY1 that regulates apoptosis, cell cycle, cell proliferation, invasion, tumorigenesis, and metastasis. These TFs were in a positive correlation with SENP1. MiR-138-5p, miR-129-1-3p, and miR-129-2-3p also inhibit tumorigenesis through targeting of SENP1. The SENP1 expression level positively correlated with the expression levels of UBN1, SP3, SAP130, NUP98, NUP153 in 32 tumor types. SENP1 and correlated and binding genes: SAP130, NUP98, and NUP153 activated cell cycle. Consistent with this finding, drug analysis was indicated SENP1 is sensitive to cell cycle, apoptosis, and RTK signaling regulators. In the end, SENP1 and its expression-correlated and functional binding genes were enriched in cell cycle, apoptosis, cellular response to DNA damage stimulus. We found that the cell cycle is the main way for tumorigenesis by SENP1. SENP1 attenuates the effect of inhibitory drugs on the cell cycle. We also introduced effective FDA-Approved drugs that can inhibit SENP1. Therefore in the treatments in which these drugs are used, SENP1 inhibition is a suitable approach. This study supplies a wide analysis of the SENP1 across The Cancer Genome Atlas (CGA) cancer types. These results suggest the potential roles of SENP1 as a biomarker for cancer. Since these drugs and the drugs that cause to resistance are applied to cancer treatment, then these two class drugs can use to inhibition of SENP1.

PMID:34276383 | PMC:PMC8280523 | DOI:10.3389/fphar.2021.700454

Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2021 Jun 28;46(6):620-627. doi: 10.11817/j.issn.1672-7347.2021.200561.

ABSTRACT

Drug resistance is the main obstacle in the treatment of many cancers. It is of great clinical significance to study the mechanism of drug resistance and find new targets. Multi-omics mainly includes genomics, epigenomics, transcriptomics, proteomics, metabolomics, and radiomics. In recent years, the research of tumor resistance has made rapid development, which has significantly accelerated the discovery of new targets.

PMID:34275931 | DOI:10.11817/j.issn.1672-7347.2021.200561

J Pharm Biomed Anal. 2021 Jul 13;204:114263. doi: 10.1016/j.jpba.2021.114263. Online ahead of print.

ABSTRACT

A sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay was developed and validated for the quantification of (S)-metoprolol (MET) and its main metabolite, (S)-α-hydroxymetoprolol (OH-MET). Human plasma samples (50 μL) were spiked with both analytes and their deuterated internal standards (IS) (S)-MET-d7 and α-OH-MET-d5. Phospholipid removal microelution-solid phase extraction (PRM-SPE) was performed using a 4-step protocol with Oasis PRiME MCX μElution 96-well cartridges. The eluates were reconstituted in 100 μL of acetonitrile with 50 μg/mL (S)-α-methylbenzyl isocyanate (MBIC) for chiral derivatization. After 60 min at room temperature, the reaction was quenched using 100 μL of water 2 % formic acid. Chromatographic separation of the derivatized analytes was performed on a Kinetex phenyl-hexyl core-shell stationary phase with an elution gradient. Mobile phases were composed of a mixture of water and methanol, with ammonium formate and formic acid as buffers. Total runtime was 15 min. Analyte detection was performed by an AB/SCIEX 4000 QTRAP mass spectrometer with multiple reaction monitoring. Chromatograms showed MBIC successfully reacted with racemic MET, α-OH-MET, and their respective IS. Detection by positive electrospray ionization did not reveal derivatized by-products. Quantification ranges were validated for (S)-MET and (S)-α-OH-MET between 0.5-500 and 1.25-500 ng/mL, respectively, with correlation coefficients (r2) >0.9906. The PRM-SPE assay showed low matrix effects (86.9-104.0 %) and reproducible recoveries (69.4-78.7 %) at low, medium, and high quality control (QC) levels. Precision and accuracy were all comprised between 85-115 % for all three QCs, and between 80-120 % for the lower limit of quantification, for intra- and inter-day values (n = 6, 3 consecutive days). Non-derivatized analytes were stable at room temperature, after 3 freeze-thaw cycles, and stored for 30 days at -80 °C (n = 4). Reinjection reproducibility of a previously validated batch was achieved after 8 days under auto-sampler conditions, indicating the stability of (S)-MET and (S)-α-OH-MET derivatives. Its clinical use was established in a cohort of 50 patients and could be used to further investigate the clinical impact of (S)-MET concentrations.

PMID:34274593 | DOI:10.1016/j.jpba.2021.114263

Toxicology. 2021 Jul 14:152858. doi: 10.1016/j.tox.2021.152858. Online ahead of print.

ABSTRACT

The incidence and mortality of cancer are rapidly growing all over the word. Nowadays, antineoplastic antimetabolites still play a key role in the chemotherapy of cancer. However, the interindividual variations in the efficacy and toxicity of antineoplastic antimetabolites are nonnegligible challenges to their clinical applications. Although many studies have focused on genetic variation, the reasons for these interindividual variations have still not been fully understood. Gut microbiota is reported to be associated with the efficacy and toxicity of antineoplastic antimetabolites. In this review, we summarize the interaction of antineoplastic antimetabolites on gut microbiota and the influences of shifted gut microbiota profiles on the efficacy and toxicity of antineoplastic antimetabolites. The factors affecting the efficacy and toxicity of antineoplastic antimetabolites via gut microbiota are also discussed. In addition, we present our viewpoints that regulating the gut microbiota may increase the efficacy and decrease the toxicity of antineoplastic antimetabolites. This will help us better understand the new mechanism via gut microbiota and promote individualized use of antineoplastic antimetabolites.

PMID:34273448 | DOI:10.1016/j.tox.2021.152858

Methods Mol Biol. 2021;2342:481-550. doi: 10.1007/978-1-0716-1554-6_17.

ABSTRACT

The efficacy, safety, and tolerability of drugs are dependent on numerous factors that influence their disposition. A dose that is efficacious and safe for one individual may result in sub-therapeutic or toxic blood concentrations in others. A significant source of this variability in drug response is drug metabolism, where differences in presystemic and systemic biotransformation efficiency result in variable degrees of systemic exposure (e.g., AUC, Cmax, and/or Cmin) following administration of a fixed dose.Interindividual differences in drug biotransformation have been studied extensively. It is recognized that both intrinsic factors (e.g., genetics, age, sex, and disease states) and extrinsic factors (e.g., diet , chemical exposures from the environment, and the microbiome) play a significant role. For drug-metabolizing enzymes, genetic variation can result in the complete absence or enhanced expression of a functional enzyme. In addition, upregulation and downregulation of gene expression, in response to an altered cellular environment, can achieve the same range of metabolic function (phenotype), but often in a less predictable and time-dependent manner. Understanding the mechanistic basis for variability in drug disposition and response is essential if we are to move beyond the era of empirical, trial-and-error dose selection and into an age of personalized medicine that will improve outcomes in maintaining health and treating disease.

PMID:34272705 | DOI:10.1007/978-1-0716-1554-6_17

Methods Mol Biol. 2021;2342:443-479. doi: 10.1007/978-1-0716-1554-6_16.

ABSTRACT

There are many factors which are known to cause variability in human in vitro enzyme kinetic data. Factors such as the source of enzyme and how it was prepared, the genetics and background of the donor, how the in vitro studies are designed, and how the data are analyzed contribute to variability in the resulting kinetic parameters. It is important to consider not only the factors which cause variability within an experiment, such as selection of a probe substrate, but also those that cause variability when comparing kinetic data across studies and laboratories. For example, the artificial nature of the microsomal lipid membrane and microenvironment in some recombinantly expressed enzymes, relative to those found in native tissue microsomes, has been shown to influence enzyme activity and thus can be a source of variability when comparing across the two different systems. All of these factors, and several others, are discussed in detail in the chapter below. In addition, approaches which can be used to visualize the uncertainty arising from the use of enzyme kinetic data within the context of predicting human pharmacokinetics are discussed.

PMID:34272704 | DOI:10.1007/978-1-0716-1554-6_16

Int Immunopharmacol. 2021 Jul 13;99:107964. doi: 10.1016/j.intimp.2021.107964. Online ahead of print.

ABSTRACT

OBJECTIVE: The pro-inflammatory cytokine IL-32 has high susceptibility to develop cancer. But no previous meta-analysis was done to provide firm evidence. This systematic review and meta-analysis was designed to evaluate the association of IL-32 gene polymorphisms (rs28372698 and rs12934561) with cancer.

METHOD: Eligible studies were selected using authentic databases searching from January 2013 to January 2021. Demographic data and genotypic information were extracted and organized from the selected studies. Review Manager (RevMan) version 5.4 was used to perform data analysis and data arrangement for meta-analysis.

RESULTS: A total of seven studies with 3395 patients and 3781 controls were included in this study. IL-32 rs28372698 polymorphism implied that mutant allele (TT) carriers had a significantly higher risk of cancer (OR = 1.43, p = 0.032). Codominant 3, recessive and allele models also showed 1.36-, 1.38- and 1.11-fold increased risk, respectively (p < 0.05). Besides, the Asian population showed a significantly increased risk in codominant 2 (OR = 1.74), codominant 3 (OR = 1.78), recessive (OR = 1.76) and allele model (OR = 1.16). IL-32 rs12934561 showed significantly reduced cancer risk in codominant 1 (OR = 0.66. p = 0.035), codominant 2 (OR = 0.76, p = 0.007), and dominant model (OR = 0.72, p = 0.012). After subgroup analysis, an association of rs12934561 was found in Asians (codominant 1: OR = 0.54, p = 7.28 × 10-8; codominant 2: OR = 1.40, p = 0.019; codominant 3: OR = 0.76, p = 0.0006; dominant model: OR = 0.64, p = 1.12 × 10-5; overdominant model: OR = 0.64, p = 3.92 × 10-7) but not in Caucasians. After stratifying with the control source, a significant (p < 0.05) association of rs28372698 and rs12934561 was found with cancer in population-based controls. No publication bias was found, and the outcome of this meta-analysis was not influenced by any individual study confirmed from sensitivity analysis. Moreover, trial sequential analysis (TSA) established a link between rs28372698 and rs12934561 polymorphisms and cancer.

CONCLUSION: The outcome of this meta-analysis revealed that IL-32 rs28372698 and rs12934561 polymorphisms are associated with cancer. Moreover, the Asian dynasty had a significant association compared to Caucasians.

PMID:34271417 | DOI:10.1016/j.intimp.2021.107964

J Mol Biol. 2021 Jul 14:167149. doi: 10.1016/j.jmb.2021.167149. Online ahead of print.

ABSTRACT

Infectious diseases in humans appear to be one of the most primary public health issues. Identification of novel disease-associated proteins will furnish an efficient recognition of the novel therapeutic targets. Here, we develop a Graph Convolutional Network (GCN)-based model called PINDeL to identify the disease-associated host proteins by integrating the human Protein Locality Graph and its corresponding topological features. Because of the amalgamation of GCN with the protein interaction network, PINDeL achieves the highest accuracy of 83.45%while AUROC and AUPRC values are 0.90and 0.88, respectively. With high accuracy, recall, F1-score, specificity, AUROC, and AUPRC, PINDeL outperforms other existing machine-learning and deep-learning techniques for disease gene/protein identification in humans. Application of PINDeL on an independent dataset of 24320proteins, which are not used for training, validation, or testing purposes, predicts 6448new disease-protein associations of which we verify 3196disease-proteins through experimental evidence like disease ontology, Gene Ontology, and KEGG pathway enrichment analyses. Our investigation informs that experimentally-verified 748proteins are indeed responsible for pathogen-host protein interactions of which 22disease-proteins share their association with multiple diseases such as cancer, aging, chem-dependency, pharmacogenomics, normal variation, infection, and immune-related diseases. This unique Graph Convolution Network-based prediction model is of utmost use in large-scale disease-protein association prediction and hence, will provide crucial insights on disease pathogenesis and will further aid in developing novel therapeutics.

PMID:34271012 | DOI:10.1016/j.jmb.2021.167149

Clin Transl Sci. 2021 Jul 16. doi: 10.1111/cts.13110. Online ahead of print.

ABSTRACT

Since the publication of the Human Genome Project, genetic information has been used as an accepted, evidence-based biomarker to optimize patient care through the delivery of precision health. Pharmacogenetics (PGx) uses information about genes that encode proteins involved in pharmacokinetics, pharmacodynamics, and hypersensitivity reactions to guide clinical decision making to optimize medication therapy selection. Clinical PGx implementation is growing from the dramatic increase in PGx studies over the last decade. However, an overwhelming lack of genetic diversity in current PGx studies is evident. This lack of diverse representation in PGx studies will impede equitable clinical implementation through potentially inappropriate application of gene-based dosing algorithms, while representing a missed opportunity for identification of population specific single nucleotide variants and alleles. In this review we discuss the challenges of studying PGx in underrepresented populations, highlight two successful PGx studies conducted in non-European populations, and propose a path forward through community-based participatory research for equitable PGx research and clinical translation.

PMID:34268895 | DOI:10.1111/cts.13110

Ecancermedicalscience. 2021 Jun 21;15:1253. doi: 10.3332/ecancer.2021.1253. eCollection 2021.

ABSTRACT

The rapidly rising cancer burden and mortality rate in Africa are in contrast to the increase in cancer survivorship in Europe and North America. Genomic medicine has contributed to the rise in survival and has facilitated precision cancer control. However, there is a shortage of African representation in genomic databases, even for cancers that disproportionately affect Africans. To improve this outlook and address research in genomics and genetics relevant to Africa and people of African descent, the African Organisation for Research and Training in Cancer (AORTIC), under the Research Committee's auspices, organised the Cancer Genomic Conference. The conference aimed to develop a roadmap for cancer genomics research to control the continent's increasing cancer burden. Presentations at the conference revealed that: (1) Africa is made up of a highly heterogeneous group of people with diverse ethnic groups, (2) Very few African countries have been the focus of cancer genomics research, (3) Cancer exacts a heavy burden on global populations across the African diaspora with obvious genetic variants and cancer disparities and (4) There are differences in the contribution of genetics by race or ancestry and these differences are likely due to evolutionary genetics, contextual factors and genomic architecture. The importance of data security, ethics and integrity of the African genomics data was emphasised. The implementation of the conference highlights will provide the bedrock for pharmacogenomics to guide treatment decisions for cancer in Africa. The conference concluded with the formation of an AORTIC Special Interest Group on cancer genomics. It is the goal of this group to drive the implementation of this Conference's outcomes.

PMID:34267809 | PMC:PMC8241447 | DOI:10.3332/ecancer.2021.1253

Eur J Hum Genet. 2021 Jul 15. doi: 10.1038/s41431-021-00920-y. Online ahead of print.

ABSTRACT

The current Dutch Pharmacogenetics Working Group (DPWG) guideline, describes the gene-drug interaction between CYP2D6 and the opioids codeine, tramadol and oxycodone. CYP2D6 genotype is translated into normal metaboliser (NM), intermediate metaboliser (IM), poor metaboliser (PM) or ultra-rapid metaboliser (UM). Codeine is contraindicated in UM adults if doses >20 mg every 6 h (q6h), in children ≥12 years if doses >10 mg q6h, or with additional risk factors. In PMs, an alternative analgesic should be given which is not or to a lesser extent metabolised by CYP2D6 (not tramadol). In IMs with insufficient analgesia, a higher dose or alternative analgesic should be given. For tramadol, the recommendations for IMs and PMs are the same as the recommendation for codeine and IMs. UMs should receive an alternative drug not or to a lesser extent metabolised by CYP2D6 or the dose should be decreased to 40% of the commonly prescribed dose. Due to the absence of effect on clinical outcomes of oxycodone in PMs, IMs and UMs no action is required. DPWG classifies CYP2D6 genotyping for codeine "beneficial" and recommends testing prior to, or shortly after initiation of treatment in case of higher doses or additional risk factors. CYP2D6 genotyping is classified as "potentially beneficial" for tramadol and can be considered on an individual patient basis.

PMID:34267337 | DOI:10.1038/s41431-021-00920-y

Aust N Z J Psychiatry. 2021 Jul 16:48674211031491. doi: 10.1177/00048674211031491. Online ahead of print.

ABSTRACT

INTRODUCTION: Chronic pain and depression are highly comorbid and difficult-to-treat disorders. We previously showed this comorbidity is associated with higher depression severity, lower antidepressant treatment effectiveness and poorer prognosis in the Australian Genetics of Depression Study.

OBJECTIVE: The current study aimed to assess whether a genetic liability to chronic pain is associated with antidepressant effectiveness over and above the effect of genetic factors for depression in a sample of 12,863 Australian Genetics of Depression Study participants.

METHODS: Polygenic risk scores were calculated using summary statistics from genome-wide association studies of multisite chronic pain and major depression. Cumulative linked regressions were employed to assess the association between polygenic risk scores and antidepressant treatment effectiveness across 10 different medications.

RESULTS: Mixed-effects logistic regressions showed that individual genetic propensity for chronic pain, but not major depression, was significantly associated with patient-reported chronic pain (PainPRS OR = 1.17 [1.12, 1.22]; MDPRS OR = 1.01 [0.98, 1.06]). Significant associations were also found between lower antidepressant effectiveness and genetic risk for chronic pain or for major depression. However, a fully adjusted model showed the effect of PainPRS (adjOR = 0.93 [0.90, 0.96]) was independent of MDPRS (adjOR = 0.96 [0.93, 0.99]). Sensitivity analyses were performed to assess the robustness of these results. After adjusting for depression severity measures (i.e. age of onset; number of depressive episodes; interval between age at study participation and at depression onset), the associations between PainPRS and patient-reported chronic pain with lower antidepressant effectiveness remained significant (0.95 [0.92, 0.98] and 0.84 [0.78, 0.90], respectively).

CONCLUSION: These results suggest genetic risk for chronic pain accounted for poorer antidepressant effectiveness, independent of the genetic risk for major depression. Our results, along with independent converging evidence from other studies, point towards a difficult-to-treat depression subtype characterised by comorbid chronic pain. This finding warrants further investigation into the implications for biologically based nosology frameworks in pain medicine and psychiatry.

PMID:34266302 | DOI:10.1177/00048674211031491

Pharmacology. 2021 Jul 15:1-9. doi: 10.1159/000517462. Online ahead of print.

ABSTRACT

INTRODUCTION: Genetic variants could aid in predicting antidiabetic drug response by associating them with markers of glucose control, such as glycated hemoglobin (HbA1c). However, pharmacogenetic implementation for antidiabetics is still under development, as the list of actionable markers is being populated and validated. This study explores potential associations between genetic variants and plasma levels of HbA1c in 100 patients under treatment with metformin.

METHODS: HbA1c was measured in a clinical chemistry analyzer (Roche), genotyping was performed in an Illumina-GSA array and data were analyzed using PLINK. Association and prediction models were developed using R and a 10-fold cross-validation approach.

RESULTS: We identified genetic variants on SLC47A1, SLC28A1, ABCG2, TBC1D4, and ARID5B that can explain up to 55% of the interindividual variability of HbA1c plasma levels in diabetic patients under treatment. Variants on SLC47A1, SLC28A1, and ABCG2 likely impact the pharmacokinetics (PK) of metformin, while the role of the two latter can be related to insulin resistance and regulation of adipogenesis.

CONCLUSIONS: Our results confirm previous genetic associations and point to previously unassociated gene variants for metformin PK and glucose control.

PMID:34265779 | DOI:10.1159/000517462

J Appl Lab Med. 2021 Jul 15:jfab056. doi: 10.1093/jalm/jfab056. Online ahead of print.

ABSTRACT

BACKGROUND: Pharmacogenomics has the potential to improve patient outcomes through predicting drug response. We designed and evaluated the analytical performance of a custom OpenArray® pharmacogenomics panel targeting 478 single-nucleotide variants (SNVs).

METHODS: Forty Coriell Institute cell line (CCL) DNA samples and DNA isolated from 28 whole-blood samples were used for accuracy evaluation. Genotyping calls were compared to at least 1 reference method: next-generation sequencing, Sequenom MassARRAY®, or Sanger sequencing. For precision evaluation, 23 CCL samples were analyzed 3 times and reproducibility of the assays was assessed. For sensitivity evaluation, 6 CCL samples and 5 whole-blood DNA samples were analyzed at DNA concentrations of 10 ng/µL and 50 ng/µL, and their reproducibility and genotyping call rates were compared.

RESULTS: For 443 variants, all samples assayed had concordant calls with at least 1 reference genotype and also demonstrated reproducibility. However, 6 of these 443 variants showed an unsatisfactory performance, such as low PCR amplification or insufficient separation of genotypes in scatter plots. Call rates were comparable between 50 ng/µL DNA (99.6%) and 10 ng/µL (99.2%). Use of 10 ng/µL DNA resulted in an incorrect call for a single sample for a single variant. Thus, as recommended by the manufacturer, 50 ng/µL is the preferred concentration for patient genotyping.

CONCLUSIONS: We evaluated a custom-designed pharmacogenomics panel and found that it reliably interrogated 437 variants. Clinically actionable results from selected variants on this panel are currently used in clinical studies employing pharmacogenomics for clinical decision-making.

PMID:34263311 | DOI:10.1093/jalm/jfab056

Front Pharmacol. 2021 Jun 28;12:696960. doi: 10.3389/fphar.2021.696960. eCollection 2021.

ABSTRACT

The use of small molecules became one key cornerstone of targeted anti-cancer therapy. Among them, tyrosine kinase inhibitors (TKIs) are especially important, as they were the first molecules to proof the concept of targeted anti-cancer treatment. Since 2001, TKIs can be successfully used to treat chronic myelogenous leukemia (CML). CML is a hematologic neoplasm, predominantly caused by reciprocal translocation t(9;22)(q34;q11) leading to formation of the so-called BCR-ABL1 fusion gene. By binding to the BCR-ABL1 kinase and inhibition of downstream target phosphorylation, TKIs, such as imatinib or nilotinib, can be used as single agents to treat CML patients resulting in 80 % 10-year survival rates. However, treatment failure can be observed in 20-25 % of CML patients occurring either dependent or independent from the BCR-ABL1 kinase. Here, we review approved TKIs that are indicated for the treatment of CML, their side effects and limitations. We point out mechanisms of TKI resistance focusing either on BCR-ABL1-dependent mechanisms by summarizing the clinically observed BCR-ABL1-mutations and their implications on TKI binding, as well as on BCR-ABL1-independent mechanisms of resistances. For the latter, we discuss potential mechanisms, among them cytochrome P450 implications, drug efflux transporter variants and expression, microRNA deregulation, as well as the role of alternative signaling pathways. Further, we give insights on how TKI resistance could be analyzed and what could be learned from studying TKI resistance in CML in vitro.

PMID:34262462 | PMC:PMC8273252 | DOI:10.3389/fphar.2021.696960

Front Pharmacol. 2021 Jun 28;12:684907. doi: 10.3389/fphar.2021.684907. eCollection 2021.

ABSTRACT

Background: Administration of pharmacogenomics (PGx) testing in clinical practice has been suboptimal, presumably due to lack of PGx education. Here, we aim to evaluate the standpoint of PGx testing among a diverse group of healthcare professionals (HCPs) through conducting surveys before and after training. Materials and Methods: Training modules were designed to cover three key learning objectives and deployed in five sections. A pre- and post-training survey questionnaire was used to evaluate participants' self-assessments on employing PGx in clinical practice. Results and Conclusion: Out of all enrollments, 102 survey responses were collected. Overall, respondents agree on the benefits of PGx testing, but have inadequate self-efficacy and competency in utilizing PGx data. Our results show that a 90 min long training significantly improves these, and could lead to greater anticipation of PGx adoption.

PMID:34262455 | PMC:PMC8273230 | DOI:10.3389/fphar.2021.684907

Alzheimers Res Ther. 2021 Jul 13;13(1):129. doi: 10.1186/s13195-021-00869-6.

ABSTRACT

BACKGROUND: We aimed to systematically describe the burden and distribution of white matter hyperintensities (WMH) and investigate correlations with neuropsychiatric symptoms in pathologically proven Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD).

METHODS: Autopsy-confirmed cases were identified from the Sunnybrook Dementia Study, including 15 cases of AD and 58 cases of FTLD (22 FTLD-TDP cases; 10 FTLD-Tau [Pick's] cases; 11 FTLD-Tau Corticobasal Degeneration cases; and 15 FTLD-Tau Progressive Supranuclear Palsy cases). Healthy matched controls (n = 35) were included for comparison purposes. Data analyses included ANCOVA to compare the burden of WMH on antemortem brain MRI between groups, adjusted linear regression models to identify associations between WMH burden and neuropsychiatric symptoms, and image-guided pathology review of selected areas of WMH from each pathologic group.

RESULTS: Burden and regional distribution of WMH differed significantly between neuropathological groups (F5,77 = 2.67, P' = 0.029), with the FTLD-TDP group having the highest mean volume globally (8032 ± 8889 mm3) and in frontal regions (4897 ± 6163 mm3). The AD group had the highest mean volume in occipital regions (468 ± 420 mm3). Total score on the Neuropsychiatric Inventory correlated with bilateral frontal WMH volume (β = 0.330, P = 0.006), depression correlated with bilateral occipital WMH volume (β = 0.401, P < 0.001), and apathy correlated with bilateral frontal WMH volume (β = 0.311, P = 0.009), all corrected for the false discovery rate. Image-guided neuropathological assessment of selected cases with the highest burden of WMH in each pathologic group revealed presence of severe gliosis, myelin pallor, and axonal loss, but with no distinguishing features indicative of the underlying proteinopathy.

CONCLUSIONS: These findings suggest that WMH are associated with neuropsychiatric manifestations in AD and FTLD and that WMH burden and regional distribution in neurodegenerative disorders differ according to the underlying neuropathological processes.

PMID:34256835 | PMC:PMC8278704 | DOI:10.1186/s13195-021-00869-6

Medicine (Baltimore). 2021 Jul 16;100(28):e26215. doi: 10.1097/MD.0000000000026215.

ABSTRACT

OBJECTIVE: To explore whether rs4784227 polymorphism of CASC16 is correlated with risk of breast cancer.

METHODS: Relevant studies up to December 24, 2020 were searched in PubMed, Embase, Web of Science, CNKI, VIP, and WANFANG databases. Data were analyzed by using Stata 12.0. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated, and country-based subgroup analyses were conducted. Sensitivity analysis was conducted to assess the stability of the results. Publication bias was assessed by using the Egger regression asymmetry test and visualization of funnel plots.

RESULTS: Seven case-control studies enrolling 4055 breast cancer cases and 4229 controls were included. rs4784227 was found significantly associated with increased risk of breast cancer in a dominant (OR = 1.301, 95% CI = 1.190-1.423, P < .001), a recessive (OR = 1.431, 95% CI = 1.216-1.685, P < .001), and an allele model (OR = 1.257, 95% CI = 1.172-1.348, P < .001), while an over-dominant model showed that rs4784227 was correlated with decreased breast cancer risk (OR = 0.852, 95% CI = 0.778-0.933, P = .001).

CONCLUSION: The rs4784227 polymorphism of CASC16 gene is correlated with breast cancer susceptibility.

PMID:34260521 | DOI:10.1097/MD.0000000000026215